Delay differential analysis of time series.

PubMed

Lainscsek, Claudia; Sejnowski, Terrence J

2015-03-01

Nonlinear dynamical system analysis based on embedding theory has been used for modeling and prediction, but it also has applications to signal detection and classification of time series. An embedding creates a multidimensional geometrical object from a single time series. Traditionally either delay or derivative embeddings have been used. The delay embedding is composed of delayed versions of the signal, and the derivative embedding is composed of successive derivatives of the signal. The delay embedding has been extended to nonuniform embeddings to take multiple timescales into account. Both embeddings provide information on the underlying dynamical system without having direct access to all the system variables. Delay differential analysis is based on functional embeddings, a combination of the derivative embedding with nonuniform delay embeddings. Small delay differential equation (DDE) models that best represent relevant dynamic features of time series data are selected from a pool of candidate models for detection or classification. We show that the properties of DDEs support spectral analysis in the time domain where nonlinear correlation functions are used to detect frequencies, frequency and phase couplings, and bispectra. These can be efficiently computed with short time windows and are robust to noise. For frequency analysis, this framework is a multivariate extension of discrete Fourier transform (DFT), and for higher-order spectra, it is a linear and multivariate alternative to multidimensional fast Fourier transform of multidimensional correlations. This method can be applied to short or sparse time series and can be extended to cross-trial and cross-channel spectra if multiple short data segments of the same experiment are available. Together, this time-domain toolbox provides higher temporal resolution, increased frequency and phase coupling information, and it allows an easy and straightforward implementation of higher-order spectra across time compared with frequency-based methods such as the DFT and cross-spectral analysis.

Micro-Doppler Signal Time-Frequency Algorithm Based on STFRFT.

PubMed

Pang, Cunsuo; Han, Yan; Hou, Huiling; Liu, Shengheng; Zhang, Nan

2016-09-24

This paper proposes a time-frequency algorithm based on short-time fractional order Fourier transformation (STFRFT) for identification of a complicated movement targets. This algorithm, consisting of a STFRFT order-changing and quick selection method, is effective in reducing the computation load. A multi-order STFRFT time-frequency algorithm is also developed that makes use of the time-frequency feature of each micro-Doppler component signal. This algorithm improves the estimation accuracy of time-frequency curve fitting through multi-order matching. Finally, experiment data were used to demonstrate STFRFT's performance in micro-Doppler time-frequency analysis. The results validated the higher estimate accuracy of the proposed algorithm. It may be applied to an LFM (Linear frequency modulated) pulse radar, SAR (Synthetic aperture radar), or ISAR (Inverse synthetic aperture radar), for improving the probability of target recognition.

Time-frequency analysis of acoustic scattering from elastic objects

NASA Astrophysics Data System (ADS)

Yen, Nai-Chyuan; Dragonette, Louis R.; Numrich, Susan K.

1990-06-01

A time-frequency analysis of acoustic scattering from elastic objects was carried out using the time-frequency representation based on a modified version of the Wigner distribution function (WDF) algorithm. A simple and efficient processing algorithm was developed, which provides meaningful interpretation of the scattering physics. The time and frequency representation derived from the WDF algorithm was further reduced to a display which is a skeleton plot, called a vein diagram, that depicts the essential features of the form function. The physical parameters of the scatterer are then extracted from this diagram with the proper interpretation of the scattering phenomena. Several examples, based on data obtained from numerically simulated models and laboratory measurements for elastic spheres and shells, are used to illustrate the capability and proficiency of the algorithm.

Gear fault diagnosis based on the structured sparsity time-frequency analysis

NASA Astrophysics Data System (ADS)

Sun, Ruobin; Yang, Zhibo; Chen, Xuefeng; Tian, Shaohua; Xie, Yong

2018-03-01

Over the last decade, sparse representation has become a powerful paradigm in mechanical fault diagnosis due to its excellent capability and the high flexibility for complex signal description. The structured sparsity time-frequency analysis (SSTFA) is a novel signal processing method, which utilizes mixed-norm priors on time-frequency coefficients to obtain a fine match for the structure of signals. In order to extract the transient feature from gear vibration signals, a gear fault diagnosis method based on SSTFA is proposed in this work. The steady modulation components and impulsive components of the defective gear vibration signals can be extracted simultaneously by choosing different time-frequency neighborhood and generalized thresholding operators. Besides, the time-frequency distribution with high resolution is obtained by piling different components in the same diagram. The diagnostic conclusion can be made according to the envelope spectrum of the impulsive components or by the periodicity of impulses. The effectiveness of the method is verified by numerical simulations, and the vibration signals registered from a gearbox fault simulator and a wind turbine. To validate the efficiency of the presented methodology, comparisons are made among some state-of-the-art vibration separation methods and the traditional time-frequency analysis methods. The comparisons show that the proposed method possesses advantages in separating feature signals under strong noise and accounting for the inner time-frequency structure of the gear vibration signals.

Improving resolution of crosswell seismic section based on time-frequency analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Luo, H.; Li, Y.

1994-12-31

According to signal theory, to improve resolution of seismic section is to extend high-frequency band of seismic signal. In cross-well section, sonic log can be regarded as a reliable source providing high-frequency information to the trace near the borehole. In such case, what to do is to introduce this high-frequency information into the whole section. However, neither traditional deconvolution algorithms nor some new inversion methods such as BCI (Broad Constraint Inversion) are satisfied because of high-frequency noise and nonuniqueness of inversion results respectively. To overcome their disadvantages, this paper presents a new algorithm based on Time-Frequency Analysis (TFA) technology whichmore » has been increasingly received much attention as an useful signal analysis too. Practical applications show that the new method is a stable scheme to improve resolution of cross-well seismic section greatly without decreasing Signal to Noise Ratio (SNR).« less

Non-stationary signal analysis based on general parameterized time-frequency transform and its application in the feature extraction of a rotary machine

NASA Astrophysics Data System (ADS)

Zhou, Peng; Peng, Zhike; Chen, Shiqian; Yang, Yang; Zhang, Wenming

2018-06-01

With the development of large rotary machines for faster and more integrated performance, the condition monitoring and fault diagnosis for them are becoming more challenging. Since the time-frequency (TF) pattern of the vibration signal from the rotary machine often contains condition information and fault feature, the methods based on TF analysis have been widely-used to solve these two problems in the industrial community. This article introduces an effective non-stationary signal analysis method based on the general parameterized time-frequency transform (GPTFT). The GPTFT is achieved by inserting a rotation operator and a shift operator in the short-time Fourier transform. This method can produce a high-concentrated TF pattern with a general kernel. A multi-component instantaneous frequency (IF) extraction method is proposed based on it. The estimation for the IF of every component is accomplished by defining a spectrum concentration index (SCI). Moreover, such an IF estimation process is iteratively operated until all the components are extracted. The tests on three simulation examples and a real vibration signal demonstrate the effectiveness and superiority of our method.

Frequency hopping signal detection based on wavelet decomposition and Hilbert-Huang transform

NASA Astrophysics Data System (ADS)

Zheng, Yang; Chen, Xihao; Zhu, Rui

2017-07-01

Frequency hopping (FH) signal is widely adopted by military communications as a kind of low probability interception signal. Therefore, it is very important to research the FH signal detection algorithm. The existing detection algorithm of FH signals based on the time-frequency analysis cannot satisfy the time and frequency resolution requirement at the same time due to the influence of window function. In order to solve this problem, an algorithm based on wavelet decomposition and Hilbert-Huang transform (HHT) was proposed. The proposed algorithm removes the noise of the received signals by wavelet decomposition and detects the FH signals by Hilbert-Huang transform. Simulation results show the proposed algorithm takes into account both the time resolution and the frequency resolution. Correspondingly, the accuracy of FH signals detection can be improved.

Glutenite bodies sequence division of the upper Es4 in northern Minfeng zone of Dongying Sag, Bohai Bay Basin, China

NASA Astrophysics Data System (ADS)

Shao, Xupeng

2017-04-01

Glutenite bodies are widely developed in northern Minfeng zone of Dongying Sag. Their litho-electric relationship is not clear. In addition, as the conventional sequence stratigraphic research method drawbacks of involving too many subjective human factors, it has limited deepening of the regional sequence stratigraphic research. The wavelet transform technique based on logging data and the time-frequency analysis technique based on seismic data have advantages of dividing sequence stratigraphy quantitatively comparing with the conventional methods. Under the basis of the conventional sequence research method, this paper used the above techniques to divide the fourth-order sequence of the upper Es4 in northern Minfeng zone of Dongying Sag. The research shows that the wavelet transform technique based on logging data and the time-frequency analysis technique based on seismic data are essentially consistent, both of which divide sequence stratigraphy quantitatively in the frequency domain; wavelet transform technique has high resolutions. It is suitable for areas with wells. The seismic time-frequency analysis technique has wide applicability, but a low resolution. Both of the techniques should be combined; the upper Es4 in northern Minfeng zone of Dongying Sag is a complete set of third-order sequence, which can be further subdivided into 5 fourth-order sequences that has the depositional characteristics of fine-upward sequence in granularity. Key words: Dongying sag, northern Minfeng zone, wavelet transform technique, time-frequency analysis technique ,the upper Es4, sequence stratigraphy

Radar Imaging Using The Wigner-Ville Distribution

NASA Astrophysics Data System (ADS)

Boashash, Boualem; Kenny, Owen P.; Whitehouse, Harper J.

1989-12-01

The need for analysis of time-varying signals has led to the formulation of a class of joint time-frequency distributions (TFDs). One of these TFDs, the Wigner-Ville distribution (WVD), has useful properties which can be applied to radar imaging. This paper first discusses the radar equation in terms of the time-frequency representation of the signal received from a radar system. It then presents a method of tomographic reconstruction for time-frequency images to estimate the scattering function of the aircraft. An optical archi-tecture is then discussed for the real-time implementation of the analysis method based on the WVD.

Time-Frequency Learning Machines for Nonstationarity Detection Using Surrogates

NASA Astrophysics Data System (ADS)

Borgnat, Pierre; Flandrin, Patrick; Richard, Cédric; Ferrari, André; Amoud, Hassan; Honeine, Paul

2012-03-01

Time-frequency representations provide a powerful tool for nonstationary signal analysis and classification, supporting a wide range of applications [12]. As opposed to conventional Fourier analysis, these techniques reveal the evolution in time of the spectral content of signals. In Ref. [7,38], time-frequency analysis is used to test stationarity of any signal. The proposed method consists of a comparison between global and local time-frequency features. The originality is to make use of a family of stationary surrogate signals for defining the null hypothesis of stationarity and, based upon this information, to derive statistical tests. An open question remains, however, about how to choose relevant time-frequency features. Over the last decade, a number of new pattern recognition methods based on reproducing kernels have been introduced. These learning machines have gained popularity due to their conceptual simplicity and their outstanding performance [30]. Initiated by Vapnik’s support vector machines (SVM) [35], they offer now a wide class of supervised and unsupervised learning algorithms. In Ref. [17-19], the authors have shown how the most effective and innovative learning machines can be tuned to operate in the time-frequency domain. This chapter follows this line of research by taking advantage of learning machines to test and quantify stationarity. Based on one-class SVM, our approach uses the entire time-frequency representation and does not require arbitrary feature extraction. Applied to a set of surrogates, it provides the domain boundary that includes most of these stationarized signals. This allows us to test the stationarity of the signal under investigation. This chapter is organized as follows. In Section 22.2, we introduce the surrogate data method to generate stationarized signals, namely, the null hypothesis of stationarity. The concept of time-frequency learning machines is presented in Section 22.3, and applied to one-class SVM in order to derive a stationarity test in Section 22.4. The relevance of the latter is illustrated by simulation results in Section 22.5.

A time and frequency synchronization method for CO-OFDM based on CMA equalizers

NASA Astrophysics Data System (ADS)

Ren, Kaixuan; Li, Xiang; Huang, Tianye; Cheng, Zhuo; Chen, Bingwei; Wu, Xu; Fu, Songnian; Ping, Perry Shum

2018-06-01

In this paper, an efficient time and frequency synchronization method based on a new training symbol structure is proposed for polarization division multiplexing (PDM) coherent optical orthogonal frequency division multiplexing (CO-OFDM) systems. The coarse timing synchronization is achieved by exploiting the correlation property of the first training symbol, and the fine timing synchronization is accomplished by using the time-domain symmetric conjugate of the second training symbol. Furthermore, based on these training symbols, a constant modulus algorithm (CMA) is proposed for carrier frequency offset (CFO) estimation. Theoretical analysis and simulation results indicate that the algorithm has the advantages of robustness to poor optical signal-to-noise ratio (OSNR) and chromatic dispersion (CD). The frequency offset estimation range can achieve [ -Nsc/2 ΔfN , + Nsc/2 ΔfN ] GHz with the mean normalized estimation error below 12 × 10-3 even under the condition of OSNR as low as 10 dB.

Basic gait analysis based on continuous wave radar.

PubMed

Zhang, Jun

2012-09-01

A gait analysis method based on continuous wave (CW) radar is proposed in this paper. Time-frequency analysis is used to analyze the radar micro-Doppler echo from walking humans, and the relationships between the time-frequency spectrogram and human biological gait are discussed. The methods for extracting the gait parameters from the spectrogram are studied in depth and experiments on more than twenty subjects have been performed to acquire the radar gait data. The gait parameters are calculated and compared. The gait difference between men and women are presented based on the experimental data and extracted features. Gait analysis based on CW radar will provide a new method for clinical diagnosis and therapy. Copyright © 2012 Elsevier B.V. All rights reserved.

Ultrasonic test of resistance spot welds based on wavelet package analysis.

PubMed

Liu, Jing; Xu, Guocheng; Gu, Xiaopeng; Zhou, Guanghao

2015-02-01

In this paper, ultrasonic test of spot welds for stainless steel sheets has been studied. It is indicated that traditional ultrasonic signal analysis in either time domain or frequency domain remains inadequate to evaluate the nugget diameter of spot welds. However, the method based on wavelet package analysis in time-frequency domain can easily distinguish the nugget from the corona bond by extracting high-frequency signals in different positions of spot welds, thereby quantitatively evaluating the nugget diameter. The results of ultrasonic test fit the actual measured value well. Mean value of normal distribution of error statistics is 0.00187, and the standard deviation is 0.1392. Furthermore, the quality of spot welds was evaluated, and it is showed ultrasonic nondestructive test based on wavelet packet analysis can be used to evaluate the quality of spot welds, and it is more reliable than single tensile destructive test. Copyright © 2014 Elsevier B.V. All rights reserved.

Aurally-adequate time-frequency analysis for scattered sound in auditoria

NASA Astrophysics Data System (ADS)

Norris, Molly K.; Xiang, Ning; Kleiner, Mendel

2005-04-01

The goal of this work was to apply an aurally-adequate time-frequency analysis technique to the analysis of sound scattering effects in auditoria. Time-frequency representations were developed as a motivated effort that takes into account binaural hearing, with a specific implementation of interaural cross-correlation process. A model of the human auditory system was implemented in the MATLAB platform based on two previous models [A. Härmä and K. Palomäki, HUTear, Espoo, Finland; and M. A. Akeroyd, A. Binaural Cross-correlogram Toolbox for MATLAB (2001), University of Sussex, Brighton]. These stages include proper frequency selectivity, the conversion of the mechanical motion of the basilar membrane to neural impulses, and binaural hearing effects. The model was then used in the analysis of room impulse responses with varying scattering characteristics. This paper discusses the analysis results using simulated and measured room impulse responses. [Work supported by the Frank H. and Eva B. Buck Foundation.

Distributed Optimization Design of Continuous-Time Multiagent Systems With Unknown-Frequency Disturbances.

PubMed

Wang, Xinghu; Hong, Yiguang; Yi, Peng; Ji, Haibo; Kang, Yu

2017-05-24

In this paper, a distributed optimization problem is studied for continuous-time multiagent systems with unknown-frequency disturbances. A distributed gradient-based control is proposed for the agents to achieve the optimal consensus with estimating unknown frequencies and rejecting the bounded disturbance in the semi-global sense. Based on convex optimization analysis and adaptive internal model approach, the exact optimization solution can be obtained for the multiagent system disturbed by exogenous disturbances with uncertain parameters.

Phase and amplitude analysis in time-frequency space--application to voluntary finger movement.

PubMed

Ginter, J; Blinowska, K J; Kamiński, M; Durka, P J

2001-09-30

Two methods operating in time-frequency space were applied to analysis of EEG activity accompanying voluntary finger movements. The first one, based on matching pursuit approach provided high-resolution distributions of power in time-frequency space. The phenomena of event related desynchronization (ERD) and synchronization (ERS) were investigated without the need of band-pass filtering. Time evolution of mu- and beta-components was observed in a detailed way. The second method was based on a multichannel autoregressive model (MVAR) adapted for investigation of short-time changes in EEG signal. The direction and spectral content of the EEG activity propagation was estimated by means of short-time directed transfer function (SDTF). The evidence of 'cross-talk' between different areas of motor and sensory cortex was found. The earlier known phenomena, connected with voluntary movements, were confirmed and a new evidence concerning focal ERD/surround ERS and beta activity post-movement synchronization was found.

Highly sensitive index of sympathetic activity based on time-frequency spectral analysis of electrodermal activity.

PubMed

Posada-Quintero, Hugo F; Florian, John P; Orjuela-Cañón, Álvaro D; Chon, Ki H

2016-09-01

Time-domain indices of electrodermal activity (EDA) have been used as a marker of sympathetic tone. However, they often show high variation between subjects and low consistency, which has precluded their general use as a marker of sympathetic tone. To examine whether power spectral density analysis of EDA can provide more consistent results, we recently performed a variety of sympathetic tone-evoking experiments (43). We found significant increase in the spectral power in the frequency range of 0.045 to 0.25 Hz when sympathetic tone-evoking stimuli were induced. The sympathetic tone assessed by the power spectral density of EDA was found to have lower variation and more sensitivity for certain, but not all, stimuli compared with the time-domain analysis of EDA. We surmise that this lack of sensitivity in certain sympathetic tone-inducing conditions with time-invariant spectral analysis of EDA may lie in its inability to characterize time-varying dynamics of the sympathetic tone. To overcome the disadvantages of time-domain and time-invariant power spectral indices of EDA, we developed a highly sensitive index of sympathetic tone, based on time-frequency analysis of EDA signals. Its efficacy was tested using experiments designed to elicit sympathetic dynamics. Twelve subjects underwent four tests known to elicit sympathetic tone arousal: cold pressor, tilt table, stand test, and the Stroop task. We hypothesize that a more sensitive measure of sympathetic control can be developed using time-varying spectral analysis. Variable frequency complex demodulation, a recently developed technique for time-frequency analysis, was used to obtain spectral amplitudes associated with EDA. We found that the time-varying spectral frequency band 0.08-0.24 Hz was most responsive to stimulation. Spectral power for frequencies higher than 0.24 Hz were determined to be not related to the sympathetic dynamics because they comprised less than 5% of the total power. The mean value of time-varying spectral amplitudes in the frequency band 0.08-0.24 Hz were used as the index of sympathetic tone, termed TVSymp. TVSymp was found to be overall the most sensitive to the stimuli, as evidenced by a low coefficient of variation (0.54), and higher consistency (intra-class correlation, 0.96) and sensitivity (Youden's index > 0.75), area under the receiver operating characteristic (ROC) curve (>0.8, accuracy > 0.88) compared with time-domain and time-invariant spectral indices, including heart rate variability. Copyright © 2016 the American Physiological Society.

The Researches on Damage Detection Method for Truss Structures

NASA Astrophysics Data System (ADS)

Wang, Meng Hong; Cao, Xiao Nan

2018-06-01

This paper presents an effective method to detect damage in truss structures. Numerical simulation and experimental analysis were carried out on a damaged truss structure under instantaneous excitation. The ideal excitation point and appropriate hammering method were determined to extract time domain signals under two working conditions. The frequency response function and principal component analysis were used for data processing, and the angle between the frequency response function vectors was selected as a damage index to ascertain the location of a damaged bar in the truss structure. In the numerical simulation, the time domain signal of all nodes was extracted to determine the location of the damaged bar. In the experimental analysis, the time domain signal of a portion of the nodes was extracted on the basis of an optimal sensor placement method based on the node strain energy coefficient. The results of the numerical simulation and experimental analysis showed that the damage detection method based on the frequency response function and principal component analysis could locate the damaged bar accurately.

Fast-Running Aeroelastic Code Based on Unsteady Linearized Aerodynamic Solver Developed

NASA Technical Reports Server (NTRS)

Reddy, T. S. R.; Bakhle, Milind A.; Keith, T., Jr.

2003-01-01

The NASA Glenn Research Center has been developing aeroelastic analyses for turbomachines for use by NASA and industry. An aeroelastic analysis consists of a structural dynamic model, an unsteady aerodynamic model, and a procedure to couple the two models. The structural models are well developed. Hence, most of the development for the aeroelastic analysis of turbomachines has involved adapting and using unsteady aerodynamic models. Two methods are used in developing unsteady aerodynamic analysis procedures for the flutter and forced response of turbomachines: (1) the time domain method and (2) the frequency domain method. Codes based on time domain methods require considerable computational time and, hence, cannot be used during the design process. Frequency domain methods eliminate the time dependence by assuming harmonic motion and, hence, require less computational time. Early frequency domain analyses methods neglected the important physics of steady loading on the analyses for simplicity. A fast-running unsteady aerodynamic code, LINFLUX, which includes steady loading and is based on the frequency domain method, has been modified for flutter and response calculations. LINFLUX, solves unsteady linearized Euler equations for calculating the unsteady aerodynamic forces on the blades, starting from a steady nonlinear aerodynamic solution. First, we obtained a steady aerodynamic solution for a given flow condition using the nonlinear unsteady aerodynamic code TURBO. A blade vibration analysis was done to determine the frequencies and mode shapes of the vibrating blades, and an interface code was used to convert the steady aerodynamic solution to a form required by LINFLUX. A preprocessor was used to interpolate the mode shapes from the structural dynamic mesh onto the computational dynamics mesh. Then, we used LINFLUX to calculate the unsteady aerodynamic forces for a given mode, frequency, and phase angle. A postprocessor read these unsteady pressures and calculated the generalized aerodynamic forces, eigenvalues, and response amplitudes. The eigenvalues determine the flutter frequency and damping. As a test case, the flutter of a helical fan was calculated with LINFLUX and compared with calculations from TURBO-AE, a nonlinear time domain code, and from ASTROP2, a code based on linear unsteady aerodynamics.

Double Fourier analysis for Emotion Identification in Voiced Speech

NASA Astrophysics Data System (ADS)

Sierra-Sosa, D.; Bastidas, M.; Ortiz P., D.; Quintero, O. L.

2016-04-01

We propose a novel analysis alternative, based on two Fourier Transforms for emotion recognition from speech. Fourier analysis allows for display and synthesizes different signals, in terms of power spectral density distributions. A spectrogram of the voice signal is obtained performing a short time Fourier Transform with Gaussian windows, this spectrogram portraits frequency related features, such as vocal tract resonances and quasi-periodic excitations during voiced sounds. Emotions induce such characteristics in speech, which become apparent in spectrogram time-frequency distributions. Later, the signal time-frequency representation from spectrogram is considered an image, and processed through a 2-dimensional Fourier Transform in order to perform the spatial Fourier analysis from it. Finally features related with emotions in voiced speech are extracted and presented.

Time-variant random interval natural frequency analysis of structures

NASA Astrophysics Data System (ADS)

Wu, Binhua; Wu, Di; Gao, Wei; Song, Chongmin

2018-02-01

This paper presents a new robust method namely, unified interval Chebyshev-based random perturbation method, to tackle hybrid random interval structural natural frequency problem. In the proposed approach, random perturbation method is implemented to furnish the statistical features (i.e., mean and standard deviation) and Chebyshev surrogate model strategy is incorporated to formulate the statistical information of natural frequency with regards to the interval inputs. The comprehensive analysis framework combines the superiority of both methods in a way that computational cost is dramatically reduced. This presented method is thus capable of investigating the day-to-day based time-variant natural frequency of structures accurately and efficiently under concrete intrinsic creep effect with probabilistic and interval uncertain variables. The extreme bounds of the mean and standard deviation of natural frequency are captured through the embedded optimization strategy within the analysis procedure. Three particularly motivated numerical examples with progressive relationship in perspective of both structure type and uncertainty variables are demonstrated to justify the computational applicability, accuracy and efficiency of the proposed method.

The Fourier decomposition method for nonlinear and non-stationary time series analysis.

PubMed

Singh, Pushpendra; Joshi, Shiv Dutt; Patney, Rakesh Kumar; Saha, Kaushik

2017-03-01

for many decades, there has been a general perception in the literature that Fourier methods are not suitable for the analysis of nonlinear and non-stationary data. In this paper, we propose a novel and adaptive Fourier decomposition method (FDM), based on the Fourier theory, and demonstrate its efficacy for the analysis of nonlinear and non-stationary time series. The proposed FDM decomposes any data into a small number of 'Fourier intrinsic band functions' (FIBFs). The FDM presents a generalized Fourier expansion with variable amplitudes and variable frequencies of a time series by the Fourier method itself. We propose an idea of zero-phase filter bank-based multivariate FDM (MFDM), for the analysis of multivariate nonlinear and non-stationary time series, using the FDM. We also present an algorithm to obtain cut-off frequencies for MFDM. The proposed MFDM generates a finite number of band-limited multivariate FIBFs (MFIBFs). The MFDM preserves some intrinsic physical properties of the multivariate data, such as scale alignment, trend and instantaneous frequency. The proposed methods provide a time-frequency-energy (TFE) distribution that reveals the intrinsic structure of a data. Numerical computations and simulations have been carried out and comparison is made with the empirical mode decomposition algorithms.

Adaptive synchrosqueezing based on a quilted short-time Fourier transform

NASA Astrophysics Data System (ADS)

Berrian, Alexander; Saito, Naoki

2017-08-01

In recent years, the synchrosqueezing transform (SST) has gained popularity as a method for the analysis of signals that can be broken down into multiple components determined by instantaneous amplitudes and phases. One such version of SST, based on the short-time Fourier transform (STFT), enables the sharpening of instantaneous frequency (IF) information derived from the STFT, as well as the separation of amplitude-phase components corresponding to distinct IF curves. However, this SST is limited by the time-frequency resolution of the underlying window function, and may not resolve signals exhibiting diverse time-frequency behaviors with sufficient accuracy. In this work, we develop a framework for an SST based on a "quilted" short-time Fourier transform (SST-QSTFT), which allows adaptation to signal behavior in separate time-frequency regions through the use of multiple windows. This motivates us to introduce a discrete reassignment frequency formula based on a finite difference of the phase spectrum, ensuring computational accuracy for a wider variety of windows. We develop a theoretical framework for the SST-QSTFT in both the continuous and the discrete settings, and describe an algorithm for the automatic selection of optimal windows depending on the region of interest. Using synthetic data, we demonstrate the superior numerical performance of SST-QSTFT relative to other SST methods in a noisy context. Finally, we apply SST-QSTFT to audio recordings of animal calls to demonstrate the potential of our method for the analysis of real bioacoustic signals.

A Novel EEG Based Spectral Analysis of Persistent Brain Function Alteration in Athletes with Concussion History.

PubMed

Munia, Tamanna T K; Haider, Ali; Schneider, Charles; Romanick, Mark; Fazel-Rezai, Reza

2017-12-08

The neurocognitive sequelae of a sport-related concussion and its management are poorly defined. Detecting deficits are vital in making a decision about the treatment plan as it can persist one year or more following a brain injury. The reliability of traditional cognitive assessment tools is debatable, and thus attention has turned to assessments based on electroencephalogram (EEG) to evaluate subtle post-concussive alterations. In this study, we calculated neurocognitive deficits combining EEG analysis with three standard post-concussive assessment tools. Data were collected for all testing modalities from 21 adolescent athletes (seven concussive and fourteen healthy) in three different trials. For EEG assessment, along with linear frequency-based features, we introduced a set of time-frequency (Hjorth Parameters) and nonlinear features (approximate entropy and Hurst exponent) for the first time to explore post-concussive deficits. Besides traditional frequency-band analysis, we also presented a new individual frequency-based approach for EEG assessment. While EEG analysis exhibited significant discrepancies between the groups, none of the cognitive assessment resulted in significant deficits. Therefore, the evidence from the study highlights that our proposed EEG analysis and markers are more efficient at deciphering post-concussion residual neurocognitive deficits and thus has a potential clinical utility of proper concussion assessment and management.

When Interpolation-Induced Reflection Artifact Meets Time-Frequency Analysis.

PubMed

Lin, Yu-Ting; Flandrin, Patrick; Wu, Hau-Tieng

2016-10-01

While extracting the temporal dynamical features based on the time-frequency analyses, like the reassignment and synchrosqueezing transform, attracts more and more interest in biomedical data analysis, we should be careful about artifacts generated by interpolation schemes, in particular when the sampling rate is not significantly higher than the frequency of the oscillatory component we are interested in. We formulate the problem called the reflection effect and provide a theoretical justification of the statement. We also show examples in the anesthetic depth analysis with clear but undesirable artifacts. The artifact associated with the reflection effect exists not only theoretically but practically as well. Its influence is pronounced when we apply the time-frequency analyses to extract the time-varying dynamics hidden inside the signal. We have to carefully deal with the artifact associated with the reflection effect by choosing a proper interpolation scheme.

Spectral negentropy based sidebands and demodulation analysis for planet bearing fault diagnosis

NASA Astrophysics Data System (ADS)

Feng, Zhipeng; Ma, Haoqun; Zuo, Ming J.

2017-12-01

Planet bearing vibration signals are highly complex due to intricate kinematics (involving both revolution and spinning) and strong multiple modulations (including not only the fault induced amplitude modulation and frequency modulation, but also additional amplitude modulations due to load zone passing, time-varying vibration transfer path, and time-varying angle between the gear pair mesh lines of action and fault impact force vector), leading to difficulty in fault feature extraction. Rolling element bearing fault diagnosis essentially relies on detection of fault induced repetitive impulses carried by resonance vibration, but they are usually contaminated by noise and therefor are hard to be detected. This further adds complexity to planet bearing diagnostics. Spectral negentropy is able to reveal the frequency distribution of repetitive transients, thus providing an approach to identify the optimal frequency band of a filter for separating repetitive impulses. In this paper, we find the informative frequency band (including the center frequency and bandwidth) of bearing fault induced repetitive impulses using the spectral negentropy based infogram. In Fourier spectrum, we identify planet bearing faults according to sideband characteristics around the center frequency. For demodulation analysis, we filter out the sensitive component based on the informative frequency band revealed by the infogram. In amplitude demodulated spectrum (squared envelope spectrum) of the sensitive component, we diagnose planet bearing faults by matching the present peaks with the theoretical fault characteristic frequencies. We further decompose the sensitive component into mono-component intrinsic mode functions (IMFs) to estimate their instantaneous frequencies, and select a sensitive IMF with an instantaneous frequency fluctuating around the center frequency for frequency demodulation analysis. In the frequency demodulated spectrum (Fourier spectrum of instantaneous frequency) of selected IMF, we discern planet bearing fault reasons according to the present peaks. The proposed spectral negentropy infogram based spectrum and demodulation analysis method is illustrated via a numerical simulated signal analysis. Considering the unique load bearing feature of planet bearings, experimental validations under both no-load and loading conditions are done to verify the derived fault symptoms and the proposed method. The localized faults on outer race, rolling element and inner race are successfully diagnosed.

A general theory on frequency and time-frequency analysis of irregularly sampled time series based on projection methods - Part 2: Extension to time-frequency analysis

NASA Astrophysics Data System (ADS)

Lenoir, Guillaume; Crucifix, Michel

2018-03-01

Geophysical time series are sometimes sampled irregularly along the time axis. The situation is particularly frequent in palaeoclimatology. Yet, there is so far no general framework for handling the continuous wavelet transform when the time sampling is irregular. Here we provide such a framework. To this end, we define the scalogram as the continuous-wavelet-transform equivalent of the extended Lomb-Scargle periodogram defined in Part 1 of this study (Lenoir and Crucifix, 2018). The signal being analysed is modelled as the sum of a locally periodic component in the time-frequency plane, a polynomial trend, and a background noise. The mother wavelet adopted here is the Morlet wavelet classically used in geophysical applications. The background noise model is a stationary Gaussian continuous autoregressive-moving-average (CARMA) process, which is more general than the traditional Gaussian white and red noise processes. The scalogram is smoothed by averaging over neighbouring times in order to reduce its variance. The Shannon-Nyquist exclusion zone is however defined as the area corrupted by local aliasing issues. The local amplitude in the time-frequency plane is then estimated with least-squares methods. We also derive an approximate formula linking the squared amplitude and the scalogram. Based on this property, we define a new analysis tool: the weighted smoothed scalogram, which we recommend for most analyses. The estimated signal amplitude also gives access to band and ridge filtering. Finally, we design a test of significance for the weighted smoothed scalogram against the stationary Gaussian CARMA background noise, and provide algorithms for computing confidence levels, either analytically or with Monte Carlo Markov chain methods. All the analysis tools presented in this article are available to the reader in the Python package WAVEPAL.

A New Instantaneous Frequency Measure Based on The Stockwell Transform

NASA Astrophysics Data System (ADS)

yedlin, M. J.; Ben-Horrin, Y.; Fraser, J. D.

2011-12-01

We propose the use of a new transform, the Stockwell transform[1], as a means of creating time-frequency maps and applying them to distinguish blasts from earthquakes. This new transform, the Stockwell transform can be considered as a variant of the continuous wavelet transform, that preserves the absolute phase.The Stockwell transform employs a complex Morlet mother wavelet. The novelty of this transform lies in its resolution properties. High frequencies in the candidate signal are well-resolved in time but poorly resolved in frequency, while the converse is true for low frequency signal components. The goal of this research is to obtain the instantaneous frequency as a function of time for both the earthquakes and the blasts. Two methods will be compared. In the first method, we will compute the analytic signal, the envelope and the instantaneous phase as a function of time[2]. The instantaneous phase derivative will yield the instantaneous angular frequency. The second method will be based on time-frequency analysis using the Stockwell transform. The Stockwell transform will be computed in non-redundant fashion using a dyadic representation[3]. For each time-point, the frequency centroid will be computed -- a representation for the most likely frequency at that time. A detailed comparison will be presented for both approaches to the computation of the instantaneous frequency. An advantage of the Stockwell approach is that no differentiation is applied. The Hilbert transform method can be less sensitive to edge effects. The goal of this research is to see if the new Stockwell-based method could be used as a discriminant between earthquakes and blasts. References [1] Stockwell, R.G., Mansinha, L. and Lowe, R.P. "Localization of the complex spectrum: the S transform", IEEE Trans. Signal Processing, vol.44, no.4, pp.998-1001, (1996). [2]Taner, M.T., Koehler, F. "Complex seismic trace analysis", Geophysics, vol. 44, Issue 6, pp. 1041-1063 (1979). [3] Brown, R.A., Lauzon, M.L. and Frayne, R. "General Description of Linear Time-Frequency Transforms and Formulation of a Fast, Invertible Transform That Samples the Continuous S-Transform Spectrum Nonredundantly", IEEE Transactions on Signal Processing, 1:281-90 (2010).

[Application of the computer-based respiratory sound analysis system based on Mel-frequency cepstral coefficient and dynamic time warping in healthy children].

PubMed

Yan, W Y; Li, L; Yang, Y G; Lin, X L; Wu, J Z

2016-08-01

We designed a computer-based respiratory sound analysis system to identify pediatric normal lung sound. To verify the validity of the computer-based respiratory sound analysis system. First we downloaded the standard lung sounds from the network database (website: http: //www.easyauscultation.com/lung-sounds-reference-guide) and recorded 3 samples of abnormal loud sound (rhonchi, wheeze and crackles) from three patients of The Department of Pediatrics, the First Affiliated Hospital of Xiamen University. We regarded such lung sounds as"reference lung sounds". The"test lung sounds"were recorded from 29 children form Kindergarten of Xiamen University. we recorded lung sound by portable electronic stethoscope and valid lung sounds were selected by manual identification. We introduced Mel-frequency cepstral coefficient (MFCC) to extract lung sound features and dynamic time warping (DTW) for signal classification. We had 39 standard lung sounds, recorded 58 test lung sounds. This computer-based respiratory sound analysis system was carried out in 58 lung sound recognition, correct identification of 52 times, error identification 6 times. Accuracy was 89.7%. Based on MFCC and DTW, our computer-based respiratory sound analysis system can effectively identify healthy lung sounds of children (accuracy can reach 89.7%), fully embodies the reliability of the lung sounds analysis system.

Statistical significance of task related deep brain EEG dynamic changes in the time-frequency domain.

PubMed

Chládek, J; Brázdil, M; Halámek, J; Plešinger, F; Jurák, P

2013-01-01

We present an off-line analysis procedure for exploring brain activity recorded from intra-cerebral electroencephalographic data (SEEG). The objective is to determine the statistical differences between different types of stimulations in the time-frequency domain. The procedure is based on computing relative signal power change and subsequent statistical analysis. An example of characteristic statistically significant event-related de/synchronization (ERD/ERS) detected across different frequency bands following different oddball stimuli is presented. The method is used for off-line functional classification of different brain areas.

Time frequency analysis for automated sleep stage identification in fullterm and preterm neonates.

PubMed

Fraiwan, Luay; Lweesy, Khaldon; Khasawneh, Natheer; Fraiwan, Mohammad; Wenz, Heinrich; Dickhaus, Hartmut

2011-08-01

This work presents a new methodology for automated sleep stage identification in neonates based on the time frequency distribution of single electroencephalogram (EEG) recording and artificial neural networks (ANN). Wigner-Ville distribution (WVD), Hilbert-Hough spectrum (HHS) and continuous wavelet transform (CWT) time frequency distributions were used to represent the EEG signal from which features were extracted using time frequency entropy. The classification of features was done using feed forward back-propagation ANN. The system was trained and tested using data taken from neonates of post-conceptual age of 40 weeks for both preterm (14 recordings) and fullterm (15 recordings). The identification of sleep stages was successfully implemented and the classification based on the WVD outperformed the approaches based on CWT and HHS. The accuracy and kappa coefficient were found to be 0.84 and 0.65 respectively for the fullterm neonates' recordings and 0.74 and 0.50 respectively for preterm neonates' recordings.

Performance comparison of ISAR imaging method based on time frequency transforms

NASA Astrophysics Data System (ADS)

Xie, Chunjian; Guo, Chenjiang; Xu, Jiadong

2013-03-01

Inverse synthetic aperture radar (ISAR) can image the moving target, especially the target in the air, so it is important in the air defence and missile defence system. Time-frequency Transform was applied to ISAR imaging process widely. Several time frequency transforms were introduced. Noise jamming methods were analysed, and when these noise jamming were added to the echo of the ISAR receiver, the image can become blur even can't to be identify. But the effect is different to the different time frequency analysis. The results of simulation experiment show the Performance Comparison of the method.

Analysis of Scattering from Archival Pulsar Data using a CLEAN-based Method

NASA Astrophysics Data System (ADS)

Tsai, -Wei, Jr.; Simonetti, John H.; Kavic, Michael

2017-02-01

In this work, we adopted a CLEAN-based method to determine the scatter time, τ, from archived pulsar profiles under both the thin screen and uniform medium scattering models and to calculate the scatter time frequency scale index α, where τ \\propto {ν }α . The value of α is -4.4, if a Kolmogorov spectrum of the interstellar medium turbulence is assumed. We deconvolved 1342 profiles from 347 pulsars over a broad range of frequencies and dispersion measures. In our survey, in the majority of cases the scattering effect was not significant compared to pulse profile widths. For a subset of 21 pulsars scattering at the lowest frequencies was large enough to be measured. Because reliable scatter time measurements were determined only for the lowest frequency, we were limited to using upper limits on scatter times at higher frequencies for the purpose of our scatter time frequency slope estimation. We scaled the deconvolved scatter time to 1 GHz assuming α =-4.4 and considered our results in the context of other observations which yielded a broad relation between scatter time and dispersion measure.

Time-frequency analysis of the bistatic acoustic scattering from a spherical elastic shell.

PubMed

Anderson, Shaun D; Sabra, Karim G; Zakharia, Manell E; Sessarego, Jean-Pierre

2012-01-01

The development of low-frequency sonar systems, using, for instance, a network of autonomous systems in unmanned vehicles, provides a practical means for bistatic measurements (i.e., when the source and receiver are widely separated) allowing for multiple viewpoints of the target of interest. Time-frequency analysis, in particular, Wigner-Ville analysis, takes advantage of the evolution time dependent aspect of the echo spectrum to differentiate a man-made target, such as an elastic spherical shell, from a natural object of the similar shape. A key energetic feature of fluid-loaded and thin spherical shell is the coincidence pattern, also referred to as the mid-frequency enhancement (MFE), that results from antisymmetric Lamb-waves propagating around the circumference of the shell. This article investigates numerically the bistatic variations of the MFE with respect to the monostatic configuration using the Wigner-Ville analysis. The observed time-frequency shifts of the MFE are modeled using a previously derived quantitative ray theory by Zhang et al. [J. Acoust. Soc. Am. 91, 1862-1874 (1993)] for spherical shell's scattering. Additionally, the advantage of an optimal array beamformer, based on joint time delays and frequency shifts is illustrated for enhancing the detection of the MFE recorded across a bistatic receiver array when compared to a conventional time-delay beamformer. © 2012 Acoustical Society of America.

On reliable time-frequency characterization and delay estimation of stimulus frequency otoacoustic emissions

NASA Astrophysics Data System (ADS)

Biswal, Milan; Mishra, Srikanta

2018-05-01

The limited information on origin and nature of stimulus frequency otoacoustic emissions (SFOAEs) necessitates a thorough reexamination into SFOAE analysis procedures. This will lead to a better understanding of the generation of SFOAEs. The SFOAE response waveform in the time domain can be interpreted as a summation of amplitude modulated and frequency modulated component waveforms. The efficiency of a technique to segregate these components is critical to describe the nature of SFOAEs. Recent advancements in robust time-frequency analysis algorithms have staked claims on the more accurate extraction of these components, from composite signals buried in noise. However, their potential has not been fully explored for SFOAEs analysis. Indifference to distinct information, due to nature of these analysis techniques, may impact the scientific conclusions. This paper attempts to bridge this gap in literature by evaluating the performance of three linear time-frequency analysis algorithms: short-time Fourier transform (STFT), continuous Wavelet transform (CWT), S-transform (ST) and two nonlinear algorithms: Hilbert-Huang Transform (HHT), synchrosqueezed Wavelet transform (SWT). We revisit the extraction of constituent components and estimation of their magnitude and delay, by carefully evaluating the impact of variation in analysis parameters. The performance of HHT and SWT from the perspective of time-frequency filtering and delay estimation were found to be relatively less efficient for analyzing SFOAEs. The intrinsic mode functions of HHT does not completely characterize the reflection components and hence IMF based filtering alone, is not recommended for segregating principal emission from multiple reflection components. We found STFT, WT, and ST to be suitable for canceling multiple internal reflection components with marginal altering in SFOAE.

Time/Frequency Analysis of Terrestrial Impack Crater Records

NASA Astrophysics Data System (ADS)

Chang, Heon-Young

2006-09-01

The terrestrial impact cratering record recently has been examined in the time domain by Chang & Moon (2005). It was found that the ˜ 26 Myr periodicity in the impact cratering rate exists over the last ˜ 250 Myrs. Such a periodicity can be found regardless of the lower limit of the diameter up to D ˜ 35 km. It immediately called pros and cons. The aim of this paper is two-fold: (1) to test if reported periodicities can be obtained with an independent method, (2) to see, as attempted earlier, if the phase is modulated. To achieve these goals we employ the time/frequency analysis and for the first time apply this method to the terrestrial impact cratering records. We have confirmed that without exceptions noticeable peaks appear around ˜ 25 Myr, corresponding to a frequency of ˜ 0.04 (Myr)^{-1}. We also find periodicities in the data base including small impact craters, which are longer. Though the time/frequency analysis allows us to observe directly phase variations, we cannot find any indications of such changes. Instead, modes display slow variations of power in time. The time/frequency analysis shows a nonstationary behavior of the modes. The power can grow from just above the noise level and then decrease back to its initial level in a time of order of 10 Myrs.

A comprehensive prediction and evaluation method of pilot workload

PubMed Central

Feng, Chuanyan; Wanyan, Xiaoru; Yang, Kun; Zhuang, Damin; Wu, Xu

2018-01-01

BACKGROUND: The prediction and evaluation of pilot workload is a key problem in human factor airworthiness of cockpit. OBJECTIVE: A pilot traffic pattern task was designed in a flight simulation environment in order to carry out the pilot workload prediction and improve the evaluation method. METHODS: The prediction of typical flight subtasks and dynamic workloads (cruise, approach, and landing) were built up based on multiple resource theory, and a favorable validity was achieved by the correlation analysis verification between sensitive physiological data and the predicted value. RESULTS: Statistical analysis indicated that eye movement indices (fixation frequency, mean fixation time, saccade frequency, mean saccade time, and mean pupil diameter), Electrocardiogram indices (mean normal-to-normal interval and the ratio between low frequency and sum of low frequency and high frequency), and Electrodermal Activity indices (mean tonic and mean phasic) were all sensitive to typical workloads of subjects. CONCLUSION: A multinominal logistic regression model based on combination of physiological indices (fixation frequency, mean normal-to-normal interval, the ratio between low frequency and sum of low frequency and high frequency, and mean tonic) was constructed, and the discriminate accuracy was comparatively ideal with a rate of 84.85%. PMID:29710742

A comprehensive prediction and evaluation method of pilot workload.

PubMed

Feng, Chuanyan; Wanyan, Xiaoru; Yang, Kun; Zhuang, Damin; Wu, Xu

2018-01-01

The prediction and evaluation of pilot workload is a key problem in human factor airworthiness of cockpit. A pilot traffic pattern task was designed in a flight simulation environment in order to carry out the pilot workload prediction and improve the evaluation method. The prediction of typical flight subtasks and dynamic workloads (cruise, approach, and landing) were built up based on multiple resource theory, and a favorable validity was achieved by the correlation analysis verification between sensitive physiological data and the predicted value. Statistical analysis indicated that eye movement indices (fixation frequency, mean fixation time, saccade frequency, mean saccade time, and mean pupil diameter), Electrocardiogram indices (mean normal-to-normal interval and the ratio between low frequency and sum of low frequency and high frequency), and Electrodermal Activity indices (mean tonic and mean phasic) were all sensitive to typical workloads of subjects. A multinominal logistic regression model based on combination of physiological indices (fixation frequency, mean normal-to-normal interval, the ratio between low frequency and sum of low frequency and high frequency, and mean tonic) was constructed, and the discriminate accuracy was comparatively ideal with a rate of 84.85%.

Time-frequency analysis of phonocardiogram signals using wavelet transform: a comparative study.

PubMed

Ergen, Burhan; Tatar, Yetkin; Gulcur, Halil Ozcan

2012-01-01

Analysis of phonocardiogram (PCG) signals provides a non-invasive means to determine the abnormalities caused by cardiovascular system pathology. In general, time-frequency representation (TFR) methods are used to study the PCG signal because it is one of the non-stationary bio-signals. The continuous wavelet transform (CWT) is especially suitable for the analysis of non-stationary signals and to obtain the TFR, due to its high resolution, both in time and in frequency and has recently become a favourite tool. It decomposes a signal in terms of elementary contributions called wavelets, which are shifted and dilated copies of a fixed mother wavelet function, and yields a joint TFR. Although the basic characteristics of the wavelets are similar, each type of the wavelets produces a different TFR. In this study, eight real types of the most known wavelets are examined on typical PCG signals indicating heart abnormalities in order to determine the best wavelet to obtain a reliable TFR. For this purpose, the wavelet energy and frequency spectrum estimations based on the CWT and the spectra of the chosen wavelets were compared with the energy distribution and the autoregressive frequency spectra in order to determine the most suitable wavelet. The results show that Morlet wavelet is the most reliable wavelet for the time-frequency analysis of PCG signals.

A time-frequency classifier for human gait recognition

NASA Astrophysics Data System (ADS)

Mobasseri, Bijan G.; Amin, Moeness G.

2009-05-01

Radar has established itself as an effective all-weather, day or night sensor. Radar signals can penetrate walls and provide information on moving targets. Recently, radar has been used as an effective biometric sensor for classification of gait. The return from a coherent radar system contains a frequency offset in the carrier frequency, known as the Doppler Effect. The movements of arms and legs give rise to micro Doppler which can be clearly detailed in the time-frequency domain using traditional or modern time-frequency signal representation. In this paper we propose a gait classifier based on subspace learning using principal components analysis(PCA). The training set consists of feature vectors defined as either time or frequency snapshots taken from the spectrogram of radar backscatter. We show that gait signature is captured effectively in feature vectors. Feature vectors are then used in training a minimum distance classifier based on Mahalanobis distance metric. Results show that gait classification with high accuracy and short observation window is achievable using the proposed classifier.

Time-frequency analysis of neuronal populations with instantaneous resolution based on noise-assisted multivariate empirical mode decomposition.

PubMed

Alegre-Cortés, J; Soto-Sánchez, C; Pizá, Á G; Albarracín, A L; Farfán, F D; Felice, C J; Fernández, E

2016-07-15

Linear analysis has classically provided powerful tools for understanding the behavior of neural populations, but the neuron responses to real-world stimulation are nonlinear under some conditions, and many neuronal components demonstrate strong nonlinear behavior. In spite of this, temporal and frequency dynamics of neural populations to sensory stimulation have been usually analyzed with linear approaches. In this paper, we propose the use of Noise-Assisted Multivariate Empirical Mode Decomposition (NA-MEMD), a data-driven template-free algorithm, plus the Hilbert transform as a suitable tool for analyzing population oscillatory dynamics in a multi-dimensional space with instantaneous frequency (IF) resolution. The proposed approach was able to extract oscillatory information of neurophysiological data of deep vibrissal nerve and visual cortex multiunit recordings that were not evidenced using linear approaches with fixed bases such as the Fourier analysis. Texture discrimination analysis performance was increased when Noise-Assisted Multivariate Empirical Mode plus Hilbert transform was implemented, compared to linear techniques. Cortical oscillatory population activity was analyzed with precise time-frequency resolution. Similarly, NA-MEMD provided increased time-frequency resolution of cortical oscillatory population activity. Noise-Assisted Multivariate Empirical Mode Decomposition plus Hilbert transform is an improved method to analyze neuronal population oscillatory dynamics overcoming linear and stationary assumptions of classical methods. Copyright © 2016 Elsevier B.V. All rights reserved.

Bladed wheels damage detection through Non-Harmonic Fourier Analysis improved algorithm

NASA Astrophysics Data System (ADS)

Neri, P.

2017-05-01

Recent papers introduced the Non-Harmonic Fourier Analysis for bladed wheels damage detection. This technique showed its potential in estimating the frequency of sinusoidal signals even when the acquisition time is short with respect to the vibration period, provided that some hypothesis are fulfilled. Anyway, previously proposed algorithms showed severe limitations in cracks detection at their early stage. The present paper proposes an improved algorithm which allows to detect a blade vibration frequency shift due to a crack whose size is really small compared to the blade width. Such a technique could be implemented for condition-based maintenance, allowing to use non-contact methods for vibration measurements. A stator-fixed laser sensor could monitor all the blades as they pass in front of the spot, giving precious information about the wheel health. This configuration determines an acquisition time for each blade which become shorter as the machine rotational speed increases. In this situation, traditional Discrete Fourier Transform analysis results in poor frequency resolution, being not suitable for small frequency shift detection. Non-Harmonic Fourier Analysis instead showed high reliability in vibration frequency estimation even with data samples collected in a short time range. A description of the improved algorithm is provided in the paper, along with a comparison with the previous one. Finally, a validation of the method is presented, based on finite element simulations results.

Real time recognition of explosophorous group and explosive material using laser induced photoacoustic spectroscopy associated with novel algorithm for time and frequency domain analysis.

PubMed

El-Sharkawy, Yasser H; Elbasuney, Sherif

2018-06-07

Energy-rich bonds such as nitrates (NO 3 - ) and percholorates (ClO 4 - ) have an explosive nature; they are frequently encountered in high energy materials. These bonds encompass two highly electronegative atoms competing for electrons. Common explosive materials including urea nitrate, ammonium nitrate, and ammonium percholorates were subjected to photoacoustic spectroscopy. The captured signal was processed using novel digital algorithm designed for time and frequency domain analysis. Frequency domain analysis offered not only characteristic frequencies for NO 3 - and ClO 4 - groups; but also characteristic fingerprint spectra (based on thermal, acoustical, and optical properties) for different materials. The main outcome of this study is that phase-shift domain analysis offered an outstanding signature for each explosive material, with novel discrimination between explosive and similar non-explosive material. Photoacoustic spectroscopy offered different characteristic signatures that can be employed for real time detection with stand-off capabilities. There is no two materials could have the same optical, thermal, and acoustical properties. Copyright © 2018 Elsevier B.V. All rights reserved.

Fast time- and frequency-domain finite-element methods for electromagnetic analysis

NASA Astrophysics Data System (ADS)

Lee, Woochan

Fast electromagnetic analysis in time and frequency domain is of critical importance to the design of integrated circuits (IC) and other advanced engineering products and systems. Many IC structures constitute a very large scale problem in modeling and simulation, the size of which also continuously grows with the advancement of the processing technology. This results in numerical problems beyond the reach of existing most powerful computational resources. Different from many other engineering problems, the structure of most ICs is special in the sense that its geometry is of Manhattan type and its dielectrics are layered. Hence, it is important to develop structure-aware algorithms that take advantage of the structure specialties to speed up the computation. In addition, among existing time-domain methods, explicit methods can avoid solving a matrix equation. However, their time step is traditionally restricted by the space step for ensuring the stability of a time-domain simulation. Therefore, making explicit time-domain methods unconditionally stable is important to accelerate the computation. In addition to time-domain methods, frequency-domain methods have suffered from an indefinite system that makes an iterative solution difficult to converge fast. The first contribution of this work is a fast time-domain finite-element algorithm for the analysis and design of very large-scale on-chip circuits. The structure specialty of on-chip circuits such as Manhattan geometry and layered permittivity is preserved in the proposed algorithm. As a result, the large-scale matrix solution encountered in the 3-D circuit analysis is turned into a simple scaling of the solution of a small 1-D matrix, which can be obtained in linear (optimal) complexity with negligible cost. Furthermore, the time step size is not sacrificed, and the total number of time steps to be simulated is also significantly reduced, thus achieving a total cost reduction in CPU time. The second contribution is a new method for making an explicit time-domain finite-element method (TDFEM) unconditionally stable for general electromagnetic analysis. In this method, for a given time step, we find the unstable modes that are the root cause of instability, and deduct them directly from the system matrix resulting from a TDFEM based analysis. As a result, an explicit TDFEM simulation is made stable for an arbitrarily large time step irrespective of the space step. The third contribution is a new method for full-wave applications from low to very high frequencies in a TDFEM based on matrix exponential. In this method, we directly deduct the eigenmodes having large eigenvalues from the system matrix, thus achieving a significantly increased time step in the matrix exponential based TDFEM. The fourth contribution is a new method for transforming the indefinite system matrix of a frequency-domain FEM to a symmetric positive definite one. We deduct non-positive definite component directly from the system matrix resulting from a frequency-domain FEM-based analysis. The resulting new representation of the finite-element operator ensures an iterative solution to converge in a small number of iterations. We then add back the non-positive definite component to synthesize the original solution with negligible cost.

Error Analysis of Clay-Rock Water Content Estimation with Broadband High-Frequency Electromagnetic Sensors—Air Gap Effect

PubMed Central

Bore, Thierry; Wagner, Norman; Delepine Lesoille, Sylvie; Taillade, Frederic; Six, Gonzague; Daout, Franck; Placko, Dominique

2016-01-01

Broadband electromagnetic frequency or time domain sensor techniques present high potential for quantitative water content monitoring in porous media. Prior to in situ application, the impact of the relationship between the broadband electromagnetic properties of the porous material (clay-rock) and the water content on the frequency or time domain sensor response is required. For this purpose, dielectric properties of intact clay rock samples experimental determined in the frequency range from 1 MHz to 10 GHz were used as input data in 3-D numerical frequency domain finite element field calculations to model the one port broadband frequency or time domain transfer function for a three rods based sensor embedded in the clay-rock. The sensor response in terms of the reflection factor was analyzed in time domain with classical travel time analysis in combination with an empirical model according to Topp equation, as well as the theoretical Lichtenecker and Rother model (LRM) to estimate the volumetric water content. The mixture equation considering the appropriate porosity of the investigated material provide a practical and efficient approach for water content estimation based on classical travel time analysis with the onset-method. The inflection method is not recommended for water content estimation in electrical dispersive and absorptive material. Moreover, the results clearly indicate that effects due to coupling of the sensor to the material cannot be neglected. Coupling problems caused by an air gap lead to dramatic effects on water content estimation, even for submillimeter gaps. Thus, the quantitative determination of the in situ water content requires careful sensor installation in order to reach a perfect probe clay rock coupling. PMID:27096865

Error Analysis of Clay-Rock Water Content Estimation with Broadband High-Frequency Electromagnetic Sensors--Air Gap Effect.

PubMed

Bore, Thierry; Wagner, Norman; Lesoille, Sylvie Delepine; Taillade, Frederic; Six, Gonzague; Daout, Franck; Placko, Dominique

2016-04-18

Broadband electromagnetic frequency or time domain sensor techniques present high potential for quantitative water content monitoring in porous media. Prior to in situ application, the impact of the relationship between the broadband electromagnetic properties of the porous material (clay-rock) and the water content on the frequency or time domain sensor response is required. For this purpose, dielectric properties of intact clay rock samples experimental determined in the frequency range from 1 MHz to 10 GHz were used as input data in 3-D numerical frequency domain finite element field calculations to model the one port broadband frequency or time domain transfer function for a three rods based sensor embedded in the clay-rock. The sensor response in terms of the reflection factor was analyzed in time domain with classical travel time analysis in combination with an empirical model according to Topp equation, as well as the theoretical Lichtenecker and Rother model (LRM) to estimate the volumetric water content. The mixture equation considering the appropriate porosity of the investigated material provide a practical and efficient approach for water content estimation based on classical travel time analysis with the onset-method. The inflection method is not recommended for water content estimation in electrical dispersive and absorptive material. Moreover, the results clearly indicate that effects due to coupling of the sensor to the material cannot be neglected. Coupling problems caused by an air gap lead to dramatic effects on water content estimation, even for submillimeter gaps. Thus, the quantitative determination of the in situ water content requires careful sensor installation in order to reach a perfect probe clay rock coupling.

Time-frequency analysis of time-varying modulated signals based on improved energy separation by iterative generalized demodulation

NASA Astrophysics Data System (ADS)

Feng, Zhipeng; Chu, Fulei; Zuo, Ming J.

2011-03-01

Energy separation algorithm is good at tracking instantaneous changes in frequency and amplitude of modulated signals, but it is subject to the constraints of mono-component and narrow band. In most cases, time-varying modulated vibration signals of machinery consist of multiple components, and have so complicated instantaneous frequency trajectories on time-frequency plane that they overlap in frequency domain. For such signals, conventional filters fail to obtain mono-components of narrow band, and their rectangular decomposition of time-frequency plane may split instantaneous frequency trajectories thus resulting in information loss. Regarding the advantage of generalized demodulation method in decomposing multi-component signals into mono-components, an iterative generalized demodulation method is used as a preprocessing tool to separate signals into mono-components, so as to satisfy the requirements by energy separation algorithm. By this improvement, energy separation algorithm can be generalized to a broad range of signals, as long as the instantaneous frequency trajectories of signal components do not intersect on time-frequency plane. Due to the good adaptability of energy separation algorithm to instantaneous changes in signals and the mono-component decomposition nature of generalized demodulation, the derived time-frequency energy distribution has fine resolution and is free from cross term interferences. The good performance of the proposed time-frequency analysis is illustrated by analyses of a simulated signal and the on-site recorded nonstationary vibration signal of a hydroturbine rotor during a shut-down transient process, showing that it has potential to analyze time-varying modulated signals of multi-components.

Array magnetics modal analysis for the DIII-D tokamak based on localized time-series modelling

DOE PAGES

Olofsson, K. Erik J.; Hanson, Jeremy M.; Shiraki, Daisuke; ...

2014-07-14

Here, time-series analysis of magnetics data in tokamaks is typically done using block-based fast Fourier transform methods. This work presents the development and deployment of a new set of algorithms for magnetic probe array analysis. The method is based on an estimation technique known as stochastic subspace identification (SSI). Compared with the standard coherence approach or the direct singular value decomposition approach, the new technique exhibits several beneficial properties. For example, the SSI method does not require that frequencies are orthogonal with respect to the timeframe used in the analysis. Frequencies are obtained directly as parameters of localized time-series models.more » The parameters are extracted by solving small-scale eigenvalue problems. Applications include maximum-likelihood regularized eigenmode pattern estimation, detection of neoclassical tearing modes, including locked mode precursors, and automatic clustering of modes, and magnetics-pattern characterization of sawtooth pre- and postcursors, edge harmonic oscillations and fishbones.« less

Time-domain representation of frequency-dependent foundation impedance functions

USGS Publications Warehouse

Safak, E.

2006-01-01

Foundation impedance functions provide a simple means to account for soil-structure interaction (SSI) when studying seismic response of structures. Impedance functions represent the dynamic stiffness of the soil media surrounding the foundation. The fact that impedance functions are frequency dependent makes it difficult to incorporate SSI in standard time-history analysis software. This paper introduces a simple method to convert frequency-dependent impedance functions into time-domain filters. The method is based on the least-squares approximation of impedance functions by ratios of two complex polynomials. Such ratios are equivalent, in the time-domain, to discrete-time recursive filters, which are simple finite-difference equations giving the relationship between foundation forces and displacements. These filters can easily be incorporated into standard time-history analysis programs. Three examples are presented to show the applications of the method.

Comparison of Signals from Gravitational Wave Detectors with Instantaneous Time-Frequency Maps

NASA Technical Reports Server (NTRS)

Stroeer, A.; Blackburn, L.; Camp, J.

2011-01-01

Gravitational wave astronomy relies on the use of multiple detectors, so that coincident detections may distinguish real signals from instrumental artifacts, and also so that relative timing of signals can provide the sky position of sources. We show that the comparison of instantaneous time-frequency and time-amplitude maps provided by the Hilbert-Huang Transform (HHT) can be used effectively for relative signal timing of common signals, to discriminate between the case of identical coincident signals and random noise coincidences and to provide a classification of signals based on their time-frequency trajectories. The comparison is done with a X(sup 2) goodness-offit method which includes contributions from both the instantaneous amplitude and frequency components of the HHT to match two signals in the time domain. This approach naturally allows the analysis of waveforms with strong frequency modulation.

Automated Bayesian model development for frequency detection in biological time series.

PubMed

Granqvist, Emma; Oldroyd, Giles E D; Morris, Richard J

2011-06-24

A first step in building a mathematical model of a biological system is often the analysis of the temporal behaviour of key quantities. Mathematical relationships between the time and frequency domain, such as Fourier Transforms and wavelets, are commonly used to extract information about the underlying signal from a given time series. This one-to-one mapping from time points to frequencies inherently assumes that both domains contain the complete knowledge of the system. However, for truncated, noisy time series with background trends this unique mapping breaks down and the question reduces to an inference problem of identifying the most probable frequencies. In this paper we build on the method of Bayesian Spectrum Analysis and demonstrate its advantages over conventional methods by applying it to a number of test cases, including two types of biological time series. Firstly, oscillations of calcium in plant root cells in response to microbial symbionts are non-stationary and noisy, posing challenges to data analysis. Secondly, circadian rhythms in gene expression measured over only two cycles highlights the problem of time series with limited length. The results show that the Bayesian frequency detection approach can provide useful results in specific areas where Fourier analysis can be uninformative or misleading. We demonstrate further benefits of the Bayesian approach for time series analysis, such as direct comparison of different hypotheses, inherent estimation of noise levels and parameter precision, and a flexible framework for modelling the data without pre-processing. Modelling in systems biology often builds on the study of time-dependent phenomena. Fourier Transforms are a convenient tool for analysing the frequency domain of time series. However, there are well-known limitations of this method, such as the introduction of spurious frequencies when handling short and noisy time series, and the requirement for uniformly sampled data. Biological time series often deviate significantly from the requirements of optimality for Fourier transformation. In this paper we present an alternative approach based on Bayesian inference. We show the value of placing spectral analysis in the framework of Bayesian inference and demonstrate how model comparison can automate this procedure.

Automated Bayesian model development for frequency detection in biological time series

PubMed Central

2011-01-01

Background A first step in building a mathematical model of a biological system is often the analysis of the temporal behaviour of key quantities. Mathematical relationships between the time and frequency domain, such as Fourier Transforms and wavelets, are commonly used to extract information about the underlying signal from a given time series. This one-to-one mapping from time points to frequencies inherently assumes that both domains contain the complete knowledge of the system. However, for truncated, noisy time series with background trends this unique mapping breaks down and the question reduces to an inference problem of identifying the most probable frequencies. Results In this paper we build on the method of Bayesian Spectrum Analysis and demonstrate its advantages over conventional methods by applying it to a number of test cases, including two types of biological time series. Firstly, oscillations of calcium in plant root cells in response to microbial symbionts are non-stationary and noisy, posing challenges to data analysis. Secondly, circadian rhythms in gene expression measured over only two cycles highlights the problem of time series with limited length. The results show that the Bayesian frequency detection approach can provide useful results in specific areas where Fourier analysis can be uninformative or misleading. We demonstrate further benefits of the Bayesian approach for time series analysis, such as direct comparison of different hypotheses, inherent estimation of noise levels and parameter precision, and a flexible framework for modelling the data without pre-processing. Conclusions Modelling in systems biology often builds on the study of time-dependent phenomena. Fourier Transforms are a convenient tool for analysing the frequency domain of time series. However, there are well-known limitations of this method, such as the introduction of spurious frequencies when handling short and noisy time series, and the requirement for uniformly sampled data. Biological time series often deviate significantly from the requirements of optimality for Fourier transformation. In this paper we present an alternative approach based on Bayesian inference. We show the value of placing spectral analysis in the framework of Bayesian inference and demonstrate how model comparison can automate this procedure. PMID:21702910

EDDIE Seismology: Introductory spectral analysis for undergraduates

NASA Astrophysics Data System (ADS)

Soule, D. C.; Gougis, R.; O'Reilly, C.

2016-12-01

We present a spectral seismology lesson in which students use spectral analysis to describe the frequency of seismic arrivals based on a conceptual presentation of waveforms and filters. The goal is for students to surpass basic waveform terminology and relate a time domain signals to their conjugates in the frequency domain. Although seismology instruction commonly engages students in analysis of authentic seismological data, this is less true for lower-level undergraduate seismology instruction due to coding barriers to many seismological analysis tasks. To address this, our module uses Seismic Canvas (Kroeger, 2015; https://seiscode.iris.washington.edu/projects/seismiccanvas), a graphically interactive application for accessing, viewing and analyzing waveform data, which we use to plot earthquake data in the time domain. Once students are familiarized with the general components of the waveform (i.e. frequency, wavelength, amplitude and period), they use Seismic Canvas to transform the data into the frequency domain. Bypassing the mathematics of Fourier Series allows focus on conceptual understanding by plotting and manipulating seismic data in both time and frequency domains. Pre/post-tests showed significant improvements in students' use of seismograms and spectrograms to estimate the frequency content of the primary wave, which demonstrated students' understanding of frequency and how data on the spectrogram and seismogram are related. Students were also able to identify the time and frequency of the largest amplitude arrival, indicating understanding of amplitude and use of a spectrogram as an analysis tool. Students were also asked to compare plots of raw data and the same data filtered with a high-pass filter, and identify the filter used to create the second plot. Students demonstrated an improved understanding of how frequency content can be removed from a signal in the spectral domain.

Multisensor signal denoising based on matching synchrosqueezing wavelet transform for mechanical fault condition assessment

NASA Astrophysics Data System (ADS)

Yi, Cancan; Lv, Yong; Xiao, Han; Huang, Tao; You, Guanghui

2018-04-01

Since it is difficult to obtain the accurate running status of mechanical equipment with only one sensor, multisensor measurement technology has attracted extensive attention. In the field of mechanical fault diagnosis and condition assessment based on vibration signal analysis, multisensor signal denoising has emerged as an important tool to improve the reliability of the measurement result. A reassignment technique termed the synchrosqueezing wavelet transform (SWT) has obvious superiority in slow time-varying signal representation and denoising for fault diagnosis applications. The SWT uses the time-frequency reassignment scheme, which can provide signal properties in 2D domains (time and frequency). However, when the measured signal contains strong noise components and fast varying instantaneous frequency, the performance of SWT-based analysis still depends on the accuracy of instantaneous frequency estimation. In this paper, a matching synchrosqueezing wavelet transform (MSWT) is investigated as a potential candidate to replace the conventional synchrosqueezing transform for the applications of denoising and fault feature extraction. The improved technology utilizes the comprehensive instantaneous frequency estimation by chirp rate estimation to achieve a highly concentrated time-frequency representation so that the signal resolution can be significantly improved. To exploit inter-channel dependencies, the multisensor denoising strategy is performed by using a modulated multivariate oscillation model to partition the time-frequency domain; then, the common characteristics of the multivariate data can be effectively identified. Furthermore, a modified universal threshold is utilized to remove noise components, while the signal components of interest can be retained. Thus, a novel MSWT-based multisensor signal denoising algorithm is proposed in this paper. The validity of this method is verified by numerical simulation, and experiments including a rolling bearing system and a gear system. The results show that the proposed multisensor matching synchronous squeezing wavelet transform (MMSWT) is superior to existing methods.

[An EMD based time-frequency distribution and its application in EEG analysis].

PubMed

Li, Xiaobing; Chu, Meng; Qiu, Tianshuang; Bao, Haiping

2007-10-01

Hilbert-Huang transform (HHT) is a new time-frequency analytic method to analyze the nonlinear and the non-stationary signals. The key step of this method is the empirical mode decomposition (EMD), with which any complicated signal can be decomposed into a finite and small number of intrinsic mode functions (IMF). In this paper, a new EMD based method for suppressing the cross-term of Wigner-Ville distribution (WVD) is developed and is applied to analyze the epileptic EEG signals. The simulation data and analysis results show that the new method suppresses the cross-term of the WVD effectively with an excellent resolution.

Self spectrum window method in wigner-ville distribution.

PubMed

Liu, Zhongguo; Liu, Changchun; Liu, Boqiang; Lv, Yangsheng; Lei, Yinsheng; Yu, Mengsun

2005-01-01

Wigner-Ville distribution (WVD) is an important type of time-frequency analysis in biomedical signal processing. The cross-term interference in WVD has a disadvantageous influence on its application. In this research, the Self Spectrum Window (SSW) method was put forward to suppress the cross-term interference, based on the fact that the cross-term and auto-WVD- terms in integral kernel function are orthogonal. With the Self Spectrum Window (SSW) algorithm, a real auto-WVD function was used as a template to cross-correlate with the integral kernel function, and the Short Time Fourier Transform (STFT) spectrum of the signal was used as window function to process the WVD in time-frequency plane. The SSW method was confirmed by computer simulation with good analysis results. Satisfactory time- frequency distribution was obtained.

Automated classification of mouse pup isolation syllables: from cluster analysis to an Excel-based "mouse pup syllable classification calculator".

PubMed

Grimsley, Jasmine M S; Gadziola, Marie A; Wenstrup, Jeffrey J

2012-01-01

Mouse pups vocalize at high rates when they are cold or isolated from the nest. The proportions of each syllable type produced carry information about disease state and are being used as behavioral markers for the internal state of animals. Manual classifications of these vocalizations identified 10 syllable types based on their spectro-temporal features. However, manual classification of mouse syllables is time consuming and vulnerable to experimenter bias. This study uses an automated cluster analysis to identify acoustically distinct syllable types produced by CBA/CaJ mouse pups, and then compares the results to prior manual classification methods. The cluster analysis identified two syllable types, based on their frequency bands, that have continuous frequency-time structure, and two syllable types featuring abrupt frequency transitions. Although cluster analysis computed fewer syllable types than manual classification, the clusters represented well the probability distributions of the acoustic features within syllables. These probability distributions indicate that some of the manually classified syllable types are not statistically distinct. The characteristics of the four classified clusters were used to generate a Microsoft Excel-based mouse syllable classifier that rapidly categorizes syllables, with over a 90% match, into the syllable types determined by cluster analysis.

Brain-computer interface using wavelet transformation and naïve bayes classifier.

PubMed

Bassani, Thiago; Nievola, Julio Cesar

2010-01-01

The main purpose of this work is to establish an exploratory approach using electroencephalographic (EEG) signal, analyzing the patterns in the time-frequency plane. This work also aims to optimize the EEG signal analysis through the improvement of classifiers and, eventually, of the BCI performance. In this paper a novel exploratory approach for data mining of EEG signal based on continuous wavelet transformation (CWT) and wavelet coherence (WC) statistical analysis is introduced and applied. The CWT allows the representation of time-frequency patterns of the signal's information content by WC qualiatative analysis. Results suggest that the proposed methodology is capable of identifying regions in time-frequency spectrum during the specified task of BCI. Furthermore, an example of a region is identified, and the patterns are classified using a Naïve Bayes Classifier (NBC). This innovative characteristic of the process justifies the feasibility of the proposed approach to other data mining applications. It can open new physiologic researches in this field and on non stationary time series analysis.

Time-varying metamaterials based on graphene-wrapped microwires: Modeling and potential applications

NASA Astrophysics Data System (ADS)

Salary, Mohammad Mahdi; Jafar-Zanjani, Samad; Mosallaei, Hossein

2018-03-01

The successful realization of metamaterials and metasurfaces requires the judicious choice of constituent elements. In this paper, we demonstrate the implementation of time-varying metamaterials in the terahertz frequency regime by utilizing graphene-wrapped microwires as building blocks and modulation of graphene conductivity through exterior electrical gating. These elements enable enhancement of light-graphene interaction by utilizing optical resonances associated with Mie scattering, yielding a large tunability and modulation depth. We develop a semianalytical framework based on transition-matrix formulation for modeling and analysis of periodic and aperiodic arrays of such time-varying building blocks. The proposed method is validated against full-wave numerical results obtained using the finite-difference time-domain method. It provides an ideal tool for mathematical synthesis and analysis of space-time gradient metamaterials, eliminating the need for computationally expensive numerical models. Moreover, it allows for a wider exploration of exotic space-time scattering phenomena in time-modulated metamaterials. We apply the method to explore the role of modulation parameters in the generation of frequency harmonics and their emerging wavefronts. Several potential applications of such platforms are demonstrated, including frequency conversion, holographic generation of frequency harmonics, and spatiotemporal manipulation of light. The presented results provide key physical insights to design time-modulated functional metadevices using various building blocks and open up new directions in the emerging paradigm of time-modulated metamaterials.

Online frequency estimation with applications to engine and generator sets

NASA Astrophysics Data System (ADS)

Manngård, Mikael; Böling, Jari M.

2017-07-01

Frequency and spectral analysis based on the discrete Fourier transform is a fundamental task in signal processing and machine diagnostics. This paper aims at presenting computationally efficient methods for real-time estimation of stationary and time-varying frequency components in signals. A brief survey of the sliding time window discrete Fourier transform and Goertzel filter is presented, and two filter banks consisting of: (i) sliding time window Goertzel filters (ii) infinite impulse response narrow bandpass filters are proposed for estimating instantaneous frequencies. The proposed methods show excellent results on both simulation studies and on a case study using angular speed data measurements of the crankshaft of a marine diesel engine-generator set.

Bilinear Time-frequency Analysis for Lamb Wave Signal Detected by Electromagnetic Acoustic Transducer

NASA Astrophysics Data System (ADS)

Sun, Wenxiu; Liu, Guoqiang; Xia, Hui; Xia, Zhengwu

2018-03-01

Accurate acquisition of the detection signal travel time plays a very important role in cross-hole tomography. The experimental platform of aluminum plate under the perpendicular magnetic field is established and the bilinear time-frequency analysis methods, Wigner-Ville Distribution (WVD) and the pseudo-Wigner-Ville distribution (PWVD), are applied to analyse the Lamb wave signals detected by electromagnetic acoustic transducer (EMAT). By extracting the same frequency component of the time-frequency spectrum as the excitation frequency, the travel time information can be obtained. In comparison with traditional linear time-frequency analysis method such as short-time Fourier transform (STFT), the bilinear time-frequency analysis method PWVD is more appropriate in extracting travel time and recognizing patterns of Lamb wave.

Laboratory and Modeling Studies of Insect Swarms

DTIC Science & Technology

2016-03-10

and measuring the response. These novel methods allowed us for the first time to characterize precisely properties of the swarm at the group level... Time series for a randomly chosen pair as well as its continuous wavelet transform (CWT; bottom panel). Nearly all of the power in the signal for... based time -frequency analysis to identify such transient interactions, as long as they modified the frequency structure of the insect flight

Multi-component separation and analysis of bat echolocation calls.

PubMed

DiCecco, John; Gaudette, Jason E; Simmons, James A

2013-01-01

The vast majority of animal vocalizations contain multiple frequency modulated (FM) components with varying amounts of non-linear modulation and harmonic instability. This is especially true of biosonar sounds where precise time-frequency templates are essential for neural information processing of echoes. Understanding the dynamic waveform design by bats and other echolocating animals may help to improve the efficacy of man-made sonar through biomimetic design. Bats are known to adapt their call structure based on the echolocation task, proximity to nearby objects, and density of acoustic clutter. To interpret the significance of these changes, a method was developed for component separation and analysis of biosonar waveforms. Techniques for imaging in the time-frequency plane are typically limited due to the uncertainty principle and interference cross terms. This problem is addressed by extending the use of the fractional Fourier transform to isolate each non-linear component for separate analysis. Once separated, empirical mode decomposition can be used to further examine each component. The Hilbert transform may then successfully extract detailed time-frequency information from each isolated component. This multi-component analysis method is applied to the sonar signals of four species of bats recorded in-flight by radiotelemetry along with a comparison of other common time-frequency representations.

Frequency and time properties of decimeter narrowband spikes in solar flares

NASA Astrophysics Data System (ADS)

Wang, Shujuan

2013-07-01

In this paper, we focus to study the frequency and time properties of a group of spikes recorded by the 1.08-2.04 GHz spectrometer of NAOC on 27 October 2003. At the first we calculate the mean and minimum bandwidth of the spikes. We apply two different methods based on the wavelet analysis according to Messmer & Benz (2000). The first method determines the dominant spike bandwidth scale based on their scalegram, and the second method is a feature detection algorithm in the time-frequency plane. Secondly the time profile of each single spike was fitted and analyzed. In particular, we determined the e-folding rise and decay times corresponding to the ascending and decaying parts of the time profile, respectively. Several important correlations were studied and compared with the results in earlier literature, i.e. those between duration and frequency, e-folding rise time and decay time, e-folding decay time and duration, and e-folding decay time and peak flux. Finally some parameters of source region were estimated and the possible decaying mechanism was discussed.

A High-Spin Rate Measurement Method for Projectiles Using a Magnetoresistive Sensor Based on Time-Frequency Domain Analysis.

PubMed

Shang, Jianyu; Deng, Zhihong; Fu, Mengyin; Wang, Shunting

2016-06-16

Traditional artillery guidance can significantly improve the attack accuracy and overall combat efficiency of projectiles, which makes it more adaptable to the information warfare of the future. Obviously, the accurate measurement of artillery spin rate, which has long been regarded as a daunting task, is the basis of precise guidance and control. Magnetoresistive (MR) sensors can be applied to spin rate measurement, especially in the high-spin and high-g projectile launch environment. In this paper, based on the theory of a MR sensor measuring spin rate, the mathematical relationship model between the frequency of MR sensor output and projectile spin rate was established through a fundamental derivation. By analyzing the characteristics of MR sensor output whose frequency varies with time, this paper proposed the Chirp z-Transform (CZT) time-frequency (TF) domain analysis method based on the rolling window of a Blackman window function (BCZT) which can accurately extract the projectile spin rate. To put it into practice, BCZT was applied to measure the spin rate of 155 mm artillery projectile. After extracting the spin rate, the impact that launch rotational angular velocity and aspect angle have on the extraction accuracy of the spin rate was analyzed. Simulation results show that the BCZT TF domain analysis method can effectively and accurately measure the projectile spin rate, especially in a high-spin and high-g projectile launch environment.

Frequency-Locked Detector Threshold Setting Criteria Based on Mean-Time-To-Lose-Lock (MTLL) for GPS Receivers

PubMed Central

Zhao, Na; Qin, Honglei; Sun, Kewen; Ji, Yuanfa

2017-01-01

Frequency-locked detector (FLD) has been widely utilized in tracking loops of Global Positioning System (GPS) receivers to indicate their locking status. The relation between FLD and lock status has been seldom discussed. The traditional PLL experience is not suitable for FLL. In this paper, the threshold setting criteria for frequency-locked detector in the GPS receiver has been proposed by analyzing statistical characteristic of FLD output. The approximate probability distribution of frequency-locked detector is theoretically derived by using a statistical approach, which reveals the relationship between probabilities of frequency-locked detector and the carrier-to-noise ratio (C/N0) of the received GPS signal. The relationship among mean-time-to-lose-lock (MTLL), detection threshold and lock probability related to C/N0 can be further discovered by utilizing this probability. Therefore, a theoretical basis for threshold setting criteria in frequency locked loops for GPS receivers is provided based on mean-time-to-lose-lock analysis. PMID:29207546

Frequency-Locked Detector Threshold Setting Criteria Based on Mean-Time-To-Lose-Lock (MTLL) for GPS Receivers.

PubMed

Jin, Tian; Yuan, Heliang; Zhao, Na; Qin, Honglei; Sun, Kewen; Ji, Yuanfa

2017-12-04

Frequency-locked detector (FLD) has been widely utilized in tracking loops of Global Positioning System (GPS) receivers to indicate their locking status. The relation between FLD and lock status has been seldom discussed. The traditional PLL experience is not suitable for FLL. In this paper, the threshold setting criteria for frequency-locked detector in the GPS receiver has been proposed by analyzing statistical characteristic of FLD output. The approximate probability distribution of frequency-locked detector is theoretically derived by using a statistical approach, which reveals the relationship between probabilities of frequency-locked detector and the carrier-to-noise ratio ( C / N ₀) of the received GPS signal. The relationship among mean-time-to-lose-lock (MTLL), detection threshold and lock probability related to C / N ₀ can be further discovered by utilizing this probability. Therefore, a theoretical basis for threshold setting criteria in frequency locked loops for GPS receivers is provided based on mean-time-to-lose-lock analysis.

Direct comparison of low- and mid-frequency Raman spectroscopy for quantitative solid-state pharmaceutical analysis.

PubMed

Lipiäinen, Tiina; Fraser-Miller, Sara J; Gordon, Keith C; Strachan, Clare J

2018-02-05

This study considers the potential of low-frequency (terahertz) Raman spectroscopy in the quantitative analysis of ternary mixtures of solid-state forms. Direct comparison between low-frequency and mid-frequency spectral regions for quantitative analysis of crystal form mixtures, without confounding sampling and instrumental variations, is reported for the first time. Piroxicam was used as a model drug, and the low-frequency spectra of piroxicam forms β, α2 and monohydrate are presented for the first time. These forms show clear spectral differences in both the low- and mid-frequency regions. Both spectral regions provided quantitative models suitable for predicting the mixture compositions using partial least squares regression (PLSR), but the low-frequency data gave better models, based on lower errors of prediction (2.7, 3.1 and 3.2% root-mean-square errors of prediction [RMSEP] values for the β, α2 and monohydrate forms, respectively) than the mid-frequency data (6.3, 5.4 and 4.8%, for the β, α2 and monohydrate forms, respectively). The better performance of low-frequency Raman analysis was attributed to larger spectral differences between the solid-state forms, combined with a higher signal-to-noise ratio. Copyright © 2017 Elsevier B.V. All rights reserved.

Impact during equine locomotion: techniques for measurement and analysis.

PubMed

Burn, J F; Wilson, A; Nason, G P

1997-05-01

Impact is implicated in the development of several types of musculoskeletal injury in the horse. Characterisation of impact experienced during strenuous exercise is an important first step towards understanding the mechanism for injury. Measurement and analysis of large, short duration impacts is difficult. The measurement system must be able to record transient peaks and high frequencies accurately. The analysis technique must be able to characterise the impact signal in time and frequency. This paper presents a measurement system and analysis technique for the characterisation of large impacts. A piezo-electric accelerometer was securely mounted on the dorsal surface of the horses hoof. Saddle mounted charge amplifiers and a 20 m coaxial cable transferred these data to a PC based logging system. Data were down-loaded onto a UNIX workstation and analysed using a proprietary statistics package. The values of parameters calculated from the time series data were comparable to those of other authors. A wavelet decomposition showed that the frequency profile of the signal changed with time. While most spectral energy was seen at impact, a significant amount of energy was contained in the signal immediately following impact. Over 99% of this energy was contained in frequencies less than 1250 Hz. The sampling rate and the frequency response of a measurement system for recording impact should be chosen carefully to prevent loss or corruption of data. Time scale analysis using a wavelet decomposition is a powerful technique which can be used to characterise impact data. The use of contour plots provides a highly visual representation of the time and frequency localisation of power during impact.

The power grid AGC frequency bias coefficient online identification method based on wide area information

NASA Astrophysics Data System (ADS)

Wang, Zian; Li, Shiguang; Yu, Ting

2015-12-01

This paper propose online identification method of regional frequency deviation coefficient based on the analysis of interconnected grid AGC adjustment response mechanism of regional frequency deviation coefficient and the generator online real-time operation state by measured data through PMU, analyze the optimization method of regional frequency deviation coefficient in case of the actual operation state of the power system and achieve a more accurate and efficient automatic generation control in power system. Verify the validity of the online identification method of regional frequency deviation coefficient by establishing the long-term frequency control simulation model of two-regional interconnected power system.

HRV Analysis to Identify Stages of Home-based Telerehabilitation Exercise.

PubMed

Jeong, In Cheol; Finkelstein, Joseph

2014-01-01

Spectral analysis of heart rate variability (HRV) has been widely used to investigate activity of autonomous nervous system. Previous studies demonstrated potential of analysis of short-term sequences of heart rate data in a time domain for continuous monitoring of levels of physiological stress however the value of HRV parameters in frequency domain for monitoring cycling exercise has not been established. The goal of this study was to assess whether HRV parameters in frequency domain differ depending on a stage of cycling exercise. We compared major HRV parameters in high, low and very low frequency ranges during rest, height of exercise, and recovery during cycling exercise. Our results indicated responsiveness of frequency-domain indices to different phases of cycling exercise program and their potential in monitoring autonomic balance and stress levels as a part of a tailored home-based telerehabilitation program.

Analysis and comparison of safety models using average daily, average hourly, and microscopic traffic.

PubMed

Wang, Ling; Abdel-Aty, Mohamed; Wang, Xuesong; Yu, Rongjie

2018-02-01

There have been plenty of traffic safety studies based on average daily traffic (ADT), average hourly traffic (AHT), or microscopic traffic at 5 min intervals. Nevertheless, not enough research has compared the performance of these three types of safety studies, and seldom of previous studies have intended to find whether the results of one type of study is transferable to the other two studies. First, this study built three models: a Bayesian Poisson-lognormal model to estimate the daily crash frequency using ADT, a Bayesian Poisson-lognormal model to estimate the hourly crash frequency using AHT, and a Bayesian logistic regression model for the real-time safety analysis using microscopic traffic. The model results showed that the crash contributing factors found by different models were comparable but not the same. Four variables, i.e., the logarithm of volume, the standard deviation of speed, the logarithm of segment length, and the existence of diverge segment, were positively significant in the three models. Additionally, weaving segments experienced higher daily and hourly crash frequencies than merge and basic segments. Then, each of the ADT-based, AHT-based, and real-time models was used to estimate safety conditions at different levels: daily and hourly, meanwhile, the real-time model was also used in 5 min intervals. The results uncovered that the ADT- and AHT-based safety models performed similar in predicting daily and hourly crash frequencies, and the real-time safety model was able to provide hourly crash frequency. Copyright © 2017 Elsevier Ltd. All rights reserved.

Combustion Instability in an Acid-Heptane Rocket with a Pressurized-Gas Propellant Pumping System

NASA Technical Reports Server (NTRS)

Tischler, Adelbert O.; Bellman, Donald R.

1951-01-01

Results of experimental measurements of low-frequency combustion instability of a 300-pound thrust acid-heptane rocket engine were compared to the trends predicted by an analysis of combustion instability in a rocket engine with a pressurized-gas propellant pumping system. The simplified analysis, which assumes a monopropellant model, was based on the concept of a combustion the delay occurring from the moment of propellant injection to the moment of propellant combustion. This combustion time delay was experimentally measured; the experimental values were of approximately half the magnitude predicted by the analysis. The pressure-fluctuation frequency for a rocket engine with a characteristic length of 100 inches and operated at a combustion-chamber pressure of 280 pounds per square inch absolute was 38 cycles per second; the analysis indicated. a frequency of 37 cycles per second. Increasing combustion-chamber characteristic length decreased the pressure-fluctuation frequency, in conformity to the analysis. Increasing the chamber operating pressure or increasing the injector pressure drop increased the frequency. These latter two effects are contrary to the analysis; the discrepancies are attributed to the conflict between the assumptions made to simplify the analysis and the experimental conditions. Oxidant-fuel ratio had no apparent effect on the experimentally measured pressure-fluctuation frequency for acid-heptane ratios from 3.0 to 7.0. The frequencies decreased with increased amplitude of the combustion-chamber pressure variations. The analysis indicated that if the combustion time delay were sufficiently short, low-frequency combustion instability would be eliminated.

Cross Time-Frequency Analysis for Combining Information of Several Sources: Application to Estimation of Spontaneous Respiratory Rate from Photoplethysmography

PubMed Central

Peláez-Coca, M. D.; Orini, M.; Lázaro, J.; Bailón, R.; Gil, E.

2013-01-01

A methodology that combines information from several nonstationary biological signals is presented. This methodology is based on time-frequency coherence, that quantifies the similarity of two signals in the time-frequency domain. A cross time-frequency analysis method, based on quadratic time-frequency distribution, has been used for combining information of several nonstationary biomedical signals. In order to evaluate this methodology, the respiratory rate from the photoplethysmographic (PPG) signal is estimated. The respiration provokes simultaneous changes in the pulse interval, amplitude, and width of the PPG signal. This suggests that the combination of information from these sources will improve the accuracy of the estimation of the respiratory rate. Another target of this paper is to implement an algorithm which provides a robust estimation. Therefore, respiratory rate was estimated only in those intervals where the features extracted from the PPG signals are linearly coupled. In 38 spontaneous breathing subjects, among which 7 were characterized by a respiratory rate lower than 0.15 Hz, this methodology provided accurate estimates, with the median error {0.00; 0.98} mHz ({0.00; 0.31}%) and the interquartile range error {4.88; 6.59} mHz ({1.60; 1.92}%). The estimation error of the presented methodology was largely lower than the estimation error obtained without combining different PPG features related to respiration. PMID:24363777

Joint estimation of 2D-DOA and frequency based on space-time matrix and conformal array.

PubMed

Wan, Liang-Tian; Liu, Lu-Tao; Si, Wei-Jian; Tian, Zuo-Xi

2013-01-01

Each element in the conformal array has a different pattern, which leads to the performance deterioration of the conventional high resolution direction-of-arrival (DOA) algorithms. In this paper, a joint frequency and two-dimension DOA (2D-DOA) estimation algorithm for conformal array are proposed. The delay correlation function is used to suppress noise. Both spatial and time sampling are utilized to construct the spatial-time matrix. The frequency and 2D-DOA estimation are accomplished based on parallel factor (PARAFAC) analysis without spectral peak searching and parameter pairing. The proposed algorithm needs only four guiding elements with precise positions to estimate frequency and 2D-DOA. Other instrumental elements can be arranged flexibly on the surface of the carrier. Simulation results demonstrate the effectiveness of the proposed algorithm.

Spectral Entropy Based Neuronal Network Synchronization Analysis Based on Microelectrode Array Measurements

PubMed Central

Kapucu, Fikret E.; Välkki, Inkeri; Mikkonen, Jarno E.; Leone, Chiara; Lenk, Kerstin; Tanskanen, Jarno M. A.; Hyttinen, Jari A. K.

2016-01-01

Synchrony and asynchrony are essential aspects of the functioning of interconnected neuronal cells and networks. New information on neuronal synchronization can be expected to aid in understanding these systems. Synchronization provides insight in the functional connectivity and the spatial distribution of the information processing in the networks. Synchronization is generally studied with time domain analysis of neuronal events, or using direct frequency spectrum analysis, e.g., in specific frequency bands. However, these methods have their pitfalls. Thus, we have previously proposed a method to analyze temporal changes in the complexity of the frequency of signals originating from different network regions. The method is based on the correlation of time varying spectral entropies (SEs). SE assesses the regularity, or complexity, of a time series by quantifying the uniformity of the frequency spectrum distribution. It has been previously employed, e.g., in electroencephalogram analysis. Here, we revisit our correlated spectral entropy method (CorSE), providing evidence of its justification, usability, and benefits. Here, CorSE is assessed with simulations and in vitro microelectrode array (MEA) data. CorSE is first demonstrated with a specifically tailored toy simulation to illustrate how it can identify synchronized populations. To provide a form of validation, the method was tested with simulated data from integrate-and-fire model based computational neuronal networks. To demonstrate the analysis of real data, CorSE was applied on in vitro MEA data measured from rat cortical cell cultures, and the results were compared with three known event based synchronization measures. Finally, we show the usability by tracking the development of networks in dissociated mouse cortical cell cultures. The results show that temporal correlations in frequency spectrum distributions reflect the network relations of neuronal populations. In the simulated data, CorSE unraveled the synchronizations. With the real in vitro MEA data, CorSE produced biologically plausible results. Since CorSE analyses continuous data, it is not affected by possibly poor spike or other event detection quality. We conclude that CorSE can reveal neuronal network synchronization based on in vitro MEA field potential measurements. CorSE is expected to be equally applicable also in the analysis of corresponding in vivo and ex vivo data analysis. PMID:27803660

Photonic microwave waveforms generation based on pulse carving and superposition in time-domain

NASA Astrophysics Data System (ADS)

Xia, Yi; Jiang, Yang; Zi, Yuejiao; He, Yutong; Tian, Jing; Zhang, Xiaoyu; Luo, Hao; Dong, Ruyang

2018-05-01

A novel photonic approach for various microwave waveforms generation based on time-domain synthesis is theoretically analyzed and experimentally investigated. In this scheme, two single-drive Mach-Zehnder modulators are used for pulses shaping. After shifting the phase and implementing envelopes superposition of the pulses, desired waveforms can be achieved in time-domain. The theoretic analysis and simulations are presented. In the experimental demonstrations, a triangular waveform, square waveform, and half duty cycle sawtooth (or reversed-sawtooth) waveform are generated successfully. By utilizing time multiplexing technique, a frequency-doubled sawtooth (or reversed-sawtooth) waveform with 100% duty cycle can be obtained. In addition, a fundamental frequency sawtooth (or reversed-sawtooth) waveform with 100% duty cycle can also be achieved by the superposition of square waveform and frequency-doubled sawtooth waveform.

The Fourier decomposition method for nonlinear and non-stationary time series analysis

PubMed Central

Joshi, Shiv Dutt; Patney, Rakesh Kumar; Saha, Kaushik

2017-01-01

for many decades, there has been a general perception in the literature that Fourier methods are not suitable for the analysis of nonlinear and non-stationary data. In this paper, we propose a novel and adaptive Fourier decomposition method (FDM), based on the Fourier theory, and demonstrate its efficacy for the analysis of nonlinear and non-stationary time series. The proposed FDM decomposes any data into a small number of ‘Fourier intrinsic band functions’ (FIBFs). The FDM presents a generalized Fourier expansion with variable amplitudes and variable frequencies of a time series by the Fourier method itself. We propose an idea of zero-phase filter bank-based multivariate FDM (MFDM), for the analysis of multivariate nonlinear and non-stationary time series, using the FDM. We also present an algorithm to obtain cut-off frequencies for MFDM. The proposed MFDM generates a finite number of band-limited multivariate FIBFs (MFIBFs). The MFDM preserves some intrinsic physical properties of the multivariate data, such as scale alignment, trend and instantaneous frequency. The proposed methods provide a time–frequency–energy (TFE) distribution that reveals the intrinsic structure of a data. Numerical computations and simulations have been carried out and comparison is made with the empirical mode decomposition algorithms. PMID:28413352

FPGA-based multi-channel fluorescence lifetime analysis of Fourier multiplexed frequency-sweeping lifetime imaging

PubMed Central

Zhao, Ming; Li, Yu; Peng, Leilei

2014-01-01

We report a fast non-iterative lifetime data analysis method for the Fourier multiplexed frequency-sweeping confocal FLIM (Fm-FLIM) system [ Opt. Express22, 10221 ( 2014)24921725]. The new method, named R-method, allows fast multi-channel lifetime image analysis in the system’s FPGA data processing board. Experimental tests proved that the performance of the R-method is equivalent to that of single-exponential iterative fitting, and its sensitivity is well suited for time-lapse FLIM-FRET imaging of live cells, for example cyclic adenosine monophosphate (cAMP) level imaging with GFP-Epac-mCherry sensors. With the R-method and its FPGA implementation, multi-channel lifetime images can now be generated in real time on the multi-channel frequency-sweeping FLIM system, and live readout of FRET sensors can be performed during time-lapse imaging. PMID:25321778

Weak Fault Feature Extraction of Rolling Bearings Based on an Improved Kurtogram.

PubMed

Chen, Xianglong; Feng, Fuzhou; Zhang, Bingzhi

2016-09-13

Kurtograms have been verified to be an efficient tool in bearing fault detection and diagnosis because of their superiority in extracting transient features. However, the short-time Fourier Transform is insufficient in time-frequency analysis and kurtosis is deficient in detecting cyclic transients. Those factors weaken the performance of the original kurtogram in extracting weak fault features. Correlated Kurtosis (CK) is then designed, as a more effective solution, in detecting cyclic transients. Redundant Second Generation Wavelet Packet Transform (RSGWPT) is deemed to be effective in capturing more detailed local time-frequency description of the signal, and restricting the frequency aliasing components of the analysis results. The authors in this manuscript, combining the CK with the RSGWPT, propose an improved kurtogram to extract weak fault features from bearing vibration signals. The analysis of simulation signals and real application cases demonstrate that the proposed method is relatively more accurate and effective in extracting weak fault features.

On the Analysis Methods for the Time Domain and Frequency Domain Response of a Buried Objects*

NASA Astrophysics Data System (ADS)

Poljak, Dragan; Šesnić, Silvestar; Cvetković, Mario

2014-05-01

There has been a continuous interest in the analysis of ground-penetrating radar systems and related applications in civil engineering [1]. Consequently, a deeper insight of scattering phenomena occurring in a lossy half-space, as well as the development of sophisticated numerical methods based on Finite Difference Time Domain (FDTD) method, Finite Element Method (FEM), Boundary Element Method (BEM), Method of Moments (MoM) and various hybrid methods, is required, e.g. [2], [3]. The present paper deals with certain techniques for time and frequency domain analysis, respectively, of buried conducting and dielectric objects. Time domain analysis is related to the assessment of a transient response of a horizontal straight thin wire buried in a lossy half-space using a rigorous antenna theory (AT) approach. The AT approach is based on the space-time integral equation of the Pocklington type (time domain electric field integral equation for thin wires). The influence of the earth-air interface is taken into account via the simplified reflection coefficient arising from the Modified Image Theory (MIT). The obtained results for the transient current induced along the electrode due to the transmitted plane wave excitation are compared to the numerical results calculated via an approximate transmission line (TL) approach and the AT approach based on the space-frequency variant of the Pocklington integro-differential approach, respectively. It is worth noting that the space-frequency Pocklington equation is numerically solved via the Galerkin-Bubnov variant of the Indirect Boundary Element Method (GB-IBEM) and the corresponding transient response is obtained by the aid of inverse fast Fourier transform (IFFT). The results calculated by means of different approaches agree satisfactorily. Frequency domain analysis is related to the assessment of frequency domain response of dielectric sphere using the full wave model based on the set of coupled electric field integral equations for surfaces. The numerical solution is carried out by means of the improved variant of the Method of Moments (MoM) providing numerically stable and an efficient procedure for the extraction of singularities arising in integral expressions. The proposed analysis method is compared to the results obtained by using some commercial software packages. A satisfactory agreement has been achieved. Both approaches discussed throughout this work and demonstrated on canonical geometries could be also useful for benchmark purpose. References [1] L. Pajewski et al., Applications of Ground Penetrating Radar in Civil Engineering - COST Action TU1208, 2013. [2] U. Oguz, L. Gurel, Frequency Responses of Ground-Penetrating Radars Operating Over Highly Lossy Grounds, IEEE Trans. Geosci. and Remote sensing, Vol. 40, No 6, 2002. [3] D.Poljak, Advanced Modeling in Computational electromagnetic Compatibility, John Wiley and Sons, New York 2007. *This work benefited from networking activities carried out within the EU funded COST Action TU1208 "Civil Engineering Applications of Ground Penetrating Radar."

Frequency domain analysis of knock images

NASA Astrophysics Data System (ADS)

Qi, Yunliang; He, Xin; Wang, Zhi; Wang, Jianxin

2014-12-01

High speed imaging-based knock analysis has mainly focused on time domain information, e.g. the spark triggered flame speed, the time when end gas auto-ignition occurs and the end gas flame speed after auto-ignition. This study presents a frequency domain analysis on the knock images recorded using a high speed camera with direct photography in a rapid compression machine (RCM). To clearly visualize the pressure wave oscillation in the combustion chamber, the images were high-pass-filtered to extract the luminosity oscillation. The luminosity spectrum was then obtained by applying fast Fourier transform (FFT) to three basic colour components (red, green and blue) of the high-pass-filtered images. Compared to the pressure spectrum, the luminosity spectra better identify the resonant modes of pressure wave oscillation. More importantly, the resonant mode shapes can be clearly visualized by reconstructing the images based on the amplitudes of luminosity spectra at the corresponding resonant frequencies, which agree well with the analytical solutions for mode shapes of gas vibration in a cylindrical cavity.

Time Correlations and the Frequency Spectrum of Sound Radiated by Turbulent Flows

NASA Technical Reports Server (NTRS)

Rubinstein, Robert; Zhou, Ye

1997-01-01

Theories of turbulent time correlations are applied to compute frequency spectra of sound radiated by isotropic turbulence and by turbulent shear flows. The hypothesis that Eulerian time correlations are dominated by the sweeping action of the most energetic scales implies that the frequency spectrum of the sound radiated by isotropic turbulence scales as omega(exp 4) for low frequencies and as omega(exp -3/4) for high frequencies. The sweeping hypothesis is applied to an approximate theory of jet noise. The high frequency noise again scales as omega(exp -3/4), but the low frequency spectrum scales as omega(exp 2). In comparison, a classical theory of jet noise based on dimensional analysis gives omega(exp -2) and omega(exp 2) scaling for these frequency ranges. It is shown that the omega(exp -2) scaling is obtained by simplifying the description of turbulent time correlations. An approximate theory of the effect of shear on turbulent time correlations is developed and applied to the frequency spectrum of sound radiated by shear turbulence. The predicted steepening of the shear dominated spectrum appears to be consistent with jet noise measurements.

Age-dependent seizures of absence epilepsy and sleep spindles dynamics in WAG/Rij rats

NASA Astrophysics Data System (ADS)

Grubov, Vadim V.; Sitnikova, Evgenia Y.; Pavlov, Alexey N.; Khramova, Marina V.; Koronovskii, Alexey A.; Hramov, Alexander E.

2015-03-01

In the given paper, a relation between time-frequency characteristics of sleep spindles and the age-dependent epileptic activity in WAG/Rij rats is discussed. Analysis of sleep spindles based on the continuous wavelet transform is performed for rats of different ages. It is shown that the epileptic activity affects the time-frequency intrinsic dynamics of sleep spindles.

Analysis of photonic Doppler velocimetry data based on the continuous wavelet transform

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu Shouxian; Wang Detian; Li Tao

2011-02-15

The short time Fourier transform (STFT) cannot resolve rapid velocity changes in most photonic Doppler velocimetry (PDV) data. A practical analysis method based on the continuous wavelet transform (CWT) was presented to overcome this difficulty. The adaptability of the wavelet family predicates that the continuous wavelet transform uses an adaptive time window to estimate the instantaneous frequency of signals. The local frequencies of signal are accurately determined by finding the ridge in the spectrogram of the CWT and then are converted to target velocity according to the Doppler effects. A performance comparison between the CWT and STFT is demonstrated bymore » a plate-impact experiment data. The results illustrate that the new method is automatic and adequate for analysis of PDV data.« less

Research on vibration signal of engine based on subband energy method

NASA Astrophysics Data System (ADS)

Wu, Chunmei; Cui, Feng; Zhao, Yong; Fu, Baohong; Ma, Junchi; Yang, Guihua

2017-04-01

Based on the research of DA462 type engine cylinder and cylinder head vibration signal of the surface, the signal measured in the time domain and frequency domain are analyzed in detail, draw the following conclusions: the analysis of vibration signal of the subband energy method is applied to the engine, the concentration response of each of the motivation band can clearly be seen. Through the analysis we can see that the combustion excitation frequency response from 0k to 1K, the vibration influence on the body piston lateral impact force is mainly concentrated in 2K˜5K frequency range of Hz, valve opening and closing the excitation response frequency is mainly concentrated in the 3K˜4K range of Hz, and thus locating the valve clearance fault. This method is simple, accurate and practical for the post processing and analysis of vibration signals.

Report of geomagnetic pulsation indices for space weather applications

USGS Publications Warehouse

Xu, Z.; Gannon, Jennifer L.; Rigler, Erin J.

2013-01-01

The phenomenon of ultra-low frequency geomagnetic pulsations was first observed in the ground-based measurements of the 1859 Carrington Event and has been studied for over 100 years. Pulsation frequency is considered to be “ultra” low when it is lower than the natural frequencies of the plasma, such as the ion gyrofrequency. Ultra-low frequency pulsations are considered a source of noise in some geophysical analysis techniques, such as aeromagnetic surveys and transient electromagnetics, so it is critical to develop near real-time space weather products to monitor these geomagnetic pulsations. The proper spectral analysis of magnetometer data, such as using wavelet analysis techniques, can also be important to Geomagnetically Induced Current risk assessment.

Nonstationary Dynamics Data Analysis with Wavelet-SVD Filtering

NASA Technical Reports Server (NTRS)

Brenner, Marty; Groutage, Dale; Bessette, Denis (Technical Monitor)

2001-01-01

Nonstationary time-frequency analysis is used for identification and classification of aeroelastic and aeroservoelastic dynamics. Time-frequency multiscale wavelet processing generates discrete energy density distributions. The distributions are processed using the singular value decomposition (SVD). Discrete density functions derived from the SVD generate moments that detect the principal features in the data. The SVD standard basis vectors are applied and then compared with a transformed-SVD, or TSVD, which reduces the number of features into more compact energy density concentrations. Finally, from the feature extraction, wavelet-based modal parameter estimation is applied.

The instantaneous frequency rate spectrogram

NASA Astrophysics Data System (ADS)

Czarnecki, Krzysztof

2016-01-01

An accelerogram of the instantaneous phase of signal components referred to as an instantaneous frequency rate spectrogram (IFRS) is presented as a joint time-frequency distribution. The distribution is directly obtained by processing the short-time Fourier transform (STFT) locally. A novel approach to amplitude demodulation based upon the reassignment method is introduced as a useful by-product. Additionally, an estimator of energy density versus the instantaneous frequency rate (IFR) is proposed and referred to as the IFR profile. The energy density is estimated based upon both the classical energy spectrogram and the IFRS smoothened by the median filter. Moreover, the impact of an analyzing window width, additive white Gaussian noise and observation time is tested. Finally, the introduced method is used for the analysis of the acoustic emission of an automotive engine. The recording of the engine of a Lamborghini Gallardo is analyzed as an example.

Windowed and Wavelet Analysis of Marine Stratocumulus Cloud Inhomogeneity

NASA Technical Reports Server (NTRS)

Gollmer, Steven M.; Harshvardhan; Cahalan, Robert F.; Snider, Jack B.

1995-01-01

To improve radiative transfer calculations for inhomogeneous clouds, a consistent means of modeling inhomogeneity is needed. One current method of modeling cloud inhomogeneity is through the use of fractal parameters. This method is based on the supposition that cloud inhomogeneity over a large range of scales is related. An analysis technique named wavelet analysis provides a means of studying the multiscale nature of cloud inhomogeneity. In this paper, the authors discuss the analysis and modeling of cloud inhomogeneity through the use of wavelet analysis. Wavelet analysis as well as other windowed analysis techniques are used to study liquid water path (LWP) measurements obtained during the marine stratocumulus phase of the First ISCCP (International Satellite Cloud Climatology Project) Regional Experiment. Statistics obtained using analysis windows, which are translated to span the LWP dataset, are used to study the local (small scale) properties of the cloud field as well as their time dependence. The LWP data are transformed onto an orthogonal wavelet basis that represents the data as a number of times series. Each of these time series lies within a frequency band and has a mean frequency that is half the frequency of the previous band. Wavelet analysis combined with translated analysis windows reveals that the local standard deviation of each frequency band is correlated with the local standard deviation of the other frequency bands. The ratio between the standard deviation of adjacent frequency bands is 0.9 and remains constant with respect to time. This ratio defined as the variance coupling parameter is applicable to all of the frequency bands studied and appears to be related to the slope of the data's power spectrum. Similar analyses are performed on two cloud inhomogeneity models, which use fractal-based concepts to introduce inhomogeneity into a uniform cloud field. The bounded cascade model does this by iteratively redistributing LWP at each scale using the value of the local mean. This model is reformulated into a wavelet multiresolution framework, thereby presenting a number of variants of the bounded cascade model. One variant introduced in this paper is the 'variance coupled model,' which redistributes LWP using the local standard deviation and the variance coupling parameter. While the bounded cascade model provides an elegant two- parameter model for generating cloud inhomogeneity, the multiresolution framework provides more flexibility at the expense of model complexity. Comparisons are made with the results from the LWP data analysis to demonstrate both the strengths and weaknesses of these models.

A time-based potential step analysis of electrochemical impedance incorporating a constant phase element: a study of commercially pure titanium in phosphate buffered saline.

PubMed

Ehrensberger, Mark T; Gilbert, Jeremy L

2010-05-01

The measurement of electrochemical impedance is a valuable tool to assess the electrochemical environment that exists at the surface of metallic biomaterials. This article describes the development and validation of a new technique, potential step impedance analysis (PSIA), to assess the electrochemical impedance of materials whose interface with solution can be modeled as a simplified Randles circuit that is modified with a constant phase element. PSIA is based upon applying a step change in voltage to a working electrode and analyzing the subsequent current transient response in a combined time and frequency domain technique. The solution resistance, polarization resistance, and interfacial capacitance are found directly in the time domain. The experimental current transient is numerically transformed to the frequency domain to determine the constant phase exponent, alpha. This combined time and frequency approach was tested using current transients generated from computer simulations, from resistor-capacitor breadboard circuits, and from commercially pure titanium samples immersed in phosphate buffered saline and polarized at -800 mV or +1000 mV versus Ag/AgCl. It was shown that PSIA calculates equivalent admittance and impedance behavior over this range of potentials when compared to standard electrochemical impedance spectroscopy. This current transient approach characterizes the frequency response of the system without the need for expensive frequency response analyzers or software. Copyright 2009 Wiley Periodicals, Inc.

Vibration Sensor Data Denoising Using a Time-Frequency Manifold for Machinery Fault Diagnosis

PubMed Central

He, Qingbo; Wang, Xiangxiang; Zhou, Qiang

2014-01-01

Vibration sensor data from a mechanical system are often associated with important measurement information useful for machinery fault diagnosis. However, in practice the existence of background noise makes it difficult to identify the fault signature from the sensing data. This paper introduces the time-frequency manifold (TFM) concept into sensor data denoising and proposes a novel denoising method for reliable machinery fault diagnosis. The TFM signature reflects the intrinsic time-frequency structure of a non-stationary signal. The proposed method intends to realize data denoising by synthesizing the TFM using time-frequency synthesis and phase space reconstruction (PSR) synthesis. Due to the merits of the TFM in noise suppression and resolution enhancement, the denoised signal would have satisfactory denoising effects, as well as inherent time-frequency structure keeping. Moreover, this paper presents a clustering-based statistical parameter to evaluate the proposed method, and also presents a new diagnostic approach, called frequency probability time series (FPTS) spectral analysis, to show its effectiveness in fault diagnosis. The proposed TFM-based data denoising method has been employed to deal with a set of vibration sensor data from defective bearings, and the results verify that for machinery fault diagnosis the method is superior to two traditional denoising methods. PMID:24379045

A High-Spin Rate Measurement Method for Projectiles Using a Magnetoresistive Sensor Based on Time-Frequency Domain Analysis

PubMed Central

Shang, Jianyu; Deng, Zhihong; Fu, Mengyin; Wang, Shunting

2016-01-01

Traditional artillery guidance can significantly improve the attack accuracy and overall combat efficiency of projectiles, which makes it more adaptable to the information warfare of the future. Obviously, the accurate measurement of artillery spin rate, which has long been regarded as a daunting task, is the basis of precise guidance and control. Magnetoresistive (MR) sensors can be applied to spin rate measurement, especially in the high-spin and high-g projectile launch environment. In this paper, based on the theory of a MR sensor measuring spin rate, the mathematical relationship model between the frequency of MR sensor output and projectile spin rate was established through a fundamental derivation. By analyzing the characteristics of MR sensor output whose frequency varies with time, this paper proposed the Chirp z-Transform (CZT) time-frequency (TF) domain analysis method based on the rolling window of a Blackman window function (BCZT) which can accurately extract the projectile spin rate. To put it into practice, BCZT was applied to measure the spin rate of 155 mm artillery projectile. After extracting the spin rate, the impact that launch rotational angular velocity and aspect angle have on the extraction accuracy of the spin rate was analyzed. Simulation results show that the BCZT TF domain analysis method can effectively and accurately measure the projectile spin rate, especially in a high-spin and high-g projectile launch environment. PMID:27322266

Full waveform inversion in the frequency domain using classified time-domain residual wavefields

NASA Astrophysics Data System (ADS)

Son, Woohyun; Koo, Nam-Hyung; Kim, Byoung-Yeop; Lee, Ho-Young; Joo, Yonghwan

2017-04-01

We perform the acoustic full waveform inversion in the frequency domain using residual wavefields that have been separated in the time domain. We sort the residual wavefields in the time domain according to the order of absolute amplitudes. Then, the residual wavefields are separated into several groups in the time domain. To analyze the characteristics of the residual wavefields, we compare the residual wavefields of conventional method with those of our residual separation method. From the residual analysis, the amplitude spectrum obtained from the trace before separation appears to have little energy at the lower frequency bands. However, the amplitude spectrum obtained from our strategy is regularized by the separation process, which means that the low-frequency components are emphasized. Therefore, our method helps to emphasize low-frequency components of residual wavefields. Then, we generate the frequency-domain residual wavefields by taking the Fourier transform of the separated time-domain residual wavefields. With these wavefields, we perform the gradient-based full waveform inversion in the frequency domain using back-propagation technique. Through a comparison of gradient directions, we confirm that our separation method can better describe the sub-salt image than the conventional approach. The proposed method is tested on the SEG/EAGE salt-dome model. The inversion results show that our algorithm is better than the conventional gradient based waveform inversion in the frequency domain, especially for deeper parts of the velocity model.

TIME-FREQUENCY ANALYSIS OF THE SUPERORBITAL MODULATION OF THE X-RAY BINARY SMC X-1 USING THE HILBERT-HUANG TRANSFORM

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hu, Chin-Ping; Chou, Yi; Yang, Ting-Chang

2011-10-20

The high-mass X-ray binary SMC X-1 exhibits a superorbital modulation with a dramatically varying period ranging between {approx}40 days and {approx}60 days. This research studies the time-frequency properties of the superorbital modulation of SMC X-1 based on the observations made by the All-Sky Monitor (ASM) onboard the Rossi X-ray Timing Explorer (RXTE). We analyzed the entire ASM database collected since 1996. The Hilbert-Huang transform (HHT), developed for non-stationary and nonlinear time-series analysis, was adopted to derive the instantaneous superorbital frequency. The resultant Hilbert spectrum is consistent with the dynamic power spectrum as it shows more detailed information in both themore » time and frequency domains. The RXTE observations show that the superorbital modulation period was mostly between {approx}50 days and {approx}65 days, whereas it changed to {approx}45 days around MJD 50,800 and MJD 54,000. Our analysis further indicates that the instantaneous frequency changed to a timescale of hundreds of days between {approx}MJD 51,500 and {approx}MJD 53,500. Based on the instantaneous phase defined by HHT, we folded the ASM light curve to derive a superorbital profile, from which an asymmetric feature and a low state with barely any X-ray emissions (lasting for {approx}0.3 cycles) were observed. We also calculated the correlation between the mean period and the amplitude of the superorbital modulation. The result is similar to the recently discovered relationship between the superorbital cycle length and the mean X-ray flux for Her X-1.« less

Effect of train carbody's parameters on vertical bending stiffness performance

NASA Astrophysics Data System (ADS)

Yang, Guangwu; Wang, Changke; Xiang, Futeng; Xiao, Shoune

2016-10-01

Finite element analysis(FEA) and modal test are main methods to give the first-order vertical bending vibration frequency of train carbody at present, but they are inefficiency and waste plenty of time. Based on Timoshenko beam theory, the bending deformation, moment of inertia and shear deformation are considered. Carbody is divided into some parts with the same length, and it's stiffness is calculated with series principle, it's cross section area, moment of inertia and shear shape coefficient is equivalent by segment length, and the fimal corrected first-order vertical bending vibration frequency analytical formula is deduced. There are 6 simple carbodies and 1 real carbody as examples to test the formula, all analysis frequencies are very close to their FEA frequencies, and especially for the real carbody, the error between analysis and experiment frequency is 0.75%. Based on the analytic formula, sensitivity analysis of the real carbody's design parameters is done, and some main parameters are found. The series principle of carbody stiffness is introduced into Timoshenko beam theory to deduce a formula, which can estimate the first-order vertical bending vibration frequency of carbody quickly without traditional FEA method and provide a reference to design engineers.

a Signal-Tuned Gabor Transform with Application to Eeg Analysis

NASA Astrophysics Data System (ADS)

Torreão, José R. A.; Victer, Silvia M. C.; Fernandes, João L.

2013-04-01

We introduce a time-frequency transform based on Gabor functions whose parameters are given by the Fourier transform of the analyzed signal. At any given frequency, the width and the phase of the Gabor function are obtained, respectively, from the magnitude and the phase of the signal's corresponding Fourier component, yielding an analyzing kernel which is a representation of the signal's content at that particular frequency. The resulting Gabor transform tunes itself to the input signal, allowing the accurate detection of time and frequency events, even in situations where the traditional Gabor and S-transform approaches tend to fail. This is the case, for instance, when considering the time-frequency representation of electroencephalogram traces (EEG) of epileptic subjects, as illustrated by the experimental study presented here.

Comparison of the results of refractometric measurements in the process of diffusion, obtained by means of the backgroundoriented schlieren method and the holographic interferometry method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kraiskii, A V; Mironova, T V

2015-08-31

The results of the study of interdiffusion of two liquids, obtained using the holographic recording scheme with a nonstationary reference wave with the frequency linearly varying in space and time are compared with the results of correlation processing of digital photographs, made with a random background screen. The spatio-temporal behaviour of the signal in four basic representations ('space – temporal frequency', 'space – time', 'spatial frequency – temporal frequency' and 'spatial frequency – time') is found in the holographic experiment and calculated (in the appropriate coordinates) based on the background-oriented schlieren method. Practical coincidence of the results of the correlationmore » analysis and the holographic double-exposure interferometry is demonstrated. (interferometry)« less

Short-time fractional Fourier methods for the time-frequency representation of chirp signals.

PubMed

Capus, Chris; Brown, Keith

2003-06-01

The fractional Fourier transform (FrFT) provides a valuable tool for the analysis of linear chirp signals. This paper develops two short-time FrFT variants which are suited to the analysis of multicomponent and nonlinear chirp signals. Outputs have similar properties to the short-time Fourier transform (STFT) but show improved time-frequency resolution. The FrFT is a parameterized transform with parameter, a, related to chirp rate. The two short-time implementations differ in how the value of a is chosen. In the first, a global optimization procedure selects one value of a with reference to the entire signal. In the second, a values are selected independently for each windowed section. Comparative variance measures based on the Gaussian function are given and are shown to be consistent with the uncertainty principle in fractional domains. For appropriately chosen FrFT orders, the derived fractional domain uncertainty relationship is minimized for Gaussian windowed linear chirp signals. The two short-time FrFT algorithms have complementary strengths demonstrated by time-frequency representations for a multicomponent bat chirp, a highly nonlinear quadratic chirp, and an output pulse from a finite-difference sonar model with dispersive change. These representations illustrate the improvements obtained in using FrFT based algorithms compared to the STFT.

A visual parallel-BCI speller based on the time-frequency coding strategy.

PubMed

Xu, Minpeng; Chen, Long; Zhang, Lixin; Qi, Hongzhi; Ma, Lan; Tang, Jiabei; Wan, Baikun; Ming, Dong

2014-04-01

Spelling is one of the most important issues in brain-computer interface (BCI) research. This paper is to develop a visual parallel-BCI speller system based on the time-frequency coding strategy in which the sub-speller switching among four simultaneously presented sub-spellers and the character selection are identified in a parallel mode. The parallel-BCI speller was constituted by four independent P300+SSVEP-B (P300 plus SSVEP blocking) spellers with different flicker frequencies, thereby all characters had a specific time-frequency code. To verify its effectiveness, 11 subjects were involved in the offline and online spellings. A classification strategy was designed to recognize the target character through jointly using the canonical correlation analysis and stepwise linear discriminant analysis. Online spellings showed that the proposed parallel-BCI speller had a high performance, reaching the highest information transfer rate of 67.4 bit min(-1), with an average of 54.0 bit min(-1) and 43.0 bit min(-1) in the three rounds and five rounds, respectively. The results indicated that the proposed parallel-BCI could be effectively controlled by users with attention shifting fluently among the sub-spellers, and highly improved the BCI spelling performance.

Analysis of cardiac signals using spatial filling index and time-frequency domain

PubMed Central

Faust, Oliver; Acharya U, Rajendra; Krishnan, SM; Min, Lim Choo

2004-01-01

Background Analysis of heart rate variation (HRV) has become a popular noninvasive tool for assessing the activities of the autonomic nervous system (ANS). HRV analysis is based on the concept that fast fluctuations may specifically reflect changes of sympathetic and vagal activity. It shows that the structure generating the signal is not simply linear, but also involves nonlinear contributions. These signals are essentially non-stationary; may contain indicators of current disease, or even warnings about impending diseases. The indicators may be present at all times or may occur at random in the time scale. However, to study and pinpoint abnormalities in voluminous data collected over several hours is strenuous and time consuming. Methods This paper presents the spatial filling index and time-frequency analysis of heart rate variability signal for disease identification. Renyi's entropy is evaluated for the signal in the Wigner-Ville and Continuous Wavelet Transformation (CWT) domain. Results This Renyi's entropy gives lower 'p' value for scalogram than Wigner-Ville distribution and also, the contours of scalogram visually show the features of the diseases. And in the time-frequency analysis, the Renyi's entropy gives better result for scalogram than the Wigner-Ville distribution. Conclusion Spatial filling index and Renyi's entropy has distinct regions for various diseases with an accuracy of more than 95%. PMID:15361254

Joint time-frequency analysis of EEG signals based on a phase-space interpretation of the recording process

NASA Astrophysics Data System (ADS)

Testorf, M. E.; Jobst, B. C.; Kleen, J. K.; Titiz, A.; Guillory, S.; Scott, R.; Bujarski, K. A.; Roberts, D. W.; Holmes, G. L.; Lenck-Santini, P.-P.

2012-10-01

Time-frequency transforms are used to identify events in clinical EEG data. Data are recorded as part of a study for correlating the performance of human subjects during a memory task with pathological events in the EEG, called spikes. The spectrogram and the scalogram are reviewed as tools for evaluating spike activity. A statistical evaluation of the continuous wavelet transform across trials is used to quantify phase-locking events. For simultaneously improving the time and frequency resolution, and for representing the EEG of several channels or trials in a single time-frequency plane, a multichannel matching pursuit algorithm is used. Fundamental properties of the algorithm are discussed as well as preliminary results, which were obtained with clinical EEG data.

Extracting Micro-Doppler Radar Signatures from Rotating Targets Using Fourier-Bessel Transform and Time-Frequency Analysis

DTIC Science & Technology

2014-10-16

Time-Frequency analysis, Short-Time Fourier Transform, Wigner Ville Distribution, Fourier Bessel Transform, Fractional Fourier Transform. I...INTRODUCTION Most widely used time-frequency transforms are short-time Fourier Transform (STFT) and Wigner Ville distribution (WVD). In STFT, time and...frequency resolutions are limited by the size of window function used in calculating STFT. For mono-component signals, WVD gives the best time and frequency

Ultrasonic Data Display and Analysis System Developed (Including Fuzzy Logic Analysis) for the Windows-Based PC

NASA Technical Reports Server (NTRS)

Lovelace, Jeffrey J.; Cios, Kryzsztof J.; Roth, Don J.; cAO, wEI n.

2001-01-01

Post-Scan Interactive Data Display (PSIDD) III is a user-oriented Windows-based system that facilitates the display and comparison of ultrasonic contact measurement data obtained at NASA Glenn Research Center's Ultrasonic Nondestructive Evaluation measurement facility. The system is optimized to compare ultrasonic measurements made at different locations within a material or at different stages of material degradation. PSIDD III provides complete analysis of the primary waveforms in the time and frequency domains along with the calculation of several frequency-dependent properties including phase velocity and attenuation coefficient and several frequency-independent properties, like the cross correlation velocity. The system allows image generation on all the frequency-dependent properties at any available frequency (limited by the bandwidth used in the scans) and on any of the frequency-independent properties. From ultrasonic contact scans, areas of interest on an image can be studied with regard to underlying raw waveforms and derived ultrasonic properties by simply selecting the point on the image. The system offers various modes of indepth comparison between scan points. Up to five scan points can be selected for comparative analysis at once. The system was developed with Borland Delphi software (Visual Pascal) and is based on an SQL data base. It is ideal for the classification of material properties or the location of microstructure variations in materials. Along with the ultrasonic contact measurement software that it is partnered with, this system is technology ready and can be transferred to users worldwide.

Vibration analysis based on electronic stroboscopic speckle-shearing pattern interferometry

NASA Astrophysics Data System (ADS)

Jia, Dagong; Yu, Changsong; Xu, Tianhua; Jin, Chao; Zhang, Hongxia; Jing, Wencai; Zhang, Yimo

2008-12-01

In this paper, an electronic speckle-shearing pattern interferometer with pulsed laser and pulse frequency controller is fabricated. The principle of measuring the vibration in the object using electronic stroboscopic speckle--shearing pattern interferometer is analyzed. Using a metal plate, the edge of which is clamped, as an experimental specimen, the shear interferogram are obtained under two experimental frequencies, 100 Hz and 200 Hz. At the same time, the vibration of this metal plate under the same experimental conditions is measured using the time-average method in order to test the performance of this electronic stroboscopic speckle-shearing pattern interferometer. The result indicated that the fringe of shear interferogram become dense with the experimental frequency increasing. Compared the fringe pattern obtained by the stroboscopic method with the fringe obtained by the time-average method, the shearing interferogram of stroboscopic method is clearer than the time-average method. In addition, both the time-average method and stroboscopic method are suited for qualitative analysis for the vibration of the object. More over, the stroboscopic method is well adapted to quantitative vibration analysis.

On the potential of Galileo E5 for time transfer.

PubMed

Martínez-Belda, Mari Carmen; Defraigne, Pascale; Bruyninx, Carine

2013-01-01

The main global navigation satellite systems (GNSS) technique currently used for accurate time and frequency transfer is based on an analysis of the ionosphere-free combinations of dual-frequency code and carrier phase measurements in a precise point positioning (PPP) mode. This technique analyses the observations of one GNSS station using external products for satellite clocks and orbits to determine the position and clock synchronization errors of this station. The frequency stability of this time transfer is limited by the noise and multipath of the Global Positioning System (GPS) and Globalnaya Navigatsionnaya Sputnikovaya Sistema (GLONASS) codes. In the near future, Galileo will offer a broadband signal E5, with low noise in the centimeter range and with the lowest multipath error ever observed. This paper investigates new analysis procedures based on the E5 codeplus- carrier (CPC) combination for time transfer. The CPC combination with E5 provides a noise level 10 times lower than the ionosphere-free combination of Galileo E1 and E5, which is very promising for improving GNSS time transfer performances. From some tests with simulated Galileo data, it is shown here that the use of the CPC combination with E5 does not improve, at present, the medium- and long-term stability of time transfer with respect to the ionosphere-free combination of Galileo E1 and E5 codes, because of the need for a second frequency signal to correct for the ionospheric delays and ambiguities.

Speech transformations based on a sinusoidal representation

NASA Astrophysics Data System (ADS)

Quatieri, T. E.; McAulay, R. J.

1986-05-01

A new speech analysis/synthesis technique is presented which provides the basis for a general class of speech transformation including time-scale modification, frequency scaling, and pitch modification. These modifications can be performed with a time-varying change, permitting continuous adjustment of a speaker's fundamental frequency and rate of articulation. The method is based on a sinusoidal representation of the speech production mechanism that has been shown to produce synthetic speech that preserves the waveform shape and is essentially perceptually indistinguishable from the original. Although the analysis/synthesis system originally was designed for single-speaker signals, it is equally capable of recovering and modifying nonspeech signals such as music; multiple speakers, marine biologic sounds, and speakers in the presence of interferences such as noise and musical backgrounds.

EMD-WVD time-frequency distribution for analysis of multi-component signals

NASA Astrophysics Data System (ADS)

Chai, Yunzi; Zhang, Xudong

2016-10-01

Time-frequency distribution (TFD) is two-dimensional function that indicates the time-varying frequency content of one-dimensional signals. And The Wigner-Ville distribution (WVD) is an important and effective time-frequency analysis method. The WVD can efficiently show the characteristic of a mono-component signal. However, a major drawback is the extra cross-terms when multi-component signals are analyzed by WVD. In order to eliminating the cross-terms, we decompose signals into single frequency components - Intrinsic Mode Function (IMF) - by using the Empirical Mode decomposition (EMD) first, then use WVD to analyze each single IMF. In this paper, we define this new time-frequency distribution as EMD-WVD. And the experiment results show that the proposed time-frequency method can solve the cross-terms problem effectively and improve the accuracy of WVD time-frequency analysis.

Time-frequency analysis in optical coherence tomography for technical objects examination

NASA Astrophysics Data System (ADS)

StrÄ kowski, Marcin R.; Kraszewski, Maciej; Trojanowski, Michał; Pluciński, Jerzy

2014-05-01

Optical coherence tomography (OCT) is one of the most advanced optical measurement techniques for complex structure visualization. The advantages of OCT have been used for surface and subsurface defect detection in composite materials, polymers, ceramics, non-metallic protective coatings, and many more. Our research activity has been focused on timefrequency spectroscopic analysis in OCT. It is based on time resolved spectral analysis of the backscattered optical signal delivered by the OCT. The time-frequency method gives spectral characteristic of optical radiation backscattered or backreflected from the particular points inside the tested device. This provides more information about the sample, which are useful for further analysis. Nowadays, the applications of spectroscopic analysis for composite layers characterization or tissue recognition have been reported. During our studies we have found new applications of spectroscopic analysis. We have used this method for thickness estimation of thin films, which are under the resolution of OCT. Also, we have combined the spectroscopic analysis with polarization sensitive OCT (PS-OCT). This approach enables to obtain a multiorder retardation value directly and may become a breakthrough in PS-OCT measurements of highly birefringent media. In this work, we present the time-frequency spectroscopic algorithms and their applications for OCT. Also, the theoretical simulations and measurement validation of this method are shown.

Safety analytics for integrating crash frequency and real-time risk modeling for expressways.

PubMed

Wang, Ling; Abdel-Aty, Mohamed; Lee, Jaeyoung

2017-07-01

To find crash contributing factors, there have been numerous crash frequency and real-time safety studies, but such studies have been conducted independently. Until this point, no researcher has simultaneously analyzed crash frequency and real-time crash risk to test whether integrating them could better explain crash occurrence. Therefore, this study aims at integrating crash frequency and real-time safety analyses using expressway data. A Bayesian integrated model and a non-integrated model were built: the integrated model linked the crash frequency and the real-time models by adding the logarithm of the estimated expected crash frequency in the real-time model; the non-integrated model independently estimated the crash frequency and the real-time crash risk. The results showed that the integrated model outperformed the non-integrated model, as it provided much better model results for both the crash frequency and the real-time models. This result indicated that the added component, the logarithm of the expected crash frequency, successfully linked and provided useful information to the two models. This study uncovered few variables that are not typically included in the crash frequency analysis. For example, the average daily standard deviation of speed, which was aggregated based on speed at 1-min intervals, had a positive effect on crash frequency. In conclusion, this study suggested a methodology to improve the crash frequency and real-time models by integrating them, and it might inspire future researchers to understand crash mechanisms better. Copyright © 2017 Elsevier Ltd. All rights reserved.

PSIDD3: Post-Scan Ultrasonic Data Display System for the Windows-Based PC Including Fuzzy Logic Analysis

NASA Technical Reports Server (NTRS)

Lovelace, Jeffrey J.; Cios, Krzysztof J.; Roth, Don J.; Cao, Wei

2000-01-01

Post-Scan Interactive Data Display (PSIDD) III is a user-oriented Windows-based system that facilitates the display and comparison of ultrasonic contact data. The system is optimized to compare ultrasonic measurements made at different locations within a material or at different stages of material degradation. PSIDD III provides complete analysis of the primary wave forms in the time and frequency domains along with the calculation of several frequency dependent properties including Phase Velocity and Attenuation Coefficient and several frequency independent properties, like the Cross Correlation Velocity. The system allows image generation on all of the frequency dependent properties at any available frequency (limited by the bandwidth used in the scans) and on any of the frequency independent properties. From ultrasonic contact scans, areas of interest on an image can be studied with regard to underlying raw waveforms and derived ultrasonic properties by simply selecting the point on the image. The system offers various modes of in-depth comparison between scan points. Up to five scan points can be selected for comparative analysis at once. The system was developed with Borland Delphi software (Visual Pascal) and is based on a SQL database. It is ideal for classification of material properties, or location of microstructure variations in materials.

How High Frequency Trading Affects a Market Index

PubMed Central

Kenett, Dror Y.; Ben-Jacob, Eshel; Stanley, H. Eugene; gur-Gershgoren, Gitit

2013-01-01

The relationship between a market index and its constituent stocks is complicated. While an index is a weighted average of its constituent stocks, when the investigated time scale is one day or longer the index has been found to have a stronger effect on the stocks than vice versa. We explore how this interaction changes in short time scales using high frequency data. Using a correlation-based analysis approach, we find that in short time scales stocks have a stronger influence on the index. These findings have implications for high frequency trading and suggest that the price of an index should be published on shorter time scales, as close as possible to those of the actual transaction time scale. PMID:23817553

Detection of epileptiform activity in EEG signals based on time-frequency and non-linear analysis

PubMed Central

Gajic, Dragoljub; Djurovic, Zeljko; Gligorijevic, Jovan; Di Gennaro, Stefano; Savic-Gajic, Ivana

2015-01-01

We present a new technique for detection of epileptiform activity in EEG signals. After preprocessing of EEG signals we extract representative features in time, frequency and time-frequency domain as well as using non-linear analysis. The features are extracted in a few frequency sub-bands of clinical interest since these sub-bands showed much better discriminatory characteristics compared with the whole frequency band. Then we optimally reduce the dimension of feature space to two using scatter matrices. A decision about the presence of epileptiform activity in EEG signals is made by quadratic classifiers designed in the reduced two-dimensional feature space. The accuracy of the technique was tested on three sets of electroencephalographic (EEG) signals recorded at the University Hospital Bonn: surface EEG signals from healthy volunteers, intracranial EEG signals from the epilepsy patients during the seizure free interval from within the seizure focus and intracranial EEG signals of epileptic seizures also from within the seizure focus. An overall detection accuracy of 98.7% was achieved. PMID:25852534

Fiber optic sensor for continuous health monitoring in CFRP composite materials

NASA Astrophysics Data System (ADS)

Rippert, Laurent; Papy, Jean-Michel; Wevers, Martine; Van Huffel, Sabine

2002-07-01

An intensity modulated sensor, based on the microbending concept, has been incorporated in laminates produced from a C/epoxy prepreg. Pencil lead break tests (Hsu-Neilsen sources) and tensile tests have been performed on this material. In this research study, fibre optic sensors will be proven to offer an alternative for the robust piezoelectric transducers used for Acoustic Emission (AE) monitoring. The main emphasis has been put on the use of advanced signal processing techniques based on time-frequency analysis. The signal Short Time Fourier Transform (STFT) has been computed and several robust noise reduction algorithms, such as Wiener adaptive filtering, improved spectral subtraction filtering, and Singular Value Decomposition (SVD) -based filtering, have been applied. An energy and frequency -based detection criterion is put forward to detect transient signals that can be correlated with Modal Acoustic Emission (MAE) results and thus damage in the composite material. There is a strong indication that time-frequency analysis and the Hankel Total Least Squares (HTLS) method can also be used for damage characterization. This study shows that the signal from a quite simple microbend optical sensor contains information on the elastic energy released whenever damage is being introduced in the host material by mechanical loading. Robust algorithms can be used to retrieve and analyze this information.

Novel high-frequency, high-power, pulsed oscillator based on a transmission line transformer.

PubMed

Burdt, R; Curry, R D

2007-07-01

Recent analysis and experiments have demonstrated the potential for transmission line transformers to be employed as compact, high-frequency, high-power, pulsed oscillators with variable rise time, high output impedance, and high operating efficiency. A prototype system was fabricated and tested that generates a damped sinusoidal wave form at a center frequency of 4 MHz into a 200 Omega load, with operating efficiency above 90% and peak power on the order of 10 MW. The initial rise time of the pulse is variable and two experiments were conducted to demonstrate initial rise times of 12 and 3 ns, corresponding to a spectral content from 4-30 and from 4-100 MHz, respectively. A SPICE model has been developed to accurately predict the circuit behavior and scaling laws have been identified to allow for circuit design at higher frequencies and higher peak power. The applications, circuit analysis, test stand, experimental results, circuit modeling, and design of future systems are all discussed.

Wavelet-based group and phase velocity measurements: Method

NASA Astrophysics Data System (ADS)

Yang, H. Y.; Wang, W. W.; Hung, S. H.

2016-12-01

Measurements of group and phase velocities of surface waves are often carried out by applying a series of narrow bandpass or stationary Gaussian filters localized at specific frequencies to wave packets and estimating the corresponding arrival times at the peak envelopes and phases of the Fourier spectra. However, it's known that seismic waves are inherently nonstationary and not well represented by a sum of sinusoids. Alternatively, a continuous wavelet transform (CWT) which decomposes a time series into a family of wavelets, translated and scaled copies of a generally fast oscillating and decaying function known as the mother wavelet, is capable of retaining localization in both the time and frequency domain and well-suited for the time-frequency analysis of nonstationary signals. Here we develop a wavelet-based method to measure frequency-dependent group and phase velocities, an essential dataset used in crust and mantle tomography. For a given time series, we employ the complex morlet wavelet to obtain the scalogram of amplitude modulus |Wg| and phase φ on the time-frequency plane. The instantaneous frequency (IF) is then calculated by taking the derivative of phase with respect to time, i.e., (1/2π)dφ(f, t)/dt. Time windows comprising strong energy arrivals to be measured can be identified by those IFs close to the frequencies with the maximum modulus and varying smoothly and monotonically with time. The respective IFs in each selected time window are further interpolated to yield a smooth branch of ridge points or representative IFs at which the arrival time, tridge(f), and phase, φridge(f), after unwrapping and correcting cycle skipping based on a priori knowledge of the possible velocity range, are determined for group and phase velocity estimation. We will demonstrate our measurement method using both ambient noise cross correlation functions and multi-mode surface waves from earthquakes. The obtained dispersion curves will be compared with those by a conventional narrow bandpass method.

Methodology for processing pressure traces used as inputs for combustion analyses in diesel engines

NASA Astrophysics Data System (ADS)

Rašić, Davor; Vihar, Rok; Žvar Baškovič, Urban; Katrašnik, Tomaž

2017-05-01

This study proposes a novel methodology for designing an optimum equiripple finite impulse response (FIR) filter for processing in-cylinder pressure traces of a diesel internal combustion engine, which serve as inputs for high-precision combustion analyses. The proposed automated workflow is based on an innovative approach of determining the transition band frequencies and optimum filter order. The methodology is based on discrete Fourier transform analysis, which is the first step to estimate the location of the pass-band and stop-band frequencies. The second step uses short-time Fourier transform analysis to refine the estimated aforementioned frequencies. These pass-band and stop-band frequencies are further used to determine the most appropriate FIR filter order. The most widely used existing methods for estimating the FIR filter order are not effective in suppressing the oscillations in the rate- of-heat-release (ROHR) trace, thus hindering the accuracy of combustion analyses. To address this problem, an innovative method for determining the order of an FIR filter is proposed in this study. This method is based on the minimization of the integral of normalized signal-to-noise differences between the stop-band frequency and the Nyquist frequency. Developed filters were validated using spectral analysis and calculation of the ROHR. The validation results showed that the filters designed using the proposed innovative method were superior compared with those using the existing methods for all analyzed cases. Highlights • Pressure traces of a diesel engine were processed by finite impulse response (FIR) filters with different orders • Transition band frequencies were determined with an innovative method based on discrete Fourier transform and short-time Fourier transform • Spectral analyses showed deficiencies of existing methods in determining the FIR filter order • A new method of determining the FIR filter order for processing pressure traces was proposed • The efficiency of the new method was demonstrated by spectral analyses and calculations of rate-of-heat-release traces

Wear detection by means of wavelet-based acoustic emission analysis

NASA Astrophysics Data System (ADS)

Baccar, D.; Söffker, D.

2015-08-01

Wear detection and monitoring during operation are complex and difficult tasks especially for materials under sliding conditions. Due to the permanent contact and repetitive motion, the material surface remains during tests non-accessible for optical inspection so that attrition of the contact partners cannot be easily detected. This paper introduces the relevant scientific components of reliable and efficient condition monitoring system for online detection and automated classification of wear phenomena by means of acoustic emission (AE) and advanced signal processing approaches. The related experiments were performed using a tribological system consisting of two martensitic plates, sliding against each other. High sensitive piezoelectric transducer was used to provide the continuous measurement of AE signals. The recorded AE signals were analyzed mainly by time-frequency analysis. A feature extraction module using a novel combination of Short-Time Fourier Transform (STFT) and Continuous Wavelet Transform (CWT) were used for the first time. A detailed correlation analysis between complex signal characteristics and the surface damage resulting from contact fatigue was investigated. Three wear process stages were detected and could be distinguished. To obtain quantitative and detailed information about different wear phases, the AE energy was calculated using STFT and decomposed into a suitable number of frequency levels. The individual energy distribution and the cumulative AE energy of each frequency components were analyzed using CWT. Results show that the behavior of individual frequency component changes when the wear state changes. Here, specific frequency ranges are attributed to the different wear states. The study reveals that the application of the STFT-/CWT-based AE analysis is an appropriate approach to distinguish and to interpret the different damage states occurred during sliding contact. Based on this results a new generation of condition monitoring systems can be build, able to evaluate automatically the surface condition of machine components with sliding surfaces.

Capture of activation during ventricular arrhythmia using distributed stimulation.

PubMed

Meunier, Jason M; Ramalingam, Sanjiv; Lin, Shien-Fong; Patwardhan, Abhijit R

2007-04-01

Results of previous studies suggest that pacing strength stimuli can capture activation during ventricular arrhythmia locally near pacing sites. The existence of spatio-temporal distribution of excitable gap during arrhythmia suggests that multiple and timed stimuli delivered over a region may permit capture over larger areas. Our objective in this study was to evaluate the efficacy of using spatially distributed pacing (DP) to capture activation during ventricular arrhythmia. Data were obtained from rabbit hearts which were placed against a lattice of parallel wires through which biphasic pacing stimuli were delivered. Electrical activity was recorded optically. Pacing stimuli were delivered in sequence through the parallel wires starting with the wire closest to the apex and ending with one closest to the base. Inter-stimulus delay was based on conduction velocity. Time-frequency analysis of optical signals was used to determine variability in activation. A decrease in standard deviation of dominant frequencies of activation from a grid of locations that spanned the captured area and a concurrence with paced frequency were used as an index of capture. Results from five animals showed that the average standard deviation decreased from 0.81 Hz during arrhythmia to 0.66 Hz during DP at pacing cycle length of 125 ms (p = 0.03) reflecting decreased spatio-temporal variability in activation during DP. Results of time-frequency analysis during these pacing trials showed agreement between activation and paced frequencies. These results show that spatially distributed and timed stimulation can be used to modify and capture activation during ventricular arrhythmia.

Weak Fault Feature Extraction of Rolling Bearings Based on an Improved Kurtogram

PubMed Central

Chen, Xianglong; Feng, Fuzhou; Zhang, Bingzhi

2016-01-01

Kurtograms have been verified to be an efficient tool in bearing fault detection and diagnosis because of their superiority in extracting transient features. However, the short-time Fourier Transform is insufficient in time-frequency analysis and kurtosis is deficient in detecting cyclic transients. Those factors weaken the performance of the original kurtogram in extracting weak fault features. Correlated Kurtosis (CK) is then designed, as a more effective solution, in detecting cyclic transients. Redundant Second Generation Wavelet Packet Transform (RSGWPT) is deemed to be effective in capturing more detailed local time-frequency description of the signal, and restricting the frequency aliasing components of the analysis results. The authors in this manuscript, combining the CK with the RSGWPT, propose an improved kurtogram to extract weak fault features from bearing vibration signals. The analysis of simulation signals and real application cases demonstrate that the proposed method is relatively more accurate and effective in extracting weak fault features. PMID:27649171

Time-frequency characterisation of paediatric heart sounds

NASA Astrophysics Data System (ADS)

Leung, Terence Sze-Tat

1998-08-01

The operation of the heart can be monitored by the sounds it emits. Structural defects or malfunction of the heart valves will cause additional abnormal sounds such as murmurs and ejection clicks. This thesis aims to characterise the heart sounds of three groups of children who either have an Atrial Septal Defect (ASD), a Ventricular Septal Defect (VSD), or are normal. Two aspects of heart sounds have been specifically investigated; the time-frequency analysis of systolic murmurs and the identification of splitting patterns in the second heart sound. The analysis is based on 42 paediatric heart sound recordings. Murmurs are sounds generated by turbulent flow of blood in the heart. They can be found in patients with both pathological and non-pathological conditions. The acoustic quality of the murmurs generated in each heart condition are different. The first aspect of this work is to characterise the three types of murmurs in the time- frequency domain. Modern time-frequency methods including, the Wigner-Ville Distribution, Smoothed Pseudo Wigner-Ville Distribution, Choi-Williams Distribution and spectrogram have been applied to characterise the murmurs. It was found that the three classes of murmurs exhibited different signatures in their time-frequency representations. By performing Discriminant Analysis, it was shown that spectral features extracted from the time- frequency representations can be used to distinguish between the three classes. The second aspect of the research is to identify splitting patterns in the second heart sound, which consists of two acoustic components due to the closure of the aortic valve and pulmonary valve. The aortic valve usually closes before the pulmonary valve, introducing a time delay known as 'split'. The split normally varies in duration over the respiratory cycle. In certain pathologies such as the ASD, the split becomes fixed over the respiration cycle. A technique based on adaptive signal decomposition is developed to measure the split and hence to identify the splitting pattern as either 'variable' or 'fixed'. This work has successfully characterised the murmurs and splitting patterns in the three groups of patients. Features extracted can be used for diagnostic purposes.

Differential neural responses to acupuncture revealed by MEG using wavelet-based time-frequency analysis: a pilot study.

PubMed

You, Youbo; Bai, Lijun; Dai, Ruwei; Xue, Ting; Zhong, Chongguang; Feng, Yuanyuan; Wang, Hu; Liu, Zhenyu; Tian, Jie

2011-01-01

Acupoint specificity, lying at the core of the Traditional Chinese Medicine, still faces many controversies. As previous neuroimaging studies on acupuncture mainly adopted relatively low time-resolution functional magnetic resonance imaging (fMRI) technology and inappropriate block-designed experimental paradigm due to sustained effect, in the current study, we employed a single block-designed paradigm together with high temporal-resolution magnetoencephalography (MEG) technology. We applied time-frequency analysis based upon Morlet wavelet transforming approach to detect differential oscillatory brain dynamics induced by acupuncture at Stomach Meridian 36 (ST36) using a nearby nonacupoint (NAP) as control condition. We observed that frequency power changes were mainly restricted to delta band for both ST36 group and NAP group. Consistently increased delta band power in contralateral temporal regions and decreased power in the counterparts of ipsilateral hemisphere were detected following stimulation at ST36 on the right leg. Compared with ST36, no significant delta ranges were found in temporal regions in NAP group, illustrating different oscillatory brain patterns. Our results may provide additional evidence to support the specificity of acupuncture modulation effects.

Dating a tropical ice core by time-frequency analysis of ion concentration depth profiles

NASA Astrophysics Data System (ADS)

Gay, M.; De Angelis, M.; Lacoume, J.-L.

2014-09-01

Ice core dating is a key parameter for the interpretation of the ice archives. However, the relationship between ice depth and ice age generally cannot be easily established and requires the combination of numerous investigations and/or modelling efforts. This paper presents a new approach to ice core dating based on time-frequency analysis of chemical profiles at a site where seasonal patterns may be significantly distorted by sporadic events of regional importance, specifically at the summit area of Nevado Illimani (6350 m a.s.l.), located in the eastern Bolivian Andes (16°37' S, 67°46' W). We used ion concentration depth profiles collected along a 100 m deep ice core. The results of Fourier time-frequency and wavelet transforms were first compared. Both methods were applied to a nitrate concentration depth profile. The resulting chronologies were checked by comparison with the multi-proxy year-by-year dating published by de Angelis et al. (2003) and with volcanic tie points. With this first experiment, we demonstrated the efficiency of Fourier time-frequency analysis when tracking the nitrate natural variability. In addition, we were able to show spectrum aliasing due to under-sampling below 70 m. In this article, we propose a method of de-aliasing which significantly improves the core dating in comparison with annual layer manual counting. Fourier time-frequency analysis was applied to concentration depth profiles of seven other ions, providing information on the suitability of each of them for the dating of tropical Andean ice cores.

Single photon detection and signal analysis for high sensitivity dosimetry based on optically stimulated luminescence with beryllium oxide

NASA Astrophysics Data System (ADS)

Radtke, J.; Sponner, J.; Jakobi, C.; Schneider, J.; Sommer, M.; Teichmann, T.; Ullrich, W.; Henniger, J.; Kormoll, T.

2018-01-01

Single photon detection applied to optically stimulated luminescence (OSL) dosimetry is a promising approach due to the low level of luminescence light and the known statistical behavior of single photon events. Time resolved detection allows to apply a variety of different and independent data analysis methods. Furthermore, using amplitude modulated stimulation impresses time- and frequency information into the OSL light and therefore allows for additional means of analysis. Considering the impressed frequency information, data analysis by using Fourier transform algorithms or other digital filters can be used for separating the OSL signal from unwanted light or events generated by other phenomena. This potentially lowers the detection limits of low dose measurements and might improve the reproducibility and stability of obtained data. In this work, an OSL system based on a single photon detector, a fast and accurate stimulation unit and an FPGA is presented. Different analysis algorithms which are applied to the single photon data are discussed.

Correlation between audible noise and corona current generated by AC corona discharge in time and frequency domains

NASA Astrophysics Data System (ADS)

Li, Xuebao; Wang, Jing; Li, Yinfei; Zhang, Qian; Lu, Tiebing; Cui, Xiang

2018-06-01

Corona-generated audible noise is induced by the collisions between space charges and air molecules. It has been proven that there is a close correlation between audible noise and corona current from DC corona discharge. Analysis on the correlation between audible noise and corona current can promote the cognition of the generation mechanism of corona discharge. In this paper, time-domain waveforms of AC corona-generated audible noise and corona current are measured simultaneously. The one-to-one relationship between sound pressure pulses and corona current pulses can be found and is used to remove the interferences from background noise. After the interferences are removed, the linear correlated relationships between sound pressure pulse amplitude and corona current pulse amplitude are obtained through statistical analysis. Besides, frequency components at the harmonics of power frequency (50 Hz) can be found both in the frequency spectrums of audible noise and corona current through frequency analysis. Furthermore, the self-correlation relationships between harmonic components below 400 Hz with the 50 Hz component are analyzed for audible noise and corona current and corresponding empirical formulas are proposed to calculate the harmonic components based on the 50 Hz component. Finally, based on the AC corona discharge process and generation mechanism of audible noise and corona current, the correlation between audible noise and corona current in time domain and frequency domain are interpreted qualitatively. Besides, with the aid of analytical expressions of periodic square waves, sound pressure pulses, and corona current pulses, the modulation effects from the AC voltage on the pulse trains are used to interpret the generation of the harmonic components of audible noise and corona current.

Coalescence computations for large samples drawn from populations of time-varying sizes

PubMed Central

Polanski, Andrzej; Szczesna, Agnieszka; Garbulowski, Mateusz; Kimmel, Marek

2017-01-01

We present new results concerning probability distributions of times in the coalescence tree and expected allele frequencies for coalescent with large sample size. The obtained results are based on computational methodologies, which involve combining coalescence time scale changes with techniques of integral transformations and using analytical formulae for infinite products. We show applications of the proposed methodologies for computing probability distributions of times in the coalescence tree and their limits, for evaluation of accuracy of approximate expressions for times in the coalescence tree and expected allele frequencies, and for analysis of large human mitochondrial DNA dataset. PMID:28170404

Low-frequency wideband vibration energy harvesting by using frequency up-conversion and quin-stable nonlinearity

NASA Astrophysics Data System (ADS)

Wang, Chen; Zhang, Qichang; Wang, Wei

2017-07-01

This work presents models and experiments of an impact-driven and frequency up-converted wideband piezoelectric-based vibration energy harvester with a quintuple-well potential induced by the combination effect of magnetic nonlinearity and mechanical piecewise-linearity. Analysis shows that the interwell motions during coupled vibration period enable to increase electrical power output in comparison to conventional frequency up-conversion technology. Besides, the quintuple-well potential with shallower potential wells could extend the harvester's operating bandwidth to lower frequencies. Experiments demonstrate our proposed approach can dramatically boost the measured power of the energy harvester as much as 35 times while its lower cut-off frequency is two times lower than that of a conventional counterpart. These results reveal our proposed approach shows promise for powering portable wireless smart devices from low-intensity, low-frequency vibration sources.

Validation of PC-based Sound Card with Biopac for Digitalization of ECG Recording in Short-term HRV Analysis.

PubMed

Maheshkumar, K; Dilara, K; Maruthy, K N; Sundareswaren, L

2016-07-01

Heart rate variability (HRV) analysis is a simple and noninvasive technique capable of assessing autonomic nervous system modulation on heart rate (HR) in healthy as well as disease conditions. The aim of the present study was to compare (validate) the HRV using a temporal series of electrocardiograms (ECG) obtained by simple analog amplifier with PC-based sound card (audacity) and Biopac MP36 module. Based on the inclusion criteria, 120 healthy participants, including 72 males and 48 females, participated in the present study. Following standard protocol, 5-min ECG was recorded after 10 min of supine rest by Portable simple analog amplifier PC-based sound card as well as by Biopac module with surface electrodes in Leads II position simultaneously. All the ECG data was visually screened and was found to be free of ectopic beats and noise. RR intervals from both ECG recordings were analyzed separately in Kubios software. Short-term HRV indexes in both time and frequency domain were used. The unpaired Student's t-test and Pearson correlation coefficient test were used for the analysis using the R statistical software. No statistically significant differences were observed when comparing the values analyzed by means of the two devices for HRV. Correlation analysis revealed perfect positive correlation (r = 0.99, P < 0.001) between the values in time and frequency domain obtained by the devices. On the basis of the results of the present study, we suggest that the calculation of HRV values in the time and frequency domains by RR series obtained from the PC-based sound card is probably as reliable as those obtained by the gold standard Biopac MP36.

Quantile regression and clustering analysis of standardized precipitation index in the Tarim River Basin, Xinjiang, China

NASA Astrophysics Data System (ADS)

Yang, Peng; Xia, Jun; Zhang, Yongyong; Han, Jian; Wu, Xia

2017-11-01

Because drought is a very common and widespread natural disaster, it has attracted a great deal of academic interest. Based on 12-month time scale standardized precipitation indices (SPI12) calculated from precipitation data recorded between 1960 and 2015 at 22 weather stations in the Tarim River Basin (TRB), this study aims to identify the trends of SPI and drought duration, severity, and frequency at various quantiles and to perform cluster analysis of drought events in the TRB. The results indicated that (1) both precipitation and temperature at most stations in the TRB exhibited significant positive trends during 1960-2015; (2) multiple scales of SPIs changed significantly around 1986; (3) based on quantile regression analysis of temporal drought changes, the positive SPI slopes indicated less severe and less frequent droughts at lower quantiles, but clear variation was detected in the drought frequency; and (4) significantly different trends were found in drought frequency probably between severe droughts and drought frequency.

Multivariate frequency domain analysis of protein dynamics

NASA Astrophysics Data System (ADS)

Matsunaga, Yasuhiro; Fuchigami, Sotaro; Kidera, Akinori

2009-03-01

Multivariate frequency domain analysis (MFDA) is proposed to characterize collective vibrational dynamics of protein obtained by a molecular dynamics (MD) simulation. MFDA performs principal component analysis (PCA) for a bandpass filtered multivariate time series using the multitaper method of spectral estimation. By applying MFDA to MD trajectories of bovine pancreatic trypsin inhibitor, we determined the collective vibrational modes in the frequency domain, which were identified by their vibrational frequencies and eigenvectors. At near zero temperature, the vibrational modes determined by MFDA agreed well with those calculated by normal mode analysis. At 300 K, the vibrational modes exhibited characteristic features that were considerably different from the principal modes of the static distribution given by the standard PCA. The influences of aqueous environments were discussed based on two different sets of vibrational modes, one derived from a MD simulation in water and the other from a simulation in vacuum. Using the varimax rotation, an algorithm of the multivariate statistical analysis, the representative orthogonal set of eigenmodes was determined at each vibrational frequency.

Carbon financial markets: A time-frequency analysis of CO2 prices

NASA Astrophysics Data System (ADS)

Sousa, Rita; Aguiar-Conraria, Luís; Soares, Maria Joana

2014-11-01

We characterize the interrelation of CO2 prices with energy prices (electricity, gas and coal), and with economic activity. Previous studies have relied on time-domain techniques, such as Vector Auto-Regressions. In this study, we use multivariate wavelet analysis, which operates in the time-frequency domain. Wavelet analysis provides convenient tools to distinguish relations at particular frequencies and at particular time horizons. Our empirical approach has the potential to identify relations getting stronger and then disappearing over specific time intervals and frequencies. We are able to examine the coherency of these variables and lead-lag relations at different frequencies for the time periods in focus.

Applying the new method of time-frequency transforms to the analysis of the characteristics of geomagnetic Pc5 pulsations

NASA Astrophysics Data System (ADS)

Zelinsky, N. R.; Kleimenova, N. G.; Gromova, L. I.

2017-09-01

This study considers the possibility of using the new methods of time-frequency transforms, such as chirplet and warblet transforms, to analyze the digital observational data of geomagnetic pulsations of Pc5 type. For this purpose, necessary algorithms of calculation and appropriate software were developed. The chirplet transform method (CT) is used to analyze signals with a linear frequency modulation. A chirplet variation, the so-called warblet transform, is used to analyze signals with a nonlinear frequency modulation. Since, in studying geomagnetic pulsations, it is difficult to make assumptions on the character of the behavior of the instantaneous frequency of the signal, the special generalized warblet transform (GWT) was used for the analysis. The GWT has a high spatiotemporal resolution and was developed to analyze oscillations both with a periodic and nonperiodic change of the instantaneous frequency. The software developed for GWT calculation was used to study daytime geomagnetic Pc5 pulsations with durations of several hours that were detected via the network of ground-based magnetometers of the Scandinavian IMAGE profile during the magnetic storm of May 29-30, 2003. For the first time, temporal variations of the instantaneous frequency of geomagnetic pulsations are determined and their possible use in studying the fine spatial structure of Pc5 waves is shown.

Trends in Fetal Medicine: A 10-Year Bibliometric Analysis of Prenatal Diagnosis

PubMed Central

Dhombres, Ferdinand; Bodenreider, Olivier

2018-01-01

The objective is to automatically identify trends in Fetal Medicine over the past 10 years through a bibliometric analysis of articles published in Prenatal Diagnosis, using text mining techniques. We processed 2,423 full-text articles published in Prenatal Diagnosis between 2006 and 2015. We extracted salient terms, calculated their frequencies over time, and established evolution profiles for terms, from which we derived falling, stable, and rising trends. We identified 618 terms with a falling trend, 2,142 stable terms, and 839 terms with a rising trend. Terms with increasing frequencies include those related to statistics and medical study design. The most recent of these terms reflect the new opportunities of next- generation sequencing. Many terms related to cytogenetics exhibit a falling trend. A bibliometric analysis based on text mining effectively supports identification of trends over time. This scalable approach is complementary to analyses based on metadata or expert opinion. PMID:29295220

3-D surface profilometry based on modulation measurement by applying wavelet transform method

NASA Astrophysics Data System (ADS)

Zhong, Min; Chen, Feng; Xiao, Chao; Wei, Yongchao

2017-01-01

A new analysis of 3-D surface profilometry based on modulation measurement technique by the application of Wavelet Transform method is proposed. As a tool excelling for its multi-resolution and localization in the time and frequency domains, Wavelet Transform method with good localized time-frequency analysis ability and effective de-noizing capacity can extract the modulation distribution more accurately than Fourier Transform method. Especially for the analysis of complex object, more details of the measured object can be well remained. In this paper, the theoretical derivation of Wavelet Transform method that obtains the modulation values from a captured fringe pattern is given. Both computer simulation and elementary experiment are used to show the validity of the proposed method by making a comparison with the results of Fourier Transform method. The results show that the Wavelet Transform method has a better performance than the Fourier Transform method in modulation values retrieval.

New clinical insights for transiently evoked otoacoustic emission protocols.

PubMed

Hatzopoulos, Stavros; Grzanka, Antoni; Martini, Alessandro; Konopka, Wieslaw

2009-08-01

The objective of the study was to optimize the area of a time-frequency analysis and then investigate any stable patterns in the time-frequency structure of otoacoustic emissions in a population of 152 healthy adults sampled over one year. TEOAE recordings were collected from 302 ears in subjects presenting normal hearing and normal impedance values. The responses were analyzed by the Wigner-Ville distribution (WVD). The TF region of analysis was optimized by examining the energy content of various rectangular and triangular TF regions. The TEOAE components from the initial and recordings 12 months later were compared in the optimized TF region. The best region for TF analysis was identified with base point 1 at 2.24 ms and 2466 Hz, base point 2 at 6.72 ms and 2466 Hz, and the top point at 2.24 ms and 5250 Hz. Correlation indices from the TF optimized region were higher, and were statistically significant, than the traditional indices in the selected time window. An analysis of the TF data within a 12-month period indicated a 85% TEOAE component similarity in 90% of the tested subjects.

Frequency-dependent FDTD methods using Z transforms

NASA Technical Reports Server (NTRS)

Sullivan, Dennis M.

1992-01-01

While the frequency-dependent finite-difference time-domain, or (FD)2TD, method can correctly calculate EM propagation through media whose dielectric properties are frequency-dependent, more elaborate applications lead to greater (FD)2TD complexity. Z-transform theory is presently used to develop the mathematical bases of the (FD)2TD method, simultaneously obtaining a clearer formulation and allowing researchers to draw on the existing literature of systems analysis and signal-processing.

A wavelet analysis of co-movements in Asian gold markets

NASA Astrophysics Data System (ADS)

Das, Debojyoti; Kannadhasan, M.; Al-Yahyaee, Khamis Hamed; Yoon, Seong-Min

2018-02-01

This study assesses the cross-country co-movements of gold spot returns among the major gold consuming countries in Asia using wavelet-based analysis for a dataset spanning over 26 years. Wavelet-based analysis is used since it allows measuring co-movements in a time-frequency space. The results suggest intense and positive co-movements in Asia after the Asian financial crisis of 1997 at all frequencies. In addition, the Asian gold spot markets depict a state of impending perfect market integration. Finally, Thailand emerges as the potential market leader in all wavelet scales except one, which is led by India. The study has important implications for international diversification of a single-asset (gold) portfolio.

A wavelet-based technique to predict treatment outcome for Major Depressive Disorder.

PubMed

Mumtaz, Wajid; Xia, Likun; Mohd Yasin, Mohd Azhar; Azhar Ali, Syed Saad; Malik, Aamir Saeed

2017-01-01

Treatment management for Major Depressive Disorder (MDD) has been challenging. However, electroencephalogram (EEG)-based predictions of antidepressant's treatment outcome may help during antidepressant's selection and ultimately improve the quality of life for MDD patients. In this study, a machine learning (ML) method involving pretreatment EEG data was proposed to perform such predictions for Selective Serotonin Reuptake Inhibitor (SSRIs). For this purpose, the acquisition of experimental data involved 34 MDD patients and 30 healthy controls. Consequently, a feature matrix was constructed involving time-frequency decomposition of EEG data based on wavelet transform (WT) analysis, termed as EEG data matrix. However, the resultant EEG data matrix had high dimensionality. Therefore, dimension reduction was performed based on a rank-based feature selection method according to a criterion, i.e., receiver operating characteristic (ROC). As a result, the most significant features were identified and further be utilized during the training and testing of a classification model, i.e., the logistic regression (LR) classifier. Finally, the LR model was validated with 100 iterations of 10-fold cross-validation (10-CV). The classification results were compared with short-time Fourier transform (STFT) analysis, and empirical mode decompositions (EMD). The wavelet features extracted from frontal and temporal EEG data were found statistically significant. In comparison with other time-frequency approaches such as the STFT and EMD, the WT analysis has shown highest classification accuracy, i.e., accuracy = 87.5%, sensitivity = 95%, and specificity = 80%. In conclusion, significant wavelet coefficients extracted from frontal and temporal pre-treatment EEG data involving delta and theta frequency bands may predict antidepressant's treatment outcome for the MDD patients.

Damping mathematical modelling and dynamic responses for FRP laminated composite plates with polymer matrix

NASA Astrophysics Data System (ADS)

Liu, Qimao

2018-02-01

This paper proposes an assumption that the fibre is elastic material and polymer matrix is viscoelastic material so that the energy dissipation depends only on the polymer matrix in dynamic response process. The damping force vectors in frequency and time domains, of FRP (Fibre-Reinforced Polymer matrix) laminated composite plates, are derived based on this assumption. The governing equations of FRP laminated composite plates are formulated in both frequency and time domains. The direct inversion method and direct time integration method for nonviscously damped systems are employed to solve the governing equations and achieve the dynamic responses in frequency and time domains, respectively. The computational procedure is given in detail. Finally, dynamic responses (frequency responses with nonzero and zero initial conditions, free vibration, forced vibrations with nonzero and zero initial conditions) of a FRP laminated composite plate are computed using the proposed methodology. The proposed methodology in this paper is easy to be inserted into the commercial finite element analysis software. The proposed assumption, based on the theory of material mechanics, needs to be further proved by experiment technique in the future.

Transient tracking of low and high-order eccentricity-related components in induction motors via TFD tools

NASA Astrophysics Data System (ADS)

Climente-Alarcon, V.; Antonino-Daviu, J.; Riera-Guasp, M.; Pons-Llinares, J.; Roger-Folch, J.; Jover-Rodriguez, P.; Arkkio, A.

2011-02-01

The present work is focused on the diagnosis of mixed eccentricity faults in induction motors via the study of currents demanded by the machine. Unlike traditional methods, based on the analysis of stationary currents (Motor Current Signature Analysis (MCSA)), this work provides new findings regarding the diagnosis approach proposed by the authors in recent years, which is mainly focused on the fault diagnosis based on the analysis of transient quantities, such as startup or plug stopping currents (Transient Motor Current Signature Analysis (TMCSA)), using suitable time-frequency decomposition (TFD) tools. The main novelty of this work is to prove the usefulness of tracking the transient evolution of high-order eccentricity-related harmonics in order to diagnose the condition of the machine, complementing the information obtained with the low-order components, whose transient evolution was well characterised in previous works. Tracking of high-order eccentricity-related harmonics during the transient, through their associated patterns in the time-frequency plane, may significantly increase the reliability of the diagnosis, since the set of fault-related patterns arising after application of the corresponding TFD tool is very unlikely to be caused by other faults or phenomena. Although there are different TFD tools which could be suitable for the transient extraction of these harmonics, this paper makes use of a Wigner-Ville distribution (WVD)-based algorithm in order to carry out the time-frequency decomposition of the startup current signal, since this is a tool showing an excellent trade-off between frequency resolution at both high and low frequencies. Several simulation results obtained with a finite element-based model and experimental results show the validity of this fault diagnosis approach under several faulty and operating conditions. Also, additional signals corresponding to the coexistence of the eccentricity and other non-fault related phenomena making difficult the diagnosis (fluctuating load torque) are included in the paper. Finally, a comparison with an alternative TFD tool - the discrete wavelet transform (DWT) - applied in previous papers, is also carried out in the contribution. The results are promising regarding the usefulness of the methodology for the reliable diagnosis of eccentricities and for their discrimination against other phenomena.

CRAFT (complete reduction to amplitude frequency table)--robust and time-efficient Bayesian approach for quantitative mixture analysis by NMR.

PubMed

Krishnamurthy, Krish

2013-12-01

The intrinsic quantitative nature of NMR is increasingly exploited in areas ranging from complex mixture analysis (as in metabolomics and reaction monitoring) to quality assurance/control. Complex NMR spectra are more common than not, and therefore, extraction of quantitative information generally involves significant prior knowledge and/or operator interaction to characterize resonances of interest. Moreover, in most NMR-based metabolomic experiments, the signals from metabolites are normally present as a mixture of overlapping resonances, making quantification difficult. Time-domain Bayesian approaches have been reported to be better than conventional frequency-domain analysis at identifying subtle changes in signal amplitude. We discuss an approach that exploits Bayesian analysis to achieve a complete reduction to amplitude frequency table (CRAFT) in an automated and time-efficient fashion - thus converting the time-domain FID to a frequency-amplitude table. CRAFT uses a two-step approach to FID analysis. First, the FID is digitally filtered and downsampled to several sub FIDs, and secondly, these sub FIDs are then modeled as sums of decaying sinusoids using the Bayesian approach. CRAFT tables can be used for further data mining of quantitative information using fingerprint chemical shifts of compounds of interest and/or statistical analysis of modulation of chemical quantity in a biological study (metabolomics) or process study (reaction monitoring) or quality assurance/control. The basic principles behind this approach as well as results to evaluate the effectiveness of this approach in mixture analysis are presented. Copyright © 2013 John Wiley & Sons, Ltd.

A visual parallel-BCI speller based on the time-frequency coding strategy

NASA Astrophysics Data System (ADS)

Xu, Minpeng; Chen, Long; Zhang, Lixin; Qi, Hongzhi; Ma, Lan; Tang, Jiabei; Wan, Baikun; Ming, Dong

2014-04-01

Objective. Spelling is one of the most important issues in brain-computer interface (BCI) research. This paper is to develop a visual parallel-BCI speller system based on the time-frequency coding strategy in which the sub-speller switching among four simultaneously presented sub-spellers and the character selection are identified in a parallel mode. Approach. The parallel-BCI speller was constituted by four independent P300+SSVEP-B (P300 plus SSVEP blocking) spellers with different flicker frequencies, thereby all characters had a specific time-frequency code. To verify its effectiveness, 11 subjects were involved in the offline and online spellings. A classification strategy was designed to recognize the target character through jointly using the canonical correlation analysis and stepwise linear discriminant analysis. Main results. Online spellings showed that the proposed parallel-BCI speller had a high performance, reaching the highest information transfer rate of 67.4 bit min-1, with an average of 54.0 bit min-1 and 43.0 bit min-1 in the three rounds and five rounds, respectively. Significance. The results indicated that the proposed parallel-BCI could be effectively controlled by users with attention shifting fluently among the sub-spellers, and highly improved the BCI spelling performance.

Precession missile feature extraction using sparse component analysis of radar measurements

NASA Astrophysics Data System (ADS)

Liu, Lihua; Du, Xiaoyong; Ghogho, Mounir; Hu, Weidong; McLernon, Des

2012-12-01

According to the working mode of the ballistic missile warning radar (BMWR), the radar return from the BMWR is usually sparse. To recognize and identify the warhead, it is necessary to extract the precession frequency and the locations of the scattering centers of the missile. This article first analyzes the radar signal model of the precessing conical missile during flight and develops the sparse dictionary which is parameterized by the unknown precession frequency. Based on the sparse dictionary, the sparse signal model is then established. A nonlinear least square estimation is first applied to roughly extract the precession frequency in the sparse dictionary. Based on the time segmented radar signal, a sparse component analysis method using the orthogonal matching pursuit algorithm is then proposed to jointly estimate the precession frequency and the scattering centers of the missile. Simulation results illustrate the validity of the proposed method.

Preliminary analysis of cross beam data from the Gun Barrel Hill site

NASA Technical Reports Server (NTRS)

Sandborn, V. A.; Bice, A. R.; Cliff, W. C.; Hablutzel, B. C.

1974-01-01

Preliminary evaluation of cross beam data taken at the Gun Barrell Hill test site of ESSA is presented. The evaluation is made using the analog Princeton Time Correlator. A study of the frequency band width limitations of the Princeton Time Correlator is made. Based on the band width limitations, it is possible to demonstrate that nearly identical correlation is obtained for frequencies from .01 to 3.9 hertz. Difficulty is encountered in that maximums in the correlation curves do not occur at zero time lag for zero beam separations.

A general theory on frequency and time-frequency analysis of irregularly sampled time series based on projection methods - Part 1: Frequency analysis

NASA Astrophysics Data System (ADS)

Lenoir, Guillaume; Crucifix, Michel

2018-03-01

We develop a general framework for the frequency analysis of irregularly sampled time series. It is based on the Lomb-Scargle periodogram, but extended to algebraic operators accounting for the presence of a polynomial trend in the model for the data, in addition to a periodic component and a background noise. Special care is devoted to the correlation between the trend and the periodic component. This new periodogram is then cast into the Welch overlapping segment averaging (WOSA) method in order to reduce its variance. We also design a test of significance for the WOSA periodogram, against the background noise. The model for the background noise is a stationary Gaussian continuous autoregressive-moving-average (CARMA) process, more general than the classical Gaussian white or red noise processes. CARMA parameters are estimated following a Bayesian framework. We provide algorithms that compute the confidence levels for the WOSA periodogram and fully take into account the uncertainty in the CARMA noise parameters. Alternatively, a theory using point estimates of CARMA parameters provides analytical confidence levels for the WOSA periodogram, which are more accurate than Markov chain Monte Carlo (MCMC) confidence levels and, below some threshold for the number of data points, less costly in computing time. We then estimate the amplitude of the periodic component with least-squares methods, and derive an approximate proportionality between the squared amplitude and the periodogram. This proportionality leads to a new extension for the periodogram: the weighted WOSA periodogram, which we recommend for most frequency analyses with irregularly sampled data. The estimated signal amplitude also permits filtering in a frequency band. Our results generalise and unify methods developed in the fields of geosciences, engineering, astronomy and astrophysics. They also constitute the starting point for an extension to the continuous wavelet transform developed in a companion article (Lenoir and Crucifix, 2018). All the methods presented in this paper are available to the reader in the Python package WAVEPAL.

Post-exercise heart rate variability recovery: a time-frequency analysis.

PubMed

Peçanha, Tiago; de Paula-Ribeiro, Marcelle; Nasario-Junior, Olivassé; de Lima, Jorge Roberto Perrout

2013-12-01

Most studies investigating the effects of non-pharmacological interventions, such as physical training (PT), on cardiac autonomic control, assessed the HRV only in resting conditions. Recently, a new time-frequency mathematical approach based on the short-time Fourier transform (STFT) method has been validated for the assessment of HRV in non-stationary conditions such as the immediate post-exercise period. The aim of this study was to evaluate the effects of the PT on post-exercise cardiac autonomic control using the time-frequency STFT analysis of the HRV. Twenty-one healthy male volunteers participated in this study. The subjects were initially evaluated for their physical exercise/sport practice and allocated to groups of low physical training ((Low)PT, n = 13) or high physical training (H(igh)PT, n = 8). The post-exercise HRV was assessed by the STFT method, which provides the analysis of dynamic changes in the power of the low- and high-frequency spectral components (LF and HF, respectively) of the HRV during the whole recovery period. Greater LF (from the min 5 to 10) and HF (from the min 6 to 10) in the post-exercise period in the H(igh)PT compared to the (Low)PT group (P < 0.05) was observed. These results indicate that exercise training exerts beneficial effects on post-exercise cardiac autonomic control.

A New Method for Nonlinear and Nonstationary Time Series Analysis and Its Application to the Earthquake and Building Response Records

NASA Technical Reports Server (NTRS)

Huang, Norden E.

1999-01-01

A new method for analyzing nonlinear and nonstationary data has been developed. The key part of the method is the Empirical Mode Decomposition method with which any complicated data set can be decomposed into a finite and often small number of Intrinsic Mode Functions (IMF). An IMF is defined as any function having the same numbers of zero-crossing and extrema, and also having symmetric envelopes defined by the local maxima and minima respectively. The IMF also admits well-behaved Hilbert transform. This decomposition method is adaptive, and, therefore, highly efficient. Since the decomposition is based on the local characteristic time scale of the data, it is applicable to nonlinear and nonstationary processes. With the Hilbert transform, the Intrinsic Mode Functions yield instantaneous frequencies as functions of time that give sharp identifications of imbedded structures. The final presentation of the results is an energy-frequency-time distribution, designated as the Hilbert Spectrum, Example of application of this method to earthquake and building response will be given. The results indicate those low frequency components, totally missed by the Fourier analysis, are clearly identified by the new method. Comparisons with Wavelet and window Fourier analysis show the new method offers much better temporal and frequency resolutions.

Extracting a shape function for a signal with intra-wave frequency modulation.

PubMed

Hou, Thomas Y; Shi, Zuoqiang

2016-04-13

In this paper, we develop an effective and robust adaptive time-frequency analysis method for signals with intra-wave frequency modulation. To handle this kind of signals effectively, we generalize our data-driven time-frequency analysis by using a shape function to describe the intra-wave frequency modulation. The idea of using a shape function in time-frequency analysis was first proposed by Wu (Wu 2013 Appl. Comput. Harmon. Anal. 35, 181-199. (doi:10.1016/j.acha.2012.08.008)). A shape function could be any smooth 2π-periodic function. Based on this model, we propose to solve an optimization problem to extract the shape function. By exploring the fact that the shape function is a periodic function with respect to its phase function, we can identify certain low-rank structure of the signal. This low-rank structure enables us to extract the shape function from the signal. Once the shape function is obtained, the instantaneous frequency with intra-wave modulation can be recovered from the shape function. We demonstrate the robustness and efficiency of our method by applying it to several synthetic and real signals. One important observation is that this approach is very stable to noise perturbation. By using the shape function approach, we can capture the intra-wave frequency modulation very well even for noise-polluted signals. In comparison, existing methods such as empirical mode decomposition/ensemble empirical mode decomposition seem to have difficulty in capturing the intra-wave modulation when the signal is polluted by noise. © 2016 The Author(s).

Detecting intrinsic dynamics of traffic flow with recurrence analysis and empirical mode decomposition

NASA Astrophysics Data System (ADS)

Xiong, Hui; Shang, Pengjian; Bian, Songhan

2017-05-01

In this paper, we apply the empirical mode decomposition (EMD) method to the recurrence plot (RP) and recurrence quantification analysis (RQA), to evaluate the frequency- and time-evolving dynamics of the traffic flow. Based on the cumulative intrinsic mode functions extracted by the EMD, the frequency-evolving RP regarding different oscillation of modes suggests that apparent dynamics of the data considered are mainly dominated by its components of medium- and low-frequencies while severely affected by fast oscillated noises contained in the signal. Noises are then eliminated to analyze the intrinsic dynamics and consequently, the denoised time-evolving RQA diversely characterizes the properties of the signal and marks crucial points more accurately where white bands in the RP occur, whereas a strongly qualitative agreement exists between all the non-denoised RQA measures. Generally, the EMD combining with the recurrence analysis sheds more reliable, abundant and inherent lights into the traffic flow, which is meaningful to the empirical analysis of complex systems.

Diagnosis of insomnia sleep disorder using short time frequency analysis of PSD approach applied on EEG signal using channel ROC-LOC.

PubMed

Siddiqui, Mohd Maroof; Srivastava, Geetika; Saeed, Syed Hasan

2016-01-01

Insomnia is a sleep disorder in which the subject encounters problems in sleeping. The aim of this study is to identify insomnia events from normal or effected person using time frequency analysis of PSD approach applied on EEG signals using channel ROC-LOC. In this research article, attributes and waveform of EEG signals of Human being are examined. The aim of this study is to draw the result in the form of signal spectral analysis of the changes in the domain of different stages of sleep. The analysis and calculation is performed in all stages of sleep of PSD of each EEG segment. Results indicate the possibility of recognizing insomnia events based on delta, theta, alpha and beta segments of EEG signals.

A new time-frequency method for identification and classification of ball bearing faults

NASA Astrophysics Data System (ADS)

Attoui, Issam; Fergani, Nadir; Boutasseta, Nadir; Oudjani, Brahim; Deliou, Adel

2017-06-01

In order to fault diagnosis of ball bearing that is one of the most critical components of rotating machinery, this paper presents a time-frequency procedure incorporating a new feature extraction step that combines the classical wavelet packet decomposition energy distribution technique and a new feature extraction technique based on the selection of the most impulsive frequency bands. In the proposed procedure, firstly, as a pre-processing step, the most impulsive frequency bands are selected at different bearing conditions using a combination between Fast-Fourier-Transform FFT and Short-Frequency Energy SFE algorithms. Secondly, once the most impulsive frequency bands are selected, the measured machinery vibration signals are decomposed into different frequency sub-bands by using discrete Wavelet Packet Decomposition WPD technique to maximize the detection of their frequency contents and subsequently the most useful sub-bands are represented in the time-frequency domain by using Short Time Fourier transform STFT algorithm for knowing exactly what the frequency components presented in those frequency sub-bands are. Once the proposed feature vector is obtained, three feature dimensionality reduction techniques are employed using Linear Discriminant Analysis LDA, a feedback wrapper method and Locality Sensitive Discriminant Analysis LSDA. Lastly, the Adaptive Neuro-Fuzzy Inference System ANFIS algorithm is used for instantaneous identification and classification of bearing faults. In order to evaluate the performances of the proposed method, different testing data set to the trained ANFIS model by using different conditions of healthy and faulty bearings under various load levels, fault severities and rotating speed. The conclusion resulting from this paper is highlighted by experimental results which prove that the proposed method can serve as an intelligent bearing fault diagnosis system.

Ultra-low frequency vibration data acquisition concerns in operating flight simulators. [Motion sickness inducing vibrations in flight simulators

DOE Office of Scientific and Technical Information (OSTI.GOV)

Van Hoy, B.W.

1988-01-01

The measurement of ultra-low frequency vibration (.01 to 1.0 Hz) in motion based flight simulators was undertaken to quantify the energy and frequencies of motion present during operation. Methods of measurement, the selection of transducers, recorders, and analyzers and the development of a test plan, as well as types of analysis are discussed. Analysis of the data using a high-speed minicomputer and a comparison of the computer analysis with standard FFT analysis are also discussed. Measurement of simulator motion with the pilot included as part of the control dynamics had not been done up to this time. The data aremore » being used to evaluate the effect of low frequency energy on the vestibular system of the air crew, and the incidence of simulator induced sickness. 11 figs.« less

Measuring border delay and crossing times at the US-Mexico border : part II. Guidebook for analysis and dissemination of border crossing time and wait time data.

DOT National Transportation Integrated Search

2012-06-01

The purpose of this guidebook is to describe to local, regional, and State agencies how to analyze and disseminate data collected by a radio frequency identification (RFID)-based system to measure travel times of commercial vehicles, which is referre...

Brillouin Scattering Spectrum Analysis Based on Auto-Regressive Spectral Estimation

NASA Astrophysics Data System (ADS)

Huang, Mengyun; Li, Wei; Liu, Zhangyun; Cheng, Linghao; Guan, Bai-Ou

2018-06-01

Auto-regressive (AR) spectral estimation technology is proposed to analyze the Brillouin scattering spectrum in Brillouin optical time-domain refelectometry. It shows that AR based method can reliably estimate the Brillouin frequency shift with an accuracy much better than fast Fourier transform (FFT) based methods provided the data length is not too short. It enables about 3 times improvement over FFT at a moderate spatial resolution.

Adaptive phase extraction: incorporating the Gabor transform in the matching pursuit algorithm.

PubMed

Wacker, Matthias; Witte, Herbert

2011-10-01

Short-time Fourier transform (STFT), Gabor transform (GT), wavelet transform (WT), and the Wigner-Ville distribution (WVD) are just some examples of time-frequency analysis methods which are frequently applied in biomedical signal analysis. However, all of these methods have their individual drawbacks. The STFT, GT, and WT have a time-frequency resolution that is determined by algorithm parameters and the WVD is contaminated by cross terms. In 1993, Mallat and Zhang introduced the matching pursuit (MP) algorithm that decomposes a signal into a sum of atoms and uses a cross-term free pseudo-WVD to generate a data-adaptive power distribution in the time-frequency space. Thus, it solved some of the problems of the GT and WT but lacks phase information that is crucial e.g., for synchronization analysis. We introduce a new time-frequency analysis method that combines the MP with a pseudo-GT. Therefore, the signal is decomposed into a set of Gabor atoms. Afterward, each atom is analyzed with a Gabor analysis, where the time-domain gaussian window of the analysis matches that of the specific atom envelope. A superposition of the single time-frequency planes gives the final result. This is the first time that a complete analysis of the complex time-frequency plane can be performed in a fully data-adaptive and frequency-selective manner. We demonstrate the capabilities of our approach on a simulation and on real-life magnetoencephalogram data.

Statistical properties and time-frequency analysis of temperature, salinity and turbidity measured by the MAREL Carnot station in the coastal waters of Boulogne-sur-Mer (France)

NASA Astrophysics Data System (ADS)

Kbaier Ben Ismail, Dhouha; Lazure, Pascal; Puillat, Ingrid

2016-10-01

In marine sciences, many fields display high variability over a large range of spatial and temporal scales, from seconds to thousands of years. The longer recorded time series, with an increasing sampling frequency, in this field are often nonlinear, nonstationary, multiscale and noisy. Their analysis faces new challenges and thus requires the implementation of adequate and specific methods. The objective of this paper is to highlight time series analysis methods already applied in econometrics, signal processing, health, etc. to the environmental marine domain, assess advantages and inconvenients and compare classical techniques with more recent ones. Temperature, turbidity and salinity are important quantities for ecosystem studies. The authors here consider the fluctuations of sea level, salinity, turbidity and temperature recorded from the MAREL Carnot system of Boulogne-sur-Mer (France), which is a moored buoy equipped with physico-chemical measuring devices, working in continuous and autonomous conditions. In order to perform adequate statistical and spectral analyses, it is necessary to know the nature of the considered time series. For this purpose, the stationarity of the series and the occurrence of unit-root are addressed with the Augmented-Dickey Fuller tests. As an example, the harmonic analysis is not relevant for temperature, turbidity and salinity due to the nonstationary condition, except for the nearly stationary sea level datasets. In order to consider the dominant frequencies associated to the dynamics, the large number of data provided by the sensors should enable the estimation of Fourier spectral analysis. Different power spectra show a complex variability and reveal an influence of environmental factors such as tides. However, the previous classical spectral analysis, namely the Blackman-Tukey method, requires not only linear and stationary data but also evenly-spaced data. Interpolating the time series introduces numerous artifacts to the data. The Lomb-Scargle algorithm is adapted to unevenly-spaced data and is used as an alternative. The limits of the method are also set out. It was found that beyond 50% of missing measures, few significant frequencies are detected, several seasonalities are no more visible, and even a whole range of high frequency disappears progressively. Furthermore, two time-frequency decomposition methods, namely wavelets and Hilbert-Huang Transformation (HHT), are applied for the analysis of the entire dataset. Using the Continuous Wavelet Transform (CWT), some properties of the time series are determined. Then, the inertial wave and several low-frequency tidal waves are identified by the application of the Empirical Mode Decomposition (EMD). Finally, EMD based Time Dependent Intrinsic Correlation (TDIC) analysis is applied to consider the correlation between two nonstationary time series.

Automated video-based assessment of surgical skills for training and evaluation in medical schools.

PubMed

Zia, Aneeq; Sharma, Yachna; Bettadapura, Vinay; Sarin, Eric L; Ploetz, Thomas; Clements, Mark A; Essa, Irfan

2016-09-01

Routine evaluation of basic surgical skills in medical schools requires considerable time and effort from supervising faculty. For each surgical trainee, a supervisor has to observe the trainees in person. Alternatively, supervisors may use training videos, which reduces some of the logistical overhead. All these approaches however are still incredibly time consuming and involve human bias. In this paper, we present an automated system for surgical skills assessment by analyzing video data of surgical activities. We compare different techniques for video-based surgical skill evaluation. We use techniques that capture the motion information at a coarser granularity using symbols or words, extract motion dynamics using textural patterns in a frame kernel matrix, and analyze fine-grained motion information using frequency analysis. We were successfully able to classify surgeons into different skill levels with high accuracy. Our results indicate that fine-grained analysis of motion dynamics via frequency analysis is most effective in capturing the skill relevant information in surgical videos. Our evaluations show that frequency features perform better than motion texture features, which in-turn perform better than symbol-/word-based features. Put succinctly, skill classification accuracy is positively correlated with motion granularity as demonstrated by our results on two challenging video datasets.

THE NANOGRAV NINE-YEAR DATA SET: EXCESS NOISE IN MILLISECOND PULSAR ARRIVAL TIMES

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lam, M. T.; Jones, M. L.; McLaughlin, M. A.

Gravitational wave (GW) astronomy using a pulsar timing array requires high-quality millisecond pulsars (MSPs), correctable interstellar propagation delays, and high-precision measurements of pulse times of arrival. Here we identify noise in timing residuals that exceeds that predicted for arrival time estimation for MSPs observed by the North American Nanohertz Observatory for Gravitational Waves. We characterize the excess noise using variance and structure function analyses. We find that 26 out of 37 pulsars show inconsistencies with a white-noise-only model based on the short timescale analysis of each pulsar, and we demonstrate that the excess noise has a red power spectrum formore » 15 pulsars. We also decompose the excess noise into chromatic (radio-frequency-dependent) and achromatic components. Associating the achromatic red-noise component with spin noise and including additional power-spectrum-based estimates from the literature, we estimate a scaling law in terms of spin parameters (frequency and frequency derivative) and data-span length and compare it to the scaling law of Shannon and Cordes. We briefly discuss our results in terms of detection of GWs at nanohertz frequencies.« less

A new method for gravity field recovery based on frequency analysis of spherical harmonics

NASA Astrophysics Data System (ADS)

Cai, Lin; Zhou, Zebing

2017-04-01

All existing methods for gravity field recovery are mostly based on the space-wise and time-wise approach, whose core processes are constructing the observation equations and solving them by the least square method. It's should be pointed that the least square method means the approximation. On the other hand, we can directly and precisely obtain the coefficients of harmonics by computing the Fast Fourier Transform (FFT) when we do 1-D data (time series) analysis. So the question whether we directly and precisely obtain the coefficients of spherical harmonic by computing 2-D FFT of measurements of satellite gravity mission is of great significance, since this may guide us to a new understanding of the signal components of gravity field and make us determine it quickly by taking advantage of FFT. Like the 1-D data analysis, the 2-D FFT of measurements of satellite can be computed rapidly. If we can determine the relationship between spherical harmonics and 2-D Fourier frequencies and the transfer function from measurements to spherical coefficients, the question mentioned above can be solved. So the objective of this research project is to establish a new method based on frequency analysis of spherical harmonic, which directly compute the confidents of spherical harmonic of gravity field, which is differ from recovery by least squares. There is a one to one correspondence between frequency spectrum and the time series in 1-D FFT. The 2-D FFT has a similar relationship to 1-D FFT. Owing to the fact that any degree or order (higher than one) of spherical function has multi frequencies and these frequencies may be aliased. Fortunately, the elements and ratio of these frequencies of spherical function can be determined, and we can compute the coefficients of spherical function from 2-D FFT. This relationship can be written as equations and equivalent to a matrix, which is solid and can be derived in advance. Until now the relationship has be determined. Some preliminary results, which only compute lower degree spherical harmonics, indicates that the difference between the input (EGM2008) and output (coefficients from recovery) is smaller than 5E-17, while the minimal precision of computer software (Matlab) is 2.2204E-16.

An interferometric fiber optic hydrophone with large upper limit of dynamic range

NASA Astrophysics Data System (ADS)

Zhang, Lei; Kan, Baoxi; Zheng, Baichao; Wang, Xuefeng; Zhang, Haiyan; Hao, Liangbin; Wang, Hailiang; Hou, Zhenxing; Yu, Wenpeng

2017-10-01

Interferometric fiber optic hydrophone based on heterodyne detection is used to measure the missile dropping point in the sea. The signal caused by the missile dropping in the water will be too large to be detected, so it is necessary to boost the upper limit of dynamic range (ULODR) of fiber optic hydrophone. In this article we analysis the factors which influence the ULODR of fiber optic hydrophone based on heterodyne detection, the ULODR is decided by the sampling frequency fsam and the heterodyne frequency Δf. The sampling frequency and the heterodyne frequency should be satisfied with the Nyquist sampling theorem which fsam will be two times larger than Δf, in this condition the ULODR is depended on the heterodyne frequency. In order to enlarge the ULODR, the Nyquist sampling theorem was broken, and we proposed a fiber optic hydrophone which the heterodyne frequency is larger than the sampling frequency. Both the simulation and experiment were done in this paper, the consequences are similar: When the sampling frequency is 100kHz, the ULODR of large heterodyne frequency fiber optic hydrophone is 2.6 times larger than that of the small heterodyne frequency fiber optic hydrophone. As the heterodyne frequency is larger than the sampling frequency, the ULODR is depended on the sampling frequency. If the sampling frequency was set at 2MHz, the ULODR of fiber optic hydrophone based on heterodyne detection will be boosted to 1000rad at 1kHz, and this large heterodyne fiber optic hydrophone can be applied to locate the drop position of the missile in the sea.

Time-frequency analysis of acoustic emission signals generated by the Glass Fibre Reinforced Polymer Composites during the tensile test

NASA Astrophysics Data System (ADS)

Świt, G.; Adamczak, A.; Krampikowska, A.

2017-10-01

Fibre reinforced polymer composites are currently dominating in the composite materials market. The lack of detailed knowledge about their properties and behaviour in various conditions of exposure under load significantly limits the broad possibilities of application of these materials. Occurring and accumulation of defects in material during the exploitation of the construction lead to the changes of its technical condition. The necessity to control the condition of the composite is therefore justified. For this purpose, non-destructive method of acoustic emission can be applied. This article presents an example of application of acoustic emission method based on time analysis and time-frequency analysis for the evaluation of the progress of the destructive processes and the level of degradation of glass fibre reinforced composite tapes that were subject to tensile testing.

New optical frequency domain differential mode delay measurement method for a multimode optical fiber.

PubMed

Ahn, T; Moon, S; Youk, Y; Jung, Y; Oh, K; Kim, D

2005-05-30

A novel mode analysis method and differential mode delay (DMD) measurement technique for a multimode optical fiber based on optical frequency domain reflectometry has been proposed for the first time. We have used a conventional OFDR with a tunable external cavity laser and a Michelson interferometer. A few-mode optical multimode fiber was prepared to test our proposed measurement technique. We have also compared the OFDR measurement results with those obtained using a traditional time-domain measurement method.

Building an EEG-fMRI Multi-Modal Brain Graph: A Concurrent EEG-fMRI Study

PubMed Central

Yu, Qingbao; Wu, Lei; Bridwell, David A.; Erhardt, Erik B.; Du, Yuhui; He, Hao; Chen, Jiayu; Liu, Peng; Sui, Jing; Pearlson, Godfrey; Calhoun, Vince D.

2016-01-01

The topological architecture of brain connectivity has been well-characterized by graph theory based analysis. However, previous studies have primarily built brain graphs based on a single modality of brain imaging data. Here we develop a framework to construct multi-modal brain graphs using concurrent EEG-fMRI data which are simultaneously collected during eyes open (EO) and eyes closed (EC) resting states. FMRI data are decomposed into independent components with associated time courses by group independent component analysis (ICA). EEG time series are segmented, and then spectral power time courses are computed and averaged within 5 frequency bands (delta; theta; alpha; beta; low gamma). EEG-fMRI brain graphs, with EEG electrodes and fMRI brain components serving as nodes, are built by computing correlations within and between fMRI ICA time courses and EEG spectral power time courses. Dynamic EEG-fMRI graphs are built using a sliding window method, versus static ones treating the entire time course as stationary. In global level, static graph measures and properties of dynamic graph measures are different across frequency bands and are mainly showing higher values in eyes closed than eyes open. Nodal level graph measures of a few brain components are also showing higher values during eyes closed in specific frequency bands. Overall, these findings incorporate fMRI spatial localization and EEG frequency information which could not be obtained by examining only one modality. This work provides a new approach to examine EEG-fMRI associations within a graph theoretic framework with potential application to many topics. PMID:27733821

Regional-specific Stochastic Simulation of Spatially-distributed Ground-motion Time Histories using Wavelet Packet Analysis

NASA Astrophysics Data System (ADS)

Huang, D.; Wang, G.

2014-12-01

Stochastic simulation of spatially distributed ground-motion time histories is important for performance-based earthquake design of geographically distributed systems. In this study, we develop a novel technique to stochastically simulate regionalized ground-motion time histories using wavelet packet analysis. First, a transient acceleration time history is characterized by wavelet-packet parameters proposed by Yamamoto and Baker (2013). The wavelet-packet parameters fully characterize ground-motion time histories in terms of energy content, time- frequency-domain characteristics and time-frequency nonstationarity. This study further investigates the spatial cross-correlations of wavelet-packet parameters based on geostatistical analysis of 1500 regionalized ground motion data from eight well-recorded earthquakes in California, Mexico, Japan and Taiwan. The linear model of coregionalization (LMC) is used to develop a permissible spatial cross-correlation model for each parameter group. The geostatistical analysis of ground-motion data from different regions reveals significant dependence of the LMC structure on regional site conditions, which can be characterized by the correlation range of Vs30 in each region. In general, the spatial correlation and cross-correlation of wavelet-packet parameters are stronger if the site condition is more homogeneous. Using the regional-specific spatial cross-correlation model and cokriging technique, wavelet packet parameters at unmeasured locations can be best estimated, and regionalized ground-motion time histories can be synthesized. Case studies and blind tests demonstrated that the simulated ground motions generally agree well with the actual recorded data, if the influence of regional-site conditions is considered. The developed method has great potential to be used in computational-based seismic analysis and loss estimation in a regional scale.

A fatigue monitoring system based on time-domain and frequency-domain analysis of pulse data

NASA Astrophysics Data System (ADS)

Shen, Jiaai

2018-04-01

Fatigue is almost a problem that everyone would face, and a psychosis that everyone hates. If we can test people's fatigue condition and remind them of the tiredness, dangers in life, for instance, traffic accidents and sudden death will be effectively reduced, people's fatigued operations will be avoided. And people can be assisted to have access to their own and others' physical condition in time to alternate work with rest. The article develops a wearable bracelet based on FFT Pulse Frequency Spectrum Analysis and IBI's standard deviation and range calculation, according to people's heart rate (BPM) and inter-beat interval (IBI) while being tired and conscious. The hardware part is based on Arduino, pulse rate sensor, and Bluetooth module, and the software part is relied on network micro database and APP. By doing sample experiment to get more accurate standard value to judge tiredness, we prove that we can judge people's fatigue condition based on heart rate (BPM) and inter-beat interval (IBI).

Optical fiber grating vibration sensor for vibration monitoring of hydraulic pump

NASA Astrophysics Data System (ADS)

Zhang, Zhengyi; Liu, Chuntong; Li, Hongcai; He, Zhenxin; Zhao, Xiaofeng

2017-06-01

In view of the existing electrical vibration monitoring traditional hydraulic pump vibration sensor, the high false alarm rate is susceptible to electromagnetic interference and is not easy to achieve long-term reliable monitoring, based on the design of a beam of the uniform strength structure of the fiber Bragg grating (FBG) vibration sensor. In this paper, based on the analysis of the vibration theory of the equal strength beam, the principle of FBG vibration tuning based on the equal intensity beam is derived. According to the practical application of the project, the structural dimensions of the equal strength beam are determined, and the optimization design of the vibrator is carried out. The finite element analysis of the sensor is carried out by ANSYS, and the first order resonant frequency is 94.739 Hz. The vibration test of the sensor is carried out by using the vibration frequency of 35 Hz and the vibration source of 50 Hz. The time domain and frequency domain analysis results of test data show that the sensor has good dynamic response characteristics, which can realize the accurate monitoring of the vibration frequency and meet the special requirements of vibration monitoring of hydraulic pump under specific environment.

Time-localized frequency analysis of ultrasonic guided waves for nondestructive testing

NASA Astrophysics Data System (ADS)

Shin, Hyeon Jae; Song, Sung-Jin

2000-05-01

A time-localized frequency (TLF) analysis is employed for the guided wave mode identification and improved guided wave applications. For the analysis of time-localized frequency contents of digitized ultrasonic signals, TLF analysis consists of splitting the time domain signal into overlapping segments, weighting each with the hanning window, and forming the columns of discrete Fourier transforms. The result is presented by a frequency versus time domain diagram showing frequency variation along the signal arrival time. For the demonstration of the utility of TLF analysis, an experimental group velocity dispersion pattern obtained by TLF analysis is compared with the dispersion diagram obtained by theory of elasticity. Sample piping is carbon steel piping that is used for the transportation of natural gas underground. Guided wave propagation characteristic on the piping is considered with TLF analysis and wave structure concepts. TLF analysis is used for the detection of simulated corrosion defects and the assessment of weld joint using ultrasonic guided waves. TLF analysis has revealed that the difficulty of mode identification in multi-mode propagation could be overcome. Group velocity dispersion pattern obtained by TLF analysis agrees well with theoretical results.

Gravitational Radiation Characteristics of Nonspinning Black-Hole Binaries

NASA Technical Reports Server (NTRS)

Kelly, B. J.; Baker, J. G.; Boggs, W. D.; Centrella, J. M.; vanMeter, J. R.; McWilliams, S. T.

2008-01-01

We present a detailed descriptive analysis of the gravitational radiation from binary mergers of non-spinning black holes, based on numerical relativity simulations of systems varying from equal-mass to a 6:1 mass ratio. Our analysis covers amplitude and phase characteristics of the radiation, suggesting a unified picture of the waveforms' dominant features in terms of an implicit rotating source, applying uniformly to the full wavetrain, from inspiral through ringdown. We construct a model of the late-stage frequency evolution that fits the l = m modes, and identify late-time relationships between waveform frequency and amplitude. These relationships allow us to construct a predictive model for the late-time waveforms, an alternative to the common practice of modelling by a sum of quasinormal mode overtones. We demonstrate an application of this in a new effective-one-body-based analytic waveform model.

Wavelet analysis of near-resonant series RLC circuit with time-dependent forcing frequency

NASA Astrophysics Data System (ADS)

Caccamo, M. T.; Cannuli, A.; Magazù, S.

2018-07-01

In this work, the results of an analysis of the response of a near-resonant series resistance‑inductance‑capacitance (RLC) electric circuit with time-dependent forcing frequency by means of a wavelet cross-correlation approach are reported. In particular, it is shown how the wavelet approach enables frequency and time analysis of the circuit response to be carried out simultaneously—this procedure not being possible by Fourier transform, since the frequency is not stationary in time. A series RLC circuit simulation is performed by using the Simulation Program with Integrated Circuits Emphasis (SPICE), in which an oscillatory sinusoidal voltage drive signal of constant amplitude is swept through the resonant condition by progressively increasing the frequency over a 20-second time window, linearly, from 0.32 Hz to 6.69 Hz. It is shown that the wavelet cross-correlation procedure quantifies the common power between the input signal (represented by the electromotive force) and the output signal, which in the present case is a current, highlighting not only which frequencies are present but also when they occur, i.e. providing a simultaneous time-frequency analysis. The work is directed toward graduate Physics, Engineering and Mathematics students, with the main intention of introducing wavelet analysis into their data analysis toolkit.

Does Implant Design Affect Implant Primary Stability? A Resonance Frequency Analysis-Based Randomized Split-Mouth Clinical Trial.

PubMed

Gehrke, Sergio Alexandre; da Silva, Ulisses Tavares; Del Fabbro, Massimo

2015-12-01

The purpose of this study was to assess implant stability in relation to implant design (conical vs. semiconical and wide-pitch vs narrow-pitch) using resonance frequency analysis. Twenty patients with bilateral edentulous maxillary premolar region were selected. In one hemiarch, conical implants with wide pitch (group 1) were installed; in the other hemiarch, semiconical implants with narrow pitch were installed (group 2). The implant allocation was randomized. The implant stability quotient (ISQ) was measured by resonance frequency analysis immediately following implant placement to assess primary stability (time 1) and at 90 days after placement (time 2). In group 1, the mean and standard deviation ISQ for time 1 was 65.8 ± 6.22 (95% confidence interval [CI], 55 to 80), and for time 2, it was 68.0 ± 5.52 (95% CI, 57 to 77). In group 2, the mean and standard deviation ISQ was 63.6 ± 5.95 (95% CI, 52 to 78) for time 1 and 67.0 ± 5.71 (95% CI, 58 to 78) for time 2. The statistical analysis demonstrated significant difference in the ISQ values between groups at time 1 (P = .007) and no statistical difference at time 2 (P = .54). The greater primary stability of conical implants with wide pitch compared with semiconical implants with narrow pitch might suggest a preference for the former in case of the adoption of immediate or early loading protocols.

A wavelet-based technique to predict treatment outcome for Major Depressive Disorder

PubMed Central

Xia, Likun; Mohd Yasin, Mohd Azhar; Azhar Ali, Syed Saad

2017-01-01

Treatment management for Major Depressive Disorder (MDD) has been challenging. However, electroencephalogram (EEG)-based predictions of antidepressant’s treatment outcome may help during antidepressant’s selection and ultimately improve the quality of life for MDD patients. In this study, a machine learning (ML) method involving pretreatment EEG data was proposed to perform such predictions for Selective Serotonin Reuptake Inhibitor (SSRIs). For this purpose, the acquisition of experimental data involved 34 MDD patients and 30 healthy controls. Consequently, a feature matrix was constructed involving time-frequency decomposition of EEG data based on wavelet transform (WT) analysis, termed as EEG data matrix. However, the resultant EEG data matrix had high dimensionality. Therefore, dimension reduction was performed based on a rank-based feature selection method according to a criterion, i.e., receiver operating characteristic (ROC). As a result, the most significant features were identified and further be utilized during the training and testing of a classification model, i.e., the logistic regression (LR) classifier. Finally, the LR model was validated with 100 iterations of 10-fold cross-validation (10-CV). The classification results were compared with short-time Fourier transform (STFT) analysis, and empirical mode decompositions (EMD). The wavelet features extracted from frontal and temporal EEG data were found statistically significant. In comparison with other time-frequency approaches such as the STFT and EMD, the WT analysis has shown highest classification accuracy, i.e., accuracy = 87.5%, sensitivity = 95%, and specificity = 80%. In conclusion, significant wavelet coefficients extracted from frontal and temporal pre-treatment EEG data involving delta and theta frequency bands may predict antidepressant’s treatment outcome for the MDD patients. PMID:28152063

A new approach to harmonic elimination based on a real-time comparison method

NASA Astrophysics Data System (ADS)

Gourisetti, Sri Nikhil Gupta

Undesired harmonics are responsible for noise in a transmission channel, power loss in power electronics and in motor control. Selective Harmonic Elimination (SHE) is a well-known method used to eliminate or suppress the unwanted harmonics between the fundamental and the carrier frequency harmonic/component. But SHE bears the disadvantage of its incapability to use in real-time applications. A novel reference-carrier comparative method has been developed which can be used to generate an SPWM signal to apply in real-time systems. A modified carrier signal is designed and tested for different carrier frequencies based on the generated SPWM FFT. The carrier signal may change for different fundamental to carrier ratio that leads to solving the equations each time. An analysis to find all possible solutions for a particular carrier frequency and fundamental amplitude is performed and found. This proves that there is no one global maxima instead several local maximas exists for a particular condition set that makes this method less sensitive. Additionally, an attempt to find a universal solution that is valid for any carrier signal with predefined fundamental amplitude is performed. A uniform distribution Monte-Carlo sensitivity analysis is performed to measure the window i.e., best and worst possible solutions. The simulations are performed using MATLAB and are justified with experimental results.

The error and bias of supplementing a short, arid climate, rainfall record with regional vs. global frequency analysis

NASA Astrophysics Data System (ADS)

Endreny, Theodore A.; Pashiardis, Stelios

2007-02-01

SummaryRobust and accurate estimates of rainfall frequencies are difficult to make with short, and arid-climate, rainfall records, however new regional and global methods were used to supplement such a constrained 15-34 yr record in Cyprus. The impact of supplementing rainfall frequency analysis with the regional and global approaches was measured with relative bias and root mean square error (RMSE) values. Analysis considered 42 stations with 8 time intervals (5-360 min) in four regions delineated by proximity to sea and elevation. Regional statistical algorithms found the sites passed discordancy tests of coefficient of variation, skewness and kurtosis, while heterogeneity tests revealed the regions were homogeneous to mildly heterogeneous. Rainfall depths were simulated in the regional analysis method 500 times, and then goodness of fit tests identified the best candidate distribution as the general extreme value (GEV) Type II. In the regional analysis, the method of L-moments was used to estimate location, shape, and scale parameters. In the global based analysis, the distribution was a priori prescribed as GEV Type II, a shape parameter was a priori set to 0.15, and a time interval term was constructed to use one set of parameters for all time intervals. Relative RMSE values were approximately equal at 10% for the regional and global method when regions were compared, but when time intervals were compared the global method RMSE had a parabolic-shaped time interval trend. Relative bias values were also approximately equal for both methods when regions were compared, but again a parabolic-shaped time interval trend was found for the global method. The global method relative RMSE and bias trended with time interval, which may be caused by fitting a single scale value for all time intervals.

Frequency analysis via the method of moment functionals

NASA Technical Reports Server (NTRS)

Pearson, A. E.; Pan, J. Q.

1990-01-01

Several variants are presented of a linear-in-parameters least squares formulation for determining the transfer function of a stable linear system at specified frequencies given a finite set of Fourier series coefficients calculated from transient nonstationary input-output data. The basis of the technique is Shinbrot's classical method of moment functionals using complex Fourier based modulating functions to convert a differential equation model on a finite time interval into an algebraic equation which depends linearly on frequency-related parameters.

Time-Frequency Based Instantaneous Frequency Estimation of Sparse Signals from an Incomplete Set of Samples

DTIC Science & Technology

2014-06-17

100 0 2 4 Wigner distribution 0 50 100 0 0.5 1 Auto-correlation function 0 50 100 0 2 4 L- Wigner distribution 0 50 100 0 0.5 1 Auto-correlation function ...bilinear or higher order autocorrelation functions will increase the number of missing samples, the analysis shows that accurate instantaneous...frequency estimation can be achieved even if we deal with only few samples, as long as the auto-correlation function is properly chosen to coincide with

Tonotopic tuning in a sound localization circuit.

PubMed

Slee, Sean J; Higgs, Matthew H; Fairhall, Adrienne L; Spain, William J

2010-05-01

Nucleus laminaris (NL) neurons encode interaural time difference (ITD), the cue used to localize low-frequency sounds. A physiologically based model of NL input suggests that ITD information is contained in narrow frequency bands around harmonics of the sound frequency. This suggested a theory, which predicts that, for each tone frequency, there is an optimal time course for synaptic inputs to NL that will elicit the largest modulation of NL firing rate as a function of ITD. The theory also suggested that neurons in different tonotopic regions of NL require specialized tuning to take advantage of the input gradient. Tonotopic tuning in NL was investigated in brain slices by separating the nucleus into three regions based on its anatomical tonotopic map. Patch-clamp recordings in each region were used to measure both the synaptic and the intrinsic electrical properties. The data revealed a tonotopic gradient of synaptic time course that closely matched the theoretical predictions. We also found postsynaptic band-pass filtering. Analysis of the combined synaptic and postsynaptic filters revealed a frequency-dependent gradient of gain for the transformation of tone amplitude to NL firing rate modulation. Models constructed from the experimental data for each tonotopic region demonstrate that the tonotopic tuning measured in NL can improve ITD encoding across sound frequencies.

Non-linear forecasting in high-frequency financial time series

NASA Astrophysics Data System (ADS)

Strozzi, F.; Zaldívar, J. M.

2005-08-01

A new methodology based on state space reconstruction techniques has been developed for trading in financial markets. The methodology has been tested using 18 high-frequency foreign exchange time series. The results are in apparent contradiction with the efficient market hypothesis which states that no profitable information about future movements can be obtained by studying the past prices series. In our (off-line) analysis positive gain may be obtained in all those series. The trading methodology is quite general and may be adapted to other financial time series. Finally, the steps for its on-line application are discussed.

40 CFR 98.34 - Monitoring and QA/QC requirements.

Code of Federal Regulations, 2012 CFR

2012-07-01

... on a specified time period (e.g., week, month, quarter, or half-year), fuel sampling and analysis is required only for those time periods in which the fuel or blend is combusted. The owner or operator may.... When the sampling frequency is based on a specified time period (e.g., week, month, quarter, or half...

40 CFR 98.34 - Monitoring and QA/QC requirements.

Code of Federal Regulations, 2014 CFR

2014-07-01

... on a specified time period (e.g., week, month, quarter, or half-year), fuel sampling and analysis is required only for those time periods in which the fuel or blend is combusted. The owner or operator may.... When the sampling frequency is based on a specified time period (e.g., week, month, quarter, or half...

40 CFR 98.34 - Monitoring and QA/QC requirements.

Code of Federal Regulations, 2013 CFR

2013-07-01

... on a specified time period (e.g., week, month, quarter, or half-year), fuel sampling and analysis is required only for those time periods in which the fuel or blend is combusted. The owner or operator may.... When the sampling frequency is based on a specified time period (e.g., week, month, quarter, or half...

The frequency-difference and frequency-sum acoustic-field autoproducts.

PubMed

Worthmann, Brian M; Dowling, David R

2017-06-01

The frequency-difference and frequency-sum autoproducts are quadratic products of solutions of the Helmholtz equation at two different frequencies (ω + and ω - ), and may be constructed from the Fourier transform of any time-domain acoustic field. Interestingly, the autoproducts may carry wave-field information at the difference (ω + - ω - ) and sum (ω + + ω - ) frequencies even though these frequencies may not be present in the original acoustic field. This paper provides analytical and simulation results that justify and illustrate this possibility, and indicate its limitations. The analysis is based on the inhomogeneous Helmholtz equation and its solutions while the simulations are for a point source in a homogeneous half-space bounded by a perfectly reflecting surface. The analysis suggests that the autoproducts have a spatial phase structure similar to that of a true acoustic field at the difference and sum frequencies if the in-band acoustic field is a plane or spherical wave. For multi-ray-path environments, this phase structure similarity persists in portions of the autoproduct fields that are not suppressed by bandwidth averaging. Discrepancies between the bandwidth-averaged autoproducts and true out-of-band acoustic fields (with potentially modified boundary conditions) scale inversely with the product of the bandwidth and ray-path arrival time differences.

Reducing variable frequency vibrations in a powertrain system with an adaptive tuned vibration absorber group

NASA Astrophysics Data System (ADS)

Gao, Pu; Xiang, Changle; Liu, Hui; Zhou, Han

2018-07-01

Based on a multiple degrees of freedom dynamic model of a vehicle powertrain system, natural vibration analyses and sensitivity analyses of the eigenvalues are performed to determine the key inertia for each natural vibration of a powertrain system. Then, the results are used to optimize the installation position of each adaptive tuned vibration absorber. According to the relationship between the variable frequency torque excitation and the natural vibration of a powertrain system, the entire vibration frequency band is divided into segments, and the auxiliary vibration absorber and dominant vibration absorber are determined for each sensitive frequency band. The optimum parameters of the auxiliary vibration absorber are calculated based on the optimal frequency ratio and the optimal damping ratio of the passive vibration absorber. The instantaneous change state of the natural vibrations of a powertrain system with adaptive tuned vibration absorbers is studied, and the optimized start and stop tuning frequencies of the adaptive tuned vibration absorber are obtained. These frequencies can be translated into the optimum parameters of the dominant vibration absorber. Finally, the optimal tuning scheme for the adaptive tuned vibration absorber group, which can be used to reduce the variable frequency vibrations of a powertrain system, is proposed, and corresponding numerical simulations are performed. The simulation time history signals are transformed into three-dimensional information related to time, frequency and vibration energy via the Hilbert-Huang transform (HHT). A comprehensive time-frequency analysis is then conducted to verify that the optimal tuning scheme for the adaptive tuned vibration absorber group can significantly reduce the variable frequency vibrations of a powertrain system.

Time-dependent vibrational spectral analysis of first principles trajectory of methylamine with wavelet transform.

PubMed

Biswas, Sohag; Mallik, Bhabani S

2017-04-12

The fluctuation dynamics of amine stretching frequencies, hydrogen bonds, dangling N-D bonds, and the orientation profile of the amine group of methylamine (MA) were investigated under ambient conditions by means of dispersion-corrected density functional theory-based first principles molecular dynamics (FPMD) simulations. Along with the dynamical properties, various equilibrium properties such as radial distribution function, spatial distribution function, combined radial and angular distribution functions and hydrogen bonding were also calculated. The instantaneous stretching frequencies of amine groups were obtained by wavelet transform of the trajectory obtained from FPMD simulations. The frequency-structure correlation reveals that the amine stretching frequency is weakly correlated with the nearest nitrogen-deuterium distance. The frequency-frequency correlation function has a short time scale of around 110 fs and a longer time scale of about 1.15 ps. It was found that the short time scale originates from the underdamped motion of intact hydrogen bonds of MA pairs. However, the long time scale of the vibrational spectral diffusion of N-D modes is determined by the overall dynamics of hydrogen bonds as well as the dangling ND groups and the inertial rotation of the amine group of the molecule.

Predictability and Prediction of Low-Frequency Rainfall Over the Lower Reaches of the Yangtze River Valley on the Time Scale of 20 to 30 days

NASA Astrophysics Data System (ADS)

Yang, Qiuming

2018-01-01

This paper presents a predictability study of the 20-30-day low-frequency rainfall over the lower reaches of the Yangtze River valley (LYRV). This study relies on an extended complex autoregressive (ECAR) model method, which is based on the principal components of the global 850 hPa low-frequency meridional wind. ECAR is a recently advanced climate forecast method, based on data-driven models. It not only reflects the lagged variations information between the leading low-frequency components of the global circulation and rainfall in a complex space, but also displays the ability to describe the synergy variations of low-frequency components of a climate system in a low dimensional space. A 6-year forecast experiment is conducted on the low-frequency rainfall over the LYRV for the extended-range daily forecasts during 2009-2014, based on the time-varying high-order ECAR. These experimental results demonstrate that the useful skills of the real-time forecasts are achieved for an extended lead-time up to 28 days with a fifth-order model, and are also shown to be 27-day lead for forecasts which are initiated from weak intraseasonal oscillation (ISO). This high-order ECAR displays the ability to significantly improve the predictions of the ISO. The analysis of the 20-30-day ISO predictability reveals a predictability limit of about 28-40 days. Therefore, the forecast framework used in this study is determined to have the potential to assist in improving the real-time forecasts for the 20-30-day oscillations related to the heavy rainfall over the LYRV in summer.

Explore the advantage of High-frequency Water Quality Data in Urban Surface Water: A Case Study in Bristol, UK

NASA Astrophysics Data System (ADS)

Chen, Y.; Han, D.

2017-12-01

Water system is an essential component in a smart city for its sustainability and resilience. The freshness and beauty of the water body would please people as well as benefit the local aquatic ecosystems. Water quality monitoring approach has evolved from the manual lab-based monitoring approach to the manual in-situ monitoring approach, and finally to the latest wireless-sensor-network (WSN) based solutions in recent decades. The development of the in-situ water quality sensors enable humans to collect high-frequency and real-time water quality data. This poster aims to explore the advantages of the high-frequency water quality data over the low-frequency data collected manually. The data is collected by a remote real-time high-frequency water quality monitor system based on the cutting edge smart city infrastructure in Bristol - `Bristol Is Open'. The water quality of Bristol Floating Harbour is monitored which is the focal area of Bristol with new buildings and features redeveloped in the past decades. This poster will first briefly introduce the water quality monitoring system, followed by the analysis of the advantages of the sub-hourly water quality data. Thus, the suggestion on the monitoring frequency will be given.

Assessing the Usefulness of Google Books’ Word Frequencies for Psycholinguistic Research on Word Processing

PubMed Central

Brysbaert, Marc; Keuleers, Emmanuel; New, Boris

2011-01-01

In this Perspective Article we assess the usefulness of Google's new word frequencies for word recognition research (lexical decision and word naming). We find that, despite the massive corpus on which the Google estimates are based (131 billion words from books published in the United States alone), the Google American English frequencies explain 11% less of the variance in the lexical decision times from the English Lexicon Project (Balota et al., 2007) than the SUBTLEX-US word frequencies, based on a corpus of 51 million words from film and television subtitles. Further analyses indicate that word frequencies derived from recent books (published after 2000) are better predictors of word processing times than frequencies based on the full corpus, and that word frequencies based on fiction books predict word processing times better than word frequencies based on the full corpus. The most predictive word frequencies from Google still do not explain more of the variance in word recognition times of undergraduate students and old adults than the subtitle-based word frequencies. PMID:21713191

Time-frequency analysis : mathematical analysis of the empirical mode decomposition.

DOT National Transportation Integrated Search

2009-01-01

Invented over 10 years ago, empirical mode : decomposition (EMD) provides a nonlinear : time-frequency analysis with the ability to successfully : analyze nonstationary signals. Mathematical : Analysis of the Empirical Mode Decomposition : is a...

Acoustic analysis of trill sounds.

PubMed

Dhananjaya, N; Yegnanarayana, B; Bhaskararao, Peri

2012-04-01

In this paper, the acoustic-phonetic characteristics of steady apical trills--trill sounds produced by the periodic vibration of the apex of the tongue--are studied. Signal processing methods, namely, zero-frequency filtering and zero-time liftering of speech signals, are used to analyze the excitation source and the resonance characteristics of the vocal tract system, respectively. Although it is natural to expect the effect of trilling on the resonances of the vocal tract system, it is interesting to note that trilling influences the glottal source of excitation as well. The excitation characteristics derived using zero-frequency filtering of speech signals are glottal epochs, strength of impulses at the glottal epochs, and instantaneous fundamental frequency of the glottal vibration. Analysis based on zero-time liftering of speech signals is used to study the dynamic resonance characteristics of vocal tract system during the production of trill sounds. Qualitative analysis of trill sounds in different vowel contexts, and the acoustic cues that may help spotting trills in continuous speech are discussed.

Wind Turbine Diagnosis under Variable Speed Conditions Using a Single Sensor Based on the Synchrosqueezing Transform Method.

PubMed

Guo, Yanjie; Chen, Xuefeng; Wang, Shibin; Sun, Ruobin; Zhao, Zhibin

2017-05-18

The gearbox is one of the key components in wind turbines. Gearbox fault signals are usually nonstationary and highly contaminated with noise. The presence of amplitude-modulated and frequency-modulated (AM-FM) characteristics compound the difficulty of precise fault diagnosis of wind turbines, therefore, it is crucial to develop an effective fault diagnosis method for such equipment. This paper presents an improved diagnosis method for wind turbines via the combination of synchrosqueezing transform and local mean decomposition. Compared to the conventional time-frequency analysis techniques, the improved method which is performed in non-real-time can effectively reduce the noise pollution of the signals and preserve the signal characteristics, and hence is suitable for the analysis of nonstationary signals with high noise. This method is further validated by simulated signals and practical vibration data measured from a 1.5 MW wind turbine. The results confirm that the proposed method can simultaneously control the noise and increase the accuracy of time-frequency representation.

Wind Turbine Diagnosis under Variable Speed Conditions Using a Single Sensor Based on the Synchrosqueezing Transform Method

PubMed Central

Guo, Yanjie; Chen, Xuefeng; Wang, Shibin; Sun, Ruobin; Zhao, Zhibin

2017-01-01

The gearbox is one of the key components in wind turbines. Gearbox fault signals are usually nonstationary and highly contaminated with noise. The presence of amplitude-modulated and frequency-modulated (AM-FM) characteristics compound the difficulty of precise fault diagnosis of wind turbines, therefore, it is crucial to develop an effective fault diagnosis method for such equipment. This paper presents an improved diagnosis method for wind turbines via the combination of synchrosqueezing transform and local mean decomposition. Compared to the conventional time-frequency analysis techniques, the improved method which is performed in non-real-time can effectively reduce the noise pollution of the signals and preserve the signal characteristics, and hence is suitable for the analysis of nonstationary signals with high noise. This method is further validated by simulated signals and practical vibration data measured from a 1.5 MW wind turbine. The results confirm that the proposed method can simultaneously control the noise and increase the accuracy of time-frequency representation. PMID:28524090

RainyDay: An Online, Open-Source Tool for Physically-based Rainfall and Flood Frequency Analysis

NASA Astrophysics Data System (ADS)

Wright, D.; Yu, G.; Holman, K. D.

2017-12-01

Flood frequency analysis in ungaged or changing watersheds typically requires rainfall intensity-duration-frequency (IDF) curves combined with hydrologic models. IDF curves only depict point-scale rainfall depth, while true rainstorms exhibit complex spatial and temporal structures. Floods result from these rainfall structures interacting with watershed features such as land cover, soils, and variable antecedent conditions as well as river channel processes. Thus, IDF curves are traditionally combined with a variety of "design storm" assumptions such as area reduction factors and idealized rainfall space-time distributions to translate rainfall depths into inputs that are suitable for flood hydrologic modeling. The impacts of such assumptions are relatively poorly understood. Meanwhile, modern precipitation estimates from gridded weather radar, grid-interpolated rain gages, satellites, and numerical weather models provide more realistic depictions of rainfall space-time structure. Usage of such datasets for rainfall and flood frequency analysis, however, are hindered by relatively short record lengths. We present RainyDay, an open-source stochastic storm transposition (SST) framework for generating large numbers of realistic rainfall "scenarios." SST "lengthens" the rainfall record by temporal resampling and geospatial transposition of observed storms to extract space-time information from regional gridded rainfall data. Relatively short (10-15 year) records of bias-corrected radar rainfall data are sufficient to estimate rainfall and flood events with much longer recurrence intervals including 100-year and 500-year events. We describe the SST methodology as implemented in RainyDay and compare rainfall IDF results from RainyDay to conventional estimates from NOAA Atlas 14. Then, we demonstrate some of the flood frequency analysis properties that are possible when RainyDay is integrated with a distributed hydrologic model, including robust estimation of flood hazards in a changing watershed. The U.S. Bureau of Reclamation is supporting the development of a web-based variant of RainyDay, a "beta" version of which is available at http://her.cee.wisc.edu/projects/rainyday/.

Detecting fixation on a target using time-frequency distributions of a retinal birefringence scanning signal

PubMed Central

2013-01-01

Background The fovea, which is the most sensitive part of the retina, is known to have birefringent properties, i.e. it changes the polarization state of light upon reflection. Existing devices use this property to obtain information on the orientation of the fovea and the direction of gaze. Such devices employ specific frequency components that appear during moments of fixation on a target. To detect them, previous methods have used solely the power spectrum of the Fast Fourier Transform (FFT), which, unfortunately, is an integral method, and does not give information as to where exactly the events of interest occur. With very young patients who are not cooperative enough, this presents a problem, because central fixation may be present only during very short-lasting episodes, and can easily be missed by the FFT. Method This paper presents a method for detecting short-lasting moments of central fixation in existing devices for retinal birefringence scanning, with the goal of a reliable detection of eye alignment. Signal analysis is based on the Continuous Wavelet Transform (CWT), which reliably localizes such events in the time-frequency plane. Even though the characteristic frequencies are not always strongly expressed due to possible artifacts, simple topological analysis of the time-frequency distribution can detect fixation reliably. Results In all six subjects tested, the CWT allowed precise identification of both frequency components. Moreover, in four of these subjects, episodes of intermittent but definitely present central fixation were detectable, similar to those in Figure 4. A simple FFT is likely to treat them as borderline cases, or entirely miss them, depending on the thresholds used. Conclusion Joint time-frequency analysis is a powerful tool in the detection of eye alignment, even in a noisy environment. The method is applicable to similar situations, where short-lasting diagnostic events need to be detected in time series acquired by means of scanning some substrate along a specific path. PMID:23668264

cyclostratigraphy, sequence stratigraphy and organic matter accumulation mechanism

NASA Astrophysics Data System (ADS)

Cong, F.; Li, J.

2016-12-01

The first member of Maokou Formation of Sichuan basin is composed of well preserved carbonate ramp couplets of limestone and marlstone/shale. It acts as one of the potential shale gas source rock, and is suitable for time-series analysis. We conducted time-series analysis to identify high-frequency sequences, reconstruct high-resolution sedimentation rate, estimate detailed primary productivity for the first time in the study intervals and discuss organic matter accumulation mechanism of source rock under sequence stratigraphic framework.Using the theory of cyclostratigraphy and sequence stratigraphy, the high-frequency sequences of one outcrop profile and one drilling well are identified. Two third-order sequences and eight fourth-order sequences are distinguished on outcrop profile based on the cycle stacking patterns. For drilling well, sequence boundary and four system tracts is distinguished by "integrated prediction error filter analysis" (INPEFA) of Gamma-ray logging data, and eight fourth-order sequences is identified by 405ka long eccentricity curve in depth domain which is quantified and filtered by integrated analysis of MTM spectral analysis, evolutive harmonic analysis (EHA), evolutive average spectral misfit (eASM) and band-pass filtering. It suggests that high-frequency sequences correlate well with Milankovitch orbital signals recorded in sediments, and it is applicable to use cyclostratigraphy theory in dividing high-frequency(4-6 orders) sequence stratigraphy.High-resolution sedimentation rate is reconstructed through the study interval by tracking the highly statistically significant short eccentricity component (123ka) revealed by EHA. Based on sedimentation rate, measured TOC and density data, the burial flux, delivery flux and primary productivity of organic carbon was estimated. By integrating redox proxies, we can discuss the controls on organic matter accumulation by primary production and preservation under the high-resolution sequence stratigraphic framework. Results show that high average organic carbon contents in the study interval are mainly attributed to high primary production. The results also show a good correlation between high organic carbon accumulation and intervals of transgression.

Linear and Nonlinear Time-Frequency Analysis for Parameter Estimation of Resident Space Objects

DTIC Science & Technology

2017-02-22

AFRL-AFOSR-UK-TR-2017-0023 Linear and Nonlinear Time -Frequency Analysis for Parameter Estimation of Resident Space Objects Marco Martorella...estimated to average 1 hour per response, including the time for reviewing instructions, searching existing   data sources, gathering and maintaining the...Nonlinear Time -Frequency Analysis for Parameter Estimation of Resident Space Objects 5a.  CONTRACT NUMBER 5b.  GRANT NUMBER FA9550-14-1-0183 5c.  PROGRAM

Aggregation of Electric Current Consumption Features to Extract Maintenance KPIs

NASA Astrophysics Data System (ADS)

Simon, Victor; Johansson, Carl-Anders; Galar, Diego

2017-09-01

All electric powered machines offer the possibility of extracting information and calculating Key Performance Indicators (KPIs) from the electric current signal. Depending on the time window, sampling frequency and type of analysis, different indicators from the micro to macro level can be calculated for such aspects as maintenance, production, energy consumption etc. On the micro-level, the indicators are generally used for condition monitoring and diagnostics and are normally based on a short time window and a high sampling frequency. The macro indicators are normally based on a longer time window with a slower sampling frequency and are used as indicators for overall performance, cost or consumption. The indicators can be calculated directly from the current signal but can also be based on a combination of information from the current signal and operational data like rpm, position etc. One or several of those indicators can be used for prediction and prognostics of a machine's future behavior. This paper uses this technique to calculate indicators for maintenance and energy optimization in electric powered machines and fleets of machines, especially machine tools.

PLATSIM: A Simulation and Analysis Package for Large-Order Flexible Systems. Version 2.0

NASA Technical Reports Server (NTRS)

Maghami, Peiman G.; Kenny, Sean P.; Giesy, Daniel P.

1997-01-01

The software package PLATSIM provides efficient time and frequency domain analysis of large-order generic space platforms. PLATSIM can perform open-loop analysis or closed-loop analysis with linear or nonlinear control system models. PLATSIM exploits the particular form of sparsity of the plant matrices for very efficient linear and nonlinear time domain analysis, as well as frequency domain analysis. A new, original algorithm for the efficient computation of open-loop and closed-loop frequency response functions for large-order systems has been developed and is implemented within the package. Furthermore, a novel and efficient jitter analysis routine which determines jitter and stability values from time simulations in a very efficient manner has been developed and is incorporated in the PLATSIM package. In the time domain analysis, PLATSIM simulates the response of the space platform to disturbances and calculates the jitter and stability values from the response time histories. In the frequency domain analysis, PLATSIM calculates frequency response function matrices and provides the corresponding Bode plots. The PLATSIM software package is written in MATLAB script language. A graphical user interface is developed in the package to provide convenient access to its various features.

On Holo-Hilbert Spectral Analysis: A Full Informational Spectral Representation for Nonlinear and Non-Stationary Data

NASA Technical Reports Server (NTRS)

Huang, Norden E.; Hu, Kun; Yang, Albert C. C.; Chang, Hsing-Chih; Jia, Deng; Liang, Wei-Kuang; Yeh, Jia Rong; Kao, Chu-Lan; Juan, Chi-Huang; Peng, Chung Kang;

Driving factors of interactions between the exchange rate market and the commodity market: A wavelet-based complex network perspective

NASA Astrophysics Data System (ADS)

Wen, Shaobo; An, Haizhong; Chen, Zhihua; Liu, Xueyong

2017-08-01

In traditional econometrics, a time series must be in a stationary sequence. However, it usually shows time-varying fluctuations, and it remains a challenge to execute a multiscale analysis of the data and discover the topological characteristics of conduction in different scales. Wavelet analysis and complex networks in physical statistics have special advantages in solving these problems. We select the exchange rate variable from the Chinese market and the commodity price index variable from the world market as the time series of our study. We explore the driving factors behind the behavior of the two markets and their topological characteristics in three steps. First, we use the Kalman filter to find the optimal estimation of the relationship between the two markets. Second, wavelet analysis is used to extract the scales of the relationship that are driven by different frequency wavelets. Meanwhile, we search for the actual economic variables corresponding to different frequency wavelets. Finally, a complex network is used to search for the transfer characteristics of the combination of states driven by different frequency wavelets. The results show that statistical physics have a unique advantage over traditional econometrics. The Chinese market has time-varying impacts on the world market: it has greater influence when the world economy is stable and less influence in times of turmoil. The process of forming the state combination is random. Transitions between state combinations have a clustering feature. Based on these characteristics, we can effectively reduce the information burden on investors and correctly respond to the government's policy mix.

Compensation based on linearized analysis for a six degree of freedom motion simulator

NASA Technical Reports Server (NTRS)

Parrish, R. V.; Dieudonne, J. E.; Martin, D. J., Jr.; Copeland, J. L.

1973-01-01

The inertial response characteristics of a synergistic, six-degree-of-freedom motion base are presented in terms of amplitude ratio and phase lag as functions of frequency data for the frequency range of interest (0 to 2 Hz) in real time, digital, flight simulators. The notch filters which smooth the digital-drive signals to continuous drive signals are presented, and appropriate compensation, based on the inertial response data, is suggested. The existence of an inverse transformation that converts actuator extensions into inertial positions makes it possible to gather the response data in the inertial axis system.

Temporal Characterization of Aircraft Noise Sources

NASA Technical Reports Server (NTRS)

Grosveld, Ferdinand W.; Sullivan, Brenda M.; Rizzi, Stephen A.

2004-01-01

Current aircraft source noise prediction tools yield time-independent frequency spectra as functions of directivity angle. Realistic evaluation and human assessment of aircraft fly-over noise require the temporal characteristics of the noise signature. The purpose of the current study is to analyze empirical data from broadband jet and tonal fan noise sources and to provide the temporal information required for prediction-based synthesis. Noise sources included a one-tenth-scale engine exhaust nozzle and a one-fifth scale scale turbofan engine. A methodology was developed to characterize the low frequency fluctuations employing the Short Time Fourier Transform in a MATLAB computing environment. It was shown that a trade-off is necessary between frequency and time resolution in the acoustic spectrogram. The procedure requires careful evaluation and selection of the data analysis parameters, including the data sampling frequency, Fourier Transform window size, associated time period and frequency resolution, and time period window overlap. Low frequency fluctuations were applied to the synthesis of broadband noise with the resulting records sounding virtually indistinguishable from the measured data in initial subjective evaluations. Amplitude fluctuations of blade passage frequency (BPF) harmonics were successfully characterized for conditions equivalent to take-off and approach. Data demonstrated that the fifth harmonic of the BPF varied more in frequency than the BPF itself and exhibited larger amplitude fluctuations over the duration of the time record. Frequency fluctuations were found to be not perceptible in the current characterization of tonal components.

A fingerprint of the epileptogenic zone in human epilepsies.

PubMed

Grinenko, Olesya; Li, Jian; Mosher, John C; Wang, Irene Z; Bulacio, Juan C; Gonzalez-Martinez, Jorge; Nair, Dileep; Najm, Imad; Leahy, Richard M; Chauvel, Patrick

2018-01-01

Defining a bio-electrical marker for the brain area responsible for initiating a seizure remains an unsolved problem. Fast gamma activity has been identified as the most specific marker for seizure onset, but conflicting results have been reported. In this study, we describe an alternative marker, based on an objective description of interictal to ictal transition, with the aim of identifying a time-frequency pattern or 'fingerprint' that can differentiate the epileptogenic zone from areas of propagation. Seventeen patients who underwent stereoelectroencephalography were included in the study. Each had seizure onset characterized by sustained gamma activity and were seizure-free after tailored resection or laser ablation. We postulated that the epileptogenic zone was always located inside the resection region based on seizure freedom following surgery. To characterize the ictal frequency pattern, we applied the Morlet wavelet transform to data from each pair of adjacent intracerebral electrode contacts. Based on a visual assessment of the time-frequency plots, we hypothesized that a specific time-frequency pattern in the epileptogenic zone should include a combination of (i) sharp transients or spikes; preceding (ii) multiband fast activity concurrent; with (iii) suppression of lower frequencies. To test this hypothesis, we developed software that automatically extracted each of these features from the time-frequency data. We then used a support vector machine to classify each contact-pair as being within epileptogenic zone or not, based on these features. Our machine learning system identified this pattern in 15 of 17 patients. The total number of identified contacts across all patients was 64, with 58 localized inside the resected area. Subsequent quantitative analysis showed strong correlation between maximum frequency of fast activity and suppression inside the resection but not outside. We did not observe significant discrimination power using only the maximum frequency or the timing of fast activity to differentiate contacts either between resected and non-resected regions or between contacts identified as epileptogenic versus non-epileptogenic. Instead of identifying a single frequency or a single timing trait, we observed the more complex pattern described above that distinguishes the epileptogenic zone. This pattern encompasses interictal to ictal transition and may extend until seizure end. Its time-frequency characteristics can be explained in light of recent models emphasizing the role of fast inhibitory interneurons acting on pyramidal cells as a prominent mechanism in seizure triggering. The pattern clearly differentiates the epileptogenic zone from areas of propagation and, as such, represents an epileptogenic zone 'fingerprint'.awx306media15687076823001. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain.

A fingerprint of the epileptogenic zone in human epilepsies

PubMed Central

Grinenko, Olesya; Li, Jian; Mosher, John C; Wang, Irene Z; Bulacio, Juan C; Gonzalez-Martinez, Jorge; Nair, Dileep; Najm, Imad; Leahy, Richard M; Chauvel, Patrick

2018-01-01

Abstract Defining a bio-electrical marker for the brain area responsible for initiating a seizure remains an unsolved problem. Fast gamma activity has been identified as the most specific marker for seizure onset, but conflicting results have been reported. In this study, we describe an alternative marker, based on an objective description of interictal to ictal transition, with the aim of identifying a time-frequency pattern or ‘fingerprint’ that can differentiate the epileptogenic zone from areas of propagation. Seventeen patients who underwent stereoelectroencephalography were included in the study. Each had seizure onset characterized by sustained gamma activity and were seizure-free after tailored resection or laser ablation. We postulated that the epileptogenic zone was always located inside the resection region based on seizure freedom following surgery. To characterize the ictal frequency pattern, we applied the Morlet wavelet transform to data from each pair of adjacent intracerebral electrode contacts. Based on a visual assessment of the time-frequency plots, we hypothesized that a specific time-frequency pattern in the epileptogenic zone should include a combination of (i) sharp transients or spikes; preceding (ii) multiband fast activity concurrent; with (iii) suppression of lower frequencies. To test this hypothesis, we developed software that automatically extracted each of these features from the time-frequency data. We then used a support vector machine to classify each contact-pair as being within epileptogenic zone or not, based on these features. Our machine learning system identified this pattern in 15 of 17 patients. The total number of identified contacts across all patients was 64, with 58 localized inside the resected area. Subsequent quantitative analysis showed strong correlation between maximum frequency of fast activity and suppression inside the resection but not outside. We did not observe significant discrimination power using only the maximum frequency or the timing of fast activity to differentiate contacts either between resected and non-resected regions or between contacts identified as epileptogenic versus non-epileptogenic. Instead of identifying a single frequency or a single timing trait, we observed the more complex pattern described above that distinguishes the epileptogenic zone. This pattern encompasses interictal to ictal transition and may extend until seizure end. Its time-frequency characteristics can be explained in light of recent models emphasizing the role of fast inhibitory interneurons acting on pyramidal cells as a prominent mechanism in seizure triggering. The pattern clearly differentiates the epileptogenic zone from areas of propagation and, as such, represents an epileptogenic zone ‘fingerprint’. PMID:29253102

Time and Frequency-Domain Cross-Verification of SLS 6DOF Trajectory Simulations

NASA Technical Reports Server (NTRS)

Johnson, Matthew; McCullough, John

2017-01-01

The Space Launch System (SLS) Guidance, Navigation, and Control (GNC) team and its partners have developed several time- and frequency-based simulations for development and analysis of the proposed SLS launch vehicle. The simulations differ in fidelity and some have unique functionality that allows them to perform specific analyses. Some examples of the purposes of the various models are: trajectory simulation, multi-body separation, Monte Carlo, hardware in the loop, loads, and frequency domain stability analyses. While no two simulations are identical, many of the models are essentially six degree-of-freedom (6DOF) representations of the SLS plant dynamics, hardware implementation, and flight software. Thus at a high level all of those models should be in agreement. Comparison of outputs from several SLS trajectory and stability analysis tools are ongoing as part of the program's current verification effort. The purpose of these comparisons is to highlight modeling and analysis differences, verify simulation data sources, identify inconsistencies and minor errors, and ultimately to verify output data as being a good representation of the vehicle and subsystem dynamics. This paper will show selected verification work in both the time and frequency domain from the current design analysis cycle of the SLS for several of the design and analysis simulations. In the time domain, the tools that will be compared are MAVERIC, CLVTOPS, SAVANT, STARS, ARTEMIS, and POST 2. For the frequency domain analysis, the tools to be compared are FRACTAL, SAVANT, and STARS. The paper will include discussion of these tools including their capabilities, configurations, and the uses to which they are put in the SLS program. Determination of the criteria by which the simulations are compared (matching criteria) requires thoughtful consideration, and there are several pitfalls that may occur that can severely punish a simulation if not considered carefully. The paper will discuss these considerations and will present a framework for responding to these issues when they arise. For example, small event timing differences can lead to large differences in mass properties if the criteria are to measure those properties at the same time, or large differences in altitude if the criteria are to measure those properties when the simulation experiences a staging event. Similarly, a tiny difference in phase can lead to large gain margin differences for frequency-domain comparisons of gain margins.

Efficient Power Network Analysis with Modeling of Inductive Effects

NASA Astrophysics Data System (ADS)

Zeng, Shan; Yu, Wenjian; Hong, Xianlong; Cheng, Chung-Kuan

In this paper, an efficient method is proposed to accurately analyze large-scale power/ground (P/G) networks, where inductive parasitics are modeled with the partial reluctance. The method is based on frequency-domain circuit analysis and the technique of vector fitting [14], and obtains the time-domain voltage response at given P/G nodes. The frequency-domain circuit equation including partial reluctances is derived, and then solved with the GMRES algorithm with rescaling, preconditioning and recycling techniques. With the merit of sparsified reluctance matrix and iterative solving techniques for the frequency-domain circuit equations, the proposed method is able to handle large-scale P/G networks with complete inductive modeling. Numerical results show that the proposed method is orders of magnitude faster than HSPICE, several times faster than INDUCTWISE [4], and capable of handling the inductive P/G structures with more than 100, 000 wire segments.

Time-frequency analysis of acoustic signals in the audio-frequency range generated during Hadfield's steel friction

NASA Astrophysics Data System (ADS)

Dobrynin, S. A.; Kolubaev, E. A.; Smolin, A. Yu.; Dmitriev, A. I.; Psakhie, S. G.

2010-07-01

Time-frequency analysis of sound waves detected by a microphone during the friction of Hadfield’s steel has been performed using wavelet transform and window Fourier transform methods. This approach reveals a relationship between the appearance of quasi-periodic intensity outbursts in the acoustic response signals and the processes responsible for the formation of wear products. It is shown that the time-frequency analysis of acoustic emission in a tribosystem can be applied, along with traditional approaches, to studying features in the wear and friction process.

Automated vessel segmentation using cross-correlation and pooled covariance matrix analysis.

PubMed

Du, Jiang; Karimi, Afshin; Wu, Yijing; Korosec, Frank R; Grist, Thomas M; Mistretta, Charles A

2011-04-01

Time-resolved contrast-enhanced magnetic resonance angiography (CE-MRA) provides contrast dynamics in the vasculature and allows vessel segmentation based on temporal correlation analysis. Here we present an automated vessel segmentation algorithm including automated generation of regions of interest (ROIs), cross-correlation and pooled sample covariance matrix analysis. The dynamic images are divided into multiple equal-sized regions. In each region, ROIs for artery, vein and background are generated using an iterative thresholding algorithm based on the contrast arrival time map and contrast enhancement map. Region-specific multi-feature cross-correlation analysis and pooled covariance matrix analysis are performed to calculate the Mahalanobis distances (MDs), which are used to automatically separate arteries from veins. This segmentation algorithm is applied to a dual-phase dynamic imaging acquisition scheme where low-resolution time-resolved images are acquired during the dynamic phase followed by high-frequency data acquisition at the steady-state phase. The segmented low-resolution arterial and venous images are then combined with the high-frequency data in k-space and inverse Fourier transformed to form the final segmented arterial and venous images. Results from volunteer and patient studies demonstrate the advantages of this automated vessel segmentation and dual phase data acquisition technique. Copyright © 2011 Elsevier Inc. All rights reserved.

Digital signal processing algorithms for automatic voice recognition

NASA Technical Reports Server (NTRS)

Botros, Nazeih M.

1987-01-01

The current digital signal analysis algorithms are investigated that are implemented in automatic voice recognition algorithms. Automatic voice recognition means, the capability of a computer to recognize and interact with verbal commands. The digital signal is focused on, rather than the linguistic, analysis of speech signal. Several digital signal processing algorithms are available for voice recognition. Some of these algorithms are: Linear Predictive Coding (LPC), Short-time Fourier Analysis, and Cepstrum Analysis. Among these algorithms, the LPC is the most widely used. This algorithm has short execution time and do not require large memory storage. However, it has several limitations due to the assumptions used to develop it. The other 2 algorithms are frequency domain algorithms with not many assumptions, but they are not widely implemented or investigated. However, with the recent advances in the digital technology, namely signal processors, these 2 frequency domain algorithms may be investigated in order to implement them in voice recognition. This research is concerned with real time, microprocessor based recognition algorithms.

Ridge extraction from the time-frequency representation (TFR) of signals based on an image processing approach: application to the analysis of uterine electromyogram AR TFR.

PubMed

Terrien, Jérémy; Marque, Catherine; Germain, Guy

2008-05-01

Time-frequency representations (TFRs) of signals are increasingly being used in biomedical research. Analysis of such representations is sometimes difficult, however, and is often reduced to the extraction of ridges, or local energy maxima. In this paper, we describe a new ridge extraction method based on the image processing technique of active contours or snakes. We have tested our method on several synthetic signals and for the analysis of uterine electromyogram or electrohysterogram (EHG) recorded during gestation in monkeys. We have also evaluated a postprocessing algorithm that is especially suited for EHG analysis. Parameters are evaluated on real EHG signals in different gestational periods. The presented method gives good results when applied to synthetic as well as EHG signals. We have been able to obtain smaller ridge extraction errors when compared to two other methods specially developed for EHG. The gradient vector flow (GVF) snake method, or GVF-snake method, appears to be a good ridge extraction tool, which could be used on TFR of mono or multicomponent signals with good results.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Goyal, Arti; Stawarz, Łukasz; Ostrowski, Michał

We present the results of our power spectral analysis for the BL Lac object PKS 0735+178, utilizing the Fermi -LAT survey at high-energy γ -rays, several ground-based optical telescopes, and single-dish radio telescopes operating at GHz frequencies. The novelty of our approach is that, by combining long-term and densely sampled intra-night light curves in the optical regime, we were able to construct for the first time the optical power spectrum of the blazar for a time domain extending from 23 years down to minutes. Our analysis reveals that: (1) the optical variability is consistent with a pure red noise, formore » which the power spectral density can be well approximated by a single power law throughout the entire time domain probed; (2) the slope of power spectral density at high-energy γ -rays (∼1) is significantly flatter than that found at radio and optical frequencies (∼2) within the corresponding time variability range; (3) for the derived power spectra, we did not detect any low-frequency flattening, nor do we see any evidence for cutoffs at the highest frequencies down to the noise floor levels due to measurement uncertainties. We interpret our findings in terms of a model where the blazar variability is generated by the underlying single stochastic process (at radio and optical frequencies), or a linear superposition of such processes (in the γ -ray regime). Along with the detailed PSD analysis, we also present the results of our extended (1998–2015) intra-night optical monitoring program and newly acquired optical photo-polarimetric data for the source.« less

Research on rolling element bearing fault diagnosis based on genetic algorithm matching pursuit

NASA Astrophysics Data System (ADS)

Rong, R. W.; Ming, T. F.

2017-12-01

In order to solve the problem of slow computation speed, matching pursuit algorithm is applied to rolling bearing fault diagnosis, and the improvement are conducted from two aspects that are the construction of dictionary and the way to search for atoms. To be specific, Gabor function which can reflect time-frequency localization characteristic well is used to construct the dictionary, and the genetic algorithm to improve the searching speed. A time-frequency analysis method based on genetic algorithm matching pursuit (GAMP) algorithm is proposed. The way to set property parameters for the improvement of the decomposition results is studied. Simulation and experimental results illustrate that the weak fault feature of rolling bearing can be extracted effectively by this proposed method, at the same time, the computation speed increases obviously.

Statistical Frequency-Dependent Analysis of Trial-to-Trial Variability in Single Time Series by Recurrence Plots.

PubMed

Tošić, Tamara; Sellers, Kristin K; Fröhlich, Flavio; Fedotenkova, Mariia; Beim Graben, Peter; Hutt, Axel

2015-01-01

For decades, research in neuroscience has supported the hypothesis that brain dynamics exhibits recurrent metastable states connected by transients, which together encode fundamental neural information processing. To understand the system's dynamics it is important to detect such recurrence domains, but it is challenging to extract them from experimental neuroscience datasets due to the large trial-to-trial variability. The proposed methodology extracts recurrent metastable states in univariate time series by transforming datasets into their time-frequency representations and computing recurrence plots based on instantaneous spectral power values in various frequency bands. Additionally, a new statistical inference analysis compares different trial recurrence plots with corresponding surrogates to obtain statistically significant recurrent structures. This combination of methods is validated by applying it to two artificial datasets. In a final study of visually-evoked Local Field Potentials in partially anesthetized ferrets, the methodology is able to reveal recurrence structures of neural responses with trial-to-trial variability. Focusing on different frequency bands, the δ-band activity is much less recurrent than α-band activity. Moreover, α-activity is susceptible to pre-stimuli, while δ-activity is much less sensitive to pre-stimuli. This difference in recurrence structures in different frequency bands indicates diverse underlying information processing steps in the brain.

Statistical Frequency-Dependent Analysis of Trial-to-Trial Variability in Single Time Series by Recurrence Plots

PubMed Central

Tošić, Tamara; Sellers, Kristin K.; Fröhlich, Flavio; Fedotenkova, Mariia; beim Graben, Peter; Hutt, Axel

2016-01-01

For decades, research in neuroscience has supported the hypothesis that brain dynamics exhibits recurrent metastable states connected by transients, which together encode fundamental neural information processing. To understand the system's dynamics it is important to detect such recurrence domains, but it is challenging to extract them from experimental neuroscience datasets due to the large trial-to-trial variability. The proposed methodology extracts recurrent metastable states in univariate time series by transforming datasets into their time-frequency representations and computing recurrence plots based on instantaneous spectral power values in various frequency bands. Additionally, a new statistical inference analysis compares different trial recurrence plots with corresponding surrogates to obtain statistically significant recurrent structures. This combination of methods is validated by applying it to two artificial datasets. In a final study of visually-evoked Local Field Potentials in partially anesthetized ferrets, the methodology is able to reveal recurrence structures of neural responses with trial-to-trial variability. Focusing on different frequency bands, the δ-band activity is much less recurrent than α-band activity. Moreover, α-activity is susceptible to pre-stimuli, while δ-activity is much less sensitive to pre-stimuli. This difference in recurrence structures in different frequency bands indicates diverse underlying information processing steps in the brain. PMID:26834580

Influence of running stride frequency in heart rate variability analysis during treadmill exercise testing.

PubMed

Bailón, Raquel; Garatachea, Nuria; de la Iglesia, Ignacio; Casajús, Jose Antonio; Laguna, Pablo

2013-07-01

The analysis and interpretation of heart rate variability (HRV) during exercise is challenging not only because of the nonstationary nature of exercise, the time-varying mean heart rate, and the fact that respiratory frequency exceeds 0.4 Hz, but there are also other factors, such as the component centered at the pedaling frequency observed in maximal cycling tests, which may confuse the interpretation of HRV analysis. The objectives of this study are to test the hypothesis that a component centered at the running stride frequency (SF) appears in the HRV of subjects during maximal treadmill exercise testing, and to study its influence in the interpretation of the low-frequency (LF) and high-frequency (HF) components of HRV during exercise. The HRV of 23 subjects during maximal treadmill exercise testing is analyzed. The instantaneous power of different HRV components is computed from the smoothed pseudo-Wigner-Ville distribution of the modulating signal assumed to carry information from the autonomic nervous system, which is estimated based on the time-varying integral pulse frequency modulation model. Besides the LF and HF components, the appearance is revealed of a component centered at the running SF as well as its aliases. The power associated with the SF component and its aliases represents 22±7% (median±median absolute deviation) of the total HRV power in all the subjects. Normalized LF power decreases as the exercise intensity increases, while normalized HF power increases. The power associated with the SF does not change significantly with exercise intensity. Consideration of the running SF component and its aliases is very important in HRV analysis since stride frequency aliases may overlap with LF and HF components.

Characterization of platelet adhesion under flow using microscopic image sequence analysis.

PubMed

Machin, M; Santomaso, A; Cozzi, M R; Battiston, M; Mazzuccato, M; De Marco, L; Canu, P

2005-07-01

A method for quantitative analysis of platelet deposition under flow is discussed here. The model system is based upon perfusion of blood platelets over an adhesive substrate immobilized on a glass coverslip acting as the lower surface of a rectangular flow chamber. The perfusion apparatus is mounted onto an inverted microscope equipped with epifluorescent illumination and intensified CCD video camera. Characterization is based on information obtained from a specific image analysis method applied to continuous sequences of microscopical images. Platelet recognition across the sequence of images is based on a time-dependent, bidimensional, gaussian-like pdf. Once a platelet is located,the variation of its position and shape as a function of time (i.e., the platelet history) can be determined. Analyzing the history we can establish if the platelet is moving on the surface, the frequency of this movement and the distance traveled before its resumes the velocity of a non-interacting cell. Therefore, we can determine how long the adhesion would last which is correlated to the resistance of the platelet-substrate bond. This algorithm enables the dynamic quantification of trajectories, as well as residence times, arrest and release frequencies for a high numbers of platelets at the same time. Statistically significant conclusions on platelet-surface interactions can then be obtained. An image analysis tool of this kind can dramatically help the investigation and characterization of the thrombogenic properties of artificial surfaces such as those used in artificial organs and biomedical devices.

Computer implemented empirical mode decomposition method apparatus, and article of manufacture utilizing curvature extrema

NASA Technical Reports Server (NTRS)

Shen, Zheng (Inventor); Huang, Norden Eh (Inventor)

2003-01-01

A computer implemented physical signal analysis method is includes two essential steps and the associated presentation techniques of the results. All the steps exist only in a computer: there are no analytic expressions resulting from the method. The first step is a computer implemented Empirical Mode Decomposition to extract a collection of Intrinsic Mode Functions (IMF) from nonlinear, nonstationary physical signals based on local extrema and curvature extrema. The decomposition is based on the direct extraction of the energy associated with various intrinsic time scales in the physical signal. Expressed in the IMF's, they have well-behaved Hilbert Transforms from which instantaneous frequencies can be calculated. The second step is the Hilbert Transform. The final result is the Hilbert Spectrum. Thus, the invention can localize any event on the time as well as the frequency axis. The decomposition can also be viewed as an expansion of the data in terms of the IMF's. Then, these IMF's, based on and derived from the data, can serve as the basis of that expansion. The local energy and the instantaneous frequency derived from the IMF's through the Hilbert transform give a full energy-frequency-time distribution of the data which is designated as the Hilbert Spectrum.

Time-frequency analysis of backscattered signals from diffuse radar targets

NASA Astrophysics Data System (ADS)

Kenny, O. P.; Boashash, B.

1993-06-01

The need for analysis of time-varying signals has led to the formulation of a class of joint time-frequency distributions (TFDs). One of these TFDs, the Wigner-Ville distribution (WVD), has useful properties which can be applied to radar imaging. The authors discuss time-frequency representation of the backscattered signal from a diffuse radar target. It is then shown that for point scatterers which are statistically dependent or for which the reflectivity coefficient has a nonzero mean value, reconstruction using time of flight positron emission tomography on time-frequency images is effective for estimating the scattering function of the target.

Adaptive noise cancelling and time-frequency techniques for rail surface defect detection

NASA Astrophysics Data System (ADS)

Liang, B.; Iwnicki, S.; Ball, A.; Young, A. E.

2015-03-01

Adaptive noise cancelling (ANC) is a technique which is very effective to remove additive noises from the contaminated signals. It has been widely used in the fields of telecommunication, radar and sonar signal processing. However it was seldom used for the surveillance and diagnosis of mechanical systems before late of 1990s. As a promising technique it has gradually been exploited for the purpose of condition monitoring and fault diagnosis. Time-frequency analysis is another useful tool for condition monitoring and fault diagnosis purpose as time-frequency analysis can keep both time and frequency information simultaneously. This paper presents an ANC and time-frequency application for railway wheel flat and rail surface defect detection. The experimental results from a scaled roller test rig show that this approach can significantly reduce unwanted interferences and extract the weak signals from strong background noises. The combination of ANC and time-frequency analysis may provide us one of useful tools for condition monitoring and fault diagnosis of railway vehicles.

The nexus between geopolitical uncertainty and crude oil markets: An entropy-based wavelet analysis

NASA Astrophysics Data System (ADS)

Uddin, Gazi Salah; Bekiros, Stelios; Ahmed, Ali

2018-04-01

The global financial crisis and the subsequent geopolitical turbulence in energy markets have brought increased attention to the proper statistical modeling especially of the crude oil markets. In particular, we utilize a time-frequency decomposition approach based on wavelet analysis to explore the inherent dynamics and the casual interrelationships between various types of geopolitical, economic and financial uncertainty indices and oil markets. Via the introduction of a mixed discrete-continuous multiresolution analysis, we employ the entropic criterion for the selection of the optimal decomposition level of a MODWT as well as the continuous-time coherency and phase measures for the detection of business cycle (a)synchronization. Overall, a strong heterogeneity in the revealed interrelationships is detected over time and across scales.

A statistical package for computing time and frequency domain analysis

NASA Technical Reports Server (NTRS)

Brownlow, J.

1978-01-01

The spectrum analysis (SPA) program is a general purpose digital computer program designed to aid in data analysis. The program does time and frequency domain statistical analyses as well as some preanalysis data preparation. The capabilities of the SPA program include linear trend removal and/or digital filtering of data, plotting and/or listing of both filtered and unfiltered data, time domain statistical characterization of data, and frequency domain statistical characterization of data.

Analytical validation of an explicit finite element model of a rolling element bearing with a localised line spall

NASA Astrophysics Data System (ADS)

Singh, Sarabjeet; Howard, Carl Q.; Hansen, Colin H.; Köpke, Uwe G.

2018-03-01

In this paper, numerically modelled vibration response of a rolling element bearing with a localised outer raceway line spall is presented. The results were obtained from a finite element (FE) model of the defective bearing solved using an explicit dynamics FE software package, LS-DYNA. Time domain vibration signals of the bearing obtained directly from the FE modelling were processed further to estimate time-frequency and frequency domain results, such as spectrogram and power spectrum, using standard signal processing techniques pertinent to the vibration-based monitoring of rolling element bearings. A logical approach to analyses of the numerically modelled results was developed with an aim to presenting the analytical validation of the modelled results. While the time and frequency domain analyses of the results show that the FE model generates accurate bearing kinematics and defect frequencies, the time-frequency analysis highlights the simulation of distinct low- and high-frequency characteristic vibration signals associated with the unloading and reloading of the rolling elements as they move in and out of the defect, respectively. Favourable agreement of the numerical and analytical results demonstrates the validation of the results from the explicit FE modelling of the bearing.

Wavelet analysis of frequency chaos game signal: a time-frequency signature of the C. elegans DNA.

PubMed

Messaoudi, Imen; Oueslati, Afef Elloumi; Lachiri, Zied

2014-12-01

Challenging tasks are encountered in the field of bioinformatics. The choice of the genomic sequence's mapping technique is one the most fastidious tasks. It shows that a judicious choice would serve in examining periodic patterns distribution that concord with the underlying structure of genomes. Despite that, searching for a coding technique that can highlight all the information contained in the DNA has not yet attracted the attention it deserves. In this paper, we propose a new mapping technique based on the chaos game theory that we call the frequency chaos game signal (FCGS). The particularity of the FCGS coding resides in exploiting the statistical properties of the genomic sequence itself. This may reflect important structural and organizational features of DNA. To prove the usefulness of the FCGS approach in the detection of different local periodic patterns, we use the wavelet analysis because it provides access to information that can be obscured by other time-frequency methods such as the Fourier analysis. Thus, we apply the continuous wavelet transform (CWT) with the complex Morlet wavelet as a mother wavelet function. Scalograms that relate to the organism Caenorhabditis elegans (C. elegans) exhibit a multitude of periodic organization of specific DNA sequences.

On Hilbert-Huang Transform Based Synthesis of a Signal Contaminated by Radio Frequency Interference or Fringes

NASA Technical Reports Server (NTRS)

Kizhner, Semion; Shiri, Ron S.; Vootukuru, Meg; Coletti, Alessandro

2015-01-01

Norden E. Huang et al. had proposed and published the Hilbert-Huang Transform (HHT) concept correspondently in 1996, 1998. The HHT is a novel method for adaptive spectral analysis of non-linear and non-stationary signals. The HHT comprises two components: - the Huang Empirical Mode Decomposition (EMD), resulting in an adaptive data-derived basis of Intrinsic Mode functions (IMFs), and the Hilbert Spectral Analysis (HSA1) based on the Hilbert Transform for 1-dimension (1D) applied to the EMD IMF's outcome. Although paper describes the HHT concept in great depth, it does not contain all needed methodology to implement the HHT computer code. In 2004, Semion Kizhner and Karin Blank implemented the reference digital HHT real-time data processing system for 1D (HHT-DPS Version 1.4). The case for 2-Dimension (2D) (HHT2) proved to be difficult due to the computational complexity of EMD for 2D (EMD2) and absence of a suitable Hilbert Transform for 2D spectral analysis (HSA2). The real-time EMD2 and HSA2 comprise the real-time HHT2. Kizhner completed the real-time EMD2 and the HSA2 reference digital implementations respectively in 2013 & 2014. Still, the HHT2 outcome synthesis remains an active research area. This paper presents the initial concepts and preliminary results of HHT2-based synthesis and its application to processing of signals contaminated by Radio-Frequency Interference (RFI), as well as optical systems' fringe detection and mitigation at design stage. The Soil Moisture Active Passive (SMAP mission (SMAP) carries a radiometer instrument that measures Earth soil moisture at L1 frequency (1.4 GHz polarimetric - H, V, 3rd and 4th Stokes parameters). There is abundant RFI at L1 and because soil moisture is a strategic parameter, it is important to be able to recover the RFI-contaminated measurement samples (15% of telemetry). State-of-the-art only allows RFI detection and removes RFI-contaminated measurements. The HHT-based analysis and synthesis facilitates recovery of measurements contaminated by all kinds of RFI, including jamming [7-8]. The fringes are inherent in optical systems and multi-layer complex contour expensive coatings are employed to remove the unwanted fringes. HHT2-based analysis allows test image decomposition to analyze and detect fringes, and HHT2-based synthesis of useful image.

High-frequency combination coding-based steady-state visual evoked potential for brain computer interface

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Feng; Zhang, Xin; Xie, Jun

2015-03-10

This study presents a new steady-state visual evoked potential (SSVEP) paradigm for brain computer interface (BCI) systems. The goal of this study is to increase the number of targets using fewer stimulation high frequencies, with diminishing subject’s fatigue and reducing the risk of photosensitive epileptic seizures. The new paradigm is High-Frequency Combination Coding-Based High-Frequency Steady-State Visual Evoked Potential (HFCC-SSVEP).Firstly, we studied SSVEP high frequency(beyond 25 Hz)response of SSVEP, whose paradigm is presented on the LED. The SNR (Signal to Noise Ratio) of high frequency(beyond 40 Hz) response is very low, which is been unable to be distinguished through the traditional analysis method;more » Secondly we investigated the HFCC-SSVEP response (beyond 25 Hz) for 3 frequencies (25Hz, 33.33Hz, and 40Hz), HFCC-SSVEP produces n{sup n} with n high stimulation frequencies through Frequence Combination Code. Further, Animproved Hilbert-huang transform (IHHT)-based variable frequency EEG feature extraction method and a local spectrum extreme target identification algorithmare adopted to extract time-frequency feature of the proposed HFCC-SSVEP response.Linear predictions and fixed sifting (iterating) 10 time is used to overcome the shortage of end effect and stopping criterion,generalized zero-crossing (GZC) is used to compute the instantaneous frequency of the proposed SSVEP respondent signals, the improved HHT-based feature extraction method for the proposed SSVEP paradigm in this study increases recognition efficiency, so as to improve ITR and to increase the stability of the BCI system. what is more, SSVEPs evoked by high-frequency stimuli (beyond 25Hz) minimally diminish subject’s fatigue and prevent safety hazards linked to photo-induced epileptic seizures, So as to ensure the system efficiency and undamaging.This study tests three subjects in order to verify the feasibility of the proposed method.« less

Assessing co-regulation of directly linked genes in biological networks using microarray time series analysis.

PubMed

Del Sorbo, Maria Rosaria; Balzano, Walter; Donato, Michele; Draghici, Sorin

2013-11-01

Differential expression of genes detected with the analysis of high throughput genomic experiments is a commonly used intermediate step for the identification of signaling pathways involved in the response to different biological conditions. The impact analysis was the first approach for the analysis of signaling pathways involved in a certain biological process that was able to take into account not only the magnitude of the expression change of the genes but also the topology of signaling pathways including the type of each interactions between the genes. In the impact analysis, signaling pathways are represented as weighted directed graphs with genes as nodes and the interactions between genes as edges. Edges weights are represented by a β factor, the regulatory efficiency, which is assumed to be equal to 1 in inductive interactions between genes and equal to -1 in repressive interactions. This study presents a similarity analysis between gene expression time series aimed to find correspondences with the regulatory efficiency, i.e. the β factor as found in a widely used pathway database. Here, we focused on correlations among genes directly connected in signaling pathways, assuming that the expression variations of upstream genes impact immediately downstream genes in a short time interval and without significant influences by the interactions with other genes. Time series were processed using three different similarity metrics. The first metric is based on the bit string matching; the second one is a specific application of the Dynamic Time Warping to detect similarities even in presence of stretching and delays; the third one is a quantitative comparative analysis resulting by an evaluation of frequency domain representation of time series: the similarity metric is the correlation between dominant spectral components. These three approaches are tested on real data and pathways, and a comparison is performed using Information Retrieval benchmark tools, indicating the frequency approach as the best similarity metric among the three, for its ability to detect the correlation based on the correspondence of the most significant frequency components. Copyright © 2013. Published by Elsevier Ireland Ltd.

Analysis of Human's Motions Based on Local Mean Decomposition in Through-wall Radar Detection

NASA Astrophysics Data System (ADS)

Lu, Qi; Liu, Cai; Zeng, Zhaofa; Li, Jing; Zhang, Xuebing

2016-04-01

Observation of human motions through a wall is an important issue in security applications and search-and rescue. Radar has advantages in looking through walls where other sensors give low performance or cannot be used at all. Ultrawideband (UWB) radar has high spatial resolution as a result of employment of ultranarrow pulses. It has abilities to distinguish the closely positioned targets and provide time-lapse information of targets. Moreover, the UWB radar shows good performance in wall penetration when the inherently short pulses spread their energy over a broad frequency range. Human's motions show periodic features including respiration, swing arms and legs, fluctuations of the torso. Detection of human targets is based on the fact that there is always periodic motion due to breathing or other body movements like walking. The radar can gain the reflections from each human body parts and add the reflections at each time sample. The periodic movements will cause micro-Doppler modulation in the reflected radar signals. Time-frequency analysis methods are consider as the effective tools to analysis and extract micro-Doppler effects caused by the periodic movements in the reflected radar signal, such as short-time Fourier transform (STFT), wavelet transform (WT), and Hilbert-Huang transform (HHT).The local mean decomposition (LMD), initially developed by Smith (2005), is to decomposed amplitude and frequency modulated signals into a small set of product functions (PFs), each of which is the product of an envelope signal and a frequency modulated signal from which a time-vary instantaneous phase and instantaneous frequency can be derived. As bypassing the Hilbert transform, the LMD has no demodulation error coming from window effect and involves no negative frequency without physical sense. Also, the instantaneous attributes obtained by LMD are more stable and precise than those obtained by the empirical mode decomposition (EMD) because LMD uses smoothed local means and local magnitudes that facilitate a more natural decomposition than that using the cubic spline approach of EMD. In this paper, we apply the UWB radar system in through-wall human detections and present a method to characterize human's motions. We start with a walker's motion model and periodic motion features are given the analysis of the experimental data based on the combination of the LMT and fast Fourier Transform (FFT). The characteristics of human's motions including respiration, swing arms and legs, and fluctuations of the torso are extracted. At last, we calculate the actual distance between the human and the wall. This work was supported in part by National Natural Science Foundation of China under Grant 41574109 and 41430322.

Iterative generalized time-frequency reassignment for planetary gearbox fault diagnosis under nonstationary conditions

NASA Astrophysics Data System (ADS)

Chen, Xiaowang; Feng, Zhipeng

2016-12-01

Planetary gearboxes are widely used in many sorts of machinery, for its large transmission ratio and high load bearing capacity in a compact structure. Their fault diagnosis relies on effective identification of fault characteristic frequencies. However, in addition to the vibration complexity caused by intricate mechanical kinematics, volatile external conditions result in time-varying running speed and/or load, and therefore nonstationary vibration signals. This usually leads to time-varying complex fault characteristics, and adds difficulty to planetary gearbox fault diagnosis. Time-frequency analysis is an effective approach to extracting the frequency components and their time variation of nonstationary signals. Nevertheless, the commonly used time-frequency analysis methods suffer from poor time-frequency resolution as well as outer and inner interferences, which hinder accurate identification of time-varying fault characteristic frequencies. Although time-frequency reassignment improves the time-frequency readability, it is essentially subject to the constraints of mono-component and symmetric time-frequency distribution about true instantaneous frequency. Hence, it is still susceptible to erroneous energy reallocation or even generates pseudo interferences, particularly for multi-component signals of highly nonlinear instantaneous frequency. In this paper, to overcome the limitations of time-frequency reassignment, we propose an improvement with fine time-frequency resolution and free from interferences for highly nonstationary multi-component signals, by exploiting the merits of iterative generalized demodulation. The signal is firstly decomposed into mono-components of constant frequency by iterative generalized demodulation. Time-frequency reassignment is then applied to each generalized demodulated mono-component, obtaining a fine time-frequency distribution. Finally, the time-frequency distribution of each signal component is restored and superposed to get the time-frequency distribution of original signal. The proposed method is validated using both numerical simulated and lab experimental planetary gearbox vibration signals. The time-varying gear fault symptoms are successfully extracted, showing effectiveness of the proposed iterative generalized time-frequency reassignment method in planetary gearbox fault diagnosis under nonstationary conditions.

Updated Intensity - Duration - Frequency Curves Under Different Future Climate Scenarios

NASA Astrophysics Data System (ADS)

Ragno, E.; AghaKouchak, A.

2016-12-01

Current infrastructure design procedures rely on the use of Intensity - Duration - Frequency (IDF) curves retrieved under the assumption of temporal stationarity, meaning that occurrences of extreme events are expected to be time invariant. However, numerous studies have observed more severe extreme events over time. Hence, the stationarity assumption for extreme analysis may not be appropriate in a warming climate. This issue raises concerns regarding the safety and resilience of the existing and future infrastructures. Here we employ historical and projected (RCP 8.5) CMIP5 runs to investigate IDF curves of 14 urban areas across the United States. We first statistically assess changes in precipitation extremes using an energy-based test for equal distributions. Then, through a Bayesian inference approach for stationary and non-stationary extreme value analysis, we provide updated IDF curves based on climatic model projections. This presentation summarizes the projected changes in statistics of extremes. We show that, based on CMIP5 simulations, extreme precipitation events in some urban areas can be 20% more severe in the future, even when projected annual mean precipitation is expected to remain similar to the ground-based climatology.

Frequency Management for Electromagnetic Continuous Wave Conductivity Meters

PubMed Central

Mazurek, Przemyslaw; Putynkowski, Grzegorz

2016-01-01

Ground conductivity meters use electromagnetic fields for the mapping of geological variations, like the determination of water amount, depending on ground layers, which is important for the state analysis of embankments. The VLF band is contaminated by numerous natural and artificial electromagnetic interference signals. Prior to the determination of ground conductivity, the meter’s working frequency is not possible, due to the variable frequency of the interferences. Frequency management based on the analysis of the selected band using track-before-detect (TBD) algorithms, which allows dynamical frequency changes of the conductivity of the meter transmitting part, is proposed in the paper. Naive maximum value search, spatio-temporal TBD (ST-TBD), Viterbi TBD and a new algorithm that uses combined ST-TBD and Viterbi TBD are compared. Monte Carlo tests are provided for the numerical analysis of the properties for a single interference signal in the considered band, and a new approach based on combined ST-TBD and Viterbi algorithms shows the best performance. The considered algorithms process spectrogram data for the selected band, so DFT (Discrete Fourier Transform) could be applied for the computation of the spectrogram. Real–time properties, related to the latency, are discussed also, and it is shown that TBD algorithms are feasible for real applications. PMID:27070608

Frequency Management for Electromagnetic Continuous Wave Conductivity Meters.

PubMed

Mazurek, Przemyslaw; Putynkowski, Grzegorz

2016-04-07

Ground conductivity meters use electromagnetic fields for the mapping of geological variations, like the determination of water amount, depending on ground layers, which is important for the state analysis of embankments. The VLF band is contaminated by numerous natural and artificial electromagnetic interference signals. Prior to the determination of ground conductivity, the meter's working frequency is not possible, due to the variable frequency of the interferences. Frequency management based on the analysis of the selected band using track-before-detect (TBD) algorithms, which allows dynamical frequency changes of the conductivity of the meter transmitting part, is proposed in the paper. Naive maximum value search, spatio-temporal TBD (ST-TBD), Viterbi TBD and a new algorithm that uses combined ST-TBD and Viterbi TBD are compared. Monte Carlo tests are provided for the numerical analysis of the properties for a single interference signal in the considered band, and a new approach based on combined ST-TBD and Viterbi algorithms shows the best performance. The considered algorithms process spectrogram data for the selected band, so DFT (Discrete Fourier Transform) could be applied for the computation of the spectrogram. Real-time properties, related to the latency, are discussed also, and it is shown that TBD algorithms are feasible for real applications.

A Study on Regional Rainfall Frequency Analysis for Flood Simulation Scenarios

NASA Astrophysics Data System (ADS)

Jung, Younghun; Ahn, Hyunjun; Joo, Kyungwon; Heo, Jun-Haeng

2014-05-01

Recently, climate change has been observed in Korea as well as in the entire world. The rainstorm has been gradually increased and then the damage has been grown. It is very important to manage the flood control facilities because of increasing the frequency and magnitude of severe rain storm. For managing flood control facilities in risky regions, data sets such as elevation, gradient, channel, land use and soil data should be filed up. Using this information, the disaster situations can be simulated to secure evacuation routes for various rainfall scenarios. The aim of this study is to investigate and determine extreme rainfall quantile estimates in Uijeongbu City using index flood method with L-moments parameter estimation. Regional frequency analysis trades space for time by using annual maximum rainfall data from nearby or similar sites to derive estimates for any given site in a homogeneous region. Regional frequency analysis based on pooled data is recommended for estimation of rainfall quantiles at sites with record lengths less than 5T, where T is return period of interest. Many variables relevant to precipitation can be used for grouping a region in regional frequency analysis. For regionalization of Han River basin, the k-means method is applied for grouping regions by variables of meteorology and geomorphology. The results from the k-means method are compared for each region using various probability distributions. In the final step of the regionalization analysis, goodness-of-fit measure is used to evaluate the accuracy of a set of candidate distributions. And rainfall quantiles by index flood method are obtained based on the appropriate distribution. And then, rainfall quantiles based on various scenarios are used as input data for disaster simulations. Keywords: Regional Frequency Analysis; Scenarios of Rainfall Quantile Acknowledgements This research was supported by a grant 'Establishing Active Disaster Management System of Flood Control Structures by using 3D BIM Technique' [NEMA-12-NH-57] from the Natural Hazard Mitigation Research Group, National Emergency Management Agency of Korea.

Possible signatures of dissipation from time-series analysis techniques using a turbulent laboratory magnetohydrodynamic plasma

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schaffner, D. A.; Brown, M. R.; Rock, A. B.

The frequency spectrum of magnetic fluctuations as measured on the Swarthmore Spheromak Experiment is broadband and exhibits a nearly Kolmogorov 5/3 scaling. It features a steepening region which is indicative of dissipation of magnetic fluctuation energy similar to that observed in fluid and magnetohydrodynamic turbulence systems. Two non-spectrum based time-series analysis techniques are implemented on this data set in order to seek other possible signatures of turbulent dissipation beyond just the steepening of fluctuation spectra. Presented here are results for the flatness, permutation entropy, and statistical complexity, each of which exhibits a particular character at spectral steepening scales which canmore » then be compared to the behavior of the frequency spectrum.« less

Automated diagnosis of autism: in search of a mathematical marker.

PubMed

Bhat, Shreya; Acharya, U Rajendra; Adeli, Hojjat; Bairy, G Muralidhar; Adeli, Amir

2014-01-01

Autism is a type of neurodevelopmental disorder affecting the memory, behavior, emotion, learning ability, and communication of an individual. An early detection of the abnormality, due to irregular processing in the brain, can be achieved using electroencephalograms (EEG). The variations in the EEG signals cannot be deciphered by mere visual inspection. Computer-aided diagnostic tools can be used to recognize the subtle and invisible information present in the irregular EEG pattern and diagnose autism. This paper presents a state-of-the-art review of automated EEG-based diagnosis of autism. Various time domain, frequency domain, time-frequency domain, and nonlinear dynamics for the analysis of autistic EEG signals are described briefly. A focus of the review is the use of nonlinear dynamics and chaos theory to discover the mathematical biomarkers for the diagnosis of the autism analogous to biological markers. A combination of the time-frequency and nonlinear dynamic analysis is the most effective approach to characterize the nonstationary and chaotic physiological signals for the automated EEG-based diagnosis of autism spectrum disorder (ASD). The features extracted using these nonlinear methods can be used as mathematical markers to detect the early stage of autism and aid the clinicians in their diagnosis. This will expedite the administration of appropriate therapies to treat the disorder.

An innovative approach for characteristic analysis and state-of-health diagnosis for a Li-ion cell based on the discrete wavelet transform

NASA Astrophysics Data System (ADS)

Kim, Jonghoon; Cho, B. H.

2014-08-01

This paper introduces an innovative approach to analyze electrochemical characteristics and state-of-health (SOH) diagnosis of a Li-ion cell based on the discrete wavelet transform (DWT). In this approach, the DWT has been applied as a powerful tool in the analysis of the discharging/charging voltage signal (DCVS) with non-stationary and transient phenomena for a Li-ion cell. Specifically, DWT-based multi-resolution analysis (MRA) is used for extracting information on the electrochemical characteristics in both time and frequency domain simultaneously. Through using the MRA with implementation of the wavelet decomposition, the information on the electrochemical characteristics of a Li-ion cell can be extracted from the DCVS over a wide frequency range. Wavelet decomposition based on the selection of the order 3 Daubechies wavelet (dB3) and scale 5 as the best wavelet function and the optimal decomposition scale is implemented. In particular, this present approach develops these investigations one step further by showing low and high frequency components (approximation component An and detail component Dn, respectively) extracted from variable Li-ion cells with different electrochemical characteristics caused by aging effect. Experimental results show the clearness of the DWT-based approach for the reliable diagnosis of the SOH for a Li-ion cell.

An analysis of a candidate control algorithm for a ride quality augmentation system

NASA Technical Reports Server (NTRS)

Suikat, Reiner; Donaldson, Kent; Downing, David R.

1987-01-01

This paper presents a detailed analysis of a candidate algorithm for a ride quality augmentation system. The algorithm consists of a full-state feedback control law based on optimal control output weighting, estimators for angle of attack and sideslip, and a maneuvering algorithm. The control law is shown to perform well by both frequency and time domain analysis. The rms vertical acceleration is reduced by about 40 percent over the whole mission flight envelope. The estimators for the angle of attack and sideslip avoid the often inaccurate or costly direct measurement of those angles. The maneuvering algorithm will allow the augmented airplane to respond to pilot inputs. The design characteristics and performance are documented by the closed-loop eigenvalues; rms levels of vertical, lateral, and longitudinal acceleration; and representative time histories and frequency response.

Cross Time-Frequency Analysis of Gastrocnemius Electromyographic Signals in Hypertensive and Nonhypertensive Subjects

NASA Astrophysics Data System (ADS)

Mitchell, Patrick; Krotish, Debra; Shin, Yong-June; Hirth, Victor

2010-12-01

The effects of hypertension are chronic and continuous; it affects gait, balance, and fall risk. Therefore, it is desirable to assess gait health across hypertensive and nonhypertensive subjects in order to prevent or reduce the risk of falls. Analysis of electromyography (EMG) signals can identify age related changes of neuromuscular activation due to various neuropathies and myopathies, but it is difficult to translate these medical changes to clinical diagnosis. To examine and compare geriatrics patients with these gait-altering diseases, we acquire EMG muscle activation signals, and by use of a timesynchronized mat capable of recording pressure information, we localize the EMG data to the gait cycle, ensuring identical comparison across subjects. Using time-frequency analysis on the EMG signal, in conjunction with several parameters obtained from the time-frequency analyses, we can determine the statistical discrepancy between diseases. We base these parameters on physiological manifestations caused by hypertension, as well as other comorbities that affect the geriatrics community. Using these metrics in a small population, we identify a statistical discrepancy between a control group and subjects with hypertension, neuropathy, diabetes, osteoporosis, arthritis, and several other common diseases which severely affect the geriatrics community.

Lock-in amplifier error prediction and correction in frequency sweep measurements.

PubMed

Sonnaillon, Maximiliano Osvaldo; Bonetto, Fabian Jose

2007-01-01

This article proposes an analytical algorithm for predicting errors in lock-in amplifiers (LIAs) working with time-varying reference frequency. Furthermore, a simple method for correcting such errors is presented. The reference frequency can be swept in order to measure the frequency response of a system within a given spectrum. The continuous variation of the reference frequency produces a measurement error that depends on three factors: the sweep speed, the LIA low-pass filters, and the frequency response of the measured system. The proposed error prediction algorithm is based on the final value theorem of the Laplace transform. The correction method uses a double-sweep measurement. A mathematical analysis is presented and validated with computational simulations and experimental measurements.

Frequency-duration analysis of dissolved-oxygen concentrations in two southwestern Wisconsin streams

USGS Publications Warehouse

Greb, Steven R.; Graczyk, David J.

2007-01-01

Historically, dissolved-oxygen (DO) data have been collected in the same manner as other water-quality constituents, typically at infrequent intervals as a grab sample or an instantaneous meter reading. Recent years have seen an increase in continuous water-quality monitoring with electronic dataloggers. This new technique requires new approaches in the statistical analysis of the continuous record. This paper presents an application of frequency-duration analysis to the continuous DO records of a cold and a warm water stream in rural southwestern Wisconsin. This method offers a quick, concise way to summarize large time-series data bases in an easily interpretable manner. Even though the two streams had similar mean DO concentrations, frequency-duration analyses showed distinct differences in their DO-concentration regime. This type of analysis also may be useful in relating DO concentrations to biological effects and in predicting low DO occurrences.

Algorithms for Efficient Computation of Transfer Functions for Large Order Flexible Systems

NASA Technical Reports Server (NTRS)

Maghami, Peiman G.; Giesy, Daniel P.

1998-01-01

An efficient and robust computational scheme is given for the calculation of the frequency response function of a large order, flexible system implemented with a linear, time invariant control system. Advantage is taken of the highly structured sparsity of the system matrix of the plant based on a model of the structure using normal mode coordinates. The computational time per frequency point of the new computational scheme is a linear function of system size, a significant improvement over traditional, still-matrix techniques whose computational times per frequency point range from quadratic to cubic functions of system size. This permits the practical frequency domain analysis of systems of much larger order than by traditional, full-matrix techniques. Formulations are given for both open- and closed-loop systems. Numerical examples are presented showing the advantages of the present formulation over traditional approaches, both in speed and in accuracy. Using a model with 703 structural modes, the present method was up to two orders of magnitude faster than a traditional method. The present method generally showed good to excellent accuracy throughout the range of test frequencies, while traditional methods gave adequate accuracy for lower frequencies, but generally deteriorated in performance at higher frequencies with worst case errors being many orders of magnitude times the correct values.

Wavelet-based clustering of resting state MRI data in the rat.

PubMed

Medda, Alessio; Hoffmann, Lukas; Magnuson, Matthew; Thompson, Garth; Pan, Wen-Ju; Keilholz, Shella

2016-01-01

While functional connectivity has typically been calculated over the entire length of the scan (5-10min), interest has been growing in dynamic analysis methods that can detect changes in connectivity on the order of cognitive processes (seconds). Previous work with sliding window correlation has shown that changes in functional connectivity can be observed on these time scales in the awake human and in anesthetized animals. This exciting advance creates a need for improved approaches to characterize dynamic functional networks in the brain. Previous studies were performed using sliding window analysis on regions of interest defined based on anatomy or obtained from traditional steady-state analysis methods. The parcellation of the brain may therefore be suboptimal, and the characteristics of the time-varying connectivity between regions are dependent upon the length of the sliding window chosen. This manuscript describes an algorithm based on wavelet decomposition that allows data-driven clustering of voxels into functional regions based on temporal and spectral properties. Previous work has shown that different networks have characteristic frequency fingerprints, and the use of wavelets ensures that both the frequency and the timing of the BOLD fluctuations are considered during the clustering process. The method was applied to resting state data acquired from anesthetized rats, and the resulting clusters agreed well with known anatomical areas. Clusters were highly reproducible across subjects. Wavelet cross-correlation values between clusters from a single scan were significantly higher than the values from randomly matched clusters that shared no temporal information, indicating that wavelet-based analysis is sensitive to the relationship between areas. Copyright © 2015 Elsevier Inc. All rights reserved.

Establishing a direct connection between detrended fluctuation analysis and Fourier analysis

NASA Astrophysics Data System (ADS)

Kiyono, Ken

2015-10-01

To understand methodological features of the detrended fluctuation analysis (DFA) using a higher-order polynomial fitting, we establish the direct connection between DFA and Fourier analysis. Based on an exact calculation of the single-frequency response of the DFA, the following facts are shown analytically: (1) in the analysis of stochastic processes exhibiting a power-law scaling of the power spectral density (PSD), S (f ) ˜f-β , a higher-order detrending in the DFA has no adverse effect in the estimation of the DFA scaling exponent α , which satisfies the scaling relation α =(β +1 )/2 ; (2) the upper limit of the scaling exponents detectable by the DFA depends on the order of polynomial fit used in the DFA, and is bounded by m +1 , where m is the order of the polynomial fit; (3) the relation between the time scale in the DFA and the corresponding frequency in the PSD are distorted depending on both the order of the DFA and the frequency dependence of the PSD. We can improve the scale distortion by introducing the corrected time scale in the DFA corresponding to the inverse of the frequency scale in the PSD. In addition, our analytical approach makes it possible to characterize variants of the DFA using different types of detrending. As an application, properties of the detrending moving average algorithm are discussed.

A comparison of the wavelet and short-time fourier transforms for Doppler spectral analysis.

PubMed

Zhang, Yufeng; Guo, Zhenyu; Wang, Weilian; He, Side; Lee, Ting; Loew, Murray

2003-09-01

Doppler spectrum analysis provides a non-invasive means to measure blood flow velocity and to diagnose arterial occlusive disease. The time-frequency representation of the Doppler blood flow signal is normally computed by using the short-time Fourier transform (STFT). This transform requires stationarity of the signal during a finite time interval, and thus imposes some constraints on the representation estimate. In addition, the STFT has a fixed time-frequency window, making it inaccurate to analyze signals having relatively wide bandwidths that change rapidly with time. In the present study, wavelet transform (WT), having a flexible time-frequency window, was used to investigate its advantages and limitations for the analysis of the Doppler blood flow signal. Representations computed using the WT with a modified Morlet wavelet were investigated and compared with the theoretical representation and those computed using the STFT with a Gaussian window. The time and frequency resolutions of these two approaches were compared. Three indices, the normalized root-mean-squared errors of the minimum, the maximum and the mean frequency waveforms, were used to evaluate the performance of the WT. Results showed that the WT can not only be used as an alternative signal processing tool to the STFT for Doppler blood flow signals, but can also generate a time-frequency representation with better resolution than the STFT. In addition, the WT method can provide both satisfactory mean frequencies and maximum frequencies. This technique is expected to be useful for the analysis of Doppler blood flow signals to quantify arterial stenoses.

Pseudo-dynamic source characterization accounting for rough-fault effects

NASA Astrophysics Data System (ADS)

Galis, Martin; Thingbaijam, Kiran K. S.; Mai, P. Martin

2016-04-01

Broadband ground-motion simulations, ideally for frequencies up to ~10Hz or higher, are important for earthquake engineering; for example, seismic hazard analysis for critical facilities. An issue with such simulations is realistic generation of radiated wave-field in the desired frequency range. Numerical simulations of dynamic ruptures propagating on rough faults suggest that fault roughness is necessary for realistic high-frequency radiation. However, simulations of dynamic ruptures are too expensive for routine applications. Therefore, simplified synthetic kinematic models are often used. They are usually based on rigorous statistical analysis of rupture models inferred by inversions of seismic and/or geodetic data. However, due to limited resolution of the inversions, these models are valid only for low-frequency range. In addition to the slip, parameters such as rupture-onset time, rise time and source time functions are needed for complete spatiotemporal characterization of the earthquake rupture. But these parameters are poorly resolved in the source inversions. To obtain a physically consistent quantification of these parameters, we simulate and analyze spontaneous dynamic ruptures on rough faults. First, by analyzing the impact of fault roughness on the rupture and seismic radiation, we develop equivalent planar-fault kinematic analogues of the dynamic ruptures. Next, we investigate the spatial interdependencies between the source parameters to allow consistent modeling that emulates the observed behavior of dynamic ruptures capturing the rough-fault effects. Based on these analyses, we formulate a framework for pseudo-dynamic source model, physically consistent with the dynamic ruptures on rough faults.

Heart rate variability analysis based on time-frequency representation and entropies in hypertrophic cardiomyopathy patients.

PubMed

Clariá, F; Vallverdú, M; Baranowski, R; Chojnowska, L; Caminal, P

2008-03-01

In hypertrophic cardiomyopathy (HCM) patients there is an increased risk of premature death, which can occur with little or no warning. Furthermore, classification for sudden cardiac death on patients with HCM is very difficult. The aim of our study was to improve the prognostic value of heart rate variability (HRV) in HCM patients, giving insight into changes of the autonomic nervous system. In this way, the suitability of linear and nonlinear measures was studied to assess the HRV. These measures were based on time-frequency representation (TFR) and on Shannon and Rényi entropies, and compared with traditional HRV measures. Holter recordings of 64 patients with HCM and 55 healthy subjects were analyzed. The HCM patients consisted of two groups: 13 high risk patients, after aborted sudden cardiac death (SCD); 51 low risk patients, without SCD. Five-hour RR signals, corresponding to the sleep period of the subjects, were considered for the analysis as a comparable standard situation. These RR signals were filtered in the three frequency bands: very low frequency band (VLF, 0-0.04 Hz), low frequency band (LF, 0.04-0.15 Hz) and high frequency band (HF, 0.15-0.45 Hz). TFR variables based on instantaneous frequency and energy functions were able to classify HCM patients and healthy subjects (control group). Results revealed that measures obtained from TFR analysis of the HRV better classified the groups of subjects than traditional HRV parameters. However, results showed that nonlinear measures improved group classification. It was observed that entropies calculated in the HF band showed the highest statistically significant levels comparing the HCM group and the control group, p-value < 0.0005. The values of entropy measures calculated in the HCM group presented lower values, indicating a decreasing of complexity, than those calculated from the control group. Moreover, similar behavior was observed comparing high and low risk of premature death, the values of the entropy being lower in high risk patients, p-value < 0.05, indicating an increase of predictability. Furthermore, measures from information entropy, but not from TFR, seem to be useful for enhanced risk stratification in HCM patients with an increased risk of sudden cardiac death.

Blind identification of full-field vibration modes of output-only structures from uniformly-sampled, possibly temporally-aliased (sub-Nyquist), video measurements

NASA Astrophysics Data System (ADS)

Yang, Yongchao; Dorn, Charles; Mancini, Tyler; Talken, Zachary; Nagarajaiah, Satish; Kenyon, Garrett; Farrar, Charles; Mascareñas, David

2017-03-01

Enhancing the spatial and temporal resolution of vibration measurements and modal analysis could significantly benefit dynamic modelling, analysis, and health monitoring of structures. For example, spatially high-density mode shapes are critical for accurate vibration-based damage localization. In experimental or operational modal analysis, higher (frequency) modes, which may be outside the frequency range of the measurement, contain local structural features that can improve damage localization as well as the construction and updating of the modal-based dynamic model of the structure. In general, the resolution of vibration measurements can be increased by enhanced hardware. Traditional vibration measurement sensors such as accelerometers have high-frequency sampling capacity; however, they are discrete point-wise sensors only providing sparse, low spatial sensing resolution measurements, while dense deployment to achieve high spatial resolution is expensive and results in the mass-loading effect and modification of structure's surface. Non-contact measurement methods such as scanning laser vibrometers provide high spatial and temporal resolution sensing capacity; however, they make measurements sequentially that requires considerable acquisition time. As an alternative non-contact method, digital video cameras are relatively low-cost, agile, and provide high spatial resolution, simultaneous, measurements. Combined with vision based algorithms (e.g., image correlation or template matching, optical flow, etc.), video camera based measurements have been successfully used for experimental and operational vibration measurement and subsequent modal analysis. However, the sampling frequency of most affordable digital cameras is limited to 30-60 Hz, while high-speed cameras for higher frequency vibration measurements are extremely costly. This work develops a computational algorithm capable of performing vibration measurement at a uniform sampling frequency lower than what is required by the Shannon-Nyquist sampling theorem for output-only modal analysis. In particular, the spatio-temporal uncoupling property of the modal expansion of structural vibration responses enables a direct modal decoupling of the temporally-aliased vibration measurements by existing output-only modal analysis methods, yielding (full-field) mode shapes estimation directly. Then the signal aliasing properties in modal analysis is exploited to estimate the modal frequencies and damping ratios. The proposed method is validated by laboratory experiments where output-only modal identification is conducted on temporally-aliased acceleration responses and particularly the temporally-aliased video measurements of bench-scale structures, including a three-story building structure and a cantilever beam.

Analysis of Mars Express Ionogram Data via a Multilayer Artificial Neural Network

NASA Astrophysics Data System (ADS)

Wilkinson, Collin; Potter, Arron; Palmer, Greg; Duru, Firdevs

2017-01-01

Mars Advanced Radar for Subsurface and Ionospheric Sounding (MARSIS), which is a low frequency radar on the Mars Express (MEX) Spacecraft, can provide electron plasma densities of the ionosphere local at the spacecraft in addition to densities obtained with remote sounding. The local electron densities are obtained, with a standard error of about 2%, by measuring the electron plasma frequencies with an electronic ruler on ionograms, which are plots of echo intensity as a function of time and frequency. This is done by using a tool created at the University of Iowa (Duru et al., 2008). This approach is time consuming due to the rapid accumulation of ionogram data. In 2013, results from an algorithm-based analysis of ionograms were reported by Andrews et al., but this method did not improve the human error. In the interest of fast, accurate data interpretation, a neural network (NN) has been created based on the Fast Artificial Neural Network C libraries. This NN consists of artificial neurons, with 4 layers of 12960, 10000, 1000 and 1 neuron(s) each, consecutively. This network was trained using 40 iterations of 1000 orbits. The algorithm-based method of Andrews et al. had a standard error of 40%, while the neural network has achieved error on the order of 20%.

Computer implemented empirical mode decomposition method, apparatus and article of manufacture

NASA Technical Reports Server (NTRS)

Huang, Norden E. (Inventor)

1999-01-01

A computer implemented physical signal analysis method is invented. This method includes two essential steps and the associated presentation techniques of the results. All the steps exist only in a computer: there are no analytic expressions resulting from the method. The first step is a computer implemented Empirical Mode Decomposition to extract a collection of Intrinsic Mode Functions (IMF) from nonlinear, nonstationary physical signals. The decomposition is based on the direct extraction of the energy associated with various intrinsic time scales in the physical signal. Expressed in the IMF's, they have well-behaved Hilbert Transforms from which instantaneous frequencies can be calculated. The second step is the Hilbert Transform. The final result is the Hilbert Spectrum. Thus, the invention can localize any event on the time as well as the frequency axis. The decomposition can also be viewed as an expansion of the data in terms of the IMF's. Then, these IMF's, based on and derived from the data, can serve as the basis of that expansion. The local energy and the instantaneous frequency derived from the IMF's through the Hilbert transform give a full energy-frequency-time distribution of the data which is designated as the Hilbert Spectrum.

Wavelet-frequency analysis for the detection of discontinuities in switched system models of human balance.

PubMed

Nema, Salam; Kowalczyk, Piotr; Loram, Ian

2017-01-01

This paper is concerned with detecting the presence of switching behavior in experimentally obtained posturographic data sets by means of a novel algorithm that is based on a combination of wavelet analysis and Hilbert transform. As a test-bed for the algorithm, we first use a switched model of human balance control during quiet standing with known switching behavior in four distinct configurations. We obtain a time-frequency representation of a signal generated by our model system. We are then able to detect manifestations of discontinuities (switchings) in the signal as spiking behavior. The frequency of switchings, measured by means of our algorithm and detected in our models systems, agrees with the frequency of spiking behavior found in the experimentally obtained posturographic data. Copyright © 2016. Published by Elsevier B.V.

Analysis of Digital Communication Signals and Extraction of Parameters.

DTIC Science & Technology

1994-12-01

Fast Fourier Transform (FFT). The correlation methods utilize modified time-frequency distributions , where one of these is based on the Wigner - Ville ... Distribution ( WVD ). Gaussian white noise is added to the signal to simulate various signal-to-noise ratios (SNRs).

Instantaneous frequency based newborn EEG seizure characterisation

NASA Astrophysics Data System (ADS)

Mesbah, Mostefa; O'Toole, John M.; Colditz, Paul B.; Boashash, Boualem

2012-12-01

The electroencephalogram (EEG), used to noninvasively monitor brain activity, remains the most reliable tool in the diagnosis of neonatal seizures. Due to their nonstationary and multi-component nature, newborn EEG seizures are better represented in the joint time-frequency domain than in either the time domain or the frequency domain. Characterising newborn EEG seizure nonstationarities helps to better understand their time-varying nature and, therefore, allow developing efficient signal processing methods for both modelling and seizure detection and classification. In this article, we used the instantaneous frequency (IF) extracted from a time-frequency distribution to characterise newborn EEG seizures. We fitted four frequency modulated (FM) models to the extracted IFs, namely a linear FM, a piecewise-linear FM, a sinusoidal FM, and a hyperbolic FM. Using a database of 30-s EEG seizure epochs acquired from 35 newborns, we were able to show that, depending on EEG channel, the sinusoidal and piecewise-linear FM models best fitted 80-98% of seizure epochs. To further characterise the EEG seizures, we calculated the mean frequency and frequency span of the extracted IFs. We showed that in the majority of the cases (>95%), the mean frequency resides in the 0.6-3 Hz band with a frequency span of 0.2-1 Hz. In terms of the frequency of occurrence of the four seizure models, the statistical analysis showed that there is no significant difference( p = 0.332) between the two hemispheres. The results also indicate that there is no significant differences between the two hemispheres in terms of the mean frequency ( p = 0.186) and the frequency span ( p = 0.302).

Analysis of digital communication signals and extraction of parameters

NASA Astrophysics Data System (ADS)

Al-Jowder, Anwar

1994-12-01

The signal classification performance of four types of electronics support measure (ESM) communications detection systems is compared from the standpoint of the unintended receiver (interceptor). Typical digital communication signals considered include binary phase shift keying (BPSK), quadrature phase shift keying (QPSK), frequency shift keying (FSK), and on-off keying (OOK). The analysis emphasizes the use of available signal processing software. Detection methods compared include broadband energy detection, FFT-based narrowband energy detection, and two correlation methods which employ the fast Fourier transform (FFT). The correlation methods utilize modified time-frequency distributions, where one of these is based on the Wigner-Ville distribution (WVD). Gaussian white noise is added to the signal to simulate various signal-to-noise ratios (SNR's).

Frequency-phase analysis of resting-state functional MRI

PubMed Central

Goelman, Gadi; Dan, Rotem; Růžička, Filip; Bezdicek, Ondrej; Růžička, Evžen; Roth, Jan; Vymazal, Josef; Jech, Robert

2017-01-01

We describe an analysis method that characterizes the correlation between coupled time-series functions by their frequencies and phases. It provides a unified framework for simultaneous assessment of frequency and latency of a coupled time-series. The analysis is demonstrated on resting-state functional MRI data of 34 healthy subjects. Interactions between fMRI time-series are represented by cross-correlation (with time-lag) functions. A general linear model is used on the cross-correlation functions to obtain the frequencies and phase-differences of the original time-series. We define symmetric, antisymmetric and asymmetric cross-correlation functions that correspond respectively to in-phase, 90° out-of-phase and any phase difference between a pair of time-series, where the last two were never introduced before. Seed maps of the motor system were calculated to demonstrate the strength and capabilities of the analysis. Unique types of functional connections, their dominant frequencies and phase-differences have been identified. The relation between phase-differences and time-delays is shown. The phase-differences are speculated to inform transfer-time and/or to reflect a difference in the hemodynamic response between regions that are modulated by neurotransmitters concentration. The analysis can be used with any coupled functions in many disciplines including electrophysiology, EEG or MEG in neuroscience. PMID:28272522

New Possibilities of Substance Identification Based on THz Time Domain Spectroscopy Using a Cascade Mechanism of High Energy Level Excitation

PubMed Central

Trofimov, Vyacheslav A.; Varentsova, Svetlana A.; Zakharova, Irina G.; Zagursky, Dmitry Yu.

2017-01-01

Using an experiment with thin paper layers and computer simulation, we demonstrate the principal limitations of standard Time Domain Spectroscopy (TDS) based on using a broadband THz pulse for the detection and identification of a substance placed inside a disordered structure. We demonstrate the spectrum broadening of both transmitted and reflected pulses due to the cascade mechanism of the high energy level excitation considering, for example, a three-energy level medium. The pulse spectrum in the range of high frequencies remains undisturbed in the presence of a disordered structure. To avoid false absorption frequencies detection, we apply the spectral dynamics analysis method (SDA-method) together with certain integral correlation criteria (ICC). PMID:29186849

Few-mode fiber based distributed curvature sensor through quasi-single-mode Brillouin frequency shift.

PubMed

Wu, Hao; Wang, Ruoxu; Liu, Deming; Fu, Songnian; Zhao, Can; Wei, Huifeng; Tong, Weijun; Shum, Perry Ping; Tang, Ming

2016-04-01

We proposed and demonstrated a few-mode fiber (FMF) based optical-fiber sensor for distributed curvature measurement through quasi-single-mode Brillouin frequency shift (BFS). By central-alignment splicing FMF and single-mode fiber (SMF) with a fusion taper, a SMF-components-compatible distributed curvature sensor based on FMF is realized using the conventional Brillouin optical time-domain analysis system. The distributed BFS change induced by bending in FMF has been theoretically and experimentally investigated. The precise BFS response to the curvature along the fiber link has been calibrated. A proof-of-concept experiment is implemented to validate its effectiveness in distributed curvature measurement.

Clinical usefulness and feasibility of time-frequency analysis of chemosensory event-related potentials.

PubMed

Huart, C; Rombaux, Ph; Hummel, T; Mouraux, A

2013-09-01

The clinical usefulness of olfactory event-related brain potentials (OERPs) to assess olfactory function is limited by the relatively low signal-to-noise ratio of the responses identified using conventional time-domain averaging. Recently, it was shown that time-frequency analysis of the obtained EEG signals can markedly improve the signal-to-noise ratio of OERPs in healthy controls, because it enhances both phase-locked and non phase-locked EEG responses. The aim of the present study was to investigate the clinical usefulness of this approach and evaluate its feasibility in a clinical setting. We retrospectively analysed EEG recordings obtained from 45 patients (15 anosmic, 15 hyposmic and 15 normos- mic). The responses to olfactory stimulation were analysed using conventional time-domain analysis and joint time-frequency analysis. The ability of the two methods to discriminate between anosmic, hyposmic and normosmic patients was assessed using a Receiver Operating Characteristic analysis. The discrimination performance of OERPs identified using conventional time-domain averaging was poor. In contrast, the discrimination performance of the EEG response identified in the time-frequency domain was relatively high. Furthermore, we found a significant correlation between the magnitude of this response and the psychophysical olfactory score. Time-frequency analysis of the EEG responses to olfactory stimulation could be used as an effective and reliable diagnostic tool for the objective clinical evaluation of olfactory function in patients.

A Sparsity-Based Approach to 3D Binaural Sound Synthesis Using Time-Frequency Array Processing

NASA Astrophysics Data System (ADS)

Cobos, Maximo; Lopez, JoseJ; Spors, Sascha

2010-12-01

Localization of sounds in physical space plays a very important role in multiple audio-related disciplines, such as music, telecommunications, and audiovisual productions. Binaural recording is the most commonly used method to provide an immersive sound experience by means of headphone reproduction. However, it requires a very specific recording setup using high-fidelity microphones mounted in a dummy head. In this paper, we present a novel processing framework for binaural sound recording and reproduction that avoids the use of dummy heads, which is specially suitable for immersive teleconferencing applications. The method is based on a time-frequency analysis of the spatial properties of the sound picked up by a simple tetrahedral microphone array, assuming source sparseness. The experiments carried out using simulations and a real-time prototype confirm the validity of the proposed approach.

Methodology for fault detection in induction motors via sound and vibration signals

NASA Astrophysics Data System (ADS)

Delgado-Arredondo, Paulo Antonio; Morinigo-Sotelo, Daniel; Osornio-Rios, Roque Alfredo; Avina-Cervantes, Juan Gabriel; Rostro-Gonzalez, Horacio; Romero-Troncoso, Rene de Jesus

2017-01-01

Nowadays, timely maintenance of electric motors is vital to keep up the complex processes of industrial production. There are currently a variety of methodologies for fault diagnosis. Usually, the diagnosis is performed by analyzing current signals at a steady-state motor operation or during a start-up transient. This method is known as motor current signature analysis, which identifies frequencies associated with faults in the frequency domain or by the time-frequency decomposition of the current signals. Fault identification may also be possible by analyzing acoustic sound and vibration signals, which is useful because sometimes this information is the only available. The contribution of this work is a methodology for detecting faults in induction motors in steady-state operation based on the analysis of acoustic sound and vibration signals. This proposed approach uses the Complete Ensemble Empirical Mode Decomposition for decomposing the signal into several intrinsic mode functions. Subsequently, the frequency marginal of the Gabor representation is calculated to obtain the spectral content of the IMF in the frequency domain. This proposal provides good fault detectability results compared to other published works in addition to the identification of more frequencies associated with the faults. The faults diagnosed in this work are two broken rotor bars, mechanical unbalance and bearing defects.

Polar plot representation of time-resolved fluorescence.

PubMed

Eichorst, John Paul; Wen Teng, Kai; Clegg, Robert M

2014-01-01

Measuring changes in a molecule's fluorescence emission is a common technique to study complex biological systems such as cells and tissues. Although the steady-state fluorescence intensity is frequently used, measuring the average amount of time that a molecule spends in the excited state (the fluorescence lifetime) reveals more detailed information about its local environment. The lifetime is measured in the time domain by detecting directly the decay of fluorescence following excitation by short pulse of light. The lifetime can also be measured in the frequency domain by recording the phase and amplitude of oscillation in the emitted fluorescence of the sample in response to repetitively modulated excitation light. In either the time or frequency domain, the analysis of data to extract lifetimes can be computationally intensive. For example, a variety of iterative fitting algorithms already exist to determine lifetimes from samples that contain multiple fluorescing species. However, recently a method of analysis referred to as the polar plot (or phasor plot) is a graphical tool that projects the time-dependent features of the sample's fluorescence in either the time or frequency domain into the Cartesian plane to characterize the sample's lifetime. The coordinate transformations of the polar plot require only the raw data, and hence, there are no uncertainties from extensive corrections or time-consuming fitting in this analysis. In this chapter, the history and mathematical background of the polar plot will be presented along with examples that highlight how it can be used in both cuvette-based and imaging applications.

Cytogenetic analysis in 16-year follow-up study of a mother and fetus exposed in a radiation accident in Xinzhou, China.

PubMed

Liu, Qing-Jie; Lu, Xue; Zhao, Hua; Chen, Sen; Wang, Ming-Ming; Bai, Yushu; Zhang, Shu-Lan; Feng, Jiang-Bin; Zhang, Zhao-Hui; Chen, De-Qing; Ma, Li-Wen; Jia, Ting-Zhen; Liang, Li

2013-07-04

In November 1992, a radiation accident occurred in Xinzhou, due to the collection by a farmer of an unused (60)Co source; 37 individuals were exposed to ionizing radiation. Three individuals died and the farmer's 19-weeks-pregnant wife suffered acute radiation symptoms. Conventional chromosome analysis, cytokinesis-block micronuclei (CBMN) assay and fluorescence in situ hybridization (FISH) painting with three pairs of whole chromosome probes were used to analyze chromosomal aberrations for the pregnant female and her baby during the 16 years following the accident. The yields of dicentrics and rings (dic+r) continually declined between 41 days and 16 years after the accident. The frequency of binucleated MN also decreased over time for both mother and daughter. Sixteen years after exposure, the yields of dic+r and binucleated MN decreased to normal levels, but the reciprocal translocation frequencies remained elevated, for both mother and daughter. FISH results showed a decreasing yield of translocations with time. Based on the changes in maternal translocation frequency, the daughter's dose at the time of exposure was estimated as 1.82 (1.35-2.54)Gy. This was consistent with the clinical manifestations of severe mental retardation and low IQ score. FISH-based translocation analysis can be used for follow-up studies on accidental exposure and, after correction, for retrospective dose estimation for individuals prenatally exposed to radiation. Copyright © 2013 Elsevier B.V. All rights reserved.

Accelerated pharmacokinetic map determination for dynamic contrast enhanced MRI using frequency-domain based Tofts model.

PubMed

Vajuvalli, Nithin N; Nayak, Krupa N; Geethanath, Sairam

2014-01-01

Dynamic Contrast Enhanced Magnetic Resonance Imaging (DCE-MRI) is widely used in the diagnosis of cancer and is also a promising tool for monitoring tumor response to treatment. The Tofts model has become a standard for the analysis of DCE-MRI. The process of curve fitting employed in the Tofts equation to obtain the pharmacokinetic (PK) parameters is time-consuming for high resolution scans. Current work demonstrates a frequency-domain approach applied to the standard Tofts equation to speed-up the process of curve-fitting in order to obtain the pharmacokinetic parameters. The results obtained show that using the frequency domain approach, the process of curve fitting is computationally more efficient compared to the time-domain approach.

Q estimation of seismic data using the generalized S-transform

NASA Astrophysics Data System (ADS)

Hao, Yaju; Wen, Xiaotao; Zhang, Bo; He, Zhenhua; Zhang, Rui; Zhang, Jinming

2016-12-01

Quality factor, Q, is a parameter that characterizes the energy dissipation during seismic wave propagation. The reservoir pore is one of the main factors that affect the value of Q. Especially, when pore space is filled with oil or gas, the rock usually exhibits a relative low Q value. Such a low Q value has been used as a direct hydrocarbon indicator by many researchers. The conventional Q estimation method based on spectral ratio suffers from the problem of waveform tuning; hence, many researchers have introduced time-frequency analysis techniques to tackle this problem. Unfortunately, the window functions adopted in time-frequency analysis algorithms such as continuous wavelet transform (CWT) and S-transform (ST) contaminate the amplitude spectra because the seismic signal is multiplied by the window functions during time-frequency decomposition. The basic assumption of the spectral ratio method is that there is a linear relationship between natural logarithmic spectral ratio and frequency. However, this assumption does not hold if we take the influence of window functions into consideration. In this paper, we first employ a recently developed two-parameter generalized S-transform (GST) to obtain the time-frequency spectra of seismic traces. We then deduce the non-linear relationship between natural logarithmic spectral ratio and frequency. Finally, we obtain a linear relationship between natural logarithmic spectral ratio and a newly defined parameter γ by ignoring the negligible second order term. The gradient of this linear relationship is 1/Q. Here, the parameter γ is a function of frequency and source wavelet. Numerical examples for VSP and post-stack reflection data confirm that our algorithm is capable of yielding accurate results. The Q-value results estimated from field data acquired in western China show reasonable comparison with oil-producing well location.

Wind turbine acoustics

NASA Technical Reports Server (NTRS)

Hubbard, Harvey H.; Shepherd, Kevin P.

1990-01-01

Available information on the physical characteristics of the noise generated by wind turbines is summarized, with example sound pressure time histories, narrow- and broadband frequency spectra, and noise radiation patterns. Reviewed are noise measurement standards, analysis technology, and a method of characterizing wind turbine noise. Prediction methods are given for both low-frequency rotational harmonics and broadband noise components. Also included are atmospheric propagation data showing the effects of distance and refraction by wind shear. Human perception thresholds, based on laboratory and field tests, are given. Building vibration analysis methods are summarized. The bibliography of this report lists technical publications on all aspects of wind turbine acoustics.

New instantaneous frequency estimation method based on the use of image processing techniques

NASA Astrophysics Data System (ADS)

Borda, Monica; Nafornita, Ioan; Isar, Alexandru

2003-05-01

The aim of this paper is to present a new method for the estimation of the instantaneous frequency of a frequency modulated signal, corrupted by additive noise. This method represents an example of fusion of two theories: the time-frequency representations and the mathematical morphology. Any time-frequency representation of a useful signal is concentrated around its instantaneous frequency law and realizes the diffusion of the noise that perturbs the useful signal in the time - frequency plane. In this paper a new time-frequency representation, useful for the estimation of the instantaneous frequency, is proposed. This time-frequency representation is the product of two others time-frequency representations: the Wigner - Ville time-frequency representation and a new one obtained by filtering with a hard thresholding filter the Gabor representation of the signal to be processed. Using the image of this new time-frequency representation the instantaneous frequency of the useful signal can be extracted with the aid of some mathematical morphology operators: the conversion in binary form, the dilation and the skeleton. The simulations of the proposed method have proved its qualities. It is better than other estimation methods, like those based on the use of adaptive notch filters.

A Removal of Eye Movement and Blink Artifacts from EEG Data Using Morphological Component Analysis

PubMed Central

Wagatsuma, Hiroaki

2017-01-01

EEG signals contain a large amount of ocular artifacts with different time-frequency properties mixing together in EEGs of interest. The artifact removal has been substantially dealt with by existing decomposition methods known as PCA and ICA based on the orthogonality of signal vectors or statistical independence of signal components. We focused on the signal morphology and proposed a systematic decomposition method to identify the type of signal components on the basis of sparsity in the time-frequency domain based on Morphological Component Analysis (MCA), which provides a way of reconstruction that guarantees accuracy in reconstruction by using multiple bases in accordance with the concept of “dictionary.” MCA was applied to decompose the real EEG signal and clarified the best combination of dictionaries for this purpose. In our proposed semirealistic biological signal analysis with iEEGs recorded from the brain intracranially, those signals were successfully decomposed into original types by a linear expansion of waveforms, such as redundant transforms: UDWT, DCT, LDCT, DST, and DIRAC. Our result demonstrated that the most suitable combination for EEG data analysis was UDWT, DST, and DIRAC to represent the baseline envelope, multifrequency wave-forms, and spiking activities individually as representative types of EEG morphologies. PMID:28194221

Spontaneous Swallowing Frequency [Has Potential to] Identify Dysphagia in Acute Stroke

PubMed Central

Carnaby, Giselle D; Sia, Isaac; Khanna, Anna; Waters, Michael

2014-01-01

Background and Purpose Spontaneous swallowing frequency has been described as an index of dysphagia in various health conditions. This study evaluated the potential of spontaneous swallow frequency analysis as a screening protocol for dysphagia in acute stroke. Methods In a cohort of 63 acute stroke cases swallow frequency rates (swallows per minute: SPM) were compared to stroke and swallow severity indices, age, time from stroke to assessment, and consciousness level. Mean differences in SPM were compared between patients with vs. without clinically significant dysphagia. ROC analysis was used to identify the optimal threshold in SPM which was compared to a validated clinical dysphagia examination for identification of dysphagia cases. Time series analysis was employed to identify the minimally adequate time period to complete spontaneous swallow frequency analysis. Results SPM correlated significantly with stroke and swallow severity indices but not with age, time from stroke onset, or consciousness level. Patients with dysphagia demonstrated significantly lower SPM rates. SPM differed by dysphagia severity. ROC analysis yielded a threshold of SPM ≤ 0.40 which identified dysphagia (per the criterion referent) with 0.96 sensitivity, 0.68 specificity, and 0.96 negative predictive value. Time series analysis indicated that a 5 to 10 minute sampling window was sufficient to calculate spontaneous swallow frequency to identify dysphagia cases in acute stroke. Conclusions Spontaneous swallowing frequency presents high potential to screen for dysphagia in acute stroke without the need for trained, available personnel. PMID:24149008

Spontaneous swallowing frequency has potential to identify dysphagia in acute stroke.

PubMed

Crary, Michael A; Carnaby, Giselle D; Sia, Isaac; Khanna, Anna; Waters, Michael F

2013-12-01

Spontaneous swallowing frequency has been described as an index of dysphagia in various health conditions. This study evaluated the potential of spontaneous swallow frequency analysis as a screening protocol for dysphagia in acute stroke. In a cohort of 63 acute stroke cases, swallow frequency rates (swallows per minute [SPM]) were compared with stroke and swallow severity indices, age, time from stroke to assessment, and consciousness level. Mean differences in SPM were compared between patients with versus without clinically significant dysphagia. Receiver operating characteristic curve analysis was used to identify the optimal threshold in SPM, which was compared with a validated clinical dysphagia examination for identification of dysphagia cases. Time series analysis was used to identify the minimally adequate time period to complete spontaneous swallow frequency analysis. SPM correlated significantly with stroke and swallow severity indices but not with age, time from stroke onset, or consciousness level. Patients with dysphagia demonstrated significantly lower SPM rates. SPM differed by dysphagia severity. Receiver operating characteristic curve analysis yielded a threshold of SPM≤0.40 that identified dysphagia (per the criterion referent) with 0.96 sensitivity, 0.68 specificity, and 0.96 negative predictive value. Time series analysis indicated that a 5- to 10-minute sampling window was sufficient to calculate spontaneous swallow frequency to identify dysphagia cases in acute stroke. Spontaneous swallowing frequency presents high potential to screen for dysphagia in acute stroke without the need for trained, available personnel.

An automated multi-scale network-based scheme for detection and location of seismic sources

NASA Astrophysics Data System (ADS)

Poiata, N.; Aden-Antoniow, F.; Satriano, C.; Bernard, P.; Vilotte, J. P.; Obara, K.

2017-12-01

We present a recently developed method - BackTrackBB (Poiata et al. 2016) - allowing to image energy radiation from different seismic sources (e.g., earthquakes, LFEs, tremors) in different tectonic environments using continuous seismic records. The method exploits multi-scale frequency-selective coherence in the wave field, recorded by regional seismic networks or local arrays. The detection and location scheme is based on space-time reconstruction of the seismic sources through an imaging function built from the sum of station-pair time-delay likelihood functions, projected onto theoretical 3D time-delay grids. This imaging function is interpreted as the location likelihood of the seismic source. A signal pre-processing step constructs a multi-band statistical representation of the non stationary signal, i.e. time series, by means of higher-order statistics or energy envelope characteristic functions. Such signal-processing is designed to detect in time signal transients - of different scales and a priori unknown predominant frequency - potentially associated with a variety of sources (e.g., earthquakes, LFE, tremors), and to improve the performance and the robustness of the detection-and-location location step. The initial detection-location, based on a single phase analysis with the P- or S-phase only, can then be improved recursively in a station selection scheme. This scheme - exploiting the 3-component records - makes use of P- and S-phase characteristic functions, extracted after a polarization analysis of the event waveforms, and combines the single phase imaging functions with the S-P differential imaging functions. The performance of the method is demonstrated here in different tectonic environments: (1) analysis of the one year long precursory phase of 2014 Iquique earthquake in Chile; (2) detection and location of tectonic tremor sources and low-frequency earthquakes during the multiple episodes of tectonic tremor activity in southwestern Japan.

Definitions of Frequency and Timing Terms, Satellite Navigation and Timing Systems, and the Behavior and Analyses of Precision Crystal and Atomic Frequency Standards and their Characteristics

DTIC Science & Technology

2009-05-01

time transfer techniques has largely been due to the improvement in frequency standards. In this document, an effort was made to provide substantial...of RCC Document 214-94, contains definitions of frequency and timing terms, time transfer techniques and analysis, and behavior of crystal and atomic...Characteristics, May 2009 viii TTG Telecommunications and Timing Group TWSTFT Two-Way Satellite Time and Frequency Transfer U.S. United States USNO

Study on time-frequency analysis method of very fast transient overvoltage

NASA Astrophysics Data System (ADS)

Li, Shuai; Liu, Shiming; Huang, Qiyan; Fu, Chuanshun

2018-04-01

The operation of the disconnector in the gas insulated substation (GIS) may produce very fast transient overvoltage (VFTO), which has the characteristics of short rise time, short duration, high amplitude and rich frequency components. VFTO can cause damage to GIS and secondary equipment, and the frequency components contained in the VFTO can cause resonance overvoltage inside the transformer, so it is necessary to study the spectral characteristics of the VFTO. From the perspective of signal processing, VFTO is a kind of non-stationary signal, the traditional Fourier transform is difficult to describe its frequency which changes with time, so it is necessary to use time-frequency analysis to analyze VFTO spectral characteristics. In this paper, we analyze the performance of short time Fourier transform (STFT), Wigner-Ville distribution (WVD), pseudo Wigner-Ville distribution (PWVD) and smooth pseudo Wigner-Ville distribution (SPWVD). The results show that SPWVD transform is the best. The time-frequency aggregation of SPWVD is higher than STFT, and it does not have cross-interference terms, which can meet the requirements of VFTO spectrum analysis.

Stress, anxiety, depression, and epilepsy: investigating the relationship between psychological factors and seizures.

PubMed

Thapar, Ajay; Kerr, Michael; Harold, Gordon

2009-01-01

The goal of the study described here was to examine the interrelationship between psychological factors (anxiety, stress, and depression) and seizures. In this longitudinal cohort study, data on anxiety, depression, perceived stress, and seizure recency (time since last seizure) and frequency were collected at two time points using standard validated questionnaire measures. Empirically based models with psychological factors explaining change in (1) seizure recency and (2) seizure frequency scores across time were specified. We then tested how these psychological factors acted together in predicting seizure recency and frequency. Our data were used to test whether these models were valid for the study population. Latent variable structural equation modeling was used for the analysis. Four hundred thirty-three of the 558 individuals who initially consented to participate provided two waves of data for this analysis. Stress (beta=0.25, P<0.01), anxiety (beta=0.30, P<0.01), and depression (beta=0.30, P<0.01) all predicted change in seizure recency. However, it was depression that mediated the relationship of both anxiety and stress with modeled change in seizure recency (beta=0.19, P<0.01) and seizure frequency (beta=0.30, P<0.01) over time. Depression mediates the relationship between stress and anxiety and change in seizure recency and seizure frequency. These findings highlight the importance of depression management in addition to seizure management in the assessment and treatment of epilepsy in an adult population.

Analysis of the Microstructure of Titles in the INSPEC Data-Base

ERIC Educational Resources Information Center

And Others; Lynch, Michael F.

1973-01-01

A high degree of constancy has been found in the microstructure of titles of samples of the INSPEC data base taken over a three-year period. Character and digram frequencies are relatively stable, while variable-length character-strings characterizing samples separated by three years in time show close similarities. (2 references) (Author/SJ)

A spectral power analysis of driving behavior changes during the transition from nondistraction to distraction.

PubMed

Wang, Yuan; Bao, Shan; Du, Wenjun; Ye, Zhirui; Sayer, James R

2017-11-17

This article investigated and compared frequency domain and time domain characteristics of drivers' behaviors before and after the start of distracted driving. Data from an existing naturalistic driving study were used. Fast Fourier transform (FFT) was applied for the frequency domain analysis to explore drivers' behavior pattern changes between nondistracted (prestarting of visual-manual task) and distracted (poststarting of visual-manual task) driving periods. Average relative spectral power in a low frequency range (0-0.5 Hz) and the standard deviation in a 10-s time window of vehicle control variables (i.e., lane offset, yaw rate, and acceleration) were calculated and further compared. Sensitivity analyses were also applied to examine the reliability of the time and frequency domain analyses. Results of the mixed model analyses from the time and frequency domain analyses all showed significant degradation in lateral control performance after engaging in visual-manual tasks while driving. Results of the sensitivity analyses suggested that the frequency domain analysis was less sensitive to the frequency bandwidth, whereas the time domain analysis was more sensitive to the time intervals selected for variation calculations. Different time interval selections can result in significantly different standard deviation values, whereas average spectral power analysis on yaw rate in both low and high frequency bandwidths showed consistent results, that higher variation values were observed during distracted driving when compared to nondistracted driving. This study suggests that driver state detection needs to consider the behavior changes during the prestarting periods, instead of only focusing on periods with physical presence of distraction, such as cell phone use. Lateral control measures can be a better indicator of distraction detection than longitudinal controls. In addition, frequency domain analyses proved to be a more robust and consistent method in assessing driving performance compared to time domain analyses.

Signal analysis by means of time-frequency (Wigner-type) distributions -- Applications to sonar and radar echoes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gaunaurd, G.; Strifors, H.C.

1996-09-01

Time series data have been traditionally analyzed in either the time or the frequency domains. For signals with a time-varying frequency content, the combined time-frequency (TF) representations, based on the Cohen class of (generalized) Wigner distributions (WD`s) offer a powerful analysis tool. Using them, it is possible to: (1) trace the time-evolution of the resonance features usually present in a standard sonar cross section (SCS), or in a radar cross section (RCS) and (2) extract target information that may be difficult to even notice in an ordinary SCS or RCS. After a brief review of the fundamental properties of themore » WD, the authors discuss ways to reduce or suppress the cross term interference that appears in the WD of multicomponent systems. These points are illustrated with a variety of three-dimensional (3-D) plots of Wigner and pseudo-Wigner distributions (PWD), in which the strength of the distribution is depicted as the height of a Wigner surface with height scales measured by various color shades or pseudocolors. The authors also review studies they have made of the echoes returned by conducting or dielectric targets in the atmosphere, when they are illuminated by broadband radar pings. A TF domain analysis of these impulse radar returns demonstrates their superior informative content. These plots allow the identification of targets in an easier and clearer fashion than by the conventional RCS of narrowband systems. The authors show computed and measured plots of WD and PWD of various types of aircraft to illustrate the classification advantages of the approach at any aspect angle. They also show analogous results for metallic objects buried underground, in dielectric media, at various depths.« less

An Improved Time-Frequency Analysis Method in Interference Detection for GNSS Receivers

PubMed Central

Sun, Kewen; Jin, Tian; Yang, Dongkai

2015-01-01

In this paper, an improved joint time-frequency (TF) analysis method based on a reassigned smoothed pseudo Wigner–Ville distribution (RSPWVD) has been proposed in interference detection for Global Navigation Satellite System (GNSS) receivers. In the RSPWVD, the two-dimensional low-pass filtering smoothing function is introduced to eliminate the cross-terms present in the quadratic TF distribution, and at the same time, the reassignment method is adopted to improve the TF concentration properties of the auto-terms of the signal components. This proposed interference detection method is evaluated by experiments on GPS L1 signals in the disturbing scenarios compared to the state-of-the-art interference detection approaches. The analysis results show that the proposed interference detection technique effectively overcomes the cross-terms problem and also preserves good TF localization properties, which has been proven to be effective and valid to enhance the interference detection performance of the GNSS receivers, particularly in the jamming environments. PMID:25905704

Detection of Geomagnetic Pulsations of the Earth Using GPS-TEC Data

NASA Astrophysics Data System (ADS)

Koroglu, Ozan; Arikan, Feza; Köroǧlu, Meltem; Sabri Ozkazanc, Yakup

2016-07-01

The magnetosphere of the Earth is made up of both magnetic fields and plasma. In this layer, plasma waves propagate as Ultra Low Frequency (ULF) waves having mHz scale frequencies. ULF waves are produced due to complicated solar-geomagnetic interactions. In the literature, these ULF waves are defined as pulsations. The geomagnetic pulsations are classified into main two groups as continuous pulsations (Pc) and irregular pulsations (Pi). These pulsations can be determined by ionospheric parameters due to the complex lithosphere-ionosphere-magnetosphere coupling processes. Total Electron Content (TEC) is one of the most important parameters for investigating the variability of ionosphere. Global Positioning System (GPS) provides a cost-effective means for estimating TEC from GPS satellite orbital height of 20,000 km to the ground based receivers. Therefore, the time series of GPS-TEC inherently contains the above mentioned ULF waves. In this study, time series analysis of GPS-TEC is carried out by applying periodogram method to the mid-latitude annual TEC data. After the analysis of GPS-TEC data obtained for GPS stations located in Central Europe and Turkey for 2011, it is observed that some of the fundamental frequencies that are indicators of Pc waves, diurnal and semi-diurnal periodicity and earth-free oscillations can be identified. These results will be used in determination of low frequency trend structure of magnetosphere and ionosphere. Further investigation of remaining relatively low magnitude frequencies, all Pi and Pc can be identified by using time and frequency domain techniques such as wavelet analysis. This study is supported by the joint TUBITAK 115E915 and joint TUBITAK114E092 and AS CR 14/001 projects.

An Efficient Implementation For Real Time Applications Of The Wigner-Ville Distribution

NASA Astrophysics Data System (ADS)

Boashash, Boualem; Black, Peter; Whitehouse, Harper J.

1986-03-01

The Wigner-Ville Distribution (WVD) is a valuable tool for time-frequency signal analysis. In order to implement the WVD in real time an efficient algorithm and architecture have been developed which may be implemented with commercial components. This algorithm successively computes the analytic signal corresponding to the input signal, forms a weighted kernel function and analyses the kernel via a Discrete Fourier Transform (DFT). To evaluate the analytic signal required by the algorithm it is shown that the time domain definition implemented as a finite impulse response (FIR) filter is practical and more efficient than the frequency domain definition of the analytic signal. The windowed resolution of the WVD in the frequency domain is shown to be similar to the resolution of a windowed Fourier Transform. A real time signal processsor has been designed for evaluation of the WVD analysis system. The system is easily paralleled and can be configured to meet a variety of frequency and time resolutions. The arithmetic unit is based on a pair of high speed VLSI floating-point multiplier and adder chips. Dual operand buses and an independent result bus maximize data transfer rates. The system is horizontally microprogrammed and utilizes a full instruction pipeline. Each microinstruction specifies two operand addresses, a result location, the type of arithmetic and the memory configuration. input and output is via shared memory blocks with front-end processors to handle data transfers during the non access periods of the analyzer.

Design of current source for multi-frequency simultaneous electrical impedance tomography

NASA Astrophysics Data System (ADS)

Han, Bing; Xu, Yanbin; Dong, Feng

2017-09-01

Multi-frequency electrical impedance tomography has been evolving from the frequency-sweep approach to the multi-frequency simultaneous measurement technique which can reduce measuring time and will be increasingly attractive for time-varying biological applications. The accuracy and stability of the current source are the key factors determining the quality of the image reconstruction. This article presents a field programmable gate array-based current source for a multi-frequency simultaneous electrical impedance tomography system. A novel current source circuit was realized by combining the classic current mirror based on the feedback amplifier AD844 with a differential topology. The optimal phase offsets of harmonic sinusoids were obtained through the crest factor analysis. The output characteristics of this current source were evaluated by simulation and actual measurement. The results include the following: (1) the output impedance was compared with one of the Howland pump circuit in simulation, showing comparable performance at low frequencies. However, the proposed current source makes lower demands for resistor tolerance but performs even better at high frequencies. (2) The output impedance in actual measurement below 200 kHz is above 1.3 MΩ and can reach 250 KΩ up to 1 MHz. (3) An experiment based on a biological RC model has been implemented. The mean error for the demodulated impedance amplitude and phase are 0.192% and 0.139°, respectively. Therefore, the proposed current source is wideband, biocompatible, and high precision, which demonstrates great potential to work as a sub-system in the multi-frequency electrical impedance tomography system.

Carrier-interleaved orthogonal multi-electrode multi-carrier resistivity-measurement tool

NASA Astrophysics Data System (ADS)

Cai, Yu; Sha, Shuang

2016-09-01

This paper proposes a new carrier-interleaved orthogonal multi-electrode multi-carrier resistivity-measurement tool used in a cylindrical borehole environment during oil-based mud drilling processes. The new tool is an orthogonal frequency division multiplexing access-based contactless multi-measurand detection tool. The tool can measure formation resistivity in different azimuthal angles and elevational depths. It can measure many more measurands simultaneously in a specified bandwidth than the legacy frequency division multiplexing multi-measurand tool without a channel-select filter while avoiding inter-carrier interference. The paper also shows that formation resistivity is not sensitive to frequency in certain frequency bands. The average resistivity collected from N subcarriers can increase the measurement of the signal-to-noise ratio (SNR) by N times given no amplitude clipping in the current-injection electrode. If the clipping limit is taken into account, with the phase rotation of each single carrier, the amplitude peak-to-average ratio can be reduced by 3 times, and the SNR can achieve a 9/N times gain over the single-carrier system. The carrier-interleaving technique is also introduced to counter the carrier frequency offset (CFO) effect, where the CFO will cause inter-pad interference. A qualitative analysis and simulations demonstrate that block-interleaving performs better than tone-interleaving when coping with a large CFO. The theoretical analysis also suggests that increasing the subcarrier number can increase the measurement speed or enhance elevational resolution without sacrificing receiver performance. The complex orthogonal multi-pad multi-carrier resistivity logging tool, in which all subcarriers are complex signals, can provide a larger available subcarrier pool than other types of transceivers.

A symmetrical method to obtain shear moduli from microrheology.

PubMed

Nishi, Kengo; Kilfoil, Maria L; Schmidt, Christoph F; MacKintosh, F C

2018-05-16

Passive microrheology typically deduces shear elastic loss and storage moduli from displacement time series or mean-squared displacements (MSD) of thermally fluctuating probe particles in equilibrium materials. Common data analysis methods use either Kramers-Kronig (KK) transformation or functional fitting to calculate frequency-dependent loss and storage moduli. We propose a new analysis method for passive microrheology that avoids the limitations of both of these approaches. In this method, we determine both real and imaginary components of the complex, frequency-dependent response function χ(ω) = χ'(ω) + iχ''(ω) as direct integral transforms of the MSD of thermal particle motion. This procedure significantly improves the high-frequency fidelity of χ(ω) relative to the use of KK transformation, which has been shown to lead to artifacts in χ'(ω). We test our method on both model and experimental data. Experiments were performed on solutions of worm-like micelles and dilute collagen solutions. While the present method agrees well with established KK-based methods at low frequencies, we demonstrate significant improvement at high frequencies using our symmetric analysis method, up to almost the fundamental Nyquist limit.

Do regional methods really help reduce uncertainties in flood frequency analyses?

NASA Astrophysics Data System (ADS)

Cong Nguyen, Chi; Payrastre, Olivier; Gaume, Eric

2013-04-01

Flood frequency analyses are often based on continuous measured series at gauge sites. However, the length of the available data sets is usually too short to provide reliable estimates of extreme design floods. To reduce the estimation uncertainties, the analyzed data sets have to be extended either in time, making use of historical and paleoflood data, or in space, merging data sets considered as statistically homogeneous to build large regional data samples. Nevertheless, the advantage of the regional analyses, the important increase of the size of the studied data sets, may be counterbalanced by the possible heterogeneities of the merged sets. The application and comparison of four different flood frequency analysis methods to two regions affected by flash floods in the south of France (Ardèche and Var) illustrates how this balance between the number of records and possible heterogeneities plays in real-world applications. The four tested methods are: (1) a local statistical analysis based on the existing series of measured discharges, (2) a local analysis valuating the existing information on historical floods, (3) a standard regional flood frequency analysis based on existing measured series at gauged sites and (4) a modified regional analysis including estimated extreme peak discharges at ungauged sites. Monte Carlo simulations are conducted to simulate a large number of discharge series with characteristics similar to the observed ones (type of statistical distributions, number of sites and records) to evaluate to which extent the results obtained on these case studies can be generalized. These two case studies indicate that even small statistical heterogeneities, which are not detected by the standard homogeneity tests implemented in regional flood frequency studies, may drastically limit the usefulness of such approaches. On the other hand, these result show that the valuation of information on extreme events, either historical flood events at gauged sites or estimated extremes at ungauged sites in the considered region, is an efficient way to reduce uncertainties in flood frequency studies.

Advance in ERG Analysis: From Peak Time and Amplitude to Frequency, Power, and Energy

PubMed Central

Lina, Jean-Marc; Lachapelle, Pierre

2014-01-01

Purpose. To compare time domain (TD: peak time and amplitude) analysis of the human photopic electroretinogram (ERG) with measures obtained in the frequency domain (Fourier analysis: FA) and in the time-frequency domain (continuous (CWT) and discrete (DWT) wavelet transforms). Methods. Normal ERGs (n = 40) were analyzed using traditional peak time and amplitude measurements of the a- and b-waves in the TD and descriptors extracted from FA, CWT, and DWT. Selected descriptors were also compared in their ability to monitor the long-term consequences of disease process. Results. Each method extracted relevant information but had distinct limitations (i.e., temporal and frequency resolutions). The DWT offered the best compromise by allowing us to extract more relevant descriptors of the ERG signal at the cost of lesser temporal and frequency resolutions. Follow-ups of disease progression were more prolonged with the DWT (max 29 years compared to 13 with TD). Conclusions. Standardized time domain analysis of retinal function should be complemented with advanced DWT descriptors of the ERG. This method should allow more sensitive/specific quantifications of ERG responses, facilitate follow-up of disease progression, and identify diagnostically significant changes of ERG waveforms that are not resolved when the analysis is only limited to time domain measurements. PMID:25061605

Detection and characterization of cultural noise sources in magnetotelluric data: individual and joint analysis of the polarization attributes of the electric and magnetic field time-series in the time-frequency domain

NASA Astrophysics Data System (ADS)

Escalas, M.; Queralt, P.; Ledo, J.; Marcuello, A.

2012-04-01

Magnetotelluric (MT) method is a passive electromagnetic technique, which is currently used to characterize sites for the geological storage of CO2. These later ones are usually located nearby industrialized, urban or farming areas, where man-made electromagnetic (EM) signals contaminate the MT data. The identification and characterization of the artificial EM sources which generate the so-called "cultural noise" is an important challenge to obtain the most reliable results with the MT method. The polarization attributes of an EM signal (tilt angle, ellipticity and phase difference between its orthogonal components) are related to the character of its source. In a previous work (Escalas et al. 2011), we proposed a method to distinguish natural signal from cultural noise in the raw MT data. It is based on the polarization analysis of the MT time-series in the time-frequency domain, using a wavelet scheme. We developed an algorithm to implement the method, and was tested with both synthetic and field data. In 2010, we carried out a controlled-source electromagnetic (CSEM) experiment in the Hontomín site (the Research Laboratory on Geological Storage of CO2 in Spain). MT time-series were contaminated at different frequencies with the signal emitted by a controlled artificial EM source: two electric dipoles (1 km long, arranged in North-South and East-West directions). The analysis with our algorithm of the electric field time-series acquired in this experiment was successful: the polarization attributes of both the natural and artificial signal were obtained in the time-frequency domain, highlighting their differences. The processing of the magnetic field time-series acquired in the Hontomín experiment has been done in the present work. This new analysis of the polarization attributes of the magnetic field data has provided additional information to detect the contribution of the artificial source in the measured data. Moreover, the joint analysis of the polarization attributes of the electric and magnetic field has been crucial to fully characterize the properties and the location of the noise source. Escalas, M., Queralt, P., Ledo, J., Marcuello, A., 2011. Identification of cultural noise sources in magnetotelluric data: estimating polarization attributes in the time-frequency domain using wavelet analysis. Geophysical Research Abstracts Vol. 13, EGU2011-6085. EGU General Assembly 2011.

Analysis of electromagnetic scattering characteristics of plasma sheath surrounding a hypersonic aerocraft based on high-order auxiliary differential equation finite-difference time-domain

NASA Astrophysics Data System (ADS)

Sun, Hao-yu; Cui, Zhiwei; Wang, Jiajie; Han, Yiping; Sun, Peng; Shi, Xiaowei

2018-06-01

A numerical analysis of electromagnetic (EM) scattering characteristics of a hypersonic aerocraft enveloped by a plasma sheath is presented. The flow field parameters around a hypersonic aerocraft are derived by numerically solving the Navier-Stokes equations. Through multiphysics coupling of flow field and electromagnetic field, distributions of plasma frequency and collision frequency in plasma sheaths are obtained. A high-order auxiliary differential equation finite-difference time-domain algorithm is employed to investigate the EM wave scattering properties of the aerocraft covered by a plasma sheath. The backward radar cross sections (RCSs) of a blunt cone in the hypersonic flows at different velocities and altitudes with frequencies from 0.1 GHz to 18 GHz are studied. Numerical results show that, for the cases of altitude ranging from 50 km to 55 km and velocity ranging from 18 Ma to 20 Ma, the plasma sheath enhances the backscattering of the blunt cone when frequencies are below 1.5 GHz, and it reduces the backward RCSs of the blunt cone as frequency ranges from 1.5 GHz to 13.5 GHz. The plasma sheath has a larger attenuation effect for frequency lying in the range of 2 GHz to 6 GHz, but it has little influence on the backward electromagnetic scattering characteristics when frequencies are above 14 GHz.

Femtosecond-level timing fluctuation suppression in atmospheric frequency transfer with passive phase conjunction correction.

PubMed

Sun, Fuyu; Hou, Dong; Zhang, Danian; Tian, Jie; Hu, Jianguo; Huang, Xianhe; Chen, Shijun

2017-09-04

We demonstrate femtosecond-level timing fluctuation suppression in indoor atmospheric comb-based frequency transfer with a passive phase conjunction correction technique. Timing fluctuations and Allan deviations are both measured to characterize the excess frequency instability incurred during the frequency transfer process. By transferring a 2 GHz microwave over a 52-m long free-space link in 5000 s, the total root-mean-square (RMS) timing fluctuation was measured to be about 280 fs with a fractional frequency instability on the order of 3 × 10 -13 at 1 s and 6 × 10 -17 at 1000 s. This atmospheric comb-based frequency transfer with passive phase conjunction correction can be used to build an atomic clock-based free-space frequency transmission link because its instability is less than that of a commercial Cs or H-master clock.

Structural damage identification using damping: a compendium of uses and features

NASA Astrophysics Data System (ADS)

Cao, M. S.; Sha, G. G.; Gao, Y. F.; Ostachowicz, W.

2017-04-01

The vibration responses of structures under controlled or ambient excitation can be used to detect structural damage by correlating changes in structural dynamic properties extracted from responses with damage. Typical dynamic properties refer to modal parameters: natural frequencies, mode shapes, and damping. Among these parameters, natural frequencies and mode shapes have been investigated extensively for their use in damage characterization by associating damage with reduction in local stiffness of structures. In contrast, the use of damping as a dynamic property to represent structural damage has not been comprehensively elucidated, primarily due to the complexities of damping measurement and analysis. With advances in measurement technologies and analysis tools, the use of damping to identify damage is becoming a focus of increasing attention in the damage detection community. Recently, a number of studies have demonstrated that damping has greater sensitivity for characterizing damage than natural frequencies and mode shapes in various applications, but damping-based damage identification is still a research direction ‘in progress’ and is not yet well resolved. This situation calls for an overall survey of the state-of-the-art and the state-of-the-practice of using damping to detect structural damage. To this end, this study aims to provide a comprehensive survey of uses and features of applying damping in structural damage detection. First, we present various methods for damping estimation in different domains including the time domain, the frequency domain, and the time-frequency domain. Second, we investigate the features and applications of damping-based damage detection methods on the basis of two predominant infrastructure elements, reinforced concrete structures and fiber-reinforced composites. Third, we clarify the influential factors that can impair the capability of damping to characterize damage. Finally, we recommend future research directions for advancing damping-based damage detection. This work holds the promise of (a) helping researchers identify crucial components in damping-based damage detection theories, methods, and technologies, and (b) leading practitioners to better implement damping-based structural damage identification.

Efficient Computation of Closed-loop Frequency Response for Large Order Flexible Systems

NASA Technical Reports Server (NTRS)

Maghami, Peiman G.; Giesy, Daniel P.

1997-01-01

An efficient and robust computational scheme is given for the calculation of the frequency response function of a large order, flexible system implemented with a linear, time invariant control system. Advantage is taken of the highly structured sparsity of the system matrix of the plant based on a model of the structure using normal mode coordinates. The computational time per frequency point of the new computational scheme is a linear function of system size, a significant improvement over traditional, full-matrix techniques whose computational times per frequency point range from quadratic to cubic functions of system size. This permits the practical frequency domain analysis of systems of much larger order than by traditional, full-matrix techniques. Formulations are given for both open and closed loop loop systems. Numerical examples are presented showing the advantages of the present formulation over traditional approaches, both in speed and in accuracy. Using a model with 703 structural modes, a speed-up of almost two orders of magnitude was observed while accuracy improved by up to 5 decimal places.

Continuous-wave cavity ringdown spectroscopy based on the control of cavity reflection.

PubMed

Li, Zhixin; Ma, Weiguang; Fu, Xiaofang; Tan, Wei; Zhao, Gang; Dong, Lei; Zhang, Lei; Yin, Wangbao; Jia, Suotang

2013-07-29

A new type of continuous-wave cavity ringdown spectrometer based on the control of cavity reflection for trace gas detection was designed and evaluated. The technique separated the acquisitions of the ringdown event and the trigger signal to optical switch by detecting the cavity reflection and transmission, respectively. A detailed description of the time sequence of the measurement process was presented. In order to avoid the wrong extraction of ringdown time encountered accidentally in fitting procedure, the laser frequency and cavity length were scanned synchronously. Based on the statistical analysis of measured ringdown times, the frequency normalized minimum detectable absorption in the reflection control mode was 1.7 × 10(-9)cm(-1)Hz(-1/2), which was 5.4 times smaller than that in the transmission control mode. However the signal-to-noise ratio of the absorption spectrum was only 3 times improved since the etalon effect existed. Finally, the peak absorption coefficients of the C(2)H(2) transition near 1530.9nm under different pressures showed a good agreement with the theoretical values.

Ground roll attenuation using polarization analysis in the t-f-k domain

NASA Astrophysics Data System (ADS)

Wang, C.; Wang, Y.

2017-07-01

S waves travel slower than P waves and have a lower dominant frequency. Therefore, applying common techniques such as time-frequency filtering and f-k filtering to separate S waves from ground roll is difficult because ground roll is also characterized by slow velocity and low frequency. In this study, we present a method for attenuating ground roll using a polarization filtering method based on the t-f-k transform. We describe the particle motion of the waves by complex vector signals. Each pair of frequency components, whose frequencies have the same absolute value but different signs, of the complex signal indicate an elliptical or linear motion. The polarization parameters of the elliptical or linear motion are explicitly related to the two Fourier coefficients. We then extend these concepts to the t-f-k domain and propose a polarization filtering method for ground roll attenuation based on the t-f-k transform. The proposed approach can define automatically the time-varying reject zones on the f-k panel at different times as a function of the reciprocal ellipticity. Four attributes, time, frequency, apparent velocity and polarization are used to identify and extract the ground roll simultaneously. Thus, the ground roll and body waves can be separated as long as they are dissimilar in one of these attributes. We compare our method with commonly used filtering techniques by applying the methods to synthetic and real seismic data. The results indicate that our method can attenuate ground roll while preserving body waves more effectively than the other methods.

Dissociable neural response signatures for slow amplitude and frequency modulation in human auditory cortex.

PubMed

Henry, Molly J; Obleser, Jonas

2013-01-01

Natural auditory stimuli are characterized by slow fluctuations in amplitude and frequency. However, the degree to which the neural responses to slow amplitude modulation (AM) and frequency modulation (FM) are capable of conveying independent time-varying information, particularly with respect to speech communication, is unclear. In the current electroencephalography (EEG) study, participants listened to amplitude- and frequency-modulated narrow-band noises with a 3-Hz modulation rate, and the resulting neural responses were compared. Spectral analyses revealed similar spectral amplitude peaks for AM and FM at the stimulation frequency (3 Hz), but amplitude at the second harmonic frequency (6 Hz) was much higher for FM than for AM. Moreover, the phase delay of neural responses with respect to the full-band stimulus envelope was shorter for FM than for AM. Finally, the critical analysis involved classification of single trials as being in response to either AM or FM based on either phase or amplitude information. Time-varying phase, but not amplitude, was sufficient to accurately classify AM and FM stimuli based on single-trial neural responses. Taken together, the current results support the dissociable nature of cortical signatures of slow AM and FM. These cortical signatures potentially provide an efficient means to dissect simultaneously communicated slow temporal and spectral information in acoustic communication signals.

Dissociable Neural Response Signatures for Slow Amplitude and Frequency Modulation in Human Auditory Cortex

PubMed Central

Henry, Molly J.; Obleser, Jonas

2013-01-01

Natural auditory stimuli are characterized by slow fluctuations in amplitude and frequency. However, the degree to which the neural responses to slow amplitude modulation (AM) and frequency modulation (FM) are capable of conveying independent time-varying information, particularly with respect to speech communication, is unclear. In the current electroencephalography (EEG) study, participants listened to amplitude- and frequency-modulated narrow-band noises with a 3-Hz modulation rate, and the resulting neural responses were compared. Spectral analyses revealed similar spectral amplitude peaks for AM and FM at the stimulation frequency (3 Hz), but amplitude at the second harmonic frequency (6 Hz) was much higher for FM than for AM. Moreover, the phase delay of neural responses with respect to the full-band stimulus envelope was shorter for FM than for AM. Finally, the critical analysis involved classification of single trials as being in response to either AM or FM based on either phase or amplitude information. Time-varying phase, but not amplitude, was sufficient to accurately classify AM and FM stimuli based on single-trial neural responses. Taken together, the current results support the dissociable nature of cortical signatures of slow AM and FM. These cortical signatures potentially provide an efficient means to dissect simultaneously communicated slow temporal and spectral information in acoustic communication signals. PMID:24205309

Photoacoustic detection of blood in dental pulp by using short-time Fourier transform

NASA Astrophysics Data System (ADS)

Yamada, Azusa; Kakino, Satoko; Matsuura, Yuji

2016-03-01

A method based on photoacoustic analysis is proposed to diagnose dental pulp vitality. Photoacoustic analysis enables to get signal from deeper tissues than other optical analyses and therefore, signal detection from root canal of thick dental tissues such as molar teeth is expected. As a light source for excitation of photoacoustic waves, a microchip Q-switched YAG laser with a wavelength of 1064 nm was used and owing to large penetration depth of the near infrared laser, photoacoustic signals from dental root were successfully obtained. It was found that the photoacoustic signals from the teeth containing hemoglobin solution in the pulp cavity provide vibration in high frequency region. It was also shown that the intensities of the high frequency component have correlation with the hemoglobin concentration of solution. We applied short-time Fourier transform for evaluation of photoacoustic signals and this analysis clearly showed photoacoustic signals from dental root.

Coital frequency and infertility: which male factors predict less frequent coitus among infertile couples?

PubMed

Perlis, Nathan; Lo, Kirk C; Grober, Ethan D; Spencer, Leia; Jarvi, Keith

2013-08-01

To determine the coital frequency among infertile couples and which factors are associated with less frequent coitus. Cross-sectional study. Tertiary-level male infertility clinic. A total of 1,298 infertile men. Administration of computer-based survey, semen analysis, and serum hormone evaluation. Monthly coital frequency. A total of 1,298 patients presented to clinic for infertility consultation and completed the computer-based survey. The median male age was 35 years (interquartile range [IQR] 32-39 years) and the median duration of infertility was 2 years (IQR 1-4 years) before consultation. Median monthly coital frequency was seven (IQR 5-10; range 0-40); 24% of couples were having intercourse ≤ 4 times per month. Overall, 0.6%, 2.7%, 4.8%, 5.8%, and 10.8% of the men reported having intercourse 0, 1, 2, 3, and 4 times per month, respectively. When simultaneously taking into account the influence of age, libido, erectile function, and semen volume on coital frequency, older patients had 1.05 times higher odds (per year of age) of less frequent coitus (odds ratio 1.05, 95% confidence interval 1.03-1.08). In addition, patients with better erectile function had 1.12 times higher odds (per point on Sexual Health Inventory for Men scale) of more frequent coitus (odds ratio 1.12, 95% confidence interval 1.09-1.18). Similar to the general population, most infertile couples report having coitus more than four times per month. Older male age and erectile dysfunction are independent risk factors for less frequent coitus among infertile men, which could have an impact on fertility. Coital frequency should be considered in infertility assessments. Copyright © 2013 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

High and low frequency unfolded partial least squares regression based on empirical mode decomposition for quantitative analysis of fuel oil samples.

PubMed

Bian, Xihui; Li, Shujuan; Lin, Ligang; Tan, Xiaoyao; Fan, Qingjie; Li, Ming

2016-06-21

Accurate prediction of the model is fundamental to the successful analysis of complex samples. To utilize abundant information embedded over frequency and time domains, a novel regression model is presented for quantitative analysis of hydrocarbon contents in the fuel oil samples. The proposed method named as high and low frequency unfolded PLSR (HLUPLSR), which integrates empirical mode decomposition (EMD) and unfolded strategy with partial least squares regression (PLSR). In the proposed method, the original signals are firstly decomposed into a finite number of intrinsic mode functions (IMFs) and a residue by EMD. Secondly, the former high frequency IMFs are summed as a high frequency matrix and the latter IMFs and residue are summed as a low frequency matrix. Finally, the two matrices are unfolded to an extended matrix in variable dimension, and then the PLSR model is built between the extended matrix and the target values. Coupled with Ultraviolet (UV) spectroscopy, HLUPLSR has been applied to determine hydrocarbon contents of light gas oil and diesel fuels samples. Comparing with single PLSR and other signal processing techniques, the proposed method shows superiority in prediction ability and better model interpretation. Therefore, HLUPLSR method provides a promising tool for quantitative analysis of complex samples. Copyright © 2016 Elsevier B.V. All rights reserved.

Accelerometer Data Analysis and Presentation Techniques

NASA Technical Reports Server (NTRS)

Rogers, Melissa J. B.; Hrovat, Kenneth; McPherson, Kevin; Moskowitz, Milton E.; Reckart, Timothy

1997-01-01

The NASA Lewis Research Center's Principal Investigator Microgravity Services project analyzes Orbital Acceleration Research Experiment and Space Acceleration Measurement System data for principal investigators of microgravity experiments. Principal investigators need a thorough understanding of data analysis techniques so that they can request appropriate analyses to best interpret accelerometer data. Accelerometer data sampling and filtering is introduced along with the related topics of resolution and aliasing. Specific information about the Orbital Acceleration Research Experiment and Space Acceleration Measurement System data sampling and filtering is given. Time domain data analysis techniques are discussed and example environment interpretations are made using plots of acceleration versus time, interval average acceleration versus time, interval root-mean-square acceleration versus time, trimmean acceleration versus time, quasi-steady three dimensional histograms, and prediction of quasi-steady levels at different locations. An introduction to Fourier transform theory and windowing is provided along with specific analysis techniques and data interpretations. The frequency domain analyses discussed are power spectral density versus frequency, cumulative root-mean-square acceleration versus frequency, root-mean-square acceleration versus frequency, one-third octave band root-mean-square acceleration versus frequency, and power spectral density versus frequency versus time (spectrogram). Instructions for accessing NASA Lewis Research Center accelerometer data and related information using the internet are provided.

Ultrasound shear wave simulation based on nonlinear wave propagation and Wigner-Ville Distribution analysis

NASA Astrophysics Data System (ADS)

Bidari, Pooya Sobhe; Alirezaie, Javad; Tavakkoli, Jahan

2017-03-01

This paper presents a method for modeling and simulation of shear wave generation from a nonlinear Acoustic Radiation Force Impulse (ARFI) that is considered as a distributed force applied at the focal region of a HIFU transducer radiating in nonlinear regime. The shear wave propagation is simulated by solving the Navier's equation from the distributed nonlinear ARFI as the source of the shear wave. Then, the Wigner-Ville Distribution (WVD) as a time-frequency analysis method is used to detect the shear wave at different local points in the region of interest. The WVD results in an estimation of the shear wave time of arrival, its mean frequency and local attenuation which can be utilized to estimate medium's shear modulus and shear viscosity using the Voigt model.

Intensity - Duration - Frequency Curves for U.S. Cities in a Warming Climate

NASA Astrophysics Data System (ADS)

Ragno, Elisa; AghaKouchak, Amir; Love, Charlotte; Vahedifard, Farshid; Cheng, Linyin; Lima, Carlos

2017-04-01

Current infrastructure design procedures rely on the use of Intensity - Duration - Frequency (IDF) curves retrieved under the assumption of temporal stationarity, meaning that occurrences of extreme events are expected to be time invariant. However, numerous studies have observed more severe extreme events over time. Hence, the stationarity assumption for extreme analysis may not be appropriate in a warming climate. This issue raises concerns regarding the safety and resilience of infrastructures and natural slopes. Here we employ daily precipitation data from historical and projected (RCP 8.5) CMIP5 runs to investigate IDF curves of 14 urban areas across the United States. We first statistically assess changes in precipitation extremes using an energy-based test for equal distributions. Then, through a Bayesian inference approach for stationary and non-stationary extreme value analysis, we provide updated IDF curves based on future climatic model projections. We show that, based on CMIP5 simulations, U.S cities may experience extreme precipitation events up to 20% more intense and twice as frequently, relative to historical records, despite the expectation of unchanged annual mean precipitation.

Network Analyses for Space-Time High Frequency Wind Data

NASA Astrophysics Data System (ADS)

Laib, Mohamed; Kanevski, Mikhail

2017-04-01

Recently, network science has shown an important contribution to the analysis, modelling and visualization of complex time series. Numerous existing methods have been proposed for constructing networks. This work studies spatio-temporal wind data by using networks based on the Granger causality test. Furthermore, a visual comparison is carried out with several frequencies of data and different size of moving window. The main attention is paid to the temporal evolution of connectivity intensity. The Hurst exponent is applied on the provided time series in order to explore if there is a long connectivity memory. The results explore the space time structure of wind data and can be applied to other environmental data. The used dataset presents a challenging case study. It consists of high frequency (10 minutes) wind data from 120 measuring stations in Switzerland, for a time period of 2012-2013. The distribution of stations covers different geomorphological zones and elevation levels. The results are compared with the Person correlation network as well.

Wideband spectrum analysis of ultra-high frequency radio-wave signals due to advanced one-phonon non-collinear anomalous light scattering.

PubMed

Shcherbakov, Alexandre S; Arellanes, Adan Omar

2017-04-20

We present a principally new acousto-optical cell providing an advanced wideband spectrum analysis of ultra-high frequency radio-wave signals. For the first time, we apply a recently developed approach with the tilt angle to a one-phonon non-collinear anomalous light scattering. In contrast to earlier cases, now one can exploit a regime with the fixed optical wavelength for processing a great number of acoustic frequencies simultaneously in the linear regime. The chosen rutile-crystal combines a moderate acoustic velocity with low acoustic attenuation and allows us wide-band data processing within GHz-frequency acoustic waves. We have created and experimentally tested a 6-cm aperture rutile-made acousto-optical cell providing the central frequency 2.0 GHz, frequency bandwidth ∼0.52  GHz with the frequency resolution about 68.3 kHz, and ∼7620 resolvable spots. A similar cell permits designing an advanced ultra-high-frequency arm within a recently developed multi-band radio-wave acousto-optical spectrometer for astrophysical studies. This spectrometer is intended to operate with a few parallel optical arms for processing the multi-frequency data flows within astrophysical observations. Keeping all the instrument's advantages of the previous schematic arrangement, now one can create the highest-frequency arm using the developed rutile-based acousto-optical cell. It permits optimizing the performances inherent in that arm via regulation of both the central frequency and the frequency bandwidth for spectrum analysis.

The use of SESK as a trend parameter for localized bearing fault diagnosis in induction machines.

PubMed

Saidi, Lotfi; Ben Ali, Jaouher; Benbouzid, Mohamed; Bechhoefer, Eric

2016-07-01

A critical work of bearing fault diagnosis is locating the optimum frequency band that contains faulty bearing signal, which is usually buried in the noise background. Now, envelope analysis is commonly used to obtain the bearing defect harmonics from the envelope signal spectrum analysis and has shown fine results in identifying incipient failures occurring in the different parts of a bearing. However, the main step in implementing envelope analysis is to determine a frequency band that contains faulty bearing signal component with the highest signal noise level. Conventionally, the choice of the band is made by manual spectrum comparison via identifying the resonance frequency where the largest change occurred. In this paper, we present a squared envelope based spectral kurtosis method to determine optimum envelope analysis parameters including the filtering band and center frequency through a short time Fourier transform. We have verified the potential of the spectral kurtosis diagnostic strategy in performance improvements for single-defect diagnosis using real laboratory-collected vibration data sets. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

The leisure style of Canadian rural recreation participants: An analysis based on three different rural leisure settings

Treesearch

Paul Heintzman; Don Dawson

2012-01-01

This study was a secondary analysis of data from a previous study of 248 Canadians on four dimensions of leisure style: time use, leisure setting, leisure activity participation, and leisure motivation. Correlation analyses were conducted to determine if frequency of participation in three rural leisure settings were related to other leisure style dimensions.

Time-Frequency Analysis of Beach Bacteria Variations and its Implication for Recreational Water Quality Modeling

EPA Science Inventory

This paper explores the potential of time-frequency wavelet analysis in resolving beach bacteria concentration and possible explanatory variables across multiple time scales with temporal information still preserved. The wavelet scalograms of E. coli concentrations and the explan...

SPA- STATISTICAL PACKAGE FOR TIME AND FREQUENCY DOMAIN ANALYSIS

NASA Technical Reports Server (NTRS)

Brownlow, J. D.

1994-01-01

The need for statistical analysis often arises when data is in the form of a time series. This type of data is usually a collection of numerical observations made at specified time intervals. Two kinds of analysis may be performed on the data. First, the time series may be treated as a set of independent observations using a time domain analysis to derive the usual statistical properties including the mean, variance, and distribution form. Secondly, the order and time intervals of the observations may be used in a frequency domain analysis to examine the time series for periodicities. In almost all practical applications, the collected data is actually a mixture of the desired signal and a noise signal which is collected over a finite time period with a finite precision. Therefore, any statistical calculations and analyses are actually estimates. The Spectrum Analysis (SPA) program was developed to perform a wide range of statistical estimation functions. SPA can provide the data analyst with a rigorous tool for performing time and frequency domain studies. In a time domain statistical analysis the SPA program will compute the mean variance, standard deviation, mean square, and root mean square. It also lists the data maximum, data minimum, and the number of observations included in the sample. In addition, a histogram of the time domain data is generated, a normal curve is fit to the histogram, and a goodness-of-fit test is performed. These time domain calculations may be performed on both raw and filtered data. For a frequency domain statistical analysis the SPA program computes the power spectrum, cross spectrum, coherence, phase angle, amplitude ratio, and transfer function. The estimates of the frequency domain parameters may be smoothed with the use of Hann-Tukey, Hamming, Barlett, or moving average windows. Various digital filters are available to isolate data frequency components. Frequency components with periods longer than the data collection interval are removed by least-squares detrending. As many as ten channels of data may be analyzed at one time. Both tabular and plotted output may be generated by the SPA program. This program is written in FORTRAN IV and has been implemented on a CDC 6000 series computer with a central memory requirement of approximately 142K (octal) of 60 bit words. This core requirement can be reduced by segmentation of the program. The SPA program was developed in 1978.

High frequency resolution terahertz time-domain spectroscopy

NASA Astrophysics Data System (ADS)

Sangala, Bagvanth Reddy

2013-12-01

A new method for the high frequency resolution terahertz time-domain spectroscopy is developed based on the characteristic matrix method. This method is useful for studying planar samples or stack of planar samples. The terahertz radiation was generated by optical rectification in a ZnTe crystal and detected by another ZnTe crystal via electro-optic sampling method. In this new characteristic matrix based method, the spectra of the sample and reference waveforms will be modeled by using characteristic matrices. We applied this new method to measure the optical constants of air. The terahertz transmission through the layered systems air-Teflon-air-Quartz-air and Nitrogen gas-Teflon-Nitrogen gas-Quartz-Nitrogen gas was modeled by the characteristic matrix method. A transmission coefficient is derived from these models which was optimized to fit the experimental transmission coefficient to extract the optical constants of air. The optimization of an error function involving the experimental complex transmission coefficient and the theoretical transmission coefficient was performed using patternsearch algorithm of MATLAB. Since this method takes account of the echo waveforms due to reflections in the layered samples, this method allows analysis of longer time-domain waveforms giving rise to very high frequency resolution in the frequency-domain. We have presented the high frequency resolution terahertz time-domain spectroscopy of air and compared the results with the literature values. We have also fitted the complex susceptibility of air to the Lorentzian and Gaussian functions to extract the linewidths.

Analysis of nonlinear modulation between sound and vibrations in metallic structure and its use for damage detection

NASA Astrophysics Data System (ADS)

Liu, Bin; Gang, Tie; Wan, Chuhao; Wang, Changxi; Luo, Zhiwei

2015-07-01

Vibro-acoustic modulation technique is a nonlinear ultrasonic method in nondestructive testing. This technique detects the defects by monitoring the modulation components generated by the interaction between the vibration and the ultrasound wave due to the nonlinear material behaviour caused by the damage. In this work, a swept frequency signal was used as high frequency excitation, then the Hilbert transform based amplitude and phase demodulation and synchronous demodulation (SD) were used to extract the modulation information from the received signal, the results were graphed in the time-frequency domain after the short time Fourier transform. The demodulation results were quite different from each other. The reason for the difference was investigated by analysing the demodulation process of the two methods. According to the analysis and the subsequent verification test, it was indicated that the SD method was more proper for the test and a new index called MISD was defined to evaluate the structure quality in the Vibro-acoustic modulation test with swept probing excitation.

An approach based on wavelet analysis for feature extraction in the a-wave of the electroretinogram.

PubMed

Barraco, R; Persano Adorno, D; Brai, M

2011-12-01

Most biomedical signals are non-stationary. The knowledge of their frequency content and temporal distribution is then useful in a clinical context. The wavelet analysis is appropriate to achieve this task. The present paper uses this method to reveal hidden characteristics and anomalies of the human a-wave, an important component of the electroretinogram since it is a measure of the functional integrity of the photoreceptors. We here analyse the time-frequency features of the a-wave both in normal subjects and in patients affected by Achromatopsia, a pathology disturbing the functionality of the cones. The results indicate the presence of two or three stable frequencies that, in the pathological case, shift toward lower values and change their times of occurrence. The present findings are a first step toward a deeper understanding of the features of the a-wave and possible applications to diagnostic procedures in order to recognise incipient photoreceptoral pathologies. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Knowledge discovery from high-frequency stream nitrate concentrations: hydrology and biology contributions.

PubMed

Aubert, Alice H; Thrun, Michael C; Breuer, Lutz; Ultsch, Alfred

2016-08-30

High-frequency, in-situ monitoring provides large environmental datasets. These datasets will likely bring new insights in landscape functioning and process scale understanding. However, tailoring data analysis methods is necessary. Here, we detach our analysis from the usual temporal analysis performed in hydrology to determine if it is possible to infer general rules regarding hydrochemistry from available large datasets. We combined a 2-year in-stream nitrate concentration time series (time resolution of 15 min) with concurrent hydrological, meteorological and soil moisture data. We removed the low-frequency variations through low-pass filtering, which suppressed seasonality. We then analyzed the high-frequency variability component using Pareto Density Estimation, which to our knowledge has not been applied to hydrology. The resulting distribution of nitrate concentrations revealed three normally distributed modes: low, medium and high. Studying the environmental conditions for each mode revealed the main control of nitrate concentration: the saturation state of the riparian zone. We found low nitrate concentrations under conditions of hydrological connectivity and dominant denitrifying biological processes, and we found high nitrate concentrations under hydrological recession conditions and dominant nitrifying biological processes. These results generalize our understanding of hydro-biogeochemical nitrate flux controls and bring useful information to the development of nitrogen process-based models at the landscape scale.

Analysis of Loss-of-Offsite-Power Events 1997-2015

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, Nancy Ellen; Schroeder, John Alton

2016-07-01

Loss of offsite power (LOOP) can have a major negative impact on a power plant’s ability to achieve and maintain safe shutdown conditions. LOOP event frequencies and times required for subsequent restoration of offsite power are important inputs to plant probabilistic risk assessments. This report presents a statistical and engineering analysis of LOOP frequencies and durations at U.S. commercial nuclear power plants. The data used in this study are based on the operating experience during calendar years 1997 through 2015. LOOP events during critical operation that do not result in a reactor trip, are not included. Frequencies and durations weremore » determined for four event categories: plant-centered, switchyard-centered, grid-related, and weather-related. Emergency diesel generator reliability is also considered (failure to start, failure to load and run, and failure to run more than 1 hour). There is an adverse trend in LOOP durations. The previously reported adverse trend in LOOP frequency was not statistically significant for 2006-2015. Grid-related LOOPs happen predominantly in the summer. Switchyard-centered LOOPs happen predominantly in winter and spring. Plant-centered and weather-related LOOPs do not show statistically significant seasonality. The engineering analysis of LOOP data shows that human errors have been much less frequent since 1997 than in the 1986 -1996 time period.« less

The identification of multi-cave combinations in carbonate reservoirs based on sparsity constraint inverse spectral decomposition

NASA Astrophysics Data System (ADS)

Li, Qian; Di, Bangrang; Wei, Jianxin; Yuan, Sanyi; Si, Wenpeng

2016-12-01

Sparsity constraint inverse spectral decomposition (SCISD) is a time-frequency analysis method based on the convolution model, in which minimizing the l1 norm of the time-frequency spectrum of the seismic signal is adopted as a sparsity constraint term. The SCISD method has higher time-frequency resolution and more concentrated time-frequency distribution than the conventional spectral decomposition methods, such as short-time Fourier transformation (STFT), continuous-wavelet transform (CWT) and S-transform. Due to these good features, the SCISD method has gradually been used in low-frequency anomaly detection, horizon identification and random noise reduction for sandstone and shale reservoirs. However, it has not yet been used in carbonate reservoir prediction. The carbonate fractured-vuggy reservoir is the major hydrocarbon reservoir in the Halahatang area of the Tarim Basin, north-west China. If reasonable predictions for the type of multi-cave combinations are not made, it may lead to an incorrect explanation for seismic responses of the multi-cave combinations. Furthermore, it will result in large errors in reserves estimation of the carbonate reservoir. In this paper, the energy and phase spectra of the SCISD are applied to identify the multi-cave combinations in carbonate reservoirs. The examples of physical model data and real seismic data illustrate that the SCISD method can detect the combination types and the number of caves of multi-cave combinations and can provide a favourable basis for the subsequent reservoir prediction and quantitative estimation of the cave-type carbonate reservoir volume.

Frequency-dependent selection predicts patterns of radiations and biodiversity.

PubMed

Melián, Carlos J; Alonso, David; Vázquez, Diego P; Regetz, James; Allesina, Stefano

2010-08-26

Most empirical studies support a decline in speciation rates through time, although evidence for constant speciation rates also exists. Declining rates have been explained by invoking pre-existing niches, whereas constant rates have been attributed to non-adaptive processes such as sexual selection and mutation. Trends in speciation rate and the processes underlying it remain unclear, representing a critical information gap in understanding patterns of global diversity. Here we show that the temporal trend in the speciation rate can also be explained by frequency-dependent selection. We construct a frequency-dependent and DNA sequence-based model of speciation. We compare our model to empirical diversity patterns observed for cichlid fish and Darwin's finches, two classic systems for which speciation rates and richness data exist. Negative frequency-dependent selection predicts well both the declining speciation rate found in cichlid fish and explains their species richness. For groups like the Darwin's finches, in which speciation rates are constant and diversity is lower, speciation rate is better explained by a model without frequency-dependent selection. Our analysis shows that differences in diversity may be driven by incipient species abundance with frequency-dependent selection. Our results demonstrate that genetic-distance-based speciation and frequency-dependent selection are sufficient to explain the high diversity observed in natural systems and, importantly, predict decay through time in speciation rate in the absence of pre-existing niches.

Time- and frequency-resolved measurements of frequency modulation and switching of a tunable semiconductor laser

NASA Astrophysics Data System (ADS)

Kuznetsov, M.; Stone, J.; Stulz, L. W.

1991-11-01

We report measurements of intensity as a function of both time and frequency for frequency modulation and switching of a tunable semiconductor laser. Because of the uncertainty principle limitations, the measured time-frequency signal can have a complex structure and does not show the simple-minded picture of a laser spectrum whose center frequency varies in time. The observations are explained by a theory of the time-dependent spectral measurements, well known in the field of speech analysis. We discuss implications for channel switching speed and channel interference in switched, frequency-multiplexed optical networks.

Frequency Analysis of Modis Ndvi Time Series for Determining Hotspot of Land Degradation in Mongolia

NASA Astrophysics Data System (ADS)

Nasanbat, E.; Sharav, S.; Sanjaa, T.; Lkhamjav, O.; Magsar, E.; Tuvdendorj, B.

2018-04-01

This study examines MODIS NDVI satellite imagery time series can be used to determine hotspot of land degradation area in whole Mongolia. The trend statistical analysis of Mann-Kendall was applied to a 16-year MODIS NDVI satellite imagery record, based on 16-day composited temporal data (from May to September) for growing seasons and from 2000 to 2016. We performed to frequency analysis that resulting NDVI residual trend pattern would enable successful determined of negative and positive changes in photo synthetically health vegetation. Our result showed that negative and positive values and generated a map of significant trends. Also, we examined long-term of meteorological parameters for the same period. The result showed positive and negative NDVI trends concurred with land cover types change representing an improve or a degrade in vegetation, respectively. Also, integrated the climate parameters which were precipitation and air temperature changes in the same time period seem to have had an affecting on huge NDVI trend area. The time series trend analysis approach applied successfully determined hotspot of an improvement and a degraded area due to land degradation and desertification.

Zero-moment point determination of worst-case manoeuvres leading to vehicle wheel lift

NASA Astrophysics Data System (ADS)

Lapapong, S.; Brown, A. A.; Swanson, K. S.; Brennan, S. N.

2012-01-01

This paper proposes a method to evaluate vehicle rollover propensity based on a frequency-domain representation of the zero-moment point (ZMP). Unlike other rollover metrics such as the static stability factor, which is based on the steady-state behaviour, and the load transfer ratio, which requires the calculation of tyre forces, the ZMP is based on a simplified kinematic model of the vehicle and the analysis of the contact point of the vehicle relative to the edge of the support polygon. Previous work has validated the use of the ZMP experimentally in its ability to predict wheel lift in the time domain. This work explores the use of the ZMP in the frequency domain to allow a chassis designer to understand how operating conditions and vehicle parameters affect rollover propensity. The ZMP analysis is then extended to calculate worst-case sinusoidal manoeuvres that lead to untripped wheel lift, and the analysis is tested across several vehicle configurations and compared with that of the standard Toyota J manoeuvre.

Fault diagnosis of motor bearing with speed fluctuation via angular resampling of transient sound signals

NASA Astrophysics Data System (ADS)

Lu, Siliang; Wang, Xiaoxian; He, Qingbo; Liu, Fang; Liu, Yongbin

2016-12-01

Transient signal analysis (TSA) has been proven an effective tool for motor bearing fault diagnosis, but has yet to be applied in processing bearing fault signals with variable rotating speed. In this study, a new TSA-based angular resampling (TSAAR) method is proposed for fault diagnosis under speed fluctuation condition via sound signal analysis. By applying the TSAAR method, the frequency smearing phenomenon is eliminated and the fault characteristic frequency is exposed in the envelope spectrum for bearing fault recognition. The TSAAR method can accurately estimate the phase information of the fault-induced impulses using neither complicated time-frequency analysis techniques nor external speed sensors, and hence it provides a simple, flexible, and data-driven approach that realizes variable-speed motor bearing fault diagnosis. The effectiveness and efficiency of the proposed TSAAR method are verified through a series of simulated and experimental case studies.

Bearing fault diagnosis under unknown time-varying rotational speed conditions via multiple time-frequency curve extraction

NASA Astrophysics Data System (ADS)

Huang, Huan; Baddour, Natalie; Liang, Ming

2018-02-01

Under normal operating conditions, bearings often run under time-varying rotational speed conditions. Under such circumstances, the bearing vibrational signal is non-stationary, which renders ineffective the techniques used for bearing fault diagnosis under constant running conditions. One of the conventional methods of bearing fault diagnosis under time-varying speed conditions is resampling the non-stationary signal to a stationary signal via order tracking with the measured variable speed. With the resampled signal, the methods available for constant condition cases are thus applicable. However, the accuracy of the order tracking is often inadequate and the time-varying speed is sometimes not measurable. Thus, resampling-free methods are of interest for bearing fault diagnosis under time-varying rotational speed for use without tachometers. With the development of time-frequency analysis, the time-varying fault character manifests as curves in the time-frequency domain. By extracting the Instantaneous Fault Characteristic Frequency (IFCF) from the Time-Frequency Representation (TFR) and converting the IFCF, its harmonics, and the Instantaneous Shaft Rotational Frequency (ISRF) into straight lines, the bearing fault can be detected and diagnosed without resampling. However, so far, the extraction of the IFCF for bearing fault diagnosis is mostly based on the assumption that at each moment the IFCF has the highest amplitude in the TFR, which is not always true. Hence, a more reliable T-F curve extraction approach should be investigated. Moreover, if the T-F curves including the IFCF, its harmonic, and the ISRF can be all extracted from the TFR directly, no extra processing is needed for fault diagnosis. Therefore, this paper proposes an algorithm for multiple T-F curve extraction from the TFR based on a fast path optimization which is more reliable for T-F curve extraction. Then, a new procedure for bearing fault diagnosis under unknown time-varying speed conditions is developed based on the proposed algorithm and a new fault diagnosis strategy. The average curve-to-curve ratios are utilized to describe the relationship of the extracted curves and fault diagnosis can then be achieved by comparing the ratios to the fault characteristic coefficients. The effectiveness of the proposed method is validated by simulated and experimental signals.

Trimming algorithm of frequency modulation for CIAE-230 MeV proton superconducting synchrocyclotron model cavity

NASA Astrophysics Data System (ADS)

Li, Pengzhan; Zhang, Tianjue; Ji, Bin; Hou, Shigang; Guo, Juanjuan; Yin, Meng; Xing, Jiansheng; Lv, Yinlong; Guan, Fengping; Lin, Jun

2017-01-01

A new project, the 230 MeV proton superconducting synchrocyclotron for cancer therapy, was proposed at CIAE in 2013. A model cavity is designed to verify the frequency modulation trimming algorithm featuring a half-wave structure and eight sets of rotating blades for 1 kHz frequency modulation. Based on the electromagnetic (EM) field distribution analysis of the model cavity, the variable capacitor works as a function of time and the frequency can be written in Maclaurin series. Curve fitting is applied for theoretical frequency and original simulation frequency. The second-order fitting excels at the approximation given its minimum variance. Constant equivalent inductance is considered as an important condition in the calculation. The equivalent parameters of theoretical frequency can be achieved through this conversion. Then the trimming formula for rotor blade outer radius is found by discretization in time domain. Simulation verification has been performed and the results show that the calculation radius with minus 0.012 m yields an acceptable result. The trimming amendment in the time range of 0.328-0.4 ms helps to reduce the frequency error to 0.69% in Simulation C with an increment of 0.075 mm/0.001 ms, which is half of the error in Simulation A (constant radius in 0.328-0.4 ms). The verification confirms the feasibility of the trimming algorithm for synchrocyclotron frequency modulation.

Detection of frequency-mode-shift during thermoacoustic combustion oscillations in a staged aircraft engine model combustor

NASA Astrophysics Data System (ADS)

Kobayashi, Hiroaki; Gotoda, Hiroshi; Tachibana, Shigeru; Yoshida, Seiji

2017-12-01

We conduct an experimental study using time series analysis based on symbolic dynamics to detect a precursor of frequency-mode-shift during thermoacoustic combustion oscillations in a staged aircraft engine model combustor. With increasing amount of the main fuel, a significant shift in the dominant frequency-mode occurs in noisy periodic dynamics, leading to a notable increase in oscillation amplitudes. The sustainment of noisy periodic dynamics during thermoacoustic combustion oscillations is clearly shown by the multiscale complexity-entropy causality plane in terms of statistical complexity. A modified version of the permutation entropy allows us to detect a precursor of the frequency-mode-shift before the amplification of pressure fluctuations.

Active vibration control for piezoelectricity cantilever beam: an adaptive feedforward control method

NASA Astrophysics Data System (ADS)

Zhu, Qiao; Yue, Jun-Zhou; Liu, Wei-Qun; Wang, Xu-Dong; Chen, Jun; Hu, Guang-Di

2017-04-01

This work is focused on the active vibration control of piezoelectric cantilever beam, where an adaptive feedforward controller (AFC) is utilized to reject the vibration with unknown multiple frequencies. First, the experiment setup and its mathematical model are introduced. Due to that the channel between the disturbance and the vibration output is unknown in practice, a concept of equivalent input disturbance (EID) is employed to put an equivalent disturbance into the input channel. In this situation, the vibration control can be achieved by setting the control input be the identified EID. Then, for the EID with known multiple frequencies, the AFC is introduced to perfectly reject the vibration but is sensitive to the frequencies. In order to accurately identify the unknown frequencies of EID in presence of the random disturbances and un-modeled nonlinear dynamics, the time-frequency-analysis (TFA) method is employed to precisely identify the unknown frequencies. Consequently, a TFA-based AFC algorithm is proposed to the active vibration control with unknown frequencies. Finally, four cases are given to illustrate the efficiency of the proposed TFA-based AFC algorithm by experiment.

Demodulation Algorithms for the Ofdm Signals in the Time- and Frequency-Scattering Channels

NASA Astrophysics Data System (ADS)

Bochkov, G. N.; Gorokhov, K. V.; Kolobkov, A. V.

2016-06-01

We consider a method based on the generalized maximum-likelihood rule for solving the problem of reception of the signals with orthogonal frequency division multiplexing of their harmonic components (OFDM signals) in the time- and frequency-scattering channels. The coherent and incoherent demodulators effectively using the time scattering due to the fast fading of the signal are developed. Using computer simulation, we performed comparative analysis of the proposed algorithms and well-known signal-reception algorithms with equalizers. The proposed symbolby-symbol detector with decision feedback and restriction of the number of searched variants is shown to have the best bit-error-rate performance. It is shown that under conditions of the limited accuracy of estimating the communication-channel parameters, the incoherent OFDMsignal detectors with differential phase-shift keying can ensure a better bit-error-rate performance compared with the coherent OFDM-signal detectors with absolute phase-shift keying.

Model-based spectral estimation of Doppler signals using parallel genetic algorithms.

PubMed

Solano González, J; Rodríguez Vázquez, K; García Nocetti, D F

2000-05-01

Conventional spectral analysis methods use a fast Fourier transform (FFT) on consecutive or overlapping windowed data segments. For Doppler ultrasound signals, this approach suffers from an inadequate frequency resolution due to the time segment duration and the non-stationarity characteristics of the signals. Parametric or model-based estimators can give significant improvements in the time-frequency resolution at the expense of a higher computational complexity. This work describes an approach which implements in real-time a parametric spectral estimator method using genetic algorithms (GAs) in order to find the optimum set of parameters for the adaptive filter that minimises the error function. The aim is to reduce the computational complexity of the conventional algorithm by using the simplicity associated to GAs and exploiting its parallel characteristics. This will allow the implementation of higher order filters, increasing the spectrum resolution, and opening a greater scope for using more complex methods.

Real-Time Processing Library for Open-Source Hardware Biomedical Sensors

PubMed Central

Castro-García, Juan A.; Lebrato-Vázquez, Clara

2018-01-01

Applications involving data acquisition from sensors need samples at a preset frequency rate, the filtering out of noise and/or analysis of certain frequency components. We propose a novel software architecture based on open-software hardware platforms which allows programmers to create data streams from input channels and easily implement filters and frequency analysis objects. The performances of the different classes given in the size of memory allocated and execution time (number of clock cycles) were analyzed in the low-cost platform Arduino Genuino. In addition, 11 people took part in an experiment in which they had to implement several exercises and complete a usability test. Sampling rates under 250 Hz (typical for many biomedical applications) makes it feasible to implement filters, sliding windows and Fourier analysis, operating in real time. Participants rated software usability at 70.2 out of 100 and the ease of use when implementing several signal processing applications was rated at just over 4.4 out of 5. Participants showed their intention of using this software because it was percieved as useful and very easy to use. The performances of the library showed that it may be appropriate for implementing small biomedical real-time applications or for human movement monitoring, even in a simple open-source hardware device like Arduino Genuino. The general perception about this library is that it is easy to use and intuitive. PMID:29596394

Real-Time Processing Library for Open-Source Hardware Biomedical Sensors.

PubMed

Molina-Cantero, Alberto J; Castro-García, Juan A; Lebrato-Vázquez, Clara; Gómez-González, Isabel M; Merino-Monge, Manuel

2018-03-29

Applications involving data acquisition from sensors need samples at a preset frequency rate, the filtering out of noise and/or analysis of certain frequency components. We propose a novel software architecture based on open-software hardware platforms which allows programmers to create data streams from input channels and easily implement filters and frequency analysis objects. The performances of the different classes given in the size of memory allocated and execution time (number of clock cycles) were analyzed in the low-cost platform Arduino Genuino. In addition, 11 people took part in an experiment in which they had to implement several exercises and complete a usability test. Sampling rates under 250 Hz (typical for many biomedical applications) makes it feasible to implement filters, sliding windows and Fourier analysis, operating in real time. Participants rated software usability at 70.2 out of 100 and the ease of use when implementing several signal processing applications was rated at just over 4.4 out of 5. Participants showed their intention of using this software because it was percieved as useful and very easy to use. The performances of the library showed that it may be appropriate for implementing small biomedical real-time applications or for human movement monitoring, even in a simple open-source hardware device like Arduino Genuino. The general perception about this library is that it is easy to use and intuitive.

Just Google It: An Approach on Word Frequencies Based on Online Search Result.

PubMed

Moret-Tatay, Carmen; Gamermann, Daniel; Murphy, Michael; Kuzmičová, Anezka

2018-01-01

Word frequency is one of the most robust factors in the literature on word processing, based on the lexical corpus of a language. However, different sources might be used in order to determine the actual frequency of each word. Recent research has determined frequencies based on movie subtitles, Twitter, blog posts, or newspapers. In this paper, we examine a determination of these frequencies based on the World Wide Web. For this purpose, a Python script was developed to obtain frequencies of a word through online search results. These frequencies were employed to estimate lexical decision times in comparison to the traditional frequencies in a lexical decision task. It was found that the Google frequencies predict reaction times comparably to the traditional frequencies. Still, the explained variance was higher for the traditional database.

The Wigner-Ville Transform, An Approach to Interpret GPR Data: Outlining a Rik Zone

NASA Astrophysics Data System (ADS)

Chavez, R. E.; Samano, M. A.; Camara, M. E.; Tejero, A.; Flores-Marquez, L. E.; Arango, C.; Velazco, V.

2006-12-01

In this investigation, a time-frequency analysis is performed, based in the decomposition of the GPR signal in high- and low-frequencies. This process is combined with a statistical approach to detect signal changes in time and position simultaneously. The spectral analysis is carried out through the Wigner-Ville distribution (WVD). A cross-correlation can be computed between the original signal and the time-frequency components to obtain structural anomalies in the GPR observations, and to perform a correlation with the available geology. An example of this methodology is presented, where a series of traces where analyzed from a GPR profile surveyed in an eastern area of Mexico City. This is a heavily urbanized region built on the bottom of an ancient lake. The sediments are poorly consolidated and the extraction water rate has increased the areas of subsidence. Nowadays, most of family homes and public buildings, mainly schools have started to suffer heavy damages. The geophysical study carried out in the area permitted to detect areas of high risk. The data analysis combined with previous geological studies, which included stratigraphic columns allowed to identify the geophysical characteristics of the area, which will allow to the authorities to plan the future development of the area.

On the relation between the peak frequency and the corresponding rise time of solar microwave impulsive bursts and the height dependence of magnetic fields

NASA Astrophysics Data System (ADS)

Zhao, Ren-Yang; Magun, Andreas; Schanda, Erwin

1990-12-01

Results are reported from a correlation analysis for 57 microwave impulsive bursts observed at six frequencies. A regression line between the peak frequency and the corresponding rise time of microwave impulsive bursts is obtained, with a correlation coefficient of -0.43. This can be explained in the frame of a thermal model. The magnetic field decrease with height has to be much slower than in a dipole field in order to explain the weak dependence of f(p) on t(r). This decrease of magnetic field with height in burst sources is based on the relationship between f(p) and t(r) found by assuming a thermal flare model with a collisionless conduction front.

Detailed Vibration Analysis of Pinion Gear with Time-Frequency Methods

NASA Technical Reports Server (NTRS)

Mosher, Marianne; Pryor, Anna H.; Lewicki, David G.

2003-01-01

In this paper, the authors show a detailed analysis of the vibration signal from the destructive testing of a spiral bevel gear and pinion pair containing seeded faults. The vibration signal is analyzed in the time domain, frequency domain and with four time-frequency transforms: the Short Time Frequency Transform (STFT), the Wigner-Ville Distribution with the Choi-Williams kernel (WV-CW), the Continuous Wavelet' Transform (CWT) and the Discrete Wavelet Transform (DWT). Vibration data of bevel gear tooth fatigue cracks, under a variety of operating load levels and damage conditions, are analyzed using these methods. A new metric for automatic anomaly detection is developed and can be produced from any systematic numerical representation of the vibration signals. This new metric reveals indications of gear damage with all of the time-frequency transforms, as well as time and frequency representations, on this data set. Analysis with the CWT detects changes in the signal at low torque levels not found with the other transforms. The WV-CW and CWT use considerably more resources than the STFT and the DWT. More testing of the new metric is needed to determine its value for automatic anomaly detection and to develop fault detection methods for the metric.

PLATSIM: An efficient linear simulation and analysis package for large-order flexible systems

NASA Technical Reports Server (NTRS)

Maghami, Periman; Kenny, Sean P.; Giesy, Daniel P.

1995-01-01

PLATSIM is a software package designed to provide efficient time and frequency domain analysis of large-order generic space platforms implemented with any linear time-invariant control system. Time domain analysis provides simulations of the overall spacecraft response levels due to either onboard or external disturbances. The time domain results can then be processed by the jitter analysis module to assess the spacecraft's pointing performance in a computationally efficient manner. The resulting jitter analysis algorithms have produced an increase in speed of several orders of magnitude over the brute force approach of sweeping minima and maxima. Frequency domain analysis produces frequency response functions for uncontrolled and controlled platform configurations. The latter represents an enabling technology for large-order flexible systems. PLATSIM uses a sparse matrix formulation for the spacecraft dynamics model which makes both the time and frequency domain operations quite efficient, particularly when a large number of modes are required to capture the true dynamics of the spacecraft. The package is written in MATLAB script language. A graphical user interface (GUI) is included in the PLATSIM software package. This GUI uses MATLAB's Handle graphics to provide a convenient way for setting simulation and analysis parameters.

Use of the Morlet mother wavelet in the frequency-scale domain decomposition technique for the modal identification of ambient vibration responses

NASA Astrophysics Data System (ADS)

Le, Thien-Phu

2017-10-01

The frequency-scale domain decomposition technique has recently been proposed for operational modal analysis. The technique is based on the Cauchy mother wavelet. In this paper, the approach is extended to the Morlet mother wavelet, which is very popular in signal processing due to its superior time-frequency localization. Based on the regressive form and an appropriate norm of the Morlet mother wavelet, the continuous wavelet transform of the power spectral density of ambient responses enables modes in the frequency-scale domain to be highlighted. Analytical developments first demonstrate the link between modal parameters and the local maxima of the continuous wavelet transform modulus. The link formula is then used as the foundation of the proposed modal identification method. Its practical procedure, combined with the singular value decomposition algorithm, is presented step by step. The proposition is finally verified using numerical examples and a laboratory test.

Dynamic Granger causality based on Kalman filter for evaluation of functional network connectivity in fMRI data

PubMed Central

Havlicek, Martin; Jan, Jiri; Brazdil, Milan; Calhoun, Vince D.

2015-01-01

Increasing interest in understanding dynamic interactions of brain neural networks leads to formulation of sophisticated connectivity analysis methods. Recent studies have applied Granger causality based on standard multivariate autoregressive (MAR) modeling to assess the brain connectivity. Nevertheless, one important flaw of this commonly proposed method is that it requires the analyzed time series to be stationary, whereas such assumption is mostly violated due to the weakly nonstationary nature of functional magnetic resonance imaging (fMRI) time series. Therefore, we propose an approach to dynamic Granger causality in the frequency domain for evaluating functional network connectivity in fMRI data. The effectiveness and robustness of the dynamic approach was significantly improved by combining a forward and backward Kalman filter that improved estimates compared to the standard time-invariant MAR modeling. In our method, the functional networks were first detected by independent component analysis (ICA), a computational method for separating a multivariate signal into maximally independent components. Then the measure of Granger causality was evaluated using generalized partial directed coherence that is suitable for bivariate as well as multivariate data. Moreover, this metric provides identification of causal relation in frequency domain, which allows one to distinguish the frequency components related to the experimental paradigm. The procedure of evaluating Granger causality via dynamic MAR was demonstrated on simulated time series as well as on two sets of group fMRI data collected during an auditory sensorimotor (SM) or auditory oddball discrimination (AOD) tasks. Finally, a comparison with the results obtained from a standard time-invariant MAR model was provided. PMID:20561919

Acquisition and Analysis of Dynamic Responses of a Historic Pedestrian Bridge using Video Image Processing

NASA Astrophysics Data System (ADS)

O'Byrne, Michael; Ghosh, Bidisha; Schoefs, Franck; O'Donnell, Deirdre; Wright, Robert; Pakrashi, Vikram

2015-07-01

Video based tracking is capable of analysing bridge vibrations that are characterised by large amplitudes and low frequencies. This paper presents the use of video images and associated image processing techniques to obtain the dynamic response of a pedestrian suspension bridge in Cork, Ireland. This historic structure is one of the four suspension bridges in Ireland and is notable for its dynamic nature. A video camera is mounted on the river-bank and the dynamic responses of the bridge have been measured from the video images. The dynamic response is assessed without the need of a reflector on the bridge and in the presence of various forms of luminous complexities in the video image scenes. Vertical deformations of the bridge were measured in this regard. The video image tracking for the measurement of dynamic responses of the bridge were based on correlating patches in time-lagged scenes in video images and utilisinga zero mean normalisedcross correlation (ZNCC) metric. The bridge was excited by designed pedestrian movement and by individual cyclists traversing the bridge. The time series data of dynamic displacement responses of the bridge were analysedto obtain the frequency domain response. Frequencies obtained from video analysis were checked against accelerometer data from the bridge obtained while carrying out the same set of experiments used for video image based recognition.

Acquisition and Analysis of Dynamic Responses of a Historic Pedestrian Bridge using Video Image Processing

NASA Astrophysics Data System (ADS)

O'Byrne, Michael; Ghosh, Bidisha; Schoefs, Franck; O'Donnell, Deirdre; Wright, Robert; Pakrashi, Vikram

2015-07-01

Video based tracking is capable of analysing bridge vibrations that are characterised by large amplitudes and low frequencies. This paper presents the use of video images and associated image processing techniques to obtain the dynamic response of a pedestrian suspension bridge in Cork, Ireland. This historic structure is one of the four suspension bridges in Ireland and is notable for its dynamic nature. A video camera is mounted on the river-bank and the dynamic responses of the bridge have been measured from the video images. The dynamic response is assessed without the need of a reflector on the bridge and in the presence of various forms of luminous complexities in the video image scenes. Vertical deformations of the bridge were measured in this regard. The video image tracking for the measurement of dynamic responses of the bridge were based on correlating patches in time-lagged scenes in video images and utilisinga zero mean normalised cross correlation (ZNCC) metric. The bridge was excited by designed pedestrian movement and by individual cyclists traversing the bridge. The time series data of dynamic displacement responses of the bridge were analysedto obtain the frequency domain response. Frequencies obtained from video analysis were checked against accelerometer data from the bridge obtained while carrying out the same set of experiments used for video image based recognition.

Impacts of Non-Stationarity in Climate on Flood Intensity-Duration-Frequency: Case Studies in Mountainous Areas with Snowmelt

NASA Astrophysics Data System (ADS)

Hou, Z.; Ren, H.; Sun, N.; Leung, L. R.; Liu, Y.; Coleman, A. M.; Skaggs, R.; Wigmosta, M. S.

2017-12-01

Hydrologic engineering design usually involves intensity-duration-frequency (IDF) analysis for calculating runoff from a design storm of specified precipitation frequency and duration using event-based hydrologic rainfall-runoff models. Traditionally, the procedure assumes climate stationarity and neglects snowmelt-driven runoff contribution to floods. In this study, we used high resolution climate simulations to provide inputs to the physics-based Distributed Hydrology Soil and Vegetation Model (DHSVM) to determine the spatially distributed precipitation and snowmelt available for runoff. Climate model outputs were extracted around different mountainous field sites in Colorado and California. IDF curves were generated at each numerical grid of DHSVM based on the simulated precipitation, temperature, and available water for runoff. Quantitative evaluation of trending and stationarity tests were conducted to identify (quasi-)stationary time periods for reliable IDF analysis. The impact of stationarity was evaluated by comparing the derived IDF attributes with respect to time windows of different length and level of stationarity. Spatial mapping of event return-period was performed for various design storms, and spatial mapping of event intensity was performed for given duration and return periods. IDF characteristics were systematically compared (historical vs RCP4.5 vs RCP8.5) using annual maximum series vs partial duration series data with the goal of providing reliable IDF analyses to support hydrologic engineering design.

Frequency Preference Response to Oscillatory Inputs in Two-dimensional Neural Models: A Geometric Approach to Subthreshold Amplitude and Phase Resonance.

PubMed

Rotstein, Horacio G

2014-01-01

We investigate the dynamic mechanisms of generation of subthreshold and phase resonance in two-dimensional linear and linearized biophysical (conductance-based) models, and we extend our analysis to account for the effect of simple, but not necessarily weak, types of nonlinearities. Subthreshold resonance refers to the ability of neurons to exhibit a peak in their voltage amplitude response to oscillatory input currents at a preferred non-zero (resonant) frequency. Phase-resonance refers to the ability of neurons to exhibit a zero-phase (or zero-phase-shift) response to oscillatory input currents at a non-zero (phase-resonant) frequency. We adapt the classical phase-plane analysis approach to account for the dynamic effects of oscillatory inputs and develop a tool, the envelope-plane diagrams, that captures the role that conductances and time scales play in amplifying the voltage response at the resonant frequency band as compared to smaller and larger frequencies. We use envelope-plane diagrams in our analysis. We explain why the resonance phenomena do not necessarily arise from the presence of imaginary eigenvalues at rest, but rather they emerge from the interplay of the intrinsic and input time scales. We further explain why an increase in the time-scale separation causes an amplification of the voltage response in addition to shifting the resonant and phase-resonant frequencies. This is of fundamental importance for neural models since neurons typically exhibit a strong separation of time scales. We extend this approach to explain the effects of nonlinearities on both resonance and phase-resonance. We demonstrate that nonlinearities in the voltage equation cause amplifications of the voltage response and shifts in the resonant and phase-resonant frequencies that are not predicted by the corresponding linearized model. The differences between the nonlinear response and the linear prediction increase with increasing levels of the time scale separation between the voltage and the gating variable, and they almost disappear when both equations evolve at comparable rates. In contrast, voltage responses are almost insensitive to nonlinearities located in the gating variable equation. The method we develop provides a framework for the investigation of the preferred frequency responses in three-dimensional and nonlinear neuronal models as well as simple models of coupled neurons.

Empirical mode decomposition apparatus, method and article of manufacture for analyzing biological signals and performing curve fitting

NASA Technical Reports Server (NTRS)

Huang, Norden E. (Inventor)

2004-01-01

A computer implemented physical signal analysis method includes four basic steps and the associated presentation techniques of the results. The first step is a computer implemented Empirical Mode Decomposition that extracts a collection of Intrinsic Mode Functions (IMF) from nonlinear, nonstationary physical signals. The decomposition is based on the direct extraction of the energy associated with various intrinsic time scales in the physical signal. Expressed in the IMF's, they have well-behaved Hilbert Transforms from which instantaneous frequencies can be calculated. The second step is the Hilbert Transform which produces a Hilbert Spectrum. Thus, the invention can localize any event on the time as well as the frequency axis. The decomposition can also be viewed as an expansion of the data in terms of the IMF's. Then, these IMF's, based on and derived from the data, can serve as the basis of that expansion. The local energy and the instantaneous frequency derived from the IMF's through the Hilbert transform give a full energy-frequency-time distribution of the data which is designated as the Hilbert Spectrum. The third step filters the physical signal by combining a subset of the IMFs. In the fourth step, a curve may be fitted to the filtered signal which may not have been possible with the original, unfiltered signal.

Empirical mode decomposition apparatus, method and article of manufacture for analyzing biological signals and performing curve fitting

NASA Technical Reports Server (NTRS)

Huang, Norden E. (Inventor)

2002-01-01

A computer implemented physical signal analysis method includes four basic steps and the associated presentation techniques of the results. The first step is a computer implemented Empirical Mode Decomposition that extracts a collection of Intrinsic Mode Functions (IMF) from nonlinear, nonstationary physical signals. The decomposition is based on the direct extraction of the energy associated with various intrinsic time scales in the physical signal. Expressed in the IMF's, they have well-behaved Hilbert Transforms from which instantaneous frequencies can be calculated. The second step is the Hilbert Transform which produces a Hilbert Spectrum. Thus, the invention can localize any event on the time as well as the frequency axis. The decomposition can also be viewed as an expansion of the data in terms of the IMF's. Then, these IMF's, based on and derived from the data, can serve as the basis of that expansion. The local energy and the instantaneous frequency derived from the IMF's through the Hilbert transform give a full energy-frequency-time distribution of the data which is designated as the Hilbert Spectrum. The third step filters the physical signal by combining a subset of the IMFs. In the fourth step, a curve may be fitted to the filtered signal which may not have been possible with the original, unfiltered signal.

Time Delay Analysis of Turbofan Engine Direct and Indirect Combustion Noise Sources

NASA Technical Reports Server (NTRS)

Miles, Jeffrey Hilton

2008-01-01

The core noise components of a dual spool turbofan engine were separated by the use of a coherence function. A source location technique based on adjusting the time delay between the combustor pressure sensor signal and the far-field microphone signal to maximize the coherence and remove as much variation of the phase angle with frequency as possible was used. The discovery was made that for the 130o microphone a 90.027 ms time shift worked best for the frequency band from 0 to 200 Hz while a 86.975 ms time shift worked best for the frequency band from 200 to 400 Hz. Hence, the 0 to 200 Hz band signal took more time than the 200 to 400 Hz band signal to travel the same distance. This suggests the 0 to 200 Hz coherent cross spectral density band is partly due to indirect combustion noise attributed to entropy fluctuations, which travel at the flow velocity, interacting with the turbine. The signal in the 200 to 400 Hz frequency band is attributed mostly to direct combustion noise. Results are presented herein for engine power settings of 48, 54, and 60 percent of the maximum power setting

Time-frequency analysis based on ensemble local mean decomposition and fast kurtogram for rotating machinery fault diagnosis

NASA Astrophysics Data System (ADS)

Wang, Lei; Liu, Zhiwen; Miao, Qiang; Zhang, Xin

2018-03-01

A time-frequency analysis method based on ensemble local mean decomposition (ELMD) and fast kurtogram (FK) is proposed for rotating machinery fault diagnosis. Local mean decomposition (LMD), as an adaptive non-stationary and nonlinear signal processing method, provides the capability to decompose multicomponent modulation signal into a series of demodulated mono-components. However, the occurring mode mixing is a serious drawback. To alleviate this, ELMD based on noise-assisted method was developed. Still, the existing environmental noise in the raw signal remains in corresponding PF with the component of interest. FK has good performance in impulse detection while strong environmental noise exists. But it is susceptible to non-Gaussian noise. The proposed method combines the merits of ELMD and FK to detect the fault for rotating machinery. Primarily, by applying ELMD the raw signal is decomposed into a set of product functions (PFs). Then, the PF which mostly characterizes fault information is selected according to kurtosis index. Finally, the selected PF signal is further filtered by an optimal band-pass filter based on FK to extract impulse signal. Fault identification can be deduced by the appearance of fault characteristic frequencies in the squared envelope spectrum of the filtered signal. The advantages of ELMD over LMD and EEMD are illustrated in the simulation analyses. Furthermore, the efficiency of the proposed method in fault diagnosis for rotating machinery is demonstrated on gearbox case and rolling bearing case analyses.

Three-dimensional dominant frequency mapping using autoregressive spectral analysis of atrial electrograms of patients in persistent atrial fibrillation.

PubMed

Salinet, João L; Masca, Nicholas; Stafford, Peter J; Ng, G André; Schlindwein, Fernando S

2016-03-08

Areas with high frequency activity within the atrium are thought to be 'drivers' of the rhythm in patients with atrial fibrillation (AF) and ablation of these areas seems to be an effective therapy in eliminating DF gradient and restoring sinus rhythm. Clinical groups have applied the traditional FFT-based approach to generate the three-dimensional dominant frequency (3D DF) maps during electrophysiology (EP) procedures but literature is restricted on using alternative spectral estimation techniques that can have a better frequency resolution that FFT-based spectral estimation. Autoregressive (AR) model-based spectral estimation techniques, with emphasis on selection of appropriate sampling rate and AR model order, were implemented to generate high-density 3D DF maps of atrial electrograms (AEGs) in persistent atrial fibrillation (persAF). For each patient, 2048 simultaneous AEGs were recorded for 20.478 s-long segments in the left atrium (LA) and exported for analysis, together with their anatomical locations. After the DFs were identified using AR-based spectral estimation, they were colour coded to produce sequential 3D DF maps. These maps were systematically compared with maps found using the Fourier-based approach. 3D DF maps can be obtained using AR-based spectral estimation after AEGs downsampling (DS) and the resulting maps are very similar to those obtained using FFT-based spectral estimation (mean 90.23 %). There were no significant differences between AR techniques (p = 0.62). The processing time for AR-based approach was considerably shorter (from 5.44 to 5.05 s) when lower sampling frequencies and model order values were used. Higher levels of DS presented higher rates of DF agreement (sampling frequency of 37.5 Hz). We have demonstrated the feasibility of using AR spectral estimation methods for producing 3D DF maps and characterised their differences to the maps produced using the FFT technique, offering an alternative approach for 3D DF computation in human persAF studies.

Analysis of Accelerometer Data from a Woven Inflatable Creep Burst Test

NASA Technical Reports Server (NTRS)

James, George H.; Grygier, Michael; Selig, Molly M.

2015-01-01

Accelerometers were used to montor an inflatable test article during a creep test to failure. The test article experienced impulse events that were classified based on the response of the sensors and their time-dependent manifestation. These impulse events required specialized techniques to process the structural dynamics data. However, certain phenomena were defined as worthy of additional study. An assessment of one phenomena (a frequency near 1000Hz) showed a time dependent frequency and an amplitude that increased significantly near the end of the test. Hence, these observations are expected to drive future understanding of and utility in inflatable space structures.

Biosensor method and system based on feature vector extraction

DOEpatents

Greenbaum, Elias; Rodriguez, Jr., Miguel; Qi, Hairong; Wang, Xiaoling

2013-07-02

A system for biosensor-based detection of toxins includes providing at least one time-dependent control signal generated by a biosensor in a gas or liquid medium, and obtaining a time-dependent biosensor signal from the biosensor in the gas or liquid medium to be monitored or analyzed for the presence of one or more toxins selected from chemical, biological or radiological agents. The time-dependent biosensor signal is processed to obtain a plurality of feature vectors using at least one of amplitude statistics and a time-frequency analysis. At least one parameter relating to toxicity of the gas or liquid medium is then determined from the feature vectors based on reference to the control signal.

Real-Time Optical Image Processing Techniques

DTIC Science & Technology

1988-10-31

pursued through the analysis, design, and fabrication of pulse frequency modulated halftone screens and the modification of micro-chan- nel spatial...required for non-linear operation. Real-time nonlinear processing was performed using the halftone screen and MSLM. The experiments showed the effectiveness...pulse frequency modulation has been pursued through the analysis, design, and fabrication of pulse frequency modulated halftone screens and the

Sub-picosecond timing fluctuation suppression in laser-based atmospheric transfer of microwave signal using electronic phase compensation

NASA Astrophysics Data System (ADS)

Chen, Shijun; Sun, Fuyu; Bai, Qingsong; Chen, Dawei; Chen, Qiang; Hou, Dong

2017-10-01

We demonstrated a timing fluctuation suppression in outdoor laser-based atmospheric radio-frequency transfer over a 110 m one-way free-space link using an electronic phase compensation technique. Timing fluctuations and Allan Deviation are both measured to characterize the instability of transferred frequency incurred during the transfer process. With transferring a 1 GHz microwave signal over a timing fluctuation suppressed transmission link, the total root-mean-square (rms) timing fluctuation was measured to be 920 femtoseconds in 5000 s, with fractional frequency instability on the order of 1 × 10-12 at 1 s, and order of 2 × 10-16 at 1000 s. This atmospheric frequency transfer scheme with the timing fluctuation suppression technique can be used to fast build an atomic clock-based frequency free-space transmission link since its stability is superior to a commercial Cs and Rb clock.

Time-Frequency Cross Mutual Information Analysis of the Brain Functional Networks Underlying Multiclass Motor Imagery.

PubMed

Gong, Anmin; Liu, Jianping; Chen, Si; Fu, Yunfa

2018-01-01

To study the physiologic mechanism of the brain during different motor imagery (MI) tasks, the authors employed a method of brain-network modeling based on time-frequency cross mutual information obtained from 4-class (left hand, right hand, feet, and tongue) MI tasks recorded as brain-computer interface (BCI) electroencephalography data. The authors explored the brain network revealed by these MI tasks using statistical analysis and the analysis of topologic characteristics, and observed significant differences in the reaction level, reaction time, and activated target during 4-class MI tasks. There was a great difference in the reaction level between the execution and resting states during different tasks: the reaction level of the left-hand MI task was the greatest, followed by that of the right-hand, feet, and tongue MI tasks. The reaction time required to perform the tasks also differed: during the left-hand and right-hand MI tasks, the brain networks of subjects reacted promptly and strongly, but there was a delay during the feet and tongue MI task. Statistical analysis and the analysis of network topology revealed the target regions of the brain network during different MI processes. In conclusion, our findings suggest a new way to explain the neural mechanism behind MI.

Computer-aided mathematical analysis of probability of intercept for ground-based communication intercept system

NASA Astrophysics Data System (ADS)

Park, Sang Chul

1989-09-01

We develop a mathematical analysis model to calculate the probability of intercept (POI) for the ground-based communication intercept (COMINT) system. The POI is a measure of the effectiveness of the intercept system. We define the POI as the product of the probability of detection and the probability of coincidence. The probability of detection is a measure of the receiver's capability to detect a signal in the presence of noise. The probability of coincidence is the probability that an intercept system is available, actively listening in the proper frequency band, in the right direction and at the same time that the signal is received. We investigate the behavior of the POI with respect to the observation time, the separation distance, antenna elevations, the frequency of the signal, and the receiver bandwidths. We observe that the coincidence characteristic between the receiver scanning parameters and the signal parameters is the key factor to determine the time to obtain a given POI. This model can be used to find the optimal parameter combination to maximize the POI in a given scenario. We expand this model to a multiple system. This analysis is conducted on a personal computer to provide the portability. The model is also flexible and can be easily implemented under different situations.

Blind identification of full-field vibration modes of output-only structures from uniformly-sampled, possibly temporally-aliased (sub-Nyquist), video measurements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Yongchao; Dorn, Charles; Mancini, Tyler

Enhancing the spatial and temporal resolution of vibration measurements and modal analysis could significantly benefit dynamic modelling, analysis, and health monitoring of structures. For example, spatially high-density mode shapes are critical for accurate vibration-based damage localization. In experimental or operational modal analysis, higher (frequency) modes, which may be outside the frequency range of the measurement, contain local structural features that can improve damage localization as well as the construction and updating of the modal-based dynamic model of the structure. In general, the resolution of vibration measurements can be increased by enhanced hardware. Traditional vibration measurement sensors such as accelerometers havemore » high-frequency sampling capacity; however, they are discrete point-wise sensors only providing sparse, low spatial sensing resolution measurements, while dense deployment to achieve high spatial resolution is expensive and results in the mass-loading effect and modification of structure's surface. Non-contact measurement methods such as scanning laser vibrometers provide high spatial and temporal resolution sensing capacity; however, they make measurements sequentially that requires considerable acquisition time. As an alternative non-contact method, digital video cameras are relatively low-cost, agile, and provide high spatial resolution, simultaneous, measurements. Combined with vision based algorithms (e.g., image correlation or template matching, optical flow, etc.), video camera based measurements have been successfully used for experimental and operational vibration measurement and subsequent modal analysis. However, the sampling frequency of most affordable digital cameras is limited to 30–60 Hz, while high-speed cameras for higher frequency vibration measurements are extremely costly. This work develops a computational algorithm capable of performing vibration measurement at a uniform sampling frequency lower than what is required by the Shannon-Nyquist sampling theorem for output-only modal analysis. In particular, the spatio-temporal uncoupling property of the modal expansion of structural vibration responses enables a direct modal decoupling of the temporally-aliased vibration measurements by existing output-only modal analysis methods, yielding (full-field) mode shapes estimation directly. Then the signal aliasing properties in modal analysis is exploited to estimate the modal frequencies and damping ratios. Furthermore, the proposed method is validated by laboratory experiments where output-only modal identification is conducted on temporally-aliased acceleration responses and particularly the temporally-aliased video measurements of bench-scale structures, including a three-story building structure and a cantilever beam.« less

Blind identification of full-field vibration modes of output-only structures from uniformly-sampled, possibly temporally-aliased (sub-Nyquist), video measurements

DOE PAGES

Yang, Yongchao; Dorn, Charles; Mancini, Tyler; ...

2016-12-05

Enhancing the spatial and temporal resolution of vibration measurements and modal analysis could significantly benefit dynamic modelling, analysis, and health monitoring of structures. For example, spatially high-density mode shapes are critical for accurate vibration-based damage localization. In experimental or operational modal analysis, higher (frequency) modes, which may be outside the frequency range of the measurement, contain local structural features that can improve damage localization as well as the construction and updating of the modal-based dynamic model of the structure. In general, the resolution of vibration measurements can be increased by enhanced hardware. Traditional vibration measurement sensors such as accelerometers havemore » high-frequency sampling capacity; however, they are discrete point-wise sensors only providing sparse, low spatial sensing resolution measurements, while dense deployment to achieve high spatial resolution is expensive and results in the mass-loading effect and modification of structure's surface. Non-contact measurement methods such as scanning laser vibrometers provide high spatial and temporal resolution sensing capacity; however, they make measurements sequentially that requires considerable acquisition time. As an alternative non-contact method, digital video cameras are relatively low-cost, agile, and provide high spatial resolution, simultaneous, measurements. Combined with vision based algorithms (e.g., image correlation or template matching, optical flow, etc.), video camera based measurements have been successfully used for experimental and operational vibration measurement and subsequent modal analysis. However, the sampling frequency of most affordable digital cameras is limited to 30–60 Hz, while high-speed cameras for higher frequency vibration measurements are extremely costly. This work develops a computational algorithm capable of performing vibration measurement at a uniform sampling frequency lower than what is required by the Shannon-Nyquist sampling theorem for output-only modal analysis. In particular, the spatio-temporal uncoupling property of the modal expansion of structural vibration responses enables a direct modal decoupling of the temporally-aliased vibration measurements by existing output-only modal analysis methods, yielding (full-field) mode shapes estimation directly. Then the signal aliasing properties in modal analysis is exploited to estimate the modal frequencies and damping ratios. Furthermore, the proposed method is validated by laboratory experiments where output-only modal identification is conducted on temporally-aliased acceleration responses and particularly the temporally-aliased video measurements of bench-scale structures, including a three-story building structure and a cantilever beam.« less

A New Approach in Time-Frequency Analysis with Applications to Experimental High Range Resolution Radar Data

DTIC Science & Technology

2003-11-01

Distributions In contrast to the linear time-frequency transforms such as the short-time Fourier transform, the Wigner - Ville distribution ( WVD ) is...23 9 Results of nine TFDs: (a) Wigner - Ville distribution , (b) Born-Jordan distribution , (c) Choi-Williams distribution , (d) bilinear TFD...are applied in the Wigner - Ville class of time-frequency transforms and the reassignment methods, which are applied to any time-frequency distribution

Variations of High-Latitude Geomagnetic Pulsation Frequencies: A Comparison of Time-of-Flight Estimates and IMAGE Magnetometer Observations

NASA Astrophysics Data System (ADS)

Sandhu, J. K.; Yeoman, T. K.; James, M. K.; Rae, I. J.; Fear, R. C.

2018-01-01

The fundamental eigenfrequencies of standing Alfvén waves on closed geomagnetic field lines are estimated for the region spanning 5.9≤L < 9.5 over all MLT (Magnetic Local Time). The T96 magnetic field model and a realistic empirical plasma mass density model are employed using the time-of-flight approximation, refining previous calculations that assumed a relatively simplistic mass density model. An assessment of the implications of using different mass density models in the time-of-flight calculations is presented. The calculated frequencies exhibit dependences on field line footprint magnetic latitude and MLT, which are attributed to both magnetic field configuration and spatial variations in mass density. In order to assess the validity of the time-of-flight calculated frequencies, the estimates are compared to observations of FLR (Field Line Resonance) frequencies. Using IMAGE (International Monitor for Auroral Geomagnetic Effects) ground magnetometer observations obtained between 2001 and 2012, an automated FLR identification method is developed, based on the cross-phase technique. The average FLR frequency is determined, including variations with footprint latitude and MLT, and compared to the time-of-flight analysis. The results show agreement in the latitudinal and local time dependences. Furthermore, with the use of the realistic mass density model in the time-of-flight calculations, closer agreement with the observed FLR frequencies is obtained. The study is limited by the latitudinal coverage of the IMAGE magnetometer array, and future work will aim to extend the ground magnetometer data used to include additional magnetometer arrays.

An analysis of first-time blood donors return behaviour using regression models.

PubMed

Kheiri, S; Alibeigi, Z

2015-08-01

Blood products have a vital role in saving many patients' lives. The aim of this study was to analyse blood donor return behaviour. Using a cross-sectional follow-up design of 5-year duration, 864 first-time donors who had donated blood were selected using a systematic sampling. The behaviours of donors via three response variables, return to donation, frequency of return to donation and the time interval between donations, were analysed based on logistic regression, negative binomial regression and Cox's shared frailty model for recurrent events respectively. Successful return to donation rated at 49·1% and the deferral rate was 13·3%. There was a significant reverse relationship between the frequency of return to donation and the time interval between donations. Sex, body weight and job had an effect on return to donation; weight and frequency of donation during the first year had a direct effect on the total frequency of donations. Age, weight and job had a significant effect on the time intervals between donations. Aging decreases the chances of return to donation and increases the time interval between donations. Body weight affects the three response variables, i.e. the higher the weight, the more the chances of return to donation and the shorter the time interval between donations. There is a positive correlation between the frequency of donations in the first year and the total number of return to donations. Also, the shorter the time interval between donations is, the higher the frequency of donations. © 2015 British Blood Transfusion Society.

Questionable sound exposure outside of the womb: frequency analysis of environmental noise in the neonatal intensive care unit.

PubMed

Lahav, Amir

2015-01-01

Recent research raises concerns about the adverse effects of noise exposure on the developing preterm infant. However, current guidelines for NICU noise remain focused on loudness levels, leaving the problem of exposure to potentially harmful sound frequencies largely overlooked. This study examined the frequency spectra present in a level-II NICU. Noise measurements were taken in two level-II open-bay nurseries. Measurements were taken over 5 days for a period of 24 h each. Spectral analysis was focused on comparing sound frequencies in the range of human speech during daytime (7 AM-7 PM) vs. night-time (7 PM-7 AM). On average, daytime noise levels (Leq = 60.05 dBA) were higher than night-time (Leq = 58.67 dBA). Spectral analysis of frequency bands (>50 dB) revealed that infants were exposed to frequencies <500 Hz 100% of the time and to frequencies >500 Hz 57% of the time. During daytime, infants were exposed to nearly 20% more sounds within the speech frequency range compared with night-time (p = 0.018). Measuring the frequency spectra of NICU sounds is necessary to attain a thorough understanding of both the noise levels and the type of sounds that preterm infants are exposed to throughout their hospital stay. The risk of high-frequency noise exposure in the preterm population is still unclear and warrants further investigation. © 2014 Foundation Acta Paediatrica. Published by John Wiley & Sons Ltd.

Time-frequency analysis of band-limited EEG with BMFLC and Kalman filter for BCI applications

PubMed Central

2013-01-01

Background Time-Frequency analysis of electroencephalogram (EEG) during different mental tasks received significant attention. As EEG is non-stationary, time-frequency analysis is essential to analyze brain states during different mental tasks. Further, the time-frequency information of EEG signal can be used as a feature for classification in brain-computer interface (BCI) applications. Methods To accurately model the EEG, band-limited multiple Fourier linear combiner (BMFLC), a linear combination of truncated multiple Fourier series models is employed. A state-space model for BMFLC in combination with Kalman filter/smoother is developed to obtain accurate adaptive estimation. By virtue of construction, BMFLC with Kalman filter/smoother provides accurate time-frequency decomposition of the bandlimited signal. Results The proposed method is computationally fast and is suitable for real-time BCI applications. To evaluate the proposed algorithm, a comparison with short-time Fourier transform (STFT) and continuous wavelet transform (CWT) for both synthesized and real EEG data is performed in this paper. The proposed method is applied to BCI Competition data IV for ERD detection in comparison with existing methods. Conclusions Results show that the proposed algorithm can provide optimal time-frequency resolution as compared to STFT and CWT. For ERD detection, BMFLC-KF outperforms STFT and BMFLC-KS in real-time applicability with low computational requirement. PMID:24274109

Spectrum analysis of radar life signal in the three kinds of theoretical models

NASA Astrophysics Data System (ADS)

Yang, X. F.; Ma, J. F.; Wang, D.

2017-02-01

In the single frequency continuous wave radar life detection system, based on the Doppler effect, the theory model of radar life signal is expressed by the real function, and there is a phenomenon that can't be confirmed by the experiment. When the phase generated by the distance between the measured object and the radar measuring head is л of integer times, the main frequency spectrum of life signal (respiration and heartbeat) is not existed in radar life signal. If this phase is л/2 of odd times, the main frequency spectrum of breath and heartbeat frequency is the strongest. In this paper, we use the Doppler effect as the basic theory, using three different mathematical expressions——real function, complex exponential function and Bessel's function expansion form. They are used to establish the theoretical model of radar life signal. Simulation analysis revealed that the Bessel expansion form theoretical model solve the problem of real function form. Compared with the theoretical model of the complex exponential function, the derived spectral line is greatly reduced in the theoretical model of Bessel expansion form, which is more consistent with the actual situation.

Josephson Radiation from Gapless Andreev Bound States in HgTe-Based Topological Junctions

NASA Astrophysics Data System (ADS)

Deacon, R. S.; Wiedenmann, J.; Bocquillon, E.; Domínguez, F.; Klapwijk, T. M.; Leubner, P.; Brüne, C.; Hankiewicz, E. M.; Tarucha, S.; Ishibashi, K.; Buhmann, H.; Molenkamp, L. W.

2017-04-01

Frequency analysis of the rf emission of oscillating Josephson supercurrent is a powerful passive way of probing properties of topological Josephson junctions. In particular, measurements of the Josephson emission enable the detection of topological gapless Andreev bound states that give rise to emission at half the Josephson frequency fJ rather than conventional emission at fJ. Here, we report direct measurement of rf emission spectra on Josephson junctions made of HgTe-based gate-tunable topological weak links. The emission spectra exhibit a clear signal at half the Josephson frequency fJ/2 . The linewidths of emission lines indicate a coherence time of 0.3-4 ns for the fJ/2 line, much shorter than for the fJ line (3-4 ns). These observations strongly point towards the presence of topological gapless Andreev bound states and pave the way for a future HgTe-based platform for topological quantum computation.

Computational Aeroacoustic Analysis of Slat Trailing-Edge Flow

NASA Technical Reports Server (NTRS)

Singer, Bart A.; Lockard, David P.; Brentner, Kenneth S.; Khorrami, Mehdi R.; Berkman, Mert E.; Choudhari, Meelan

2000-01-01

An acoustic analysis based on the Ffowcs Williams and Hawkings equation was performed for a high-lift system. As input, the acoustic analysis used un- steady flow data obtained from a highly resolved, time-dependent, Reynolds-averaged Navier-Stokes calculation. The analysis strongly suggests that vor- tex shedding from the trailing edge of the slat results in a high-amplitude, high-frequency acoustic signal, similar to that which was observed in a correspond- ing experimental study of the high-lift system.

Potentials evoked by chirp-modulated tones: a new technique to evaluate oscillatory activity in the auditory pathway.

PubMed

Artieda, J; Valencia, M; Alegre, M; Olaziregi, O; Urrestarazu, E; Iriarte, J

2004-03-01

Steady-state potentials are oscillatory responses generated by a rhythmic stimulation of a sensory pathway. The frequency of the response, which follows the frequency of stimulation, is maximal at a stimulus rate of 40 Hz for auditory stimuli. The exact cause of these maximal responses is not known, although some authors have suggested that they might be related to the 'working frequency' of the auditory cortex. Testing of the responses to different frequencies of stimulation may be lengthy if a single frequency is studied at a time. Our aim was to develop a fast technique to explore the oscillatory response to auditory stimuli, using a tone modulated in amplitude by a sinusoid whose frequency increases linearly in frequency ('chirp') from 1 to 120 Hz. Time-frequency transforms were used for the analysis of the evoked responses in 10 subjects. Also, we analyzed whether the peaks in these responses were due to increases of amplitude or to phase-locking phenomena, using single-sweep time-frequency transforms and inter-trial phase analysis. The pattern observed in the time-frequency transform of the chirp-evoked potential was very similar in all subjects: a diagonal band of energy was observed, corresponding to the frequency of modulation at each time instant. Two components were present in the band, one around 45 Hz (30-60 Hz) and a smaller one between 80 and 120 Hz. Inter-trial phase analysis showed that these components were mainly due to phase locking phenomena. A simultaneous testing of the amplitude-modulation-following oscillatory responses to auditory stimulation is feasible using a tone modulated in amplitude at increasing frequencies. The maximal energies found at stimulation frequencies around 40 Hz are probably due to increased phase-locking of the individual responses.

Pi2 detection using Empirical Mode Decomposition (EMD)

NASA Astrophysics Data System (ADS)

Mieth, Johannes Z. D.; Frühauff, Dennis; Glassmeier, Karl-Heinz

2017-04-01

Empirical Mode Decomposition has been used as an alternative method to wavelet transformation to identify onset times of Pi2 pulsations in data sets of the Scandinavian Magnetometer Array (SMA). Pi2 pulsations are magnetohydrodynamic waves occurring during magnetospheric substorms. Almost always Pi2 are observed at substorm onset in mid to low latitudes on Earth's nightside. They are fed by magnetic energy release caused by dipolarization processes. Their periods lie between 40 to 150 seconds. Usually, Pi2 are detected using wavelet transformation. Here, Empirical Mode Decomposition (EMD) is presented as an alternative approach to the traditional procedure. EMD is a young signal decomposition method designed for nonlinear and non-stationary time series. It provides an adaptive, data driven, and complete decomposition of time series into slow and fast oscillations. An optimized version using Monte-Carlo-type noise assistance is used here. By displaying the results in a time-frequency space a characteristic frequency modulation is observed. This frequency modulation can be correlated with the onset of Pi2 pulsations. A basic algorithm to find the onset is presented. Finally, the results are compared to classical wavelet-based analysis. The use of different SMA stations furthermore allows the spatial analysis of Pi2 onset times. EMD mostly finds application in the fields of engineering and medicine. This work demonstrates the applicability of this method to geomagnetic time series.

Is there a first night effect on sleep bruxism? A sleep laboratory study.

PubMed

Hasegawa, Yoko; Lavigne, Gilles; Rompré, Pierre; Kato, Takafumi; Urade, Masahiro; Huynh, Nelly

2013-11-15

Sleep bruxism (SB) is reported to vary in frequency over time. The aim of this study was to assess the first night effect on SB. A retrospective polysomnographic (PSG) analysis was performed of data from a sample of SB patients (12 females, 4 males; age range: 17-39 years) recorded in a sleep laboratory over 2 consecutive nights. Sleep parameters and jaw muscle activity variables (i.e., rhythmic masticatory muscle activity [RMMA]) for SB were quantified and compared between the 2 nights. Subjects were classified into groups according to severity of RMMA frequency, such as low frequency (2-4 episodes/h and/or < 25 bursts/h) and moderate-high frequency (≥ 4 episodes/h and ≥ 25 bursts/h). Overall, no first night effects were found for most sleep variables. However, total sleep time, sleep efficiency, and stage transitions showed significant time and group interactions (repeated measures ANOVAs, p ≤ 0.05). The RMMA episode index did not differ between the 2 nights, whereas the second night showed significantly higher burst index, bruxism time index, and mean burst duration (repeated measure ANOVAs, p ≤ 0.05). Five patients of 8 in the low frequency group were classified into the moderate-high frequency group on the second night, whereas only one patient in the moderate-high frequency group moved to the low frequency group. The results showed no overall first night effect on severity of RMMA frequency in young and healthy patients with SB. In clinical practice, one-night sleep recording may be sufficient for moderate-high frequency SB patients. However, low RMMA frequency in the first night could be confirmed by a second night based on the patient's medical and dental history.

Adaptive Sampling-Based Information Collection for Wireless Body Area Networks.

PubMed

Xu, Xiaobin; Zhao, Fang; Wang, Wendong; Tian, Hui

2016-08-31

To collect important health information, WBAN applications typically sense data at a high frequency. However, limited by the quality of wireless link, the uploading of sensed data has an upper frequency. To reduce upload frequency, most of the existing WBAN data collection approaches collect data with a tolerable error. These approaches can guarantee precision of the collected data, but they are not able to ensure that the upload frequency is within the upper frequency. Some traditional sampling based approaches can control upload frequency directly, however, they usually have a high loss of information. Since the core task of WBAN applications is to collect health information, this paper aims to collect optimized information under the limitation of upload frequency. The importance of sensed data is defined according to information theory for the first time. Information-aware adaptive sampling is proposed to collect uniformly distributed data. Then we propose Adaptive Sampling-based Information Collection (ASIC) which consists of two algorithms. An adaptive sampling probability algorithm is proposed to compute sampling probabilities of different sensed values. A multiple uniform sampling algorithm provides uniform samplings for values in different intervals. Experiments based on a real dataset show that the proposed approach has higher performance in terms of data coverage and information quantity. The parameter analysis shows the optimized parameter settings and the discussion shows the underlying reason of high performance in the proposed approach.

Adaptive Sampling-Based Information Collection for Wireless Body Area Networks

PubMed Central

Xu, Xiaobin; Zhao, Fang; Wang, Wendong; Tian, Hui

2016-01-01

To collect important health information, WBAN applications typically sense data at a high frequency. However, limited by the quality of wireless link, the uploading of sensed data has an upper frequency. To reduce upload frequency, most of the existing WBAN data collection approaches collect data with a tolerable error. These approaches can guarantee precision of the collected data, but they are not able to ensure that the upload frequency is within the upper frequency. Some traditional sampling based approaches can control upload frequency directly, however, they usually have a high loss of information. Since the core task of WBAN applications is to collect health information, this paper aims to collect optimized information under the limitation of upload frequency. The importance of sensed data is defined according to information theory for the first time. Information-aware adaptive sampling is proposed to collect uniformly distributed data. Then we propose Adaptive Sampling-based Information Collection (ASIC) which consists of two algorithms. An adaptive sampling probability algorithm is proposed to compute sampling probabilities of different sensed values. A multiple uniform sampling algorithm provides uniform samplings for values in different intervals. Experiments based on a real dataset show that the proposed approach has higher performance in terms of data coverage and information quantity. The parameter analysis shows the optimized parameter settings and the discussion shows the underlying reason of high performance in the proposed approach. PMID:27589758

Astronomical component estimation (ACE v.1) by time-variant sinusoidal modeling

NASA Astrophysics Data System (ADS)

Sinnesael, Matthias; Zivanovic, Miroslav; De Vleeschouwer, David; Claeys, Philippe; Schoukens, Johan

2016-09-01

Accurately deciphering periodic variations in paleoclimate proxy signals is essential for cyclostratigraphy. Classical spectral analysis often relies on methods based on (fast) Fourier transformation. This technique has no unique solution separating variations in amplitude and frequency. This characteristic can make it difficult to correctly interpret a proxy's power spectrum or to accurately evaluate simultaneous changes in amplitude and frequency in evolutionary analyses. This drawback is circumvented by using a polynomial approach to estimate instantaneous amplitude and frequency in orbital components. This approach was proven useful to characterize audio signals (music and speech), which are non-stationary in nature. Paleoclimate proxy signals and audio signals share similar dynamics; the only difference is the frequency relationship between the different components. A harmonic-frequency relationship exists in audio signals, whereas this relation is non-harmonic in paleoclimate signals. However, this difference is irrelevant for the problem of separating simultaneous changes in amplitude and frequency. Using an approach with overlapping analysis frames, the model (Astronomical Component Estimation, version 1: ACE v.1) captures time variations of an orbital component by modulating a stationary sinusoid centered at its mean frequency, with a single polynomial. Hence, the parameters that determine the model are the mean frequency of the orbital component and the polynomial coefficients. The first parameter depends on geologic interpretations, whereas the latter are estimated by means of linear least-squares. As output, the model provides the orbital component waveform, either in the depth or time domain. Uncertainty analyses of the model estimates are performed using Monte Carlo simulations. Furthermore, it allows for a unique decomposition of the signal into its instantaneous amplitude and frequency. Frequency modulation patterns reconstruct changes in accumulation rate, whereas amplitude modulation identifies eccentricity-modulated precession. The functioning of the time-variant sinusoidal model is illustrated and validated using a synthetic insolation signal. The new modeling approach is tested on two case studies: (1) a Pliocene-Pleistocene benthic δ18O record from Ocean Drilling Program (ODP) Site 846 and (2) a Danian magnetic susceptibility record from the Contessa Highway section, Gubbio, Italy.

Structural-change localization and monitoring through a perturbation-based inverse problem.

PubMed

Roux, Philippe; Guéguen, Philippe; Baillet, Laurent; Hamze, Alaa

2014-11-01

Structural-change detection and characterization, or structural-health monitoring, is generally based on modal analysis, for detection, localization, and quantification of changes in structure. Classical methods combine both variations in frequencies and mode shapes, which require accurate and spatially distributed measurements. In this study, the detection and localization of a local perturbation are assessed by analysis of frequency changes (in the fundamental mode and overtones) that are combined with a perturbation-based linear inverse method and a deconvolution process. This perturbation method is applied first to a bending beam with the change considered as a local perturbation of the Young's modulus, using a one-dimensional finite-element model for modal analysis. Localization is successful, even for extended and multiple changes. In a second step, the method is numerically tested under ambient-noise vibration from the beam support with local changes that are shifted step by step along the beam. The frequency values are revealed using the random decrement technique that is applied to the time-evolving vibrations recorded by one sensor at the free extremity of the beam. Finally, the inversion method is experimentally demonstrated at the laboratory scale with data recorded at the free end of a Plexiglas beam attached to a metallic support.

MOD-2 wind turbine farm stability study

NASA Technical Reports Server (NTRS)

Hinrichsen, E. N.

1980-01-01

The dynamics of single and multiple 2.5 ME, Boeing MOD-2 wind turbine generators (WTGs) connected to utility power systems were investigated. The analysis was based on digital simulation. Both time response and frequency response methods were used. The dynamics of this type of WTG are characterized by two torsional modes, a low frequency 'shaft' mode below 1 Hz and an 'electrical' mode at 3-5 Hz. High turbine inertia and low torsional stiffness between turbine and generator are inherent features. Turbine control is based on electrical power, not turbine speed as in conventional utility turbine generators. Multi-machine dynamics differ very little from single machine dynamics.

CHARACTERIZING INTERMITTENCY OF 4-Hz QUASI-PERIODIC OSCILLATION IN XTE J1550–564 USING HILBERT–HUANG TRANSFORM

DOE Office of Scientific and Technical Information (OSTI.GOV)

Su, Yi-Hao; Chou, Yi; Hu, Chin-Ping

We present time-frequency analysis results based on the Hilbert–Huang transform (HHT) for the evolution of a 4-Hz low-frequency quasi-periodic oscillation (LFQPO) around the black hole X-ray binary XTE J1550–564. The origin of LFQPOs is still debated. To understand the cause of the peak broadening, we utilized a recently developed time-frequency analysis, HHT, for tracking the evolution of the 4-Hz LFQPO from XTE J1550–564. By adaptively decomposing the ∼4-Hz oscillatory component from the light curve and acquiring its instantaneous frequency, the Hilbert spectrum illustrates that the LFQPO is composed of a series of intermittent oscillations appearing occasionally between 3 and 5more » Hz. We further characterized this intermittency by computing the confidence limits of the instantaneous amplitudes of the intermittent oscillations, and constructed both the distributions of the QPO’s high- and low-amplitude durations, which are the time intervals with and without significant ∼4-Hz oscillations, respectively. The mean high-amplitude duration is 1.45 s and 90% of the oscillation segments have lifetimes below 3.1 s. The mean low-amplitude duration is 0.42 s and 90% of these segments are shorter than 0.73 s. In addition, these intermittent oscillations exhibit a correlation between the oscillation’s rms amplitude and mean count rate. This correlation could be analogous to the linear rms-flux relation found in the 4-Hz LFQPO through Fourier analysis. We conclude that the LFQPO peak in the power spectrum is broadened owing to intermittent oscillations with varying frequencies, which could be explained by using the Lense–Thirring precession model.« less

Real time automatic detection of bearing fault in induction machine using kurtogram analysis.

PubMed

Tafinine, Farid; Mokrani, Karim

2012-11-01

A proposed signal processing technique for incipient real time bearing fault detection based on kurtogram analysis is presented in this paper. The kurtogram is a fourth-order spectral analysis tool introduced for detecting and characterizing non-stationarities in a signal. This technique starts from investigating the resonance signatures over selected frequency bands to extract the representative features. The traditional spectral analysis is not appropriate for non-stationary vibration signal and for real time diagnosis. The performance of the proposed technique is examined by a series of experimental tests corresponding to different bearing conditions. Test results show that this signal processing technique is an effective bearing fault automatic detection method and gives a good basis for an integrated induction machine condition monitor.

NOTE: Entropy-based automated classification of independent components separated from fMCG

NASA Astrophysics Data System (ADS)

Comani, S.; Srinivasan, V.; Alleva, G.; Romani, G. L.

2007-03-01

Fetal magnetocardiography (fMCG) is a noninvasive technique suitable for the prenatal diagnosis of the fetal heart function. Reliable fetal cardiac signals can be reconstructed from multi-channel fMCG recordings by means of independent component analysis (ICA). However, the identification of the separated components is usually accomplished by visual inspection. This paper discusses a novel automated system based on entropy estimators, namely approximate entropy (ApEn) and sample entropy (SampEn), for the classification of independent components (ICs). The system was validated on 40 fMCG datasets of normal fetuses with the gestational age ranging from 22 to 37 weeks. Both ApEn and SampEn were able to measure the stability and predictability of the physiological signals separated with ICA, and the entropy values of the three categories were significantly different at p <0.01. The system performances were compared with those of a method based on the analysis of the time and frequency content of the components. The outcomes of this study showed a superior performance of the entropy-based system, in particular for early gestation, with an overall ICs detection rate of 98.75% and 97.92% for ApEn and SampEn respectively, as against a value of 94.50% obtained with the time-frequency-based system.

Improved analysis of ground vibrations produced by man-made sources.

PubMed

Ainalis, Daniel; Ducarne, Loïc; Kaufmann, Olivier; Tshibangu, Jean-Pierre; Verlinden, Olivier; Kouroussis, Georges

2018-03-01

Man-made sources of ground vibration must be carefully monitored in urban areas in order to ensure that structural damage and discomfort to residents is prevented or minimised. The research presented in this paper provides a comparative evaluation of various methods used to analyse a series of tri-axial ground vibration measurements generated by rail, road, and explosive blasting. The first part of the study is focused on comparing various techniques to estimate the dominant frequency, including time-frequency analysis. The comparative evaluation of the various methods to estimate the dominant frequency revealed that, depending on the method used, there can be significant variation in the estimates obtained. A new and improved analysis approach using the continuous wavelet transform was also presented, using the time-frequency distribution to estimate the localised dominant frequency and peak particle velocity. The technique can be used to accurately identify the level and frequency content of a ground vibration signal as it varies with time, and identify the number of times the threshold limits of damage are exceeded. Copyright © 2017 Elsevier B.V. All rights reserved.

[Analysis of time domain and frequency domain heart rate variability in fighter pilot before and after upright tilt].

PubMed

Wang, L; Wu, L; Ji, G; Zhang, X; Chen, T; Wang, L

1998-12-01

Effects of upright tilt on mechanism of autonomic nervous regulation of cardiovascular system and characteristics of heart rate variability (HRV) were observed in sixty healthy male pilots. Relation between time domain and frequency domain indexes of short-time HRV (5 min) were analysed before and after upright tilt. The results showed that there are significant difference in short time HRV parameters before and after upright tilt. Significant relationship was formed between time domain and frequency domain indexes of HRV. It suggests that time domain and frequency domain HRV analysis is capable of revealing certain informations embedded in a short series of R-R intervals and can help to evaluate the status of autonomic regulation of cardiovascular function in pilots.

Frequency stability of on-orbit GPS Block-I and Block-II Navstar clocks

NASA Astrophysics Data System (ADS)

McCaskill, Thomas B.; Reid, Wilson G.; Buisson, James A.

On-orbit analysis of the Global Positioning System (GPS) Block-I and Block-II Navstar clocks has been performed by the Naval Research Laboratory using a multi-year database. The Navstar clock phase-offset measurements were computed from pseudorange measurements made by the five GPS monitor sites and from the U.S. Naval Observatory precise-time site using single or dual frequency GPS receivers. Orbital data was obtained from the Navstar broadcast ephemeris and from the best-fit, postprocessed orbital ephemerides supplied by the Naval Surface Weapons Center or by the Defense Mapping Agency. Clock performance in the time domain is characterized using frequency-stability profiles with sample times that vary from 1 to 100 days. Composite plots of Navstar frequency stability and time-prediction uncertainty are included as a summary of clock analysis results. The analysis includes plots of the clock phase offset and frequency offset histories with the eclipse seasons superimposed on selected plots to demonstrate the temperature sensitivity of one of the Block-I Navstar rubidium clocks. The potential impact on navigation and on transferring precise time of the degradation in the long-term frequency stability of the rubidium clocks is discussed.

High-frequency envelope inversion analysis of the 2003 Tokachi-Oki, JAPAN, earthquake (Mw8.0)

NASA Astrophysics Data System (ADS)

Nakahara, H.

2004-12-01

The 2003 Tokachi-Oki earthquake (Mw 8.0) took place on September 26, 2003 at the plate interface between the subducting Pacific plate and the Hokkaido island, northern Japan. The focal depth is around 30km and the focal mechanism is thrust type. This earthquake caused 2 missings, more than 100 injures, 2000 collapsed houses, and so on. Slip distribution on the fault plane was already estimated by inversion analyses of low-frequency seismograms. However, source characteristics for the earthquake in frequencies higher than 1 Hz is not so far clarified. In this study, we execute an envelope inversion analysis based on the method by Nakahara et al. (1998) and clarify the spatial distribution of high-frequency seismic energy radiation on the fault plane of this earthquake. We use three-component sum of mean squared velocity seismograms multiplied by a density of earth medium, which is called envelopes here, for the envelope inversion analysis. Three frequency bands of 1-2, 2-4, and 4-8 Hz are adopted. We use envelopes in the time window from the onset of S waves to the lapse time of 128 sec. Green functions of envelopes representing the energy propagation process through a scattering medium are calculated based on the radiative transfer theory, which are characterized by parameters of scattering attenuation and intrinsic absorption. We use the values obtained for eastern Hokkaido (Hoshiba, 1993). We assume the fault plane as follows: strike=249o, dip=15o, rake=130o, length=150km, width=165km with reference to a waveform inversion analysis in low frequencies (e.g. Yagi, 2003). We divide this fault plane into 110 subfaults, each of which is a 15km x 15km square. Rupture velocity is assumed to be constant. Seismic energy is radiated from a point source as soon as the rupture front passes the center of each subfault. Time function of energy radiation is assumed as a box-car function. The amount of seismic energy from all the subfaults and site amplification factors for all the stations are estimated by the envelope inversion method. Rupture velocity and the duration time of a box-car function should be estimated by a grid search. Theoretical envelopes calculated with best-fit parameters generally fit to observed ones. The rupture velocity and duration time were estimated as 3.0 km/s and 6 sec, respectively. The high-frequency seismic energy was found to be radiated mainly from two spots on the fault plane: The first one is the deeper part beneath the initial rupture point and the second is the southern shallow part of the fault plane. Radiated energy was estimated to be 7.2 × 1016J in the 1-8Hz band. Acknowledgements: We used strong-motion seismograms recorded by the K-NET and KiK-net of NIED, JAPAN.

Component analysis of somatosensory evoked potentials for identifying spinal cord injury location.

PubMed

Wang, Yazhou; Li, Guangsheng; Luk, Keith D K; Hu, Yong

2017-05-24

This study aims to determine whether the time-frequency components (TFCs) of somatosensory evoked potentials (SEPs) can be used to identify the specific location of a compressive spinal cord injury using a classification technique. Waveforms of SEPs after compressive injuries at various locations (C4, C5 and C6) in rat spinal cords were decomposed into a series of TFCs using a high-resolution time-frequency analysis method. A classification method based on support vector machine (SVM) was applied to the distributions of these TFCs among different pathological locations. The difference among injury locations manifests itself in different categories of SEP TFCs. High-energy TFCs of normal-state SEPs have significantly higher power and frequency than those of injury-state SEPs. The location of C5 is characterized by a unique distribution pattern of middle-energy TFCs. The difference between C4 and C6 is evidenced by the distribution pattern of low-energy TFCs. The proposed classification method based on SEP TFCs offers a discrimination accuracy of 80.2%. In this study, meaningful information contained in various SEP components was investigated and used to propose a new application of SEPs for identification of the location of pathological changes in the cervical spinal cord.

Helicopter TEM parameters analysis and system optimization based on time constant

NASA Astrophysics Data System (ADS)

Xiao, Pan; Wu, Xin; Shi, Zongyang; Li, Jutao; Liu, Lihua; Fang, Guangyou

2018-03-01

Helicopter transient electromagnetic (TEM) method is a kind of common geophysical prospecting method, widely used in mineral detection, underground water exploration and environment investigation. In order to develop an efficient helicopter TEM system, it is necessary to analyze and optimize the system parameters. In this paper, a simple and quantitative method is proposed to analyze the system parameters, such as waveform, power, base frequency, measured field and sampling time. A wire loop model is used to define a comprehensive 'time constant domain' that shows a range of time constant, analogous to a range of conductance, after which the characteristics of the system parameters in this domain is obtained. It is found that the distortion caused by the transmitting base frequency is less than 5% when the ratio of the transmitting period to the target time constant is greater than 6. When the sampling time window is less than the target time constant, the distortion caused by the sampling time window is less than 5%. According to this method, a helicopter TEM system, called CASHTEM, is designed, and flight test has been carried out in the known mining area. The test results show that the system has good detection performance, verifying the effectiveness of the method.

GNSS global real-time augmentation positioning: Real-time precise satellite clock estimation, prototype system construction and performance analysis

NASA Astrophysics Data System (ADS)

Chen, Liang; Zhao, Qile; Hu, Zhigang; Jiang, Xinyuan; Geng, Changjiang; Ge, Maorong; Shi, Chuang

2018-01-01

Lots of ambiguities in un-differenced (UD) model lead to lower calculation efficiency, which isn't appropriate for the high-frequency real-time GNSS clock estimation, like 1 Hz. Mixed differenced model fusing UD pseudo-range and epoch-differenced (ED) phase observations has been introduced into real-time clock estimation. In this contribution, we extend the mixed differenced model for realizing multi-GNSS real-time clock high-frequency updating and a rigorous comparison and analysis on same conditions are performed to achieve the best real-time clock estimation performance taking the efficiency, accuracy, consistency and reliability into consideration. Based on the multi-GNSS real-time data streams provided by multi-GNSS Experiment (MGEX) and Wuhan University, GPS + BeiDou + Galileo global real-time augmentation positioning prototype system is designed and constructed, including real-time precise orbit determination, real-time precise clock estimation, real-time Precise Point Positioning (RT-PPP) and real-time Standard Point Positioning (RT-SPP). The statistical analysis of the 6 h-predicted real-time orbits shows that the root mean square (RMS) in radial direction is about 1-5 cm for GPS, Beidou MEO and Galileo satellites and about 10 cm for Beidou GEO and IGSO satellites. Using the mixed differenced estimation model, the prototype system can realize high-efficient real-time satellite absolute clock estimation with no constant clock-bias and can be used for high-frequency augmentation message updating (such as 1 Hz). The real-time augmentation message signal-in-space ranging error (SISRE), a comprehensive accuracy of orbit and clock and effecting the users' actual positioning performance, is introduced to evaluate and analyze the performance of GPS + BeiDou + Galileo global real-time augmentation positioning system. The statistical analysis of real-time augmentation message SISRE is about 4-7 cm for GPS, whlile 10 cm for Beidou IGSO/MEO, Galileo and about 30 cm for BeiDou GEO satellites. The real-time positioning results prove that the GPS + BeiDou + Galileo RT-PPP comparing to GPS-only can effectively accelerate convergence time by about 60%, improve the positioning accuracy by about 30% and obtain averaged RMS 4 cm in horizontal and 6 cm in vertical; additionally RT-SPP accuracy in the prototype system can realize positioning accuracy with about averaged RMS 1 m in horizontal and 1.5-2 m in vertical, which are improved by 60% and 70% to SPP based on broadcast ephemeris, respectively.

Statistical analysis of earthquakes after the 1999 MW 7.7 Chi-Chi, Taiwan, earthquake based on a modified Reasenberg-Jones model

NASA Astrophysics Data System (ADS)

Chen, Yuh-Ing; Huang, Chi-Shen; Liu, Jann-Yenq

2015-12-01

We investigated the temporal-spatial hazard of the earthquakes after the 1999 September 21 MW = 7.7 Chi-Chi shock in a continental region of Taiwan. The Reasenberg-Jones (RJ) model (Reasenberg and Jones, 1989, 1994) that combines the frequency-magnitude distribution (Gutenberg and Richter, 1944) and time-decaying occurrence rate (Utsu et al., 1995) is conventionally employed for assessing the earthquake hazard after a large shock. However, it is found that the b values in the frequency-magnitude distribution of the earthquakes in the study region dramatically decreased from background values after the Chi-Chi shock, and then gradually increased up. The observation of a time-dependent frequency-magnitude distribution motivated us to propose a modified RJ model (MRJ) to assess the earthquake hazard. To see how the models perform on assessing short-term earthquake hazard, the RJ and MRJ models were separately used to sequentially forecast earthquakes in the study region. To depict the potential rupture area for future earthquakes, we further constructed relative hazard (RH) maps based on the two models. The Receiver Operating Characteristics (ROC) curves (Swets, 1988) finally demonstrated that the RH map based on the MRJ model was, in general, superior to the one based on the original RJ model for exploring the spatial hazard of earthquakes in a short time after the Chi-Chi shock.

Adjusted peak-flow frequency estimates for selected streamflow-gaging stations in or near Montana based on data through water year 2011: Chapter D in Montana StreamStats

USGS Publications Warehouse

Sando, Steven K.; Sando, Roy; McCarthy, Peter M.; Dutton, DeAnn M.

2016-04-05

The climatic conditions of the specific time period during which peak-flow data were collected at a given streamflow-gaging station (hereinafter referred to as gaging station) can substantially affect how well the peak-flow frequency (hereinafter referred to as frequency) results represent long-term hydrologic conditions. Differences in the timing of the periods of record can result in substantial inconsistencies in frequency estimates for hydrologically similar gaging stations. Potential for inconsistency increases with decreasing peak-flow record length. The representativeness of the frequency estimates for a short-term gaging station can be adjusted by various methods including weighting the at-site results in association with frequency estimates from regional regression equations (RREs) by using the Weighted Independent Estimates (WIE) program. Also, for gaging stations that cannot be adjusted by using the WIE program because of regulation or drainage areas too large for application of RREs, frequency estimates might be improved by using record extension procedures, including a mixed-station analysis using the maintenance of variance type I (MOVE.1) procedure. The U.S. Geological Survey, in cooperation with the Montana Department of Transportation and the Montana Department of Natural Resources and Conservation, completed a study to provide adjusted frequency estimates for selected gaging stations through water year 2011.The purpose of Chapter D of this Scientific Investigations Report is to present adjusted frequency estimates for 504 selected streamflow-gaging stations in or near Montana based on data through water year 2011. Estimates of peak-flow magnitudes for the 66.7-, 50-, 42.9-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities are reported. These annual exceedance probabilities correspond to the 1.5-, 2-, 2.33-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year recurrence intervals, respectively.The at-site frequency estimates were adjusted by weighting with frequency estimates from RREs using the WIE program for 438 selected gaging stations in Montana. These 438 selected gaging stations (1) had periods of record less than or equal to 40 years, (2) represented unregulated or minor regulation conditions, and (3) had drainage areas less than about 2,750 square miles.The weighted-average frequency estimates obtained by weighting with RREs generally are considered to provide improved frequency estimates. In some cases, there are substantial differences among the at-site frequency estimates, the regression-equation frequency estimates, and the weighted-average frequency estimates. In these cases, thoughtful consideration should be applied when selecting the appropriate frequency estimate. Some factors that might be considered when selecting the appropriate frequency estimate include (1) whether the specific gaging station has peak-flow characteristics that distinguish it from most other gaging stations used in developing the RREs for the hydrologic region; and (2) the length of the peak-flow record and the general climatic characteristics during the period when the peak-flow data were collected. For critical structure-design applications, a conservative approach would be to select the higher of the at-site frequency estimate and the weighted-average frequency estimate.The mixed-station MOVE.1 procedure generally was applied in cases where three or more gaging stations were located on the same large river and some of the gaging stations could not be adjusted using the weighted-average method because of regulation or drainage areas too large for application of RREs. The mixed-station MOVE.1 procedure was applied to 66 selected gaging stations on 19 large rivers.The general approach for using mixed-station record extension procedures to adjust at-site frequencies involved (1) determining appropriate base periods for the gaging stations on the large rivers, (2) synthesizing peak-flow data for the gaging stations with incomplete peak-flow records during the base periods by using the mixed-station MOVE.1 procedure, and (3) conducting frequency analysis on the combined recorded and synthesized peak-flow data for each gaging station. Frequency estimates for the combined recorded and synthesized datasets for 66 gaging stations with incomplete peak-flow records during the base periods are presented. The uncertainties in the mixed-station record extension results are difficult to directly quantify; thus, it is important to understand the intended use of the estimated frequencies based on analysis of the combined recorded and synthesized datasets. The estimated frequencies are considered general estimates of frequency relations among gaging stations on the same stream channel that might be expected if the gaging stations had been gaged during the same long-term base period. However, because the mixed-station record extension procedures involve secondary statistical analysis with accompanying errors, the uncertainty of the frequency estimates is larger than would be obtained by collecting systematic records for the same number of years in the base period.

A comparison of three approaches to non-stationary flood frequency analysis

NASA Astrophysics Data System (ADS)

Debele, S. E.; Strupczewski, W. G.; Bogdanowicz, E.

2017-08-01

Non-stationary flood frequency analysis (FFA) is applied to statistical analysis of seasonal flow maxima from Polish and Norwegian catchments. Three non-stationary estimation methods, namely, maximum likelihood (ML), two stage (WLS/TS) and GAMLSS (generalized additive model for location, scale and shape parameters), are compared in the context of capturing the effect of non-stationarity on the estimation of time-dependent moments and design quantiles. The use of a multimodel approach is recommended, to reduce the errors due to the model misspecification in the magnitude of quantiles. The results of calculations based on observed seasonal daily flow maxima and computer simulation experiments showed that GAMLSS gave the best results with respect to the relative bias and root mean square error in the estimates of trend in the standard deviation and the constant shape parameter, while WLS/TS provided better accuracy in the estimates of trend in the mean value. Within three compared methods the WLS/TS method is recommended to deal with non-stationarity in short time series. Some practical aspects of the GAMLSS package application are also presented. The detailed discussion of general issues related to consequences of climate change in the FFA is presented in the second part of the article entitled "Around and about an application of the GAMLSS package in non-stationary flood frequency analysis".

Surface electromyography based muscle fatigue detection using high-resolution time-frequency methods and machine learning algorithms.

PubMed

Karthick, P A; Ghosh, Diptasree Maitra; Ramakrishnan, S

2018-02-01

Surface electromyography (sEMG) based muscle fatigue research is widely preferred in sports science and occupational/rehabilitation studies due to its noninvasiveness. However, these signals are complex, multicomponent and highly nonstationary with large inter-subject variations, particularly during dynamic contractions. Hence, time-frequency based machine learning methodologies can improve the design of automated system for these signals. In this work, the analysis based on high-resolution time-frequency methods, namely, Stockwell transform (S-transform), B-distribution (BD) and extended modified B-distribution (EMBD) are proposed to differentiate the dynamic muscle nonfatigue and fatigue conditions. The nonfatigue and fatigue segments of sEMG signals recorded from the biceps brachii of 52 healthy volunteers are preprocessed and subjected to S-transform, BD and EMBD. Twelve features are extracted from each method and prominent features are selected using genetic algorithm (GA) and binary particle swarm optimization (BPSO). Five machine learning algorithms, namely, naïve Bayes, support vector machine (SVM) of polynomial and radial basis kernel, random forest and rotation forests are used for the classification. The results show that all the proposed time-frequency distributions (TFDs) are able to show the nonstationary variations of sEMG signals. Most of the features exhibit statistically significant difference in the muscle fatigue and nonfatigue conditions. The maximum number of features (66%) is reduced by GA and BPSO for EMBD and BD-TFD respectively. The combination of EMBD- polynomial kernel based SVM is found to be most accurate (91% accuracy) in classifying the conditions with the features selected using GA. The proposed methods are found to be capable of handling the nonstationary and multicomponent variations of sEMG signals recorded in dynamic fatiguing contractions. Particularly, the combination of EMBD- polynomial kernel based SVM could be used to detect the dynamic muscle fatigue conditions. Copyright © 2017 Elsevier B.V. All rights reserved.

State-plane analysis of parallel resonant converter

NASA Technical Reports Server (NTRS)

Oruganti, R.; Lee, F. C.

1985-01-01

A method for analyzing the complex operation of a parallel resonant converter is developed, utilizing graphical state-plane techniques. The comprehensive mode analysis uncovers, for the first time, the presence of other complex modes besides the continuous conduction mode and the discontinuous conduction mode and determines their theoretical boundaries. Based on the insight gained from the analysis, a novel, high-frequency resonant buck converter is proposed. The voltage conversion ratio of the new converter is almost independent of load.

Psychoacoustic Analysis of Synthesized Jet Noise

NASA Technical Reports Server (NTRS)

Okcu, Selen; Rathsam, Jonathan; Rizzi, Stephen A.

2013-01-01

An aircraft noise synthesis capability is being developed so the annoyance caused by proposed aircraft can be assessed during the design stage. To make synthesized signals as realistic as possible, high fidelity simulation is required for source (e.g., engine noise, airframe noise), propagation and receiver effects. This psychoacoustic study tests whether the jet noise component of synthesized aircraft engine noise can be made more realistic using a low frequency oscillator (LFO) technique to simulate fluctuations in level observed in recordings. Jet noise predictions are commonly made in the frequency domain based on models of time-averaged empirical data. The synthesis process involves conversion of the frequency domain prediction into an audible pressure time history. However, because the predictions are time-invariant, the synthesized sound lacks fluctuations observed in recordings. Such fluctuations are hypothesized to be perceptually important. To introduce time-varying characteristics into jet noise synthesis, a method has been developed that modulates measured or predicted 1/3-octave band levels with a (<20Hz) LFO. The LFO characteristics are determined through analysis of laboratory jet noise recordings. For the aft emission angle, results indicate that signals synthesized using a generic LFO are perceived as more similar to recordings than those using no LFO, and signals synthesized with an angle-specific LFO are more similar to recordings than those synthesized with a generic LFO.

Phase-locked and non-phase-locked EEG responses to pinprick stimulation before and after experimentally-induced secondary hyperalgesia.

PubMed

van den Broeke, Emanuel N; de Vries, Bart; Lambert, Julien; Torta, Diana M; Mouraux, André

2017-08-01

Pinprick-evoked brain potentials (PEPs) have been proposed as a technique to investigate secondary hyperalgesia and central sensitization in humans. However, the signal-to-noise (SNR) of PEPs is low. Here, using time-frequency analysis, we characterize the phase-locked and non-phase-locked EEG responses to pinprick stimulation, before and after secondary hyperalgesia. Secondary hyperalgesia was induced using high-frequency electrical stimulation (HFS) of the left/right forearm skin in 16 volunteers. EEG responses to 64 and 96mN pinprick stimuli were elicited from both arms, before and 20min after HFS. Pinprick stimulation applied to normal skin elicited a phase-locked low-frequency (<5Hz) response followed by a reduction of alpha-band oscillations (7-10Hz). The low-frequency response was significantly increased when pinprick stimuli were delivered to the area of secondary hyperalgesia. There was no change in the reduction of alpha-band oscillations. Whereas the low-frequency response was enhanced for both 64 and 96mN intensities, PEPs analyzed in the time domain were only significantly enhanced for the 64mN intensity. Time-frequency analysis may be more sensitive than conventional time-domain analysis in revealing EEG changes associated to secondary hyperalgesia. Time-frequency analysis of PEPs can be used to investigate central sensitization in humans. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Intermediate frequency band digitized high dynamic range radiometer system for plasma diagnostics and real-time Tokamak control

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bongers, W. A.; Beveren, V. van; Westerhof, E.

2011-06-15

An intermediate frequency (IF) band digitizing radiometer system in the 100-200 GHz frequency range has been developed for Tokamak diagnostics and control, and other fields of research which require a high flexibility in frequency resolution combined with a large bandwidth and the retrieval of the full wave information of the mm-wave signals under investigation. The system is based on directly digitizing the IF band after down conversion. The enabling technology consists of a fast multi-giga sample analog to digital converter that has recently become available. Field programmable gate arrays (FPGA) are implemented to accomplish versatile real-time data analysis. A prototypemore » system has been developed and tested and its performance has been compared with conventional electron cyclotron emission (ECE) spectrometer systems. On the TEXTOR Tokamak a proof of principle shows that ECE, together with high power injected and scattered radiation, becomes amenable to measurement by this device. In particular, its capability to measure the phase of coherent signals in the spectrum offers important advantages in diagnostics and control. One case developed in detail employs the FPGA in real-time fast Fourier transform (FFT) and additional signal processing. The major benefit of such a FFT-based system is the real-time trade-off that can be made between frequency and time resolution. For ECE diagnostics this corresponds to a flexible spatial resolution in the plasma, with potential application in smart sensing of plasma instabilities such as the neoclassical tearing mode (NTM) and sawtooth instabilities. The flexible resolution would allow for the measurement of the full mode content of plasma instabilities contained within the system bandwidth.« less

Theoretical analysis of optical poling and frequency doubling effect based on classical model

NASA Astrophysics Data System (ADS)

Feng, Xi; Li, Fuquan; Lin, Aoxiang; Wang, Fang; Chai, Xiangxu; Wang, Zhengping; Zhu, Qihua; Sun, Xun; Zhang, Sen; Sun, Xibo

2018-03-01

Optical poling and frequency doubling effect is one of the effective manners to induce second order nonlinearity and realize frequency doubling in glass materials. The classical model believes that an internal electric field is built in glass when it's exposed by fundamental and frequency-doubled light at the same time, and second order nonlinearity appears as a result of the electric field and the orientation of poles. The process of frequency doubling in glass is quasi phase matched. In this letter, the physical process of poling and doubling process in optical poling and frequency doubling effect is deeply discussed in detail. The magnitude and direction of internal electric field, second order nonlinear coefficient and its components, strength and direction of frequency doubled output signal, quasi phase matched coupled wave equations are given in analytic expression. Model of optical poling and frequency doubling effect which can be quantitatively analyzed are constructed in theory, which set a foundation for intensive study of optical poling and frequency doubling effect.

A joint probability approach for coincidental flood frequency analysis at ungauged basin confluences

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Cheng

2016-03-12

A reliable and accurate flood frequency analysis at the confluence of streams is of importance. Given that long-term peak flow observations are often unavailable at tributary confluences, at a practical level, this paper presents a joint probability approach (JPA) to address the coincidental flood frequency analysis at the ungauged confluence of two streams based on the flow rate data from the upstream tributaries. One case study is performed for comparison against several traditional approaches, including the position-plotting formula, the univariate flood frequency analysis, and the National Flood Frequency Program developed by US Geological Survey. It shows that the results generatedmore » by the JPA approach agree well with the floods estimated by the plotting position and univariate flood frequency analysis based on the observation data.« less

An investigation into the exercise behaviours of regionally based Australian pregnant women.

PubMed

Hayman, Melanie; Short, Camille; Reaburn, Peter

2016-08-01

Regular exercise during pregnancy is a recommended prenatal care strategy with short and long-term health benefits to mother and child. Unfortunately, most pregnant women are insufficiently active to obtain health benefits and there is evidence that activity levels decrease overall during pregnancy. Physical activity among regionally based women is lower than that of urban-based women within Australia. However, little is currently known about exercise behaviours of regionally based Australian pregnant women. To successfully promote exercise among regionally based pregnant women, a greater understanding of exercise behaviours must first be explored. This study investigated exercise behaviours in a sample of regionally based Australian pregnant women. Regionally based Australian pregnant women (n=142) completed a modified version of the Godin Leisure-Time Exercise Questionnaire examining exercise behaviours before and during pregnancy. Women self-reported their exercise behaviours, including exercise frequency, intensity, time and type, before and during pregnancy. Chi-square analysis revealed significantly less (χ(2)=31.66, p<0.05) women participated in exercise during pregnancy (61%) compared to before pregnancy (87%). During pregnancy, respondents exercised at a significantly lower frequency (χ(2)=111.63, p<0.05), intensity (χ(2)=67.41, p<0.05), shorter time/duration (χ(2)=114.33, p<0.05), and significantly less (χ(2)=8.55, p<0.05) women (8%) are meeting 'exercise during pregnancy' guidelines compared to women before pregnancy (49%) meeting physical activity guidelines. Exercise during pregnancy decreases to levels significantly lower than what is currently recommended. Public health initiatives that promote exercise among Australian pregnant women should aim to increase frequency, intensity, time and type of exercise to be undertaken during pregnancy. Copyright © 2015 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

On-orbit frequency stability analysis of the GPS NAVSTAR-1 quartz clock and the NAVSTARs-6 and -8 rubidium clocks

NASA Technical Reports Server (NTRS)

Mccaskill, T. B.; Buisson, J. A.; Reid, W. G.

1984-01-01

An on-orbit frequency stability performance analysis of the GPS NAVSTAR-1 quartz clock and the NAVSTARs-6 and -8 rubidium clocks is presented. The clock offsets were obtained from measurements taken at the GPS monitor stations which use high performance cesium standards as a reference. Clock performance is characterized through the use of the Allan variance, which is evaluated for sample times of 15 minutes to two hours, and from one day to 10 days. The quartz and rubidium clocks' offsets were corrected for aging rate before computing the frequency stability. The effect of small errors in aging rate is presented for the NAVSTAR-8 rubidium clock's stability analysis. The analysis includes presentation of time and frequency residuals with respect to linear and quadratic models, which aid in obtaining aging rate values and identifying systematic and random effects. The frequency stability values were further processed with a time domain noise process analysis, which is used to classify random noise process and modulation type.

Synthesis of nonlinear frequency responses with experimentally extracted nonlinear modes

NASA Astrophysics Data System (ADS)

Peter, Simon; Scheel, Maren; Krack, Malte; Leine, Remco I.

2018-02-01

Determining frequency response curves is a common task in the vibration analysis of nonlinear systems. Measuring nonlinear frequency responses is often challenging and time consuming due to, e.g., coexisting stable or unstable vibration responses and structure-exciter-interaction. The aim of the current paper is to develop a method for the synthesis of nonlinear frequency responses near an isolated resonance, based on data that can be easily and automatically obtained experimentally. The proposed purely experimental approach relies on (a) a standard linear modal analysis carried out at low vibration levels and (b) a phase-controlled tracking of the backbone curve of the considered forced resonance. From (b), the natural frequency and vibrational deflection shape are directly obtained as a function of the vibration level. Moreover, a damping measure can be extracted by power considerations or from the linear modal analysis. In accordance with the single nonlinear mode assumption, the near-resonant frequency response can then be synthesized using this data. The method is applied to a benchmark structure consisting of a cantilevered beam attached to a leaf spring undergoing large deflections. The results are compared with direct measurements of the frequency response. The proposed approach is fast, robust and provides a good estimate for the frequency response. It is also found that direct frequency response measurement is less robust due to bifurcations and using a sine sweep excitation with a conventional force controller leads to underestimation of maximum vibration response.

Code-Phase Clock Bias and Frequency Offset in PPP Clock Solutions.

PubMed

Defraigne, Pascale; Sleewaegen, Jean-Marie

2016-07-01

Precise point positioning (PPP) is a zero-difference single-station technique that has proved to be very effective for time and frequency transfer, enabling the comparison of atomic clocks with a precision of a hundred picoseconds and a one-day stability below the 1e-15 level. It was, however, noted that for some receivers, a frequency difference is observed between the clock solution based on the code measurements and the clock solution based on the carrier-phase measurements. These observations reveal some inconsistency either between the code and carrier phases measured by the receiver or between the data analysis strategy of codes and carrier phases. One explanation for this discrepancy is the time offset that can exist for some receivers between the code and the carrier-phase latching. This paper explains how a code-phase bias in the receiver hardware can induce a frequency difference between the code and the carrier-phase clock solutions. The impact on PPP is then quantified. Finally, the possibility to determine this code-phase bias in the PPP modeling is investigated, and the first results are shown to be inappropriate due to the high level of code noise.

Time-Frequency Characterization of Cerebral Hemodynamics of Migraine Sufferers as Assessed by NIRS Signals

NASA Astrophysics Data System (ADS)

Molinari, Filippo; Rosati, Samanta; Liboni, William; Negri, Emanuela; Mana, Ornella; Allais, Gianni; Benedetto, Chiara

2010-12-01

Near-infrared spectroscopy (NIRS) is a noninvasive system for the real-time monitoring of the concentration of oxygenated ([InlineEquation not available: see fulltext.]) and reduced (HHb) hemoglobin in the brain cortex. [InlineEquation not available: see fulltext.] and HHb concentrations vary in response to cerebral autoregulation. Sixty-eight women (14 migraineurs without aura, 49 migraineurs with aura, and 5 controls) performed breath-holding and hyperventilation during NIRS recordings. Signals were processed using the Choi-Williams time-frequency transform in order to measure the power variation of the very-low frequencies (VLF: 20-40 mHz) and of the low frequencies (LF: 40-140 mHz). Results showed that migraineurs without aura present different LF and VLF power levels than controls and migraineurs with aura. The accurate power measurement of the time-frequency analysis allowed for the discrimination of the subjects' hemodynamic patterns. The time-frequency analysis of NIRS signals can be used in clinical practice to assess cerebral hemodynamics.

A Wavelet Analysis Approach for Categorizing Air Traffic Behavior

NASA Technical Reports Server (NTRS)

Drew, Michael; Sheth, Kapil

2015-01-01

In this paper two frequency domain techniques are applied to air traffic analysis. The Continuous Wavelet Transform (CWT), like the Fourier Transform, is shown to identify changes in historical traffic patterns caused by Traffic Management Initiatives (TMIs) and weather with the added benefit of detecting when in time those changes take place. Next, with the expectation that it could detect anomalies in the network and indicate the extent to which they affect traffic flows, the Spectral Graph Wavelet Transform (SGWT) is applied to a center based graph model of air traffic. When applied to simulations based on historical flight plans, it identified the traffic flows between centers that have the greatest impact on either neighboring flows, or flows between centers many centers away. Like the CWT, however, it can be difficult to interpret SGWT results and relate them to simulations where major TMIs are implemented, and more research may be warranted in this area. These frequency analysis techniques can detect off-nominal air traffic behavior, but due to the nature of air traffic time series data, so far they prove difficult to apply in a way that provides significant insight or specific identification of traffic patterns.

Estimation of automobile-driver describing function from highway tests using the double steering wheel

NASA Technical Reports Server (NTRS)

Delp, P.; Crossman, E. R. F. W.; Szostak, H.

1972-01-01

The automobile-driver describing function for lateral position control was estimated for three subjects from frequency response analysis of straight road test results. The measurement procedure employed an instrumented full size sedan with known steering response characteristics, and equipped with a lateral lane position measuring device based on video detection of white stripe lane markings. Forcing functions were inserted through a servo driven double steering wheel coupling the driver to the steering system proper. Random appearing, Gaussian, and transient time functions were used. The quasi-linear models fitted to the random appearing input frequency response characterized the driver as compensating for lateral position error in a proportional, derivative, and integral manner. Similar parameters were fitted to the Gabor transformed frequency response of the driver to transient functions. A fourth term corresponding to response to lateral acceleration was determined by matching the time response histories of the model to the experimental results. The time histories show evidence of pulse-like nonlinear behavior during extended response to step transients which appear as high frequency remnant power.

Postural analysis in time and frequency domains in patients with Ehlers-Danlos syndrome.

PubMed

Galli, Manuela; Rigoldi, Chiara; Celletti, Claudia; Mainardi, Luca; Tenore, Nunzio; Albertini, Giorgio; Camerota, Filippo

2011-01-01

The goal of this work is to analyze postural control in Ehlers-Danlos syndrome (EDS) participants in time and frequency domain. This study considered a pathological group composed by 22 EDS participants performing a postural test consisting in maintaining standing position over a force platform for 30s in two conditions: open eyes (OE) and closed eyes (CE). In order to compare pathological group we acquired in the same conditions a control group composed by 20 healthy participants. The obtained center of pressure (COP) signal was analyzed in time and frequency domain using an AR model. Results revealed differences between pathological and control group: EDS participants pointed out difficulties in controlling COP displacements trying to keep it inside the BOS in AP direction and for this reason increased the use of ML mechanism in order to avoid the risk of fall. Also in CE conditions they demonstrated more difficulties in maintaining posture revealing the proprioceptive system is impaired, due to ligament laxity that characterized EDS participants. Frequency domain analysis showed no differences between the two groups, affirming that the changes in time domain reflected really the impairment to the postural control mechanism and not a different strategy assumed by EDS participants. These data could help in decision-making process to establish a correct rehabilitation approach, based on the reinforcing of muscle tone to supply the ligament laxity in order to prevent risks of falls and its consequences. Copyright © 2010 Elsevier Ltd. All rights reserved.

On the relation between the peak frequency and the corresponding rise time of solar microwave impulsive bursts and the height dependence of magnetic fields

NASA Astrophysics Data System (ADS)

Ren-Yang, Zhao; Magun, Andreas; Schanda, Erwin

1990-12-01

In the present paper we report the results of a correlation analysis for 57 microwave impulsive bursts observed at six frequencies in which we have obtained a regression line between the peak frequency and the corresponding rise time of microwave impulsive bursts: {ie361-01} (with a correlation coefficient of - 0.43). This can be explained in the frame of a thermal model. The magnetic field decrease with height has to be much slower than in a dipole field in order to explain the weak dependence of f p on t r . This decrease of magnetic field with height in burst sources is based on the relationship between f p and t r found by assuming a thermal flare model with a collisionless conduction front.

Efficacy analysis of LDPC coded APSK modulated differential space-time-frequency coded for wireless body area network using MB-pulsed OFDM UWB technology.

PubMed

Manimegalai, C T; Gauni, Sabitha; Kalimuthu, K

2017-12-04

Wireless body area network (WBAN) is a breakthrough technology in healthcare areas such as hospital and telemedicine. The human body has a complex mixture of different tissues. It is expected that the nature of propagation of electromagnetic signals is distinct in each of these tissues. This forms the base for the WBAN, which is different from other environments. In this paper, the knowledge of Ultra Wide Band (UWB) channel is explored in the WBAN (IEEE 802.15.6) system. The measurements of parameters in frequency range from 3.1-10.6 GHz are taken. The proposed system, transmits data up to 480 Mbps by using LDPC coded APSK Modulated Differential Space-Time-Frequency Coded MB-OFDM to increase the throughput and power efficiency.

Frequency analysis of uncertain structures using imprecise probability

DOE Office of Scientific and Technical Information (OSTI.GOV)

Modares, Mehdi; Bergerson, Joshua

2015-01-01

Two new methods for finite element based frequency analysis of a structure with uncertainty are developed. An imprecise probability formulation based on enveloping p-boxes is used to quantify the uncertainty present in the mechanical characteristics of the structure. For each element, independent variations are considered. Using the two developed methods, P-box Frequency Analysis (PFA) and Interval Monte-Carlo Frequency Analysis (IMFA), sharp bounds on natural circular frequencies at different probability levels are obtained. These methods establish a framework for handling incomplete information in structural dynamics. Numerical example problems are presented that illustrate the capabilities of the new methods along with discussionsmore » on their computational efficiency.« less

Roles of frequency, attitudes, and multiple intelligence modality surrounding Electricity Content-Based Reader's Theatre

NASA Astrophysics Data System (ADS)

Hosier, Julie Winchester

Integration of subjects is something elementary teachers must do to insure required objectives are covered. Science-based Reader's Theatre is one way to weave reading into science. This study examined the roles of frequency, attitudes, and Multiple Intelligence modalities surrounding Electricity Content-Based Reader's Theatre. This study used quasi-experimental, repeated measures ANOVA with time as a factor design. A convenience sample of two fifth-grade classrooms participated in the study for eighteen weeks. Five Electricity Achievement Tests were given throughout the study to assess students' growth. A Student Reader's Theatre Attitudinal Survey revealed students' attitudes before and after Electricity Content-Based Reader's Theatre treatment. The Multiple Intelligence Inventory for Kids (Faris, 2007) examined whether Multiple Intelligence modality played a role in achievement on Electricity Test 4, the post-treatment test. Analysis using repeated measures ANOVA and an independent t-test found that students in the experimental group, which practiced its student-created Electricity Content-Based Reader's Theatre skits ten times versus two times for the for control group, did significantly better on Electricity Achievement Test 4, t(76) = 3.018, p = 0.003. Dependent t-tests did not find statistically significant differences between students' attitudes about Electricity Content-Based Reader's Theatre before and after treatment. A Kruskal-Wallis test found no statistically significant difference between the various Multiple Intelligence modalities score mean ranks (x2 = 5.57, df = 2, alpha = .062). Qualitative data do, however, indicate students had strong positive feelings about Electricity Content-Based Reader's Theatre after treatment. Students indicated it to be motivating, confidence-building, and a fun way to learn about science; however, they disliked writing their own scripts. Examining the frequency, attitudes, and Multiple Intelligence modalities lead to the conclusion that the role of frequency had the greatest impact on the success of Electricity Content-Based Reader's Theatre. The participating teachers, students, and research found integrating science and reading through Electricity Content-Based Reader's Theatre beneficial.

Real-time and high accuracy frequency measurements for intermediate frequency narrowband signals

NASA Astrophysics Data System (ADS)

Tian, Jing; Meng, Xiaofeng; Nie, Jing; Lin, Liwei

2018-01-01

Real-time and accurate measurements of intermediate frequency signals based on microprocessors are difficult due to the computational complexity and limited time constraints. In this paper, a fast and precise methodology based on the sigma-delta modulator is designed and implemented by first generating the twiddle factors using the designed recursive scheme. This scheme requires zero times of multiplications and only half amounts of addition operations by using the discrete Fourier transform (DFT) and the combination of the Rife algorithm and Fourier coefficient interpolation as compared with conventional methods such as DFT and Fast Fourier Transform. Experimentally, when the sampling frequency is 10 MHz, the real-time frequency measurements with intermediate frequency and narrowband signals have a measurement mean squared error of ±2.4 Hz. Furthermore, a single measurement of the whole system only requires approximately 0.3 s to achieve fast iteration, high precision, and less calculation time.

Evaluation of Hydrologic and Meteorological Impacts on Dengue Fever Incidences in Southern Taiwan using Time- Frequency Method

NASA Astrophysics Data System (ADS)

Tsai, Christina; Yeh, Ting-Gu

2017-04-01

Extreme weather events are occurring more frequently as a result of climate change. Recently dengue fever has become a serious issue in southern Taiwan. It may have characteristic temporal scales that can be identified. Some researchers have hypothesized that dengue fever incidences are related to climate change. This study applies time-frequency analysis to time series data concerning dengue fever and hydrologic and meteorological variables. Results of three time-frequency analytical methods - the Hilbert Huang transform (HHT), the Wavelet Transform (WT) and the Short Time Fourier Transform (STFT) are compared and discussed. A more effective time-frequency analysis method will be identified to analyze relevant time series data. The most influential time scales of hydrologic and meteorological variables that are associated with dengue fever are determined. Finally, the linkage between hydrologic/meteorological factors and dengue fever incidences can be established.

Numerical Simulation of Monitoring Corrosion in Reinforced Concrete Based on Ultrasonic Guided Waves

PubMed Central

Zheng, Zhupeng; Lei, Ying; Xue, Xin

2014-01-01

Numerical simulation based on finite element method is conducted to predict the location of pitting corrosion in reinforced concrete. Simulation results show that it is feasible to predict corrosion monitoring based on ultrasonic guided wave in reinforced concrete, and wavelet analysis can be used for the extremely weak signal of guided waves due to energy leaking into concrete. The characteristic of time-frequency localization of wavelet transform is adopted in the corrosion monitoring of reinforced concrete. Guided waves can be successfully used to identify corrosion defects in reinforced concrete with the analysis of suitable wavelet-based function and its scale. PMID:25013865

Real-time volcano monitoring using GNSS single-frequency receivers

NASA Astrophysics Data System (ADS)

Lee, Seung-Woo; Yun, Sung-Hyo; Kim, Do Hyeong; Lee, Dukkee; Lee, Young J.; Schutz, Bob E.

2015-12-01

We present a real-time volcano monitoring strategy that uses the Global Navigation Satellite System (GNSS), and we examine the performance of the strategy by processing simulated and real data and comparing the results with published solutions. The cost of implementing the strategy is reduced greatly by using single-frequency GNSS receivers except for one dual-frequency receiver that serves as a base receiver. Positions of the single-frequency receivers are computed relative to the base receiver on an epoch-by-epoch basis using the high-rate double-difference (DD) GNSS technique, while the position of the base station is fixed to the values obtained with a deferred-time precise point positioning technique and updated on a regular basis. Since the performance of the single-frequency high-rate DD technique depends on the conditions of the ionosphere over the monitoring area, the ionospheric total electron content is monitored using the dual-frequency data from the base receiver. The surface deformation obtained with the high-rate DD technique is eventually processed by a real-time inversion filter based on the Mogi point source model. The performance of the real-time volcano monitoring strategy is assessed through a set of tests and case studies, in which the data recorded during the 2007 eruption of Kilauea and the 2005 eruption of Augustine are processed in a simulated real-time mode. The case studies show that the displacement time series obtained with the strategy seem to agree with those obtained with deferred-time, dual-frequency approaches at the level of 10-15 mm. Differences in the estimated volume change of the Mogi source between the real-time inversion filter and previously reported works were in the range of 11 to 13% of the maximum volume changes of the cases examined.

The impact of using mobile-enabled devices on patient engagement in remote monitoring programs.

PubMed

Agboola, Stephen; Havasy, Rob; Myint-U, Khinlei; Kvedar, Joseph; Jethwani, Kamal

2013-05-01

Different types of data transmission technologies are used in remote monitoring (RM) programs. This study reports on a retrospective analysis of how participants engage, based on the type of data transfer technology used in a blood pressure (BP) RM program, and its potential impact on RM program design and outcomes. Thirty patients, aged 23-84 years (62 ± 14 years), who had completed at least 2 months in the program and were not participating in any other clinical trial were identified from the Remote Monitoring Data Repository. Half of these patients used wireless-based data transfer devices [wireless-based device (WBD)] while the other half used telephone modem-based data transfer devices [modem-based device (MBD)]. Participants were matched by practice and age. Engagement indices, which include frequency of BP measurements, frequency of data uploads, time to first BP measurement, and time to first data upload, were compared in both groups using the Wilcoxon-Mann-Whitney two-sample rank-sum test. Help desk call data were analyzed by Chi square test. The frequency of BP measurements and data uploads was significantly higher in the WBD group versus the MBD group [median = 0.66 versus 0.2 measurements/day (p = .01) and 0.46 versus 0.01 uploads/day (p < .001), respectively]. Time to first upload was significantly lower in the WBD group (median = 4 versus 7 days; p = .02), but time to first BP measurement did not differ between the two groups (median = 2 versus 1 day; p = .98). Wireless transmission ensures instantaneous transmission of readings, providing clinicians timely data to intervene on. Our findings suggest that mobile-enabled wireless technologies can positively impact patient engagement, outcomes, and operational workflow in RM programs. © 2013 Diabetes Technology Society.

Instantaneous Real-Time Kinematic Decimeter-Level Positioning with BeiDou Triple-Frequency Signals over Medium Baselines.

PubMed

He, Xiyang; Zhang, Xiaohong; Tang, Long; Liu, Wanke

2015-12-22

Many applications, such as marine navigation, land vehicles location, etc., require real time precise positioning under medium or long baseline conditions. In this contribution, we develop a model of real-time kinematic decimeter-level positioning with BeiDou Navigation Satellite System (BDS) triple-frequency signals over medium distances. The ambiguities of two extra-wide-lane (EWL) combinations are fixed first, and then a wide lane (WL) combination is reformed based on the two EWL combinations for positioning. Theoretical analysis and empirical analysis is given of the ambiguity fixing rate and the positioning accuracy of the presented method. The results indicate that the ambiguity fixing rate can be up to more than 98% when using BDS medium baseline observations, which is much higher than that of dual-frequency Hatch-Melbourne-Wübbena (HMW) method. As for positioning accuracy, decimeter level accuracy can be achieved with this method, which is comparable to that of carrier-smoothed code differential positioning method. Signal interruption simulation experiment indicates that the proposed method can realize fast high-precision positioning whereas the carrier-smoothed code differential positioning method needs several hundreds of seconds for obtaining high precision results. We can conclude that a relatively high accuracy and high fixing rate can be achieved for triple-frequency WL method with single-epoch observations, displaying significant advantage comparing to traditional carrier-smoothed code differential positioning method.

Frequency Based Real-time Pricing for Residential Prosumers

NASA Astrophysics Data System (ADS)

Hambridge, Sarah Mabel

This work is the first to explore frequency based pricing for secondary frequency control as a price-reactive control mechanism for residential prosumers. A frequency based real-time electricity rate is designed as an autonomous market control mechanism for residential prosumers to provide frequency support as an ancillary service. In addition, prosumers are empowered to participate in dynamic energy transactions, therefore integrating Distributed Energy Resources (DERs), and increasing distributed energy storage onto the distributed grid. As the grid transitions towards DERs, a new market based control system will take the place of the legacy distributed system and possibly the legacy bulk power system. DERs provide many benefits such as energy independence, clean generation, efficiency, and reliability to prosumers during blackouts. However, the variable nature of renewable energy and current lack of installed energy storage on the grid will create imbalances in supply and demand as uptake increases, affecting the grid frequency and system operation. Through a frequency-based electricity rate, prosumers will be encouraged to purchase energy storage systems (ESS) to offset their neighbor's distributed generation (DG) such as solar. Chapter 1 explains the deregulation of the power system and move towards Distributed System Operators (DSOs), as prosumers become owners of microgrids and energy cells connected to the distributed system. Dynamic pricing has been proposed as a benefit to prosumers, giving them the ability to make decisions in the energy market, while also providing a way to influence and control their behavior. Frequency based real-time pricing is a type of dynamic pricing which falls between price-reactive control and transactive control. Prosumer-to-prosumer transactions may take the place of prosumer-to-utility transactions, building The Energy Internet. Frequency based pricing could be a mechanism for determining prosumer prices and supporting stability in a free, competitive, market. Frequency based pricing is applied to secondary frequency control in this work, providing support at one to five minute time intervals. In Chapter 2, a frequency based pricing curve is designed as a preliminary study and the response of the prosumer is optimized for economic dispatch. In Chapter 3, a day-ahead schedule and real-time adjustment energy management framework is presented for the prosumer, creating a market structure similar to the existing energy market supervised by Independent System Operators (ISOs). Enabling technology, such as the solid state transformer (SST) is described for prosumer energy transactions, controlling power flow from the prosumer's energy cell to the grid or neighboring prosumer as an energy router. Experimental results are shown to demonstrate this capability. Additionally, the SST is capable of measuring the grid frequency. Lastly, a frequency based real-time hybrid electricity rate is presented in Chapter 4 and Chapter 5. Chapter 4 specializes in a single direction rate while Chapter 5 presents a bi-directional rate. A Time-of-use (TOU) rate is combined with the real-time frequency based price to lower energy bills for a residential prosumer with ESS, in agreement with the proposed day-ahead and real-time energy management framework. The cost to the ESS is also considered in this section. Linear programming and strategic rule based methods are utilized to find the lowest energy bill. As a result, prosumers can use ESS to balance the grid, reducing their bill as much per kWh as PV or DG under a TOU net-metering price scheme, while providing distributed frequency support to the grid authority. The variability of the frequency based rate is similar to variability in the stock market, which gives a sense of how prosumers will interact with variable prices in a system supported by The Energy Internet.

Time and Frequency Activities at the U.S. Naval Observatory

DTIC Science & Technology

2005-01-01

Naval Observatory, Washington, D.C.), pp. 325-332. [15] D. Kirchner, 1999, “Two Way Satellite Time and Frequency Transfer ( TWSTFT ),” Review of...of Carrier- Phase-Based Two-Way Satellite Time and Frequency Transfer ( TWSTFT ),” in Proceedings of the 36th Annual Precise Time and Time Interval

Analysis of dual-frequency MEMS antenna using H-MRTD method

NASA Astrophysics Data System (ADS)

Yu, Wenge; Zhong, Xianxin; Chen, Yu; Wu, Zhengzhong

2004-10-01

For applying micro/nano technologies and Micro-Electro-Mechanical System (MEMS) technologies in the Radio Frequency (RF) field to manufacture miniature microstrip antennas. A novel MEMS dual-band patch antenna designed using slot-loaded and short-circuited size-reduction techniques is presented in this paper. By controlling the short-plane width, the two resonant frequencies, f10 and f30, can be significantly reduced and the frequency ratio (f30/f10) is tunable in the range 1.7~2.3. The Haar-Wavelet-Based multiresolution time domain (H-MRTD) with compactly supported scaling function for a full three-dimensional (3-D) wave to Yee's staggered cell is used for modeling and analyzing the antenna for the first time. Associated with practical model, an uniaxial perfectly matched layer (UPML) absorbing boundary conditions was developed, In addition , extending the mathematical formulae to an inhomogenous media. Numerical simulation results are compared with those using the conventional 3-D finite-difference time-domain (FDTD) method and measured. It has been demonstrated that, with this technique, space discretization with only a few cells per wavelength gives accurate results, leading to a reduction of both memory requirement and computation time.

Amplitude variations in the sdBV star PG 1605+072: Another beating time scale?

NASA Astrophysics Data System (ADS)

Pereira, T. M. D.; Lopes, I. P.

2004-10-01

PG 1605+072 has an unique and complex oscillation spectrum amongst the pulsating members of the EC 14026 stars. It has the longest periods and the richest, most puzzling frequency spectrum. We present a quantitative analysis of the photometric time-series obtained at 1-m telescope of the South African Astronomical Observatory. Thirteen oscillation parameters, frequencies, amplitudes and initial phases were determined from a 45 h time-series. Our work confirm previous observational results. The observed frequencies are within a difference smaller than 2.7% of the theoretical values, and less than 0.1% of other previous studies. We also infer the existence of variation of a periodicity of 4-5 days on the amplitude of the observed modes, similar to the yearly time-scale variation found by previous studies. Furthermore, we found a new frequency of 2133 μ Hz which has not been previously reported, its origin being yet unclear. Based on observations obtained at the South African Astronomical Observatory (SAAO). This research was supported by a grant from Fundação da Ciência e Tecnologia, grant No. PESO/P/PRO/40142/2000.

Time frequency power profile of QRS complex obtained with wavelet transform in spontaneously hypertensive rats.

PubMed

Takano, Nami K; Tsutsumi, Takeshi; Suzuki, Hiroshi; Okamoto, Yoshiwo; Nakajima, Toshiaki

2012-02-01

We evaluated whether frequency analysis could detect the development of interstitial fibrosis in rats. SHR/Izm and age-matched WKY/Izm were used. Limb lead II electrocardiograms were recorded. Continuous wavelet transform (CWT) was applied for the time-frequency analysis. The integrated time-frequency power (ITFP) between QRS complexes was measured and compared between groups. The ITFP at low-frequency bands (≤125Hz) was significantly higher in SHR/Izm. The percent change of ITFP showed the different patterns between groups. Prominent interstitial fibrosis with an increase in TIMP-1 mRNA expression was also observed in SHR/Izm. These results were partly reproduced in a computer simulation. Copyright © 2011 Elsevier Ltd. All rights reserved.

Localization of optic disc and fovea in retinal images using intensity based line scanning analysis.

PubMed

Kamble, Ravi; Kokare, Manesh; Deshmukh, Girish; Hussin, Fawnizu Azmadi; Mériaudeau, Fabrice

2017-08-01

Accurate detection of diabetic retinopathy (DR) mainly depends on identification of retinal landmarks such as optic disc and fovea. Present methods suffer from challenges like less accuracy and high computational complexity. To address this issue, this paper presents a novel approach for fast and accurate localization of optic disc (OD) and fovea using one-dimensional scanned intensity profile analysis. The proposed method utilizes both time and frequency domain information effectively for localization of OD. The final OD center is located using signal peak-valley detection in time domain and discontinuity detection in frequency domain analysis. However, with the help of detected OD location, the fovea center is located using signal valley analysis. Experiments were conducted on MESSIDOR dataset, where OD was successfully located in 1197 out of 1200 images (99.75%) and fovea in 1196 out of 1200 images (99.66%) with an average computation time of 0.52s. The large scale evaluation has been carried out extensively on nine publicly available databases. The proposed method is highly efficient in terms of quickly and accurately localizing OD and fovea structure together compared with the other state-of-the-art methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

Cluster analysis of word frequency dynamics

NASA Astrophysics Data System (ADS)

Maslennikova, Yu S.; Bochkarev, V. V.; Belashova, I. A.

2015-01-01

This paper describes the analysis and modelling of word usage frequency time series. During one of previous studies, an assumption was put forward that all word usage frequencies have uniform dynamics approaching the shape of a Gaussian function. This assumption can be checked using the frequency dictionaries of the Google Books Ngram database. This database includes 5.2 million books published between 1500 and 2008. The corpus contains over 500 billion words in American English, British English, French, German, Spanish, Russian, Hebrew, and Chinese. We clustered time series of word usage frequencies using a Kohonen neural network. The similarity between input vectors was estimated using several algorithms. As a result of the neural network training procedure, more than ten different forms of time series were found. They describe the dynamics of word usage frequencies from birth to death of individual words. Different groups of word forms were found to have different dynamics of word usage frequency variations.

Weld pool oscillation during pulsed GTA welding

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aendenroomer, A.J.R.; Ouden, G. den

1996-12-31

This paper deals with weld pool oscillation during pulsed GTA welding and with the possibility to use this oscillation for in-process control of weld penetration. Welding experiments were carried out under different welding conditions. During welding the weld pool was triggered into oscillation by the normal welding pulses or by extra current pulses. The oscillation frequency was measured both during the pulse time and during the base time by analyzing the arc voltage variation using a Fast Fourier Transformation program. Optimal results are obtained when full penetration occurs during the pulse time and partial penetration during the base time. Undermore » these conditions elliptical overlapping spot welds are formed. In the case of full penetration the weld pool oscillates in a low frequency mode (membrane oscillation), whereas in the case of partial penetration the weld pool oscillates in a high frequency mode (surface oscillation). Deviation from the optimal welding conditions occurs when high frequency oscillation is observed during both pulse time and base time (underpenetration) or when low frequency oscillation is observed during both pulse time and base time (overpenetration). In line with these results a penetration sensing system with feedback control was designed, based on the criterion that optimal weld penetration is achieved when two peaks are observed in the frequency distribution. The feasibility of this sensing system for orbital tube welding was confirmed by the results of experiments carried out under various welding conditions.« less

On the Limitations of Taylor’s Hypothesis in Parker Solar Probe’s Measurements near the Alfvén Critical Point

NASA Astrophysics Data System (ADS)

Bourouaine, Sofiane; Perez, Jean C.

2018-05-01

In this Letter, we present an analysis of two-point, two-time correlation functions from high-resolution numerical simulations of Reflection-driven Alfvén Turbulence near the Alfvén critical point r c. The simulations model the turbulence in a prescribed background solar wind model chosen to match observational constraints. This analysis allows us to investigate the temporal decorrelation of solar wind turbulence and the validity of Taylor’s approximation near the heliocentric distance r c, which Parker Solar Probe (PSP) is expected to explore in the coming years. The simulations show that the temporal decay of the Fourier-transformed turbulence decorrelation function is better described by a Gaussian model rather than a pure exponential time decay, and that the decorrelation frequency is almost linear with perpendicular wave number k ⊥ (perpendicular with respect to the background magnetic field {{\\boldsymbol{B}}}0). Based on the simulations, we conclude that Taylor’s approximation cannot be used in this instance to provide a connection between the frequency ω of the time signal (measured in the probe frame) and the wavevector k ⊥ of the fluctuations because the frequency k ⊥ V sc (V sc is the spacecraft speed) near r c is comparable to the estimated decorrelation frequency. However, the use of Taylor’s approximation still leads to the correct spectral indices of the power spectra measured at the spacecraft frame. In this Letter, based on a Gaussian model, we suggest a modified relationship between ω and k ⊥, which might be useful in the interpretation of future PSP measurements.

Fine structure of the low-frequency spectra of heart rate and blood pressure.

PubMed

Kuusela, Tom A; Kaila, Timo J; Kähönen, Mika

2003-10-13

The aim of this study was to explore the principal frequency components of the heart rate and blood pressure variability in the low frequency (LF) and very low frequency (VLF) band. The spectral composition of the R-R interval (RRI) and systolic arterial blood pressure (SAP) in the frequency range below 0.15 Hz were carefully analyzed using three different spectral methods: Fast Fourier transform (FFT), Wigner-Ville distribution (WVD), and autoregression (AR). All spectral methods were used to create time-frequency plots to uncover the principal spectral components that are least dependent on time. The accurate frequencies of these components were calculated from the pole decomposition of the AR spectral density after determining the optimal model order--the most crucial factor when using this method--with the help of FFT and WVD methods. Spectral analysis of the RRI and SAP of 12 healthy subjects revealed that there are always at least three spectral components below 0.15 Hz. The three principal frequency components are 0.026 +/- 0.003 (mean +/- SD) Hz, 0.076 +/- 0.012 Hz, and 0.117 +/- 0.016 Hz. These principal components vary only slightly over time. FFT-based coherence and phase-function analysis suggests that the second and third components are related to the baroreflex control of blood pressure, since the phase difference between SAP and RRI was negative and almost constant, whereas the origin of the first component is different since no clear SAP-RRI phase relationship was found. The above data indicate that spontaneous fluctuations in heart rate and blood pressure within the standard low-frequency range of 0.04-0.15 Hz typically occur at two frequency components rather than only at one as widely believed, and these components are not harmonically related. This new observation in humans can help explain divergent results in the literature concerning spontaneous low-frequency oscillations. It also raises methodological and computational questions regarding the usability and validity of the low-frequency spectral band when estimating sympathetic activity and baroreflex gain.

Damage detection and quantification in a structural model under seismic excitation using time-frequency analysis

NASA Astrophysics Data System (ADS)

Chan, Chun-Kai; Loh, Chin-Hsiung; Wu, Tzu-Hsiu

2015-04-01

In civil engineering, health monitoring and damage detection are typically carry out by using a large amount of sensors. Typically, most methods require global measurements to extract the properties of the structure. However, some sensors, like LVDT, cannot be used due to in situ limitation so that the global deformation remains unknown. An experiment is used to demonstrate the proposed algorithms: a one-story 2-bay reinforce concrete frame under weak and strong seismic excitation. In this paper signal processing techniques and nonlinear identification are used and applied to the response measurements of seismic response of reinforced concrete structures subject to different level of earthquake excitations. Both modal-based and signal-based system identification and feature extraction techniques are used to study the nonlinear inelastic response of RC frame using both input and output response data or output only measurement. From the signal-based damage identification method, which include the enhancement of time-frequency analysis of acceleration responses and the estimation of permanent deformation using directly from acceleration response data. Finally, local deformation measurement from dense optical tractor is also use to quantify the damage of the RC frame structure.

Analysis and development of fourth order LCLC resonant based capacitor charging power supply for pulse power applications.

PubMed

Naresh, P; Hitesh, C; Patel, A; Kolge, T; Sharma, Archana; Mittal, K C

2013-08-01

A fourth order (LCLC) resonant converter based capacitor charging power supply (CCPS) is designed and developed for pulse power applications. Resonant converters are preferred t utilize soft switching techniques such as zero current switching (ZCS) and zero voltage switching (ZVS). An attempt has been made to overcome the disadvantages in 2nd and 3rd resonant converter topologies; hence a fourth order resonant topology is used in this paper for CCPS application. In this paper a novel fourth order LCLC based resonant converter has been explored and mathematical analysis carried out to calculate load independent constant current. This topology provides load independent constant current at switching frequency (fs) equal to resonant frequency (fr). By changing switching condition (on time and dead time) this topology has both soft switching techniques such as ZCS and ZVS for better switching action to improve the converter efficiency. This novel technique has special features such as low peak current through switches, DC blocking for transformer, utilizing transformer leakage inductance as resonant component. A prototype has been developed and tested successfully to charge a 100 μF capacitor to 200 V.

Instantaneous Frequency Attribute Comparison

NASA Astrophysics Data System (ADS)

Yedlin, M. J.; Margrave, G. F.; Ben Horin, Y.

2013-12-01

The instantaneous seismic data attribute provides a different means of seismic interpretation, for all types of seismic data. It first came to the fore in exploration seismology in the classic paper of Taner et al (1979), entitled " Complex seismic trace analysis". Subsequently a vast literature has been accumulated on the subject, which has been given an excellent review by Barnes (1992). In this research we will compare two different methods of computation of the instantaneous frequency. The first method is based on the original idea of Taner et al (1979) and utilizes the derivative of the instantaneous phase of the analytic signal. The second method is based on the computation of the power centroid of the time-frequency spectrum, obtained using either the Gabor Transform as computed by Margrave et al (2011) or the Stockwell Transform as described by Stockwell et al (1996). We will apply both methods to exploration seismic data and the DPRK events recorded in 2006 and 2013. In applying the classical analytic signal technique, which is known to be unstable, due to the division of the square of the envelope, we will incorporate the stabilization and smoothing method proposed in the two paper of Fomel (2007). This method employs linear inverse theory regularization coupled with the application of an appropriate data smoother. The centroid method application is straightforward and is based on the very complete theoretical analysis provided in elegant fashion by Cohen (1995). While the results of the two methods are very similar, noticeable differences are seen at the data edges. This is most likely due to the edge effects of the smoothing operator in the Fomel method, which is more computationally intensive, when an optimal search of the regularization parameter is done. An advantage of the centroid method is the intrinsic smoothing of the data, which is inherent in the sliding window application used in all Short-Time Fourier Transform methods. The Fomel technique has a larger CPU run-time, resulting from the necessary matrix inversion. Barnes, Arthur E. "The calculation of instantaneous frequency and instantaneous bandwidth.", Geophysics, 57.11 (1992): 1520-1524. Fomel, Sergey. "Local seismic attributes.", Geophysics, 72.3 (2007): A29-A33. Fomel, Sergey. "Shaping regularization in geophysical-estimation problems." , Geophysics, 72.2 (2007): R29-R36. Stockwell, Robert Glenn, Lalu Mansinha, and R. P. Lowe. "Localization of the complex spectrum: the S transform."Signal Processing, IEEE Transactions on, 44.4 (1996): 998-1001. Taner, M. Turhan, Fulton Koehler, and R. E. Sheriff. "Complex seismic trace analysis." Geophysics, 44.6 (1979): 1041-1063. Cohen, Leon. "Time frequency analysis theory and applications."USA: Prentice Hall, (1995). Margrave, Gary F., Michael P. Lamoureux, and David C. Henley. "Gabor deconvolution: Estimating reflectivity by nonstationary deconvolution of seismic data." Geophysics, 76.3 (2011): W15-W30.

Real time analysis of voiced sounds

NASA Technical Reports Server (NTRS)

Hong, J. P. (Inventor)

1976-01-01

A power spectrum analysis of the harmonic content of a voiced sound signal is conducted in real time by phase-lock-loop tracking of the fundamental frequency, (f sub 0) of the signal and successive harmonics (h sub 1 through h sub n) of the fundamental frequency. The analysis also includes measuring the quadrature power and phase of each frequency tracked, differentiating the power measurements of the harmonics in adjacent pairs, and analyzing successive differentials to determine peak power points in the power spectrum for display or use in analysis of voiced sound, such as for voice recognition.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thorpe, J. I.; Livas, J.; Maghami, P.

Arm locking is a proposed laser frequency stabilization technique for the Laser Interferometer Space Antenna (LISA), a gravitational-wave observatory sensitive in the milliHertz frequency band. Arm locking takes advantage of the geometric stability of the triangular constellation of three spacecraft that compose LISA to provide a frequency reference with a stability in the LISA measurement band that exceeds that available from a standard reference such as an optical cavity or molecular absorption line. We have implemented a time-domain simulation of a Kalman-filter-based arm-locking system that includes the expected limiting noise sources as well as the effects of imperfect a priorimore » knowledge of the constellation geometry on which the design is based. We use the simulation to study aspects of the system performance that are difficult to capture in a steady-state frequency-domain analysis such as frequency pulling of the master laser due to errors in estimates of heterodyne frequency. We find that our implementation meets requirements on both the noise and dynamic range of the laser frequency with acceptable tolerances and that the design is sufficiently insensitive to errors in the estimated constellation geometry that the required performance can be maintained for the longest continuous measurement intervals expected for the LISA mission.« less

Biosensor method and system based on feature vector extraction

DOEpatents

Greenbaum, Elias [Knoxville, TN; Rodriguez, Jr., Miguel; Qi, Hairong [Knoxville, TN; Wang, Xiaoling [San Jose, CA

2012-04-17

A method of biosensor-based detection of toxins comprises the steps of providing at least one time-dependent control signal generated by a biosensor in a gas or liquid medium, and obtaining a time-dependent biosensor signal from the biosensor in the gas or liquid medium to be monitored or analyzed for the presence of one or more toxins selected from chemical, biological or radiological agents. The time-dependent biosensor signal is processed to obtain a plurality of feature vectors using at least one of amplitude statistics and a time-frequency analysis. At least one parameter relating to toxicity of the gas or liquid medium is then determined from the feature vectors based on reference to the control signal.

Effect of Resistance Training Frequency on Gains in Muscular Strength: A Systematic Review and Meta-Analysis.

PubMed

Grgic, Jozo; Schoenfeld, Brad J; Davies, Timothy B; Lazinica, Bruno; Krieger, James W; Pedisic, Zeljko

2018-05-01

Current recommendations on resistance training (RT) frequency for gains in muscular strength are based on extrapolations from limited evidence on the topic, and thus their practical applicability remains questionable. To elucidate this issue, we conducted a systematic review and meta-analysis of the studies that compared muscular strength outcomes with different RT frequencies. To carry out this review, English-language literature searches of the PubMed/MEDLINE, Scopus, and SPORTDiscus databases were conducted. The meta-analysis was performed using a random-effects model. The meta-analysis models were generated with RT frequencies classified as a categorical variable as either 1, 2, 3, or 4+ times/week, or, if there were insufficient data in subgroup analyses, the training frequencies were categorized as 1, 2, or 3 times/week. Subgroup analyses were performed for potential moderators, including (1) training volume; (2) exercise selection for the 1 repetition maximum (RM) test (for both multi-joint and single-joint exercises); (3) upper and lower body strength gains; (4) training to muscular failure (for studies involving and not involving training to muscular failure); (5) age (for both middle-aged/older adults and young adults); and (6) sex (for men and for women). The methodological quality of studies was appraised using the modified Downs and Black checklist. A total of 22 studies were found to meet the inclusion criteria. The average score on the Downs and Black checklist was 18 (range 13-22 points). Four studies were classified as being of good methodological quality, while the rest were classified as being of moderate methodological quality. Results of the meta-analysis showed a significant effect (p = 0.003) of RT frequency on muscular strength gains. Effect sizes increased in magnitude from 0.74, 0.82, 0.93, and 1.08 for training 1, 2, 3, and 4+ times per week, respectively. A subgroup analysis of volume-equated studies showed no significant effect (p = 0.421) of RT frequency on muscular strength gains. The subgroup analysis for exercise selection for the 1RM test suggested a significant effect of RT frequency on multi-joint (p < 0.001), but not single-joint, 1RM test results (p = 0.324). The subgroup analysis for upper and lower body showed a significant effect of frequency (p = 0.004) for upper body, but not lower body, strength gains (p = 0.070). In the subgroup analysis for studies in which the training was and was not carried out to muscular failure, no significant effect of RT frequency was found. The subgroup analysis for the age groups suggested a significant effect of training frequency among young adults (p = 0.024), but not among middle-aged and older adults (p = 0.093). Finally, the subgroup analysis for sex indicated a significant effect of RT frequency on strength gains in women (p = 0.030), but not men (p = 0.190). The results of the present systematic review and meta-analysis suggest a significant effect of RT frequency as higher training frequencies are translated into greater muscular strength gains. However, these effects seem to be primarily driven by training volume because when the volume is equated, there was no significant effect of RT frequency on muscular strength gains. Thus, from a practical standpoint, greater training frequencies can be used for additional RT volume, which is then likely to result in greater muscular strength gains. However, it remains unclear whether RT frequency on its own has significant effects on strength gain. It seems that higher RT frequencies result in greater gains in muscular strength on multi-joint exercises in the upper body and in women, and, finally, in contrast to older adults, young individuals seem to respond more positively to greater RT frequencies. More evidence among resistance-trained individuals is needed as most of the current studies were performed in untrained participants.

Uncertainty in low-flow data from three streamflow-gaging stations on the upper Verde River, Arizona

USGS Publications Warehouse

Anning, D.W.; ,

2004-01-01

The evaluation of uncertainty in low-flow data collected from three streamflow-gaging stations on the upper Verde River, Arizona, was presented. In downstream order, the stations are Verde River near Paulden, Verde River near Clarkdale, and Verde River near Camp Verde. A monitoring objective of the evaluation was to characterize discharge of the lower flow regime through a variety of procedures such as frequency analysis and base-flow analysis. For Verde River near Paulden and near Camp Verde, the uncertainty of daily low flows can be reduced by decreasing the uncertainty of discharge-measurement frequency, or building an artificial control that would have a stable stage-discharge relation over time.

Real time system design of motor imagery brain-computer interface based on multi band CSP and SVM

NASA Astrophysics Data System (ADS)

Zhao, Li; Li, Xiaoqin; Bian, Yan

2018-04-01

Motion imagery (MT) is an effective method to promote the recovery of limbs in patients after stroke. Though an online MT brain computer interface (BCT) system, which apply MT, can enhance the patient's participation and accelerate their recovery process. The traditional method deals with the electroencephalogram (EEG) induced by MT by common spatial pattern (CSP), which is used to extract information from a frequency band. Tn order to further improve the classification accuracy of the system, information of two characteristic frequency bands is extracted. The effectiveness of the proposed feature extraction method is verified by off-line analysis of competition data and the analysis of online system.

Tourism climate and thermal comfort in Sun Moon Lake, Taiwan.

PubMed

Lin, Tzu-Ping; Matzarakis, Andreas

2008-03-01

Bioclimate conditions at Sun Moon Lake, one of Taiwan's most popular tourist destinations, are presented. Existing tourism-related climate is typically based on mean monthly conditions of air temperature and precipitation and excludes the thermal perception of tourists. This study presents a relatively more detailed analysis of tourism climate by using a modified thermal comfort range for both Taiwan and Western/Middle European conditions, presented by frequency analysis of 10-day intervals. Furthermore, an integrated approach (climate tourism information scheme) is applied to present the frequencies of each facet under particular criteria for each 10-day interval, generating a time-series of climate data with temporal resolution for tourists and tourism authorities.

Tourism climate and thermal comfort in Sun Moon Lake, Taiwan

NASA Astrophysics Data System (ADS)

Lin, Tzu-Ping; Matzarakis, Andreas

2008-03-01

Bioclimate conditions at Sun Moon Lake, one of Taiwan’s most popular tourist destinations, are presented. Existing tourism-related climate is typically based on mean monthly conditions of air temperature and precipitation and excludes the thermal perception of tourists. This study presents a relatively more detailed analysis of tourism climate by using a modified thermal comfort range for both Taiwan and Western/Middle European conditions, presented by frequency analysis of 10-day intervals. Furthermore, an integrated approach (climate tourism information scheme) is applied to present the frequencies of each facet under particular criteria for each 10-day interval, generating a time-series of climate data with temporal resolution for tourists and tourism authorities.

Flood frequency analysis for nonstationary annual peak records in an urban drainage basin

USGS Publications Warehouse

Villarini, G.; Smith, J.A.; Serinaldi, F.; Bales, J.; Bates, P.D.; Krajewski, W.F.

2009-01-01

Flood frequency analysis in urban watersheds is complicated by nonstationarities of annual peak records associated with land use change and evolving urban stormwater infrastructure. In this study, a framework for flood frequency analysis is developed based on the Generalized Additive Models for Location, Scale and Shape parameters (GAMLSS), a tool for modeling time series under nonstationary conditions. GAMLSS is applied to annual maximum peak discharge records for Little Sugar Creek, a highly urbanized watershed which drains the urban core of Charlotte, North Carolina. It is shown that GAMLSS is able to describe the variability in the mean and variance of the annual maximum peak discharge by modeling the parameters of the selected parametric distribution as a smooth function of time via cubic splines. Flood frequency analyses for Little Sugar Creek (at a drainage area of 110 km2) show that the maximum flow with a 0.01-annual probability (corresponding to 100-year flood peak under stationary conditions) over the 83-year record has ranged from a minimum unit discharge of 2.1 m3 s- 1 km- 2 to a maximum of 5.1 m3 s- 1 km- 2. An alternative characterization can be made by examining the estimated return interval of the peak discharge that would have an annual exceedance probability of 0.01 under the assumption of stationarity (3.2 m3 s- 1 km- 2). Under nonstationary conditions, alternative definitions of return period should be adapted. Under the GAMLSS model, the return interval of an annual peak discharge of 3.2 m3 s- 1 km- 2 ranges from a maximum value of more than 5000 years in 1957 to a minimum value of almost 8 years for the present time (2007). The GAMLSS framework is also used to examine the links between population trends and flood frequency, as well as trends in annual maximum rainfall. These analyses are used to examine evolving flood frequency over future decades. ?? 2009 Elsevier Ltd.

Frequency comb-based multiple-access ultrastable frequency dissemination with 7 × 10(-17) instability.

PubMed

Zhang, Shuangyou; Zhao, Jianye

2015-01-01

In this letter, we demonstrate frequency-comb-based multiple-access ultrastable frequency dissemination over a 10-km single-mode fiber link. First, we synchronize optical pulse trains from an Er-fiber frequency comb to the remote site by using a simple and robust phase-conjugate stabilization method. The fractional frequency-transfer instability at the remote site is 2.6×10(-14) and 4.9×10(-17) for averaging times of 1 and 10,000 s, respectively. Then, we reproduce the harmonic of the repetition rate from the disseminated optical pulse trains at an arbitrary point along the fiber link to test comb-based multiple-access performance, and demonstrate frequency instability of 4×10(-14) and 7×10(-17) at 1 and 10,000 s averaging time, respectively. The proposed comb-based multiple-access frequency dissemination can easily achieve highly stable wideband microwave extraction along the whole link.

Modeling and evaluating the performance of Brillouin distributed optical fiber sensors.

PubMed

Soto, Marcelo A; Thévenaz, Luc

2013-12-16

A thorough analysis of the key factors impacting on the performance of Brillouin distributed optical fiber sensors is presented. An analytical expression is derived to estimate the error on the determination of the Brillouin peak gain frequency, based for the first time on real experimental conditions. This expression is experimentally validated, and describes how this frequency uncertainty depends on measurement parameters, such as Brillouin gain linewidth, frequency scanning step and signal-to-noise ratio. Based on the model leading to this expression and considering the limitations imposed by nonlinear effects and pump depletion, a figure-of-merit is proposed to fairly compare the performance of Brillouin distributed sensing systems. This figure-of-merit offers to the research community and to potential users the possibility to evaluate with an objective metric the real performance gain resulting from any proposed configuration.

Macro-motion detection using ultra-wideband impulse radar.

PubMed

Xin Li; Dengyu Qiao; Ye Li

2014-01-01

Radar has the advantage of being able to detect hidden individuals, which can be used in homeland security, disaster rescue, and healthcare monitoring-related applications. Human macro-motion detection using ultra-wideband impulse radar is studied in this paper. First, a frequency domain analysis is carried out to show that the macro-motion yields a bandpass signal in slow-time. Second, the FTFW (fast-time frequency windowing), which has the advantage of avoiding the measuring range reduction, and the HLF (high-pass linear-phase filter), which can preserve the motion signal effectively, are proposed to preprocess the radar echo. Last, a threshold decision method, based on the energy detector structure, is presented.

Relative importance of precipitation frequency and intensity in inter-annual variation of precipitation in Singapore during 1980-2013

NASA Astrophysics Data System (ADS)

Li, Xin; Babovic, Vladan

2017-04-01

Observed studies on inter-annual variation of precipitation provide insight into the response of precipitation to anthropogenic climate change and natural climate variability. Inter-annual variation of precipitation results from the concurrent variations of precipitation frequency and intensity, understanding of the relative importance of frequency and intensity in the variability of precipitation can help fathom its changing properties. Investigation of the long-term changes of precipitation schemes has been extensively carried out in many regions across the world, however, detailed studies of the relative importance of precipitation frequency and intensity in inter-annual variation of precipitation are still limited, especially in the tropics. Therefore, this study presents a comprehensive framework to investigate the inter-annual variation of precipitation and the dominance of precipitation frequency and intensity in a tropical urban city-state, Singapore, based on long-term (1980-2013) daily precipitation series from 22 rain gauges. First, an iterative Mann-Kendall trend test method is applied to detect long-term trends in precipitation total, frequency and intensity at both annual and seasonal time scales. Then, the relative importance of precipitation frequency and intensity in inducing the inter-annual variation of wet-day precipitation total is analyzed using a dominance analysis method based on linear regression. The results show statistically significant upward trends in wet-day precipitation total, frequency and intensity at annual time scale, however, these trends are not evident during the monsoon seasons. The inter-annual variation of wet-day precipitation is mainly dominated by precipitation intensity for most of the stations at annual time scale and during the Northeast monsoon season. However, during the Southwest monsoon season, the inter-annual variation of wet-day precipitation is mainly dominated by precipitation frequency. These results have implications for water resources management practices in Singapore.

TDR method for determine IC's parameters

NASA Astrophysics Data System (ADS)

Timoshenkov, V.; Rodionov, D.; Khlybov, A.

2016-12-01

Frequency domain simulation is a widely used approach for determine integrated circuits parameters. This approach can be found in most of software tools used in IC industry. Time domain simulation approach shows intensive usage last years due to some advantages. In particular it applicable for analysis of nonlinear and nonstationary systems where frequency domain is inapplicable. Resolution of time domain systems allow see heterogeneities on distance 1mm, determine it parameters and properties. Authors used approach based on detecting reflected signals from heterogeneities - time domain reflectometry (TDR). Field effect transistor technology scaling up to 30-60nm gate length and 10nm gate dielectric, heterojunction bi-polar transistors with 10-30nm base width allows fabricate digital IC's with 20GHz clock frequency and RF-IC's with tens GHz bandwidth. Such devices and operation speed suppose transit signal by use microwave lines. There are local heterogeneities can be found inside of the signal path due to connections between different parts of signal lines (stripe line-RF-connector pin, stripe line - IC package pin). These heterogeneities distort signals that cause bandwidth decrease for RF-devices. Time domain research methods of transmission and reflected signals give the opportunities to determine heterogeneities, it properties, parameters and built up equivalent circuits. Experimental results are provided and show possibility for inductance and capacitance measurement up to 25GHz. Measurements contains result of signal path research on IC and printed circuit board (PCB) used for 12GHz RF chips. Also dielectric constant versus frequency was measured up to 35GHz.

An energy-efficient readout circuit for resonant sensors based on ring-down measurement

NASA Astrophysics Data System (ADS)

Zeng, Z.; Pertijs, M. A. P.; Karabacak, D. M.

2013-02-01

This paper presents an energy-efficient readout circuit for resonant sensors that operates based on a transient measurement method. The resonant sensor is driven at a frequency close to its resonance frequency by an excitation source that can be intermittently disconnected, causing the sensor to oscillate at its resonance frequency with exponentially decaying amplitude. By counting the zero crossings of this ring-down response, the interface circuit can detect the resonance frequency. In contrast with oscillator-based readout, the presented readout circuit is readily able to detect quality factor (Q) of the resonator from the envelope of the ring-down response, and can be used even in the presence of large parasitic capacitors. A prototype of the readout circuit has been integrated in 0.35 μm CMOS technology, and consumes only 36 μA from a 3.3 V supply during a measurement time of 2 ms. The resonance frequency and quality factor of a micro-machined SiN resonator obtained using this prototype are in good agreement with results obtained using impedance analysis. Furthermore, a clear transient response is observed to ethanol flow using the presented readout, demonstrating the use of this technique in sensing applications.

The Design and Operation of Ultra-Sensitive and Tunable Radio-Frequency Interferometers.

PubMed

Cui, Yan; Wang, Pingshan

2014-12-01

Dielectric spectroscopy (DS) is an important technique for scientific and technological investigations in various areas. DS sensitivity and operating frequency ranges are critical for many applications, including lab-on-chip development where sample volumes are small with a wide range of dynamic processes to probe. In this work, we present the design and operation considerations of radio-frequency (RF) interferometers that are based on power-dividers (PDs) and quadrature-hybrids (QHs). Such interferometers are proposed to address the sensitivity and frequency tuning challenges of current DS techniques. Verified algorithms together with mathematical models are presented to quantify material properties from scattering parameters for three common transmission line sensing structures, i.e., coplanar waveguides (CPWs), conductor-backed CPWs, and microstrip lines. A high-sensitivity and stable QH-based interferometer is demonstrated by measuring glucose-water solution at a concentration level that is ten times lower than some recent RF sensors while our sample volume is ~1 nL. Composition analysis of ternary mixture solutions are also demonstrated with a PD-based interferometer. Further work is needed to address issues like system automation, model improvement at high frequencies, and interferometer scaling.

The level crossing rates and associated statistical properties of a random frequency response function

NASA Astrophysics Data System (ADS)

Langley, Robin S.

2018-03-01

This work is concerned with the statistical properties of the frequency response function of the energy of a random system. Earlier studies have considered the statistical distribution of the function at a single frequency, or alternatively the statistics of a band-average of the function. In contrast the present analysis considers the statistical fluctuations over a frequency band, and results are obtained for the mean rate at which the function crosses a specified level (or equivalently, the average number of times the level is crossed within the band). Results are also obtained for the probability of crossing a specified level at least once, the mean rate of occurrence of peaks, and the mean trough-to-peak height. The analysis is based on the assumption that the natural frequencies and mode shapes of the system have statistical properties that are governed by the Gaussian Orthogonal Ensemble (GOE), and the validity of this assumption is demonstrated by comparison with numerical simulations for a random plate. The work has application to the assessment of the performance of dynamic systems that are sensitive to random imperfections.

Sparse time-frequency decomposition based on dictionary adaptation.

PubMed

Hou, Thomas Y; Shi, Zuoqiang

2016-04-13

In this paper, we propose a time-frequency analysis method to obtain instantaneous frequencies and the corresponding decomposition by solving an optimization problem. In this optimization problem, the basis that is used to decompose the signal is not known a priori. Instead, it is adapted to the signal and is determined as part of the optimization problem. In this sense, this optimization problem can be seen as a dictionary adaptation problem, in which the dictionary is adaptive to one signal rather than a training set in dictionary learning. This dictionary adaptation problem is solved by using the augmented Lagrangian multiplier (ALM) method iteratively. We further accelerate the ALM method in each iteration by using the fast wavelet transform. We apply our method to decompose several signals, including signals with poor scale separation, signals with outliers and polluted by noise and a real signal. The results show that this method can give accurate recovery of both the instantaneous frequencies and the intrinsic mode functions. © 2016 The Author(s).

Tissue classification using depth-dependent ultrasound time series analysis: in-vitro animal study

NASA Astrophysics Data System (ADS)

Imani, Farhad; Daoud, Mohammad; Moradi, Mehdi; Abolmaesumi, Purang; Mousavi, Parvin

2011-03-01

Time series analysis of ultrasound radio-frequency (RF) signals has been shown to be an effective tissue classification method. Previous studies of this method for tissue differentiation at high and clinical-frequencies have been reported. In this paper, analysis of RF time series is extended to improve tissue classification at the clinical frequencies by including novel features extracted from the time series spectrum. The primary feature examined is the Mean Central Frequency (MCF) computed for regions of interest (ROIs) in the tissue extending along the axial axis of the transducer. In addition, the intercept and slope of a line fitted to the MCF-values of the RF time series as a function of depth have been included. To evaluate the accuracy of the new features, an in vitro animal study is performed using three tissue types: bovine muscle, bovine liver, and chicken breast, where perfect two-way classification is achieved. The results show statistically significant improvements over the classification accuracies with previously reported features.

Appropriate control time constant in relation to characteristics of the baroreflex vascular system in 1/R control of the total artificial heart.

PubMed

Mizuta, Sora; Saito, Itsuro; Isoyama, Takashi; Hara, Shintaro; Yurimoto, Terumi; Li, Xinyang; Murakami, Haruka; Ono, Toshiya; Mabuchi, Kunihiko; Abe, Yusuke

2017-09-01

1/R control is a physiological control method of the total artificial heart (TAH) with which long-term survival was obtained with animal experiments. However, 1/R control occasionally diverged in the undulation pump TAH (UPTAH) animal experiment. To improve the control stability of the 1/R control, appropriate control time constant in relation to characteristics of the baroreflex vascular system was investigated with frequency analysis and numerical simulation. In the frequency analysis, data of five goats in which the UPTAH was implanted were analyzed with first Fourier transform technique to examine the vasomotion frequency. The numerical simulation was carried out repeatedly changing baroreflex parameters and control time constant using the elements-expanded Windkessel model. Results of the frequency analysis showed that the 1/R control tended to diverge when very low frequency band that was an indication of the vasomotion frequency was relative high. In numerical simulation, divergence of the 1/R control could be reproduced and the boundary curves between the divergence and convergence of the 1/R control varied depending on the control time constant. These results suggested that the 1/R control tended to be unstable when the TAH recipient had high reflex speed in the baroreflex vascular system. Therefore, the control time constant should be adjusted appropriately with the individual vasomotion frequency.

A practical approach to tramway track condition monitoring: vertical track defects detection and identification using time-frequency processing technique

NASA Astrophysics Data System (ADS)

Bocz, Péter; Vinkó, Ákos; Posgay, Zoltán

2018-03-01

This paper presents an automatic method for detecting vertical track irregularities on tramway operation using acceleration measurements on trams. For monitoring of tramway tracks, an unconventional measurement setup is developed, which records the data of 3-axes wireless accelerometers mounted on wheel discs. Accelerations are processed to obtain the vertical track irregularities to determine whether the track needs to be repaired. The automatic detection algorithm is based on time-frequency distribution analysis and determines the defect locations. Admissible limits (thresholds) are given for detecting moderate and severe defects using statistical analysis. The method was validated on frequented tram lines in Budapest and accurately detected severe defects with a hit rate of 100%, with no false alarms. The methodology is also sensitive to moderate and small rail surface defects at the low operational speed.

Multi-frequency data analysis in AFM by wavelet transform

NASA Astrophysics Data System (ADS)

Pukhova, V.; Ferrini, G.

2017-10-01

Interacting cantilevers in AFM experiments generate non-stationary, multi-frequency signals consisting of numerous excited flexural and torsional modes and their harmonics. The analysis of such signals is challenging, requiring special methodological approaches and a powerful mathematical apparatus. The most common approach to the signal analysis is to apply Fourier transform analysis. However, FT gives accurate spectra for stationary signals, and for signals changing their spectral content over time, FT provides only an averaged spectrum. Hence, for non-stationary and rapidly varying signals, such as those from interacting cantilevers, a method that shows the spectral evolution in time is needed. One of the most powerful techniques, allowing detailed time-frequency representation of signals, is the wavelet transform. It is a method of analysis that allows representation of energy associated to the signal at a particular frequency and time, providing correlation between the spectral and temporal features of the signal, unlike FT. This is particularly important in AFM experiments because signals nonlinearities contains valuable information about tip-sample interactions and consequently surfaces properties. The present work is aimed to show the advantages of wavelet transform in comparison with FT using as an example the force curve analysis in dynamic force spectroscopy.

Time and Frequency Activities at the U.S. Naval Observatory

DTIC Science & Technology

2007-01-01

Time and Frequency Transfer ( TWSTFT ),” Review of Radio Science (Oxford Science Publications), pp. 27-44. 14 38th Annual Precise Time and Time Interval...Fonville, D. Matsakis, W. Shäfer, and A. Pawlitzki, 2005, “Development of Carrier- Phase-Based Two-Way Satellite Time and Frequency Transfer ( TWSTFT

Electrodermal Activity Is Sensitive to Cognitive Stress under Water.

PubMed

Posada-Quintero, Hugo F; Florian, John P; Orjuela-Cañón, Alvaro D; Chon, Ki H

2017-01-01

When divers are at depth in water, the high pressure and low temperature alone can cause severe stress, challenging the human physiological control systems. The addition of cognitive stress, for example during a military mission, exacerbates the challenge. In these conditions, humans are more susceptible to autonomic imbalance. Reliable tools for the assessment of the autonomic nervous system (ANS) could be used as indicators of the relative degree of stress a diver is experiencing, which could reveal heightened risk during a mission. Electrodermal activity (EDA), a measure of the changes in conductance at the skin surface due to sweat production, is considered a promising alternative for the non-invasive assessment of sympathetic control of the ANS. EDA is sensitive to stress of many kinds. Therefore, as a first step, we tested the sensitivity of EDA, in the time and frequency domains, specifically to cognitive stress during water immersion of the subject (albeit with their measurement finger dry for safety). The data from 14 volunteer subjects were used from the experiment. After a 4-min adjustment and baseline period after being immersed in water, subjects underwent the Stroop task, which is known to induce cognitive stress. The time-domain indices of EDA, skin conductance level (SCL) and non-specific skin conductance responses (NS.SCRs), did not change during cognitive stress, compared to baseline measurements. Frequency-domain indices of EDA, EDASymp (based on power spectral analysis) and TVSymp (based on time-frequency analysis), did significantly change during cognitive stress. This leads to the conclusion that EDA, assessed by spectral analysis, is sensitive to cognitive stress in water-immersed subjects, and can potentially be used to detect cognitive stress in divers.

Ultrasonic data compression via parameter estimation.

PubMed

Cardoso, Guilherme; Saniie, Jafar

2005-02-01

Ultrasonic imaging in medical and industrial applications often requires a large amount of data collection. Consequently, it is desirable to use data compression techniques to reduce data and to facilitate the analysis and remote access of ultrasonic information. The precise data representation is paramount to the accurate analysis of the shape, size, and orientation of ultrasonic reflectors, as well as to the determination of the properties of the propagation path. In this study, a successive parameter estimation algorithm based on a modified version of the continuous wavelet transform (CWT) to compress and denoise ultrasonic signals is presented. It has been shown analytically that the CWT (i.e., time x frequency representation) yields an exact solution for the time-of-arrival and a biased solution for the center frequency. Consequently, a modified CWT (MCWT) based on the Gabor-Helstrom transform is introduced as a means to exactly estimate both time-of-arrival and center frequency of ultrasonic echoes. Furthermore, the MCWT also has been used to generate a phase x bandwidth representation of the ultrasonic echo. This representation allows the exact estimation of the phase and the bandwidth. The performance of this algorithm for data compression and signal analysis is studied using simulated and experimental ultrasonic signals. The successive parameter estimation algorithm achieves a data compression ratio of (1-5N/J), where J is the number of samples and N is the number of echoes in the signal. For a signal with 10 echoes and 2048 samples, a compression ratio of 96% is achieved with a signal-to-noise ratio (SNR) improvement above 20 dB. Furthermore, this algorithm performs robustly, yields accurate echo estimation, and results in SNR enhancements ranging from 10 to 60 dB for composite signals having SNR as low as -10 dB.

4D monitoring of actively failing rockslopes

NASA Astrophysics Data System (ADS)

Rosser, Nick; Williams, Jack; Hardy, Richard; Brain, Matthew

2017-04-01

Assessing the conditions which promote rockfall to collapse relies upon detailed monitoring, ideally before, during and immediately after failure. With standard repeat surveys it is common that surveys do not coincide with or capture precursors, or that surveys are widely spaced relative to the timing and duration of driving forces such as storms. As a result gaining insight into the controls on failure and the timescales over which precursors operate remains difficult to establish with certainty, and establishing direct links between environmental conditions and rock-falls, or sequences of events prior to rockfall, remain difficult to define. To address this, we present analysis of a high-frequency 3D laser scan dataset captured using a new permanently installed system developed to constantly monitor actively failing rock slopes. The system is based around a time of flight laser scanner, integrated with and remotely controlled by dedicated controls and analysis software. The system is configured to capture data at 0.1 m spacing across > 22,000 m3 at up to 30 minute intervals. Here we present results captured with this system over a period of 9 months, spanning spring to winter 2015. Our analysis is focussed upon improving the understanding of the nature of small (< 1m^3) rockfalls falling from near vertical rock cliffs. We focus here on the development of a set of algorithms for differencing that trade-off the temporal resolution of frequent surveys (hourly) against high spatial resolution point clouds (< 0.05 m) to enhance the precision of change detection, allowing both deformation and detachments to be monitored through time. From this dataset we derive rockfall volume frequency distributions based upon short-interval surveys, and identify the presence and/or absence of precursors, in what we believe to be the first constant volumetric measurement of rock face erosion. The results hold implications for understanding of rockfall mechanics, but also for how actively eroding surfaces can be monitored at high temporal frequency. Whilst high frequency data is ideal for describing processes that evolve rapidly through time, the cumulative errors that accumulate when monitored changes are dominated by inverse power-law distributed volumes are significant. To conclude we consider the benefits of defining survey frequency on the basis of the changes being detected relative to the accumulation of errors that inevitably arises when comparing high numbers of sequential surveys.

Characteristics of Dry Chin-Tuck Swallowing Vibrations and Sounds

PubMed Central

Dudik, Joshua M; Jestrović, Iva; Luan, Bo; Coyle, James L.; Sejdić, Ervin

2015-01-01

Objective The effects of the chin-tuck maneuver, a technique commonly employed to compensate for dysphagia, on cervical auscultation are not fully understood. Characterizing a technique that is known to affect swallowing function is an important step on the way to developing a new instrumentation-based swallowing screening tool. Methods In this study, we recorded data from 55 adult participants who each completed five saliva swallows in a chin-tuck position. The resulting data was processed using previously designed filtering and segmentation algorithms. We then calculated 9 time, frequency, and time-frequency domain features for each independent signal. Results We found that multiple frequency and time domain features varied significantly between male and female subjects as well as between swallowing sounds and vibrations. However, our analysis showed that participant age did not play a significant role on the values of the extracted features. Finally, we found that various frequency features corresponding to swallowing vibrations did demonstrate statistically significant variation between the neutral and chin-tuck positions but sounds showed no changes between these two positions. Conclusion The chin-tuck maneuver affects many facets of swallowing vibrations and sounds and its effects can be monitored via cervical auscultation. Significance These results suggest that a subject’s swallowing technique does need to be accounted for when monitoring their performance with cervical auscultation based instrumentation. PMID:25974926

Computer-Aided Design/Manufacturing (CAD/M) for High-Speed Interconnect.

DTIC Science & Technology

1981-10-01

are frequency sensitive and hence lend themselves to frequency domain ananlysis . Most of the classical microwave analysis is handled in the frequency ...capability integrated into a time-domain analysis program. This approach allows determination of frequency -dependent transmission line (interconnect...the items to consider in any interconnect study is that of the frequency range of interest. This determines whether the interconnections must be treated

Automatic classification of sleep stages based on the time-frequency image of EEG signals.

PubMed

Bajaj, Varun; Pachori, Ram Bilas

2013-12-01

In this paper, a new method for automatic sleep stage classification based on time-frequency image (TFI) of electroencephalogram (EEG) signals is proposed. Automatic classification of sleep stages is an important part for diagnosis and treatment of sleep disorders. The smoothed pseudo Wigner-Ville distribution (SPWVD) based time-frequency representation (TFR) of EEG signal has been used to obtain the time-frequency image (TFI). The segmentation of TFI has been performed based on the frequency-bands of the rhythms of EEG signals. The features derived from the histogram of segmented TFI have been used as an input feature set to multiclass least squares support vector machines (MC-LS-SVM) together with the radial basis function (RBF), Mexican hat wavelet, and Morlet wavelet kernel functions for automatic classification of sleep stages from EEG signals. The experimental results are presented to show the effectiveness of the proposed method for classification of sleep stages from EEG signals. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

The effect of area size and predation on the time to extinction of prairie vole populations. simulation studies via SERDYCA: a Spatially-Explicit Individual-Based Model of Rodent Dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kostova, T; Carlsen, T

2003-11-21

We present a spatially-explicit individual-based computational model of rodent dynamics, customized for the prairie vole species, M. Ochrogaster. The model is based on trophic relationships and represents important features such as territorial competition, mating behavior, density-dependent predation and dispersal out of the modeled spatial region. Vegetation growth and vole fecundity are dependent on climatic components. The results of simulations show that the model correctly predicts the overall temporal dynamics of the population density. Time-series analysis shows a very good match between the periods corresponding to the peak population density frequencies predicted by the model and the ones reported in themore » literature. The model is used to study the relation between persistence, landscape area and predation. We introduce the notions of average time to extinction (ATE) and persistence frequency to quantify persistence. While the ATE decreases with decrease of area, it is a bell-shaped function of the predation level: increasing for 'small' and decreasing for 'large' predation levels.« less

Three Dimensional Transient Analysis of Microstrip Circuits in Multilayered Anisotropic Media

DTIC Science & Technology

1994-01-18

time fat rfVWh ifl~ttUktOnS. watching e..,ing| galai• fld t gatlwnq and maintaningn~ te data needed. an cems~l~lzn andI reuiewing 1h cOllection Of...noise on the passive via are derived. The coupling responses in the frequency domain and crosstalk waveforms in the time domain for some multilayered...source, developed across the module-backplane connector. The finite-difference time -domain (FD-TD) technique, which is based on the discretization of

Static and Dynamic Frequency Scaling on Multicore CPUs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bao, Wenlei; Hong, Changwan; Chunduri, Sudheer

2016-12-28

Dynamic voltage and frequency scaling (DVFS) adapts CPU power consumption by modifying a processor’s operating frequency (and the associated voltage). Typical approaches employing DVFS involve default strategies such as running at the lowest or the highest frequency, or observing the CPU’s runtime behavior and dynamically adapting the voltage/frequency configuration based on CPU usage. In this paper, we argue that many previous approaches suffer from inherent limitations, such as not account- ing for processor-specific impact of frequency changes on energy for different workload types. We first propose a lightweight runtime-based approach to automatically adapt the frequency based on the CPU workload,more » that is agnostic of the processor characteristics. We then show that further improvements can be achieved for affine kernels in the application, using a compile-time characterization instead of run-time monitoring to select the frequency and number of CPU cores to use. Our framework relies on a one-time energy characterization of CPU-specific DVFS profiles followed by a compile-time categorization of loop-based code segments in the application. These are combined to determine a priori of the frequency and the number of cores to use to execute the application so as to optimize energy or energy-delay product, outperforming runtime approach. Extensive evaluation on 60 benchmarks and five multi-core CPUs show that our approach systematically outperforms the powersave Linux governor, while improving overall performance.« less

Hilbert-Huang spectral analysis for characterizing the intrinsic time-scales of variability in decennial time-series of surface solar radiation

NASA Astrophysics Data System (ADS)

Bengulescu, Marc; Blanc, Philippe; Wald, Lucien

2016-04-01

An analysis of the variability of the surface solar irradiance (SSI) at different local time-scales is presented in this study. Since geophysical signals, such as long-term measurements of the SSI, are often produced by the non-linear interaction of deterministic physical processes that may also be under the influence of non-stationary external forcings, the Hilbert-Huang transform (HHT), an adaptive, noise-assisted, data-driven technique, is employed to extract locally - in time and in space - the embedded intrinsic scales at which a signal oscillates. The transform consists of two distinct steps. First, by means of the Empirical Mode Decomposition (EMD), the time-series is "de-constructed" into a finite number - often small - of zero-mean components that have distinct temporal scales of variability, termed hereinafter the Intrinsic Mode Functions (IMFs). The signal model of the components is an amplitude modulation - frequency modulation (AM - FM) one, and can also be thought of as an extension of a Fourier series having both time varying amplitude and frequency. Following the decomposition, Hilbert spectral analysis is then employed on the IMFs, yielding a time-frequency-energy representation that portrays changes in the spectral contents of the original data, with respect to time. As measurements of surface solar irradiance may possibly be contaminated by the manifestation of different type of stochastic processes (i.e. noise), the identification of real, physical processes from this background of random fluctuations is of interest. To this end, an adaptive background noise null hypothesis is assumed, based on the robust statistical properties of the EMD when applied to time-series of different classes of noise (e.g. white, red or fractional Gaussian). Since the algorithm acts as an efficient constant-Q dyadic, "wavelet-like", filter bank, the different noise inputs are decomposed into components having the same spectral shape, but that are translated to the next lower octave in the spectral domain. Thus, when the sampling step is increased, the spectral shape of IMFs cannot remain at its original position, due to the new lower Nyquist frequency, and is instead pushed toward the lower scaled frequency. Based on these features, the identification of potential signals within the data should become possible without any prior knowledge of the background noises. When applying the above outlined procedure to decennial time-series of surface solar irradiance, only the component that has an annual time-scale of variability is shown to have statistical properties that diverge from those of noise. Nevertheless, the noise-like components are not completely devoid of information, as it is found that their AM components have a non-null rank correlation coefficient with the annual mode, i.e. the background noise intensity seems to be modulated by the seasonal cycle. The findings have possible implications on the modelling and forecast of the surface solar irradiance, by discriminating its deterministic from its quasi-stochastic constituents, at distinct local time-scales.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eto, Joseph H.; Parashar, Manu; Lewis, Nancy Jo

The Real Time System Operations (RTSO) 2006-2007 project focused on two parallel technical tasks: (1) Real-Time Applications of Phasors for Monitoring, Alarming and Control; and (2) Real-Time Voltage Security Assessment (RTVSA) Prototype Tool. The overall goal of the phasor applications project was to accelerate adoption and foster greater use of new, more accurate, time-synchronized phasor measurements by conducting research and prototyping applications on California ISO's phasor platform - Real-Time Dynamics Monitoring System (RTDMS) -- that provide previously unavailable information on the dynamic stability of the grid. Feasibility assessment studies were conducted on potential application of this technology for small-signal stabilitymore » monitoring, validating/improving existing stability nomograms, conducting frequency response analysis, and obtaining real-time sensitivity information on key metrics to assess grid stress. Based on study findings, prototype applications for real-time visualization and alarming, small-signal stability monitoring, measurement based sensitivity analysis and frequency response assessment were developed, factory- and field-tested at the California ISO and at BPA. The goal of the RTVSA project was to provide California ISO with a prototype voltage security assessment tool that runs in real time within California ISO?s new reliability and congestion management system. CERTS conducted a technical assessment of appropriate algorithms, developed a prototype incorporating state-of-art algorithms (such as the continuation power flow, direct method, boundary orbiting method, and hyperplanes) into a framework most suitable for an operations environment. Based on study findings, a functional specification was prepared, which the California ISO has since used to procure a production-quality tool that is now a part of a suite of advanced computational tools that is used by California ISO for reliability and congestion management.« less

An exploratory data analysis of electroencephalograms using the functional boxplots approach

PubMed Central

Ngo, Duy; Sun, Ying; Genton, Marc G.; Wu, Jennifer; Srinivasan, Ramesh; Cramer, Steven C.; Ombao, Hernando

2015-01-01

Many model-based methods have been developed over the last several decades for analysis of electroencephalograms (EEGs) in order to understand electrical neural data. In this work, we propose to use the functional boxplot (FBP) to analyze log periodograms of EEG time series data in the spectral domain. The functional bloxplot approach produces a median curve—which is not equivalent to connecting medians obtained from frequency-specific boxplots. In addition, this approach identifies a functional median, summarizes variability, and detects potential outliers. By extending FBPs analysis from one-dimensional curves to surfaces, surface boxplots are also used to explore the variation of the spectral power for the alpha (8–12 Hz) and beta (16–32 Hz) frequency bands across the brain cortical surface. By using rank-based nonparametric tests, we also investigate the stationarity of EEG traces across an exam acquired during resting-state by comparing the spectrum during the early vs. late phases of a single resting-state EEG exam. PMID:26347598

Noise modeling and analysis of an IMU-based attitude sensor: improvement of performance by filtering and sensor fusion

NASA Astrophysics Data System (ADS)

K., Nirmal; A. G., Sreejith; Mathew, Joice; Sarpotdar, Mayuresh; Suresh, Ambily; Prakash, Ajin; Safonova, Margarita; Murthy, Jayant

2016-07-01

We describe the characterization and removal of noises present in the Inertial Measurement Unit (IMU) MPU- 6050, which was initially used in an attitude sensor, and later used in the development of a pointing system for small balloon-borne astronomical payloads. We found that the performance of the IMU degraded with time because of the accumulation of different errors. Using Allan variance analysis method, we identified the different components of noise present in the IMU, and verified the results by the power spectral density analysis (PSD). We tried to remove the high-frequency noise using smooth filters such as moving average filter and then Savitzky Golay (SG) filter. Even though we managed to filter some high-frequency noise, these filters performance wasn't satisfactory for our application. We found the distribution of the random noise present in IMU using probability density analysis and identified that the noise in our IMU was white Gaussian in nature. Hence, we used a Kalman filter to remove the noise and which gave us good performance real time.

Post-processing of auditory steady-state responses to correct spectral leakage.

PubMed

Felix, Leonardo Bonato; de Sá, Antonio Mauricio Ferreira Leite Miranda; Mendes, Eduardo Mazoni Andrade Marçal; Moraes, Márcio Flávio Dutra

2009-06-30

Auditory steady-state responses (ASSRs) are electrical manifestations of brain due to high rate sound stimulation. These evoked responses can be used to assess the hearing capabilities of a subject in an objective, automatic fashion. Usually, the detection protocol is accomplished by frequency-domain techniques, such as magnitude-squared coherence, whose estimation is based on the fast Fourier transform (FFT) of several data segments. In practice, the FFT-based spectrum may spread out the energy of a given frequency to its side bins and this escape of energy in the spectrum is called spectral leakage. The distortion of the spectrum due to leakage may severely compromise statistical significance of objective detection. This work presents an offline, a posteriori method for spectral leakage minimization in the frequency-domain analysis of ASSRs using coherent sampling criterion and interpolation in time. The technique was applied to the local field potentials of 10 Wistar rats and the results, together with those from simulated data, indicate that a leakage-free analysis of ASSRs is possible for any dataset if the methods showed in this paper were followed.

Frequency Dynamics of the First Heart Sound

NASA Astrophysics Data System (ADS)

Wood, John Charles

Cardiac auscultation is a fundamental clinical tool but first heart sound origins and significance remain controversial. Previous clinical studies have implicated resonant vibrations of both the myocardium and the valves. Accordingly, the goals of this thesis were threefold, (1) to characterize the frequency dynamics of the first heart sound, (2) to determine the relative contribution of the myocardium and the valves in determining first heart sound frequency, and (3) to develop new tools for non-stationary signal analysis. A resonant origin for first heart sound generation was tested through two studies in an open-chest canine preparation. Heart sounds were recorded using ultralight acceleration transducers cemented directly to the epicardium. The first heart sound was observed to be non-stationary and multicomponent. The most dominant feature was a powerful, rapidly-rising frequency component that preceded mitral valve closure. Two broadband components were observed; the first coincided with mitral valve closure while the second significantly preceded aortic valve opening. The spatial frequency of left ventricular vibrations was both high and non-stationary which indicated that the left ventricle was not vibrating passively in response to intracardiac pressure fluctuations but suggested instead that the first heart sound is a propagating transient. In the second study, regional myocardial ischemia was induced by left coronary circumflex arterial occlusion. Acceleration transducers were placed on the ischemic and non-ischemic myocardium to determine whether ischemia produced local or global changes in first heart sound amplitude and frequency. The two zones exhibited disparate amplitude and frequency behavior indicating that the first heart sound is not a resonant phenomenon. To objectively quantify the presence and orientation of signal components, Radon transformation of the time -frequency plane was performed and found to have considerable potential for pattern classification. Radon transformation of the Wigner spectrum (Radon-Wigner transform) was derived to be equivalent to dechirping in the time and frequency domains. Based upon this representation, an analogy between time-frequency estimation and computed tomography was drawn. Cohen's class of time-frequency representations was subsequently shown to result from simple changes in reconstruction filtering parameters. Time-varying filtering, adaptive time-frequency transformation and linear signal synthesis were also performed from the Radon-Wigner representation.

Transient analysis of intercalation electrodes for parameter estimation

NASA Astrophysics Data System (ADS)

Devan, Sheba

An essential part of integrating batteries as power sources in any application, be it a large scale automotive application or a small scale portable application, is an efficient Battery Management System (BMS). The combination of a battery with the microprocessor based BMS (called "smart battery") helps prolong the life of the battery by operating in the optimal regime and provides accurate information regarding the battery to the end user. The main purposes of BMS are cell protection, monitoring and control, and communication between different components. These purposes are fulfilled by tracking the change in the parameters of the intercalation electrodes in the batteries. Consequently, the functions of the BMS should be prompt, which requires the methodology of extracting the parameters to be efficient in time. The traditional transient techniques applied so far may not be suitable due to reasons such as the inability to apply these techniques when the battery is under operation, long experimental time, etc. The primary aim of this research work is to design a fast, accurate and reliable technique that can be used to extract parameter values of the intercalation electrodes. A methodology based on analysis of the short time response to a sinusoidal input perturbation, in the time domain is demonstrated using a porous electrode model for an intercalation electrode. It is shown that the parameters associated with the interfacial processes occurring in the electrode can be determined rapidly, within a few milliseconds, by measuring the response in the transient region. The short time analysis in the time domain is then extended to a single particle model that involves bulk diffusion in the solid phase in addition to interfacial processes. A systematic procedure for sequential parameter estimation using sensitivity analysis is described. Further, the short time response and the input perturbation are transformed into the frequency domain using Fast Fourier Transform (FFT) to generate impedance spectra to derive immediate qualitative information regarding the nature of the system. The short time analysis technique gives the ability to perform both time domain and frequency domain analysis using data measured within short durations.

EEG-Based Brain-Computer Interface for Decoding Motor Imagery Tasks within the Same Hand Using Choi-Williams Time-Frequency Distribution

PubMed Central

Alwanni, Hisham; Baslan, Yara; Alnuman, Nasim; Daoud, Mohammad I.

2017-01-01

This paper presents an EEG-based brain-computer interface system for classifying eleven motor imagery (MI) tasks within the same hand. The proposed system utilizes the Choi-Williams time-frequency distribution (CWD) to construct a time-frequency representation (TFR) of the EEG signals. The constructed TFR is used to extract five categories of time-frequency features (TFFs). The TFFs are processed using a hierarchical classification model to identify the MI task encapsulated within the EEG signals. To evaluate the performance of the proposed approach, EEG data were recorded for eighteen intact subjects and four amputated subjects while imagining to perform each of the eleven hand MI tasks. Two performance evaluation analyses, namely channel- and TFF-based analyses, are conducted to identify the best subset of EEG channels and the TFFs category, respectively, that enable the highest classification accuracy between the MI tasks. In each evaluation analysis, the hierarchical classification model is trained using two training procedures, namely subject-dependent and subject-independent procedures. These two training procedures quantify the capability of the proposed approach to capture both intra- and inter-personal variations in the EEG signals for different MI tasks within the same hand. The results demonstrate the efficacy of the approach for classifying the MI tasks within the same hand. In particular, the classification accuracies obtained for the intact and amputated subjects are as high as 88.8% and 90.2%, respectively, for the subject-dependent training procedure, and 80.8% and 87.8%, respectively, for the subject-independent training procedure. These results suggest the feasibility of applying the proposed approach to control dexterous prosthetic hands, which can be of great benefit for individuals suffering from hand amputations. PMID:28832513

An alternative approach to measure similarity between two deterministic transient signals

NASA Astrophysics Data System (ADS)

Shin, Kihong

2016-06-01

In many practical engineering applications, it is often required to measure the similarity of two signals to gain insight into the conditions of a system. For example, an application that monitors machinery can regularly measure the signal of the vibration and compare it to a healthy reference signal in order to monitor whether or not any fault symptom is developing. Also in modal analysis, a frequency response function (FRF) from a finite element model (FEM) is often compared with an FRF from experimental modal analysis. Many different similarity measures are applicable in such cases, and correlation-based similarity measures may be most frequently used among these such as in the case where the correlation coefficient in the time domain and the frequency response assurance criterion (FRAC) in the frequency domain are used. Although correlation-based similarity measures may be particularly useful for random signals because they are based on probability and statistics, we frequently deal with signals that are largely deterministic and transient. Thus, it may be useful to develop another similarity measure that takes the characteristics of the deterministic transient signal properly into account. In this paper, an alternative approach to measure the similarity between two deterministic transient signals is proposed. This newly proposed similarity measure is based on the fictitious system frequency response function, and it consists of the magnitude similarity and the shape similarity. Finally, a few examples are presented to demonstrate the use of the proposed similarity measure.

Collaborative Research with Chinese, Indian, Filipino and North European Research Organizations on Infectious Disease Epidemics.

PubMed

Sumi, Ayako; Kobayashi, Nobumichi

2017-01-01

In this report, we present a short review of applications of time series analysis, which consists of spectral analysis based on the maximum entropy method in the frequency domain and the least squares method in the time domain, to the incidence data of infectious diseases. This report consists of three parts. First, we present our results obtained by collaborative research on infectious disease epidemics with Chinese, Indian, Filipino and North European research organizations. Second, we present the results obtained with the Japanese infectious disease surveillance data and the time series numerically generated from a mathematical model, called the susceptible/exposed/infectious/recovered (SEIR) model. Third, we present an application of the time series analysis to pathologic tissues to examine the usefulness of time series analysis for investigating the spatial pattern of pathologic tissue. It is anticipated that time series analysis will become a useful tool for investigating not only infectious disease surveillance data but also immunological and genetic tests.

Evaluation of image quality in terahertz pulsed imaging using test objects.

PubMed

Fitzgerald, A J; Berry, E; Miles, R E; Zinovev, N N; Smith, M A; Chamberlain, J M

2002-11-07

As with other imaging modalities, the performance of terahertz (THz) imaging systems is limited by factors of spatial resolution, contrast and noise. The purpose of this paper is to introduce test objects and image analysis methods to evaluate and compare THz image quality in a quantitative and objective way, so that alternative terahertz imaging system configurations and acquisition techniques can be compared, and the range of image parameters can be assessed. Two test objects were designed and manufactured, one to determine the modulation transfer functions (MTF) and the other to derive image signal to noise ratio (SNR) at a range of contrasts. As expected the higher THz frequencies had larger MTFs, and better spatial resolution as determined by the spatial frequency at which the MTF dropped below the 20% threshold. Image SNR was compared for time domain and frequency domain image parameters and time delay based images consistently demonstrated higher SNR than intensity based parameters such as relative transmittance because the latter are more strongly affected by the sources of noise in the THz system such as laser fluctuations and detector shot noise.

Joint Bearing and Range Estimation of Multiple Objects from Time-Frequency Analysis.

PubMed

Liu, Jeng-Cheng; Cheng, Yuang-Tung; Hung, Hsien-Sen

2018-01-19

Direction-of-arrival (DOA) and range estimation is an important issue of sonar signal processing. In this paper, a novel approach using Hilbert-Huang transform (HHT) is proposed for joint bearing and range estimation of multiple targets based on a uniform linear array (ULA) of hydrophones. The structure of this ULA based on micro-electro-mechanical systems (MEMS) technology, and thus has attractive features of small size, high sensitivity and low cost, and is suitable for Autonomous Underwater Vehicle (AUV) operations. This proposed target localization method has the following advantages: only a single snapshot of data is needed and real-time processing is feasible. The proposed algorithm transforms a very complicated nonlinear estimation problem to a simple nearly linear one via time-frequency distribution (TFD) theory and is verified with HHT. Theoretical discussions of resolution issue are also provided to facilitate the design of a MEMS sensor with high sensitivity. Simulation results are shown to verify the effectiveness of the proposed method.

Real-Time Monitoring of Psychotherapeutic Processes: Concept and Compliance

PubMed Central

Schiepek, Günter; Aichhorn, Wolfgang; Gruber, Martin; Strunk, Guido; Bachler, Egon; Aas, Benjamin

2016-01-01

Objective: The feasibility of a high-frequency real-time monitoring approach to psychotherapy is outlined and tested for patients' compliance to evaluate its integration to everyday practice. Criteria concern the ecological momentary assessment, the assessment of therapy-related cognitions and emotions, equidistant time sampling, real-time nonlinear time series analysis, continuous participative process control by client and therapist, and the application of idiographic (person-specific) surveys. Methods: The process-outcome monitoring is technically realized by an internet-based device for data collection and data analysis, the Synergetic Navigation System. Its feasibility is documented by a compliance study on 151 clients treated in an inpatient and a day-treatment clinic. Results: We found high compliance rates (mean: 78.3%, median: 89.4%) amongst the respondents, independent of the severity of symptoms or the degree of impairment. Compared to other diagnoses, the compliance rate was lower in the group diagnosed with personality disorders. Conclusion: The results support the feasibility of high-frequency monitoring in routine psychotherapy settings. Daily collection of psychological surveys allows for the assessment of highly resolved, equidistant time series data which gives insight into the nonlinear qualities of therapeutic change processes (e.g., pattern transitions, critical instabilities). PMID:27199837

cBathy: A robust algorithm for estimating nearshore bathymetry

USGS Publications Warehouse

Plant, Nathaniel G.; Holman, Rob; Holland, K. Todd

2013-01-01

A three-part algorithm is described and tested to provide robust bathymetry maps based solely on long time series observations of surface wave motions. The first phase consists of frequency-dependent characterization of the wave field in which dominant frequencies are estimated by Fourier transform while corresponding wave numbers are derived from spatial gradients in cross-spectral phase over analysis tiles that can be small, allowing high-spatial resolution. Coherent spatial structures at each frequency are extracted by frequency-dependent empirical orthogonal function (EOF). In phase two, depths are found that best fit weighted sets of frequency-wave number pairs. These are subsequently smoothed in time in phase 3 using a Kalman filter that fills gaps in coverage and objectively averages new estimates of variable quality with prior estimates. Objective confidence intervals are returned. Tests at Duck, NC, using 16 surveys collected over 2 years showed a bias and root-mean-square (RMS) error of 0.19 and 0.51 m, respectively but were largest near the offshore limits of analysis (roughly 500 m from the camera) and near the steep shoreline where analysis tiles mix information from waves, swash and static dry sand. Performance was excellent for small waves but degraded somewhat with increasing wave height. Sand bars and their small-scale alongshore variability were well resolved. A single ground truth survey from a dissipative, low-sloping beach (Agate Beach, OR) showed similar errors over a region that extended several kilometers from the camera and reached depths of 14 m. Vector wave number estimates can also be incorporated into data assimilation models of nearshore dynamics.

Effect of age, period and birth-cohort on the frequency of glucose-6-phosphate dehydrogenase deficiency in Sardinian adults.

PubMed

Pes, Giovanni Mario; Errigo, Alessandra; Bitti, Angela; Dore, Maria Pina

2018-02-01

Glucose-6-phosphate dehydrogenase (G6PD) deficiency is an inherited disorder common in Sardinia. In this study, the frequency variation of G6PD-deficiency across age groups and birth cohorts was investigated using Age-Period-Cohort analysis. Data were collected from the clinical records of 11,252 patients (6975 women, age range 17-94 years) who underwent endoscopy between 2000 and 2016 at a teaching hospital (University of Sassari), Italy. G6PD status was assessed by enzymatic assay based on G6PD/6GPD ratio. A Poisson log-linear regression model was used to identify age and time trend in G6PD deficiency. Enzyme deficiency was detected in 11.4% of the entire cohort (men: 7.9%; women: 13.6%). Age-Period-Cohort analysis showed no inflection points across age groups, especially after age 80. The effects of time period and birth cohorts on G6PD deficiency were negligible (frequencies before and after 1950 were 11.0% and 11.8%, respectively). These findings indicate that the frequency of G6PD deficiency does not vary significantly in oldest subjects. The lack of evidence for selection across the malaria eradication time may be explained by other factors, including somatic cell selection or misclassification of heterozygotes women as G6PD normal in the older birth cohorts. Additional molecular studies may help clarify these issues. Key message The frequency of glucose-6-phosphate dehydrogenase deficiency is stable across age groups and does not vary in generations born before or after malaria eradication.

On-line Monitoring for Cutting Tool Wear Condition Based on the Parameters

NASA Astrophysics Data System (ADS)

Han, Fenghua; Xie, Feng

2017-07-01

In the process of cutting tools, it is very important to monitor the working state of the tools. On the basis of acceleration signal acquisition under the constant speed, time domain and frequency domain analysis of relevant indicators monitor the online of tool wear condition. The analysis results show that the method can effectively judge the tool wear condition in the process of machining. It has certain application value.

Large-Eddy Simulation of Turbulent Wall-Pressure Fluctuations

NASA Technical Reports Server (NTRS)

Singer, Bart A.

1996-01-01

Large-eddy simulations of a turbulent boundary layer with Reynolds number based on displacement thickness equal to 3500 were performed with two grid resolutions. The computations were continued for sufficient time to obtain frequency spectra with resolved frequencies that correspond to the most important structural frequencies on an aircraft fuselage. The turbulent stresses were adequately resolved with both resolutions. Detailed quantitative analysis of a variety of statistical quantities associated with the wall-pressure fluctuations revealed similar behavior for both simulations. The primary differences were associated with the lack of resolution of the high-frequency data in the coarse-grid calculation and the increased jitter (due to the lack of multiple realizations for averaging purposes) in the fine-grid calculation. A new curve fit was introduced to represent the spanwise coherence of the cross-spectral density.

A developed nearly analytic discrete method for forward modeling in the frequency domain

NASA Astrophysics Data System (ADS)

Liu, Shaolin; Lang, Chao; Yang, Hui; Wang, Wenshuai

2018-02-01

High-efficiency forward modeling methods play a fundamental role in full waveform inversion (FWI). In this paper, the developed nearly analytic discrete (DNAD) method is proposed to accelerate frequency-domain forward modeling processes. We first derive the discretization of frequency-domain wave equations via numerical schemes based on the nearly analytic discrete (NAD) method to obtain a linear system. The coefficients of numerical stencils are optimized to make the linear system easier to solve and to minimize computing time. Wavefield simulation and numerical dispersion analysis are performed to compare the numerical behavior of DNAD method with that of the conventional NAD method. The results demonstrate the superiority of our proposed method. Finally, the DNAD method is implemented in frequency-domain FWI, and high-resolution inverse results are obtained.

Frequency- and Time-Domain Methods in Soil-Structure Interaction Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bolisetti, Chandrakanth; Whittaker, Andrew S.; Coleman, Justin L.

2015-06-01

Soil-structure interaction (SSI) analysis in the nuclear industry is currently performed using linear codes that function in the frequency domain. There is a consensus that these frequency-domain codes give reasonably accurate results for low-intensity ground motions that result in almost linear response. For higher intensity ground motions, which may result in nonlinear response in the soil, structure or at the vicinity of the foundation, the adequacy of frequency-domain codes is unproven. Nonlinear analysis, which is only possible in the time domain, is theoretically more appropriate in such cases. These methods are available but are rarely used due to the largemore » computational requirements and a lack of experience with analysts and regulators. This paper presents an assessment of the linear frequency-domain code, SASSI, which is widely used in the nuclear industry, and the time-domain commercial finite-element code, LS-DYNA, for SSI analysis. The assessment involves benchmarking the SSI analysis procedure in LS-DYNA against SASSI for linearly elastic models. After affirming that SASSI and LS-DYNA result in almost identical responses for these models, they are used to perform nonlinear SSI analyses of two structures founded on soft soil. An examination of the results shows that, in spite of using identical material properties, the predictions of frequency- and time-domain codes are significantly different in the presence of nonlinear behavior such as gapping and sliding of the foundation.« less

Past crops yield dynamics reconstruction from tree-ring chronologies in the forest-steppe zone based on low- and high-frequency components

NASA Astrophysics Data System (ADS)

Babushkina, Elena A.; Belokopytova, Liliana V.; Shah, Santosh K.; Zhirnova, Dina F.

2018-05-01

Interrelations of the yield variability of the main crops (wheat, barley, and oats) with hydrothermal regime and growth of conifer trees ( Pinus sylvestris and Larix sibirica) in forest-steppes were investigated in Khakassia, South Siberia. An attempt has been made to understand the role and mechanisms of climatic impact on plants productivity. It was found that amongst variables describing moisture supply, wetness index had maximum impact. Strength of climatic response and correlations with tree growth are different for rain-fed and irrigated crops yield. Separated high-frequency variability components of yield and tree-ring width have more pronounced relationships between each other and with climatic variables than their chronologies per se. Corresponding low-frequency variability components are strongly correlated with maxima observed after 1- to 5-year time shift of tree-ring width. Results of analysis allowed us to develop original approach of crops yield dynamics reconstruction on the base of high-frequency variability component of the growth of pine and low-frequency one of larch.

Time-frequency feature representation using multi-resolution texture analysis and acoustic activity detector for real-life speech emotion recognition.

PubMed

Wang, Kun-Ching

2015-01-14

The classification of emotional speech is mostly considered in speech-related research on human-computer interaction (HCI). In this paper, the purpose is to present a novel feature extraction based on multi-resolutions texture image information (MRTII). The MRTII feature set is derived from multi-resolution texture analysis for characterization and classification of different emotions in a speech signal. The motivation is that we have to consider emotions have different intensity values in different frequency bands. In terms of human visual perceptual, the texture property on multi-resolution of emotional speech spectrogram should be a good feature set for emotion classification in speech. Furthermore, the multi-resolution analysis on texture can give a clearer discrimination between each emotion than uniform-resolution analysis on texture. In order to provide high accuracy of emotional discrimination especially in real-life, an acoustic activity detection (AAD) algorithm must be applied into the MRTII-based feature extraction. Considering the presence of many blended emotions in real life, in this paper make use of two corpora of naturally-occurring dialogs recorded in real-life call centers. Compared with the traditional Mel-scale Frequency Cepstral Coefficients (MFCC) and the state-of-the-art features, the MRTII features also can improve the correct classification rates of proposed systems among different language databases. Experimental results show that the proposed MRTII-based feature information inspired by human visual perception of the spectrogram image can provide significant classification for real-life emotional recognition in speech.

On Holo-Hilbert spectral analysis: a full informational spectral representation for nonlinear and non-stationary data

PubMed Central

Huang, Norden E.; Hu, Kun; Yang, Albert C. C.; Chang, Hsing-Chih; Jia, Deng; Liang, Wei-Kuang; Yeh, Jia Rong; Kao, Chu-Lan; Juan, Chi-Hung; Peng, Chung Kang; Meijer, Johanna H.; Wang, Yung-Hung; Long, Steven R.; Wu, Zhauhua

2016-01-01

The Holo-Hilbert spectral analysis (HHSA) method is introduced to cure the deficiencies of traditional spectral analysis and to give a full informational representation of nonlinear and non-stationary data. It uses a nested empirical mode decomposition and Hilbert–Huang transform (HHT) approach to identify intrinsic amplitude and frequency modulations often present in nonlinear systems. Comparisons are first made with traditional spectrum analysis, which usually achieved its results through convolutional integral transforms based on additive expansions of an a priori determined basis, mostly under linear and stationary assumptions. Thus, for non-stationary processes, the best one could do historically was to use the time–frequency representations, in which the amplitude (or energy density) variation is still represented in terms of time. For nonlinear processes, the data can have both amplitude and frequency modulations (intra-mode and inter-mode) generated by two different mechanisms: linear additive or nonlinear multiplicative processes. As all existing spectral analysis methods are based on additive expansions, either a priori or adaptive, none of them could possibly represent the multiplicative processes. While the earlier adaptive HHT spectral analysis approach could accommodate the intra-wave nonlinearity quite remarkably, it remained that any inter-wave nonlinear multiplicative mechanisms that include cross-scale coupling and phase-lock modulations were left untreated. To resolve the multiplicative processes issue, additional dimensions in the spectrum result are needed to account for the variations in both the amplitude and frequency modulations simultaneously. HHSA accommodates all the processes: additive and multiplicative, intra-mode and inter-mode, stationary and non-stationary, linear and nonlinear interactions. The Holo prefix in HHSA denotes a multiple dimensional representation with both additive and multiplicative capabilities. PMID:26953180

An image based vibration sensor for soft tissue modal analysis in a Digital Image Elasto Tomography (DIET) system.

PubMed

Feng, Sheng; Lotz, Thomas; Chase, J Geoffrey; Hann, Christopher E

2010-01-01

Digital Image Elasto Tomography (DIET) is a non-invasive elastographic breast cancer screening technology, based on image-based measurement of surface vibrations induced on a breast by mechanical actuation. Knowledge of frequency response characteristics of a breast prior to imaging is critical to maximize the imaging signal and diagnostic capability of the system. A feasibility analysis for a non-invasive image based modal analysis system is presented that is able to robustly and rapidly identify resonant frequencies in soft tissue. Three images per oscillation cycle are enough to capture the behavior at a given frequency. Thus, a sweep over critical frequency ranges can be performed prior to imaging to determine critical imaging settings of the DIET system to optimize its tumor detection performance.

Increasing sensitivity in the measurement of heart rate variability: the method of non-stationary RR time-frequency analysis.

PubMed

Melkonian, D; Korner, A; Meares, R; Bahramali, H

2012-10-01

A novel method of the time-frequency analysis of non-stationary heart rate variability (HRV) is developed which introduces the fragmentary spectrum as a measure that brings together the frequency content, timing and duration of HRV segments. The fragmentary spectrum is calculated by the similar basis function algorithm. This numerical tool of the time to frequency and frequency to time Fourier transformations accepts both uniform and non-uniform sampling intervals, and is applicable to signal segments of arbitrary length. Once the fragmentary spectrum is calculated, the inverse transform recovers the original signal and reveals accuracy of spectral estimates. Numerical experiments show that discontinuities at the boundaries of the succession of inter-beat intervals can cause unacceptable distortions of the spectral estimates. We have developed a measure that we call the "RR deltagram" as a form of the HRV data that minimises spectral errors. The analysis of the experimental HRV data from real-life and controlled breathing conditions suggests transient oscillatory components as functionally meaningful elements of highly complex and irregular patterns of HRV. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Inter-trial alignment of EEG data and phase-locking

NASA Astrophysics Data System (ADS)

Testorf, M. E.; Horak, P.; Connolly, A.; Holmes, G. L.; Jobst, B. C.

2015-09-01

Neuro-scientific studies are often aimed at imaging brain activity, which is time-locked to external stimuli. This provides the possibility to use statistical methods to extract even weak signal components, which occur with each stimulus. For electroencephalographic recordings this concept is limited by inevitable time jitter, which cannot be controlled in all cases. Our study is based on a cross-correlation analysis of trials to alignment trials based on the recorded data. This is demonstrated both with simulated signals and with clinical EEG data, which were recorded intracranially. Special attention is given to the evaluation of the time-frequency resolved phase-locking across multiple trails.

Synthesis, spectroscopic characterization, DFT studies and antifungal activity of (E)-4-amino-5-[N'-(2-nitro-benzylidene)-hydrazino]-2,4-dihydro-[1,2,4]triazole-3-thione

NASA Astrophysics Data System (ADS)

Joshi, Rachana; Pandey, Nidhi; Yadav, Swatantra Kumar; Tilak, Ragini; Mishra, Hirdyesh; Pokharia, Sandeep

2018-07-01

The hydrazino Schiff base (E)-4-amino-5-[N'-(2-nitro-benzylidene)-hydrazino]-2,4-dihydro-[1,2,4]triazole-3-thione was synthesized and structurally characterized by elemental analysis, FT-IR, Raman, 1H and 13C-NMR and UV-Vis studies. A density functional theory (DFT) based electronic structure calculations were accomplished at B3LYP/6-311++G(d,p) level of theory. A comparative analysis of calculated vibrational frequencies with experimental vibrational frequencies was carried out and significant bands were assigned. The results indicate a good correlation (R2 = 0.9974) between experimental and theoretical IR frequencies. The experimental 1H and 13C-NMR resonance signals were also compared to the calculated values. The theoretical UV-Vis spectral studies were carried out using time dependent-DFT method in gas phase and IEFPCM model in solvent field calculation. The geometrical parameters were calculated in the gas phase. Atomic charges at selected atoms were calculated by Mulliken population analysis (MPA), Hirshfeld population analysis (HPA) and Natural population analysis (NPA) schemes. The molecular electrostatic potential (MEP) map was calculated to assign reactive site on the surface of the molecule. The conceptual-DFT based global and local reactivity descriptors were calculated to obtain an insight into the reactivity behaviour. The frontier molecular orbital analysis was carried out to study the charge transfer within the molecule. The detailed natural bond orbital (NBO) analysis was performed to obtain an insight into the intramolecular conjugative electronic interactions. The titled compound was screened for in vitro antifungal activity against four fungal strains and the results obtained are explained through in silico molecular docking studies.

Model verifies design of mobile data modem

NASA Technical Reports Server (NTRS)

Davarian, F.; Sumida, J.

1986-01-01

It has been proposed to use differential minimum shift keying (DMSK) modems in spacecraft-based mobile communications systems. For an employment of these modems, it is necessary that the transmitted carrier frequency be known prior to signal detection. In addition, the time needed by the receiver to lock onto the carrier frequency must be minimized. The present article is concerned with a DMSK modem developed for the Mobile Satellite Service. This device demonstrated fast acquisition time and good performance in the presence of fading. However, certain problems arose in initial attempts to study the acquisition behavior of the AFC loop through breadboard techniques. The development of a software model of the AFC loop is discussed, taking into account two cases which were plotted using the model. Attention is given to a demonstration of the viability of the modem by an approach involving modeling and analysis of the frequency synchronizer.

Using social marketing to understand the family dinner with working mothers.

PubMed

Martinasek, Mary P; DeBate, Rita D; Walvoord, Ashley G; Melton, Stephanie T; Himmelgreen, David; Allen, Tammy D; McDermott, Robert J

2010-01-01

The family dinner is a valued tradition that affords opportunities for social interaction and attachment, as well as sharing events of the day, role modeling, connectedness, and problem solving. Guided by the social-marketing framework, this study explored factors associated with the frequency of the family dinner among working mothers with children ages 8-11 years. A qualitative design was used, employing focus groups and Atlas-ti software for thematic analysis. Lack of time, cost, and exhaustion/lack of energy emerged as barriers. Working mothers indicated that a youth-based organization operating as a community partner could increase the frequency of the family dinner by helping with homework completion during after-school care, thereby providing mothers with the time necessary to prepare dinner. This research identified both community partners and working mothers as valued resources for prevention strategies. Interventions developed to increase family dinner frequency should emphasize the perceived value while decreasing the costs/barriers.

Comparison Tools for Assessing the Microgravity Environment of Missions, Carriers and Conditions

NASA Technical Reports Server (NTRS)

DeLombard, Richard; McPherson, Kevin; Moskowitz, Milton; Hrovat, Ken

1997-01-01

The Principal Component Spectral Analysis and the Quasi-steady Three-dimensional Histogram techniques provide the means to describe the microgravity acceleration environment of an entire mission on a single plot. This allows a straight forward comparison of the microgravity environment between missions, carriers, and conditions. As shown in this report, the PCSA and QTH techniques bring both the range and median of the microgravity environment onto a single page for an entire mission or another time period or condition of interest. These single pages may then be used to compare similar analyses of other missions, time periods or conditions. The PCSA plot is based on the frequency distribution of the vibrational energy and is normally used for an acceleration data set containing frequencies above the lowest natural frequencies of the vehicle. The QTH plot is based on the direction and magnitude of the acceleration and is normally used for acceleration data sets with frequency content less than 0.1 Hz. Various operating conditions are made evident by using PCSA and QTH plots. Equipment operating either full or part time with sufficient magnitude to be considered a disturbance is very evident as well as equipment contributing to the background acceleration environment. A source's magnitude and/or frequency variability is also evident by the source's appearance on a PCSA plot. The PCSA and QTH techniques are valuable tools for extracting useful information from acceleration data taken over large spans of time. This report shows that these techniques provide a tool for comparison between different sets of microgravity acceleration data, for example different missions, different activities within a mission, and/or different attitudes within a mission. These techniques, as well as others, may be employed in order to derive useful information from acceleration data.

Design verification of large time constant thermal shields for optical reference cavities.

PubMed

Zhang, J; Wu, W; Shi, X H; Zeng, X Y; Deng, K; Lu, Z H

2016-02-01

In order to achieve high frequency stability in ultra-stable lasers, the Fabry-Pérot reference cavities shall be put inside vacuum chambers with large thermal time constants to reduce the sensitivity to external temperature fluctuations. Currently, the determination of thermal time constants of vacuum chambers is based either on theoretical calculation or time-consuming experiments. The first method can only apply to simple system, while the second method will take a lot of time to try out different designs. To overcome these limitations, we present thermal time constant simulation using finite element analysis (FEA) based on complete vacuum chamber models and verify the results with measured time constants. We measure the thermal time constants using ultrastable laser systems and a frequency comb. The thermal expansion coefficients of optical reference cavities are precisely measured to reduce the measurement error of time constants. The simulation results and the experimental results agree very well. With this knowledge, we simulate several simplified design models using FEA to obtain larger vacuum thermal time constants at room temperature, taking into account vacuum pressure, shielding layers, and support structure. We adopt the Taguchi method for shielding layer optimization and demonstrate that layer material and layer number dominate the contributions to the thermal time constant, compared with layer thickness and layer spacing.

Location identification of closed crack based on Duffing oscillator transient transition

NASA Astrophysics Data System (ADS)

Liu, Xiaofeng; Bo, Lin; Liu, Yaolu; Zhao, Youxuan; Zhang, Jun; Deng, Mingxi; Hu, Ning

2018-02-01

The existence of a closed micro-crack in plates can be detected by using the nonlinear harmonic characteristics of the Lamb wave. However, its location identification is difficult. By considering the transient nonlinear Lamb under the noise interference, we proposed a location identification method for the closed crack based on the quantitative measurement of Duffing oscillator transient transfer in the phase space. The sliding short-time window was used to create a window truncation of to-be-detected signal. And then, the periodic extension processing for transient nonlinear Lamb wave was performed to ensure that the Duffing oscillator has adequate response time to reach a steady state. The transient autocorrelation method was used to reduce the occurrence of missed harmonic detection due to the random variable phase of nonlinear Lamb wave. Moreover, to overcome the deficiency in the quantitative analysis of Duffing system state by phase trajectory diagram and eliminate the misjudgment caused by harmonic frequency component contained in broadband noise, logic operation method of oscillator state transition function based on circular zone partition was adopted to establish the mapping relation between the oscillator transition state and the nonlinear harmonic time domain information. Final state transition discriminant function of Duffing oscillator was used as basis for identifying the reflected and transmitted harmonics from the crack. Chirplet time-frequency analysis was conducted to identify the mode of generated harmonics and determine the propagation speed. Through these steps, accurate position identification of the closed crack was achieved.

Tool Condition Monitoring and Remaining Useful Life Prognostic Based on a Wireless Sensor in Dry Milling Operations.

PubMed

Zhang, Cunji; Yao, Xifan; Zhang, Jianming; Jin, Hong

2016-05-31

Tool breakage causes losses of surface polishing and dimensional accuracy for machined part, or possible damage to a workpiece or machine. Tool Condition Monitoring (TCM) is considerably vital in the manufacturing industry. In this paper, an indirect TCM approach is introduced with a wireless triaxial accelerometer. The vibrations in the three vertical directions (x, y and z) are acquired during milling operations, and the raw signals are de-noised by wavelet analysis. These features of de-noised signals are extracted in the time, frequency and time-frequency domains. The key features are selected based on Pearson's Correlation Coefficient (PCC). The Neuro-Fuzzy Network (NFN) is adopted to predict the tool wear and Remaining Useful Life (RUL). In comparison with Back Propagation Neural Network (BPNN) and Radial Basis Function Network (RBFN), the results show that the NFN has the best performance in the prediction of tool wear and RUL.

Impact of a community gardening project on vegetable intake, food security and family relationships: a community-based participatory research study.

PubMed

Carney, Patricia A; Hamada, Janet L; Rdesinski, Rebecca; Sprager, Lorena; Nichols, Katelyn R; Liu, Betty Y; Pelayo, Joel; Sanchez, Maria Antonia; Shannon, Jacklien

2012-08-01

This community-based participatory research project used popular education techniques to support and educate Hispanic farmworker families in planting and maintaining organic gardens. Measures included a pre- post gardening survey, key informant interviews and observations made at community-based gardening meetings to assess food security, safety and family relationships. Thirty-eight families enrolled in the study during the pre-garden time period, and four more families enrolled in the study during the post-garden period, for a total of 42 families enrolled in the 2009 gardening season. Of the families enrolled during the pre-gardening time period there were 163 household members. The mean age of the interviewee was 44.0, ranging from 21 to 78 years of age. The median number of occupants in a household was 4.0 (range: 2-8), Frequency of adult vegetable intake of "Several time a day" increased from 18.2 to 84.8%, (P < 0.001) and frequency of children's vegetable intake of "Several time a day" increased from 24.0 to 64.0%, (P = 0.003). Before the gardening season, the sum of the frequencies of "Sometimes" and "Frequently" worrying in the past month that food would run out before money was available to buy more was 31.2% and the sum of these frequencies dropped to 3.1% during the post garden period, (P = 0.006). The frequency of skipping meals due to lack of money was not statistically significantly different before and after the gardening season for either adults or children. Analysis of text responses and key informant interviews revealed that physical and mental health benefits were reported as well as economic and family health benefits from the gardening study, primarily because the families often worked in their gardens together. A community gardening program can reduce food insecurity, improve dietary intake and strengthen family relationships.

Kepler Flares. IV. A Comprehensive Analysis of the Activity of the dM4e Star GJ 1243

NASA Astrophysics Data System (ADS)

Silverberg, Steven M.; Kowalski, Adam F.; Davenport, James R. A.; Wisniewski, John P.; Hawley, Suzanne L.; Hilton, Eric J.

2016-10-01

We present a comprehensive study of the active dM4e star GJ 1243. We use previous observations and ground-based echelle spectroscopy to determine that GJ 1243 is a member of the Argus association of field stars, suggesting it is ∼ 30{--}50 {{Myr}} old. We analyze 11 months of 1 minute cadence data from Kepler, presenting Kepler flare frequency distributions, as well as determining correlations between flare energy, amplitude, duration, and decay time. We find that the exponent α of the power-law flare energy distribution varies in time, primarily due to completeness of sample and the low frequency of high-energy flares. We also find a deviation from a single power law at high energy. We use ground-based spectroscopic observations that were simultaneous with the Kepler data to provide simultaneous photometric and spectroscopic analysis of three low-energy flares, the lowest-energy dMe flares with detailed spectral analysis to date on any star. The spectroscopic data from these flares extend constraints for radiative hydrodynamic flare models to a lower energy regime than has previously been studied. We use this simultaneous spectroscopy and Kepler photometry to develop approximate conversions from the Kepler bandpass to the traditional U and B bands. This conversion will be a critical factor in comparing any Kepler flare analyses to the canon of previous ground-based flare studies.

The matrix exponential in transient structural analysis

NASA Technical Reports Server (NTRS)

Minnetyan, Levon

1987-01-01

The primary usefulness of the presented theory is in the ability to represent the effects of high frequency linear response with accuracy, without requiring very small time steps in the analysis of dynamic response. The matrix exponential contains a series approximation to the dynamic model. However, unlike the usual analysis procedure which truncates the high frequency response, the approximation in the exponential matrix solution is in the time domain. By truncating the series solution to the matrix exponential short, the solution is made inaccurate after a certain time. Yet, up to that time the solution is extremely accurate, including all high frequency effects. By taking finite time increments, the exponential matrix solution can compute the response very accurately. Use of the exponential matrix in structural dynamics is demonstrated by simulating the free vibration response of multi degree of freedom models of cantilever beams.

Frequency-Specific Fractal Analysis of Postural Control Accounts for Control Strategies

PubMed Central

Gilfriche, Pierre; Deschodt-Arsac, Véronique; Blons, Estelle; Arsac, Laurent M.

2018-01-01

Diverse indicators of postural control in Humans have been explored for decades, mostly based on the trajectory of the center-of-pressure. Classical approaches focus on variability, based on the notion that if a posture is too variable, the subject is not stable. Going deeper, an improved understanding of underlying physiology has been gained from studying variability in different frequency ranges, pointing to specific short-loops (proprioception), and long-loops (visuo-vestibular) in neural control. More recently, fractal analyses have proliferated and become useful additional metrics of postural control. They allowed identifying two scaling phenomena, respectively in short and long timescales. Here, we show that one of the most widely used methods for fractal analysis, Detrended Fluctuation Analysis, could be enhanced to account for scalings on specific frequency ranges. By computing and filtering a bank of synthetic fractal signals, we established how scaling analysis can be focused on specific frequency components. We called the obtained method Frequency-specific Fractal Analysis (FsFA) and used it to associate the two scaling phenomena of postural control to proprioceptive-based control loop and visuo-vestibular based control loop. After that, convincing arguments of method validity came from an application on the study of unaltered vs. altered postural control in athletes. Overall, the analysis suggests that at least two timescales contribute to postural control: a velocity-based control in short timescales relying on proprioceptive sensors, and a position-based control in longer timescales with visuo-vestibular sensors, which is a brand-new vision of postural control. Frequency-specific scaling exponents are promising markers of control strategies in Humans. PMID:29643816

Diagnostics of plasma in the ionospheric D-region: detection and study of different ionospheric disturbance types

NASA Astrophysics Data System (ADS)

Nina, Aleksandra; Čadež, Vladimir M.; Popović, Luka Č.; Srećković, Vladimir A.

2017-07-01

Here we discuss our recent investigations of the ionospheric plasma by using very low and low frequency (VLF/LF) radio waves. We give a review of how to detect different low ionospheric reactions (sudden ionospheric disturbances) to various terrestrial and extra-terrestrial events, show their classification according to intensity and time duration, and present some methods for their detections in time and frequency domains. Investigations of detection in time domain are carried out for intensive long-lasting perturbations induced by solar X-ray flares and for short-lasting perturbations caused by gamma ray bursts. We also analyze time variations of signals used in the low ionospheric monitoring after earthquake events. In addition, we describe a procedure for the detection of acoustic and gravity waves from the VLF/LF signal analysis in frequency domain. The research of the low ionospheric plasma is based on data collected by the VLF/LF receivers located in Belgrade, Serbia. Contribution to the Topical Issue "Physics of Ionized Gases (SPIG 2016)", edited by Goran Poparic, Bratislav Obradovic, Dragana Maric and Aleksandar Milosavljevic.