Open Rotor Computational Aeroacoustic Analysis with an Immersed Boundary Method

NASA Technical Reports Server (NTRS)

Brehm, Christoph; Barad, Michael F.; Kiris, Cetin C.

2016-01-01

Reliable noise prediction capabilities are essential to enable novel fuel efficient open rotor designs that can meet the community and cabin noise standards. Toward this end, immersed boundary methods have reached a level of maturity so that they are being frequently employed for specific real world applications within NASA. This paper demonstrates that our higher-order immersed boundary method provides the ability for aeroacoustic analysis of wake-dominated flow fields generated by highly complex geometries. This is the first of a kind aeroacoustic simulation of an open rotor propulsion system employing an immersed boundary method. In addition to discussing the peculiarities of applying the immersed boundary method to this moving boundary problem, we will provide a detailed aeroacoustic analysis of the noise generation mechanisms encountered in the open rotor flow. The simulation data is compared to available experimental data and other computational results employing more conventional CFD methods. The noise generation mechanisms are analyzed employing spectral analysis, proper orthogonal decomposition and the causality method.

An Application of the Acoustic Similarity Law to the Numerical Analysis of Centrifugal Fan Noise

NASA Astrophysics Data System (ADS)

Jeon, Wan-Ho; Lee, Duck-Joo; Rhee, Huinam

Centrifugal fans, which are frequently used in our daily lives and various industries, usually make severe noise problems. Generally, the centrifugal fan noise consists of tones at the blade passing frequency and its higher harmonics. These tonal sounds come from the interaction between the flow discharged from the impeller and the cutoff in the casing. Prediction of the noise from a centrifugal fan becomes more necessary to optimize the design to meet both the performance and noise criteria. However, only some limited studies on noise prediction method exist because there are difficulties in obtaining detailed information about the flow field and casing effect on noise radiation. This paper aims to investigate the noise generation mechanism of a centrifugal fan and to develop a prediction method for the unsteady flow and acoustic pressure fields. In order to do this, a numerical analysis method using acoustic similarity law is proposed, and it is verified that the method can predict the noise generation mechanism very well by comparing the predicted results with available experimental results.

Comparison of classical statistical methods and artificial neural network in traffic noise prediction

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

Nedic, Vladimir, E-mail: vnedic@kg.ac.rs; Despotovic, Danijela, E-mail: ddespotovic@kg.ac.rs; Cvetanovic, Slobodan, E-mail: slobodan.cvetanovic@eknfak.ni.ac.rs

2014-11-15

Traffic is the main source of noise in urban environments and significantly affects human mental and physical health and labor productivity. Therefore it is very important to model the noise produced by various vehicles. Techniques for traffic noise prediction are mainly based on regression analysis, which generally is not good enough to describe the trends of noise. In this paper the application of artificial neural networks (ANNs) for the prediction of traffic noise is presented. As input variables of the neural network, the proposed structure of the traffic flow and the average speed of the traffic flow are chosen. Themore » output variable of the network is the equivalent noise level in the given time period L{sub eq}. Based on these parameters, the network is modeled, trained and tested through a comparative analysis of the calculated values and measured levels of traffic noise using the originally developed user friendly software package. It is shown that the artificial neural networks can be a useful tool for the prediction of noise with sufficient accuracy. In addition, the measured values were also used to calculate equivalent noise level by means of classical methods, and comparative analysis is given. The results clearly show that ANN approach is superior in traffic noise level prediction to any other statistical method. - Highlights: • We proposed an ANN model for prediction of traffic noise. • We developed originally designed user friendly software package. • The results are compared with classical statistical methods. • The results are much better predictive capabilities of ANN model.« less

Analysis of noise-induced temporal correlations in neuronal spike sequences

NASA Astrophysics Data System (ADS)

Reinoso, José A.; Torrent, M. C.; Masoller, Cristina

2016-11-01

We investigate temporal correlations in sequences of noise-induced neuronal spikes, using a symbolic method of time-series analysis. We focus on the sequence of time-intervals between consecutive spikes (inter-spike-intervals, ISIs). The analysis method, known as ordinal analysis, transforms the ISI sequence into a sequence of ordinal patterns (OPs), which are defined in terms of the relative ordering of consecutive ISIs. The ISI sequences are obtained from extensive simulations of two neuron models (FitzHugh-Nagumo, FHN, and integrate-and-fire, IF), with correlated noise. We find that, as the noise strength increases, temporal order gradually emerges, revealed by the existence of more frequent ordinal patterns in the ISI sequence. While in the FHN model the most frequent OP depends on the noise strength, in the IF model it is independent of the noise strength. In both models, the correlation time of the noise affects the OP probabilities but does not modify the most probable pattern.

NASA's Aeroacoustic Tools and Methods for Analysis of Aircraft Noise

NASA Technical Reports Server (NTRS)

Rizzi, Stephen A.; Lopes, Leonard V.; Burley, Casey L.

2015-01-01

Aircraft community noise is a significant concern due to continued growth in air traffic, increasingly stringent environmental goals, and operational limitations imposed by airport authorities. The ability to quantify aircraft noise at the source and ultimately at observers is required to develop low noise aircraft designs and flight procedures. Predicting noise at the source, accounting for scattering and propagation through the atmosphere to the observer, and assessing the perception and impact on a community requires physics-based aeroacoustics tools. Along with the analyses for aero-performance, weights and fuel burn, these tools can provide the acoustic component for aircraft MDAO (Multidisciplinary Design Analysis and Optimization). Over the last decade significant progress has been made in advancing the aeroacoustic tools such that acoustic analyses can now be performed during the design process. One major and enabling advance has been the development of the system noise framework known as Aircraft NOise Prediction Program2 (ANOPP2). ANOPP2 is NASA's aeroacoustic toolset and is designed to facilitate the combination of acoustic approaches of varying fidelity for the analysis of noise from conventional and unconventional aircraft. The toolset includes a framework that integrates noise prediction and propagation methods into a unified system for use within general aircraft analysis software. This includes acoustic analyses, signal processing and interfaces that allow for the assessment of perception of noise on a community. ANOPP2's capability to incorporate medium fidelity shielding predictions and wind tunnel experiments into a design environment is presented. An assessment of noise from a conventional and Hybrid Wing Body (HWB) aircraft using medium fidelity scattering methods combined with noise measurements from a model-scale HWB recently placed in NASA's 14x22 wind tunnel are presented. The results are in the form of community noise metrics and auralizations.

Analysis of de-noising methods to improve the precision of the ILSF BPM electronic readout system

NASA Astrophysics Data System (ADS)

Shafiee, M.; Feghhi, S. A. H.; Rahighi, J.

2016-12-01

In order to have optimum operation and precise control system at particle accelerators, it is required to measure the beam position with the precision of sub-μm. We developed a BPM electronic readout system at Iranian Light Source Facility and it has been experimentally tested at ALBA accelerator facility. The results show the precision of 0.54 μm in beam position measurements. To improve the precision of this beam position monitoring system to sub-μm level, we have studied different de-noising methods such as principal component analysis, wavelet transforms, filtering by FIR, and direct averaging method. An evaluation of the noise reduction was given to testify the ability of these methods. The results show that the noise reduction based on Daubechies wavelet transform is better than other algorithms, and the method is suitable for signal noise reduction in beam position monitoring system.

Measurement of pattern roughness and local size variation using CD-SEM: current status

NASA Astrophysics Data System (ADS)

Fukuda, Hiroshi; Kawasaki, Takahiro; Kawada, Hiroki; Sakai, Kei; Kato, Takashi; Yamaguchi, Satoru; Ikota, Masami; Momonoi, Yoshinori

2018-03-01

Measurement of line edge roughness (LER) is discussed from four aspects: edge detection, PSD prediction, sampling strategy, and noise mitigation, and general guidelines and practical solutions for LER measurement today are introduced. Advanced edge detection algorithms such as wave-matching method are shown effective for robustly detecting edges from low SNR images, while conventional algorithm with weak filtering is still effective in suppressing SEM noise and aliasing. Advanced PSD prediction method such as multi-taper method is effective in suppressing sampling noise within a line edge to analyze, while number of lines is still required for suppressing line to line variation. Two types of SEM noise mitigation methods, "apparent noise floor" subtraction method and LER-noise decomposition using regression analysis are verified to successfully mitigate SEM noise from PSD curves. These results are extended to LCDU measurement to clarify the impact of SEM noise and sampling noise on LCDU.

Measurement and analysis of blank tire tread vibration and radiated noise

DOT National Transportation Integrated Search

2003-07-01

Traffic noise is a major concern in many communities. Although there are many measures being taken to reduce exposure to traffic noise, the most efficient method is to reduce the noise at its source. Tire noise has been shown to exceed the noise leve...

Noise source separation of diesel engine by combining binaural sound localization method and blind source separation method

NASA Astrophysics Data System (ADS)

Yao, Jiachi; Xiang, Yang; Qian, Sichong; Li, Shengyang; Wu, Shaowei

2017-11-01

In order to separate and identify the combustion noise and the piston slap noise of a diesel engine, a noise source separation and identification method that combines a binaural sound localization method and blind source separation method is proposed. During a diesel engine noise and vibration test, because a diesel engine has many complex noise sources, a lead covering method was carried out on a diesel engine to isolate other interference noise from the No. 1-5 cylinders. Only the No. 6 cylinder parts were left bare. Two microphones that simulated the human ears were utilized to measure the radiated noise signals 1 m away from the diesel engine. First, a binaural sound localization method was adopted to separate the noise sources that are in different places. Then, for noise sources that are in the same place, a blind source separation method is utilized to further separate and identify the noise sources. Finally, a coherence function method, continuous wavelet time-frequency analysis method, and prior knowledge of the diesel engine are combined to further identify the separation results. The results show that the proposed method can effectively separate and identify the combustion noise and the piston slap noise of a diesel engine. The frequency of the combustion noise and the piston slap noise are respectively concentrated at 4350 Hz and 1988 Hz. Compared with the blind source separation method, the proposed method has superior separation and identification effects, and the separation results have fewer interference components from other noise.

Analysis and modeling of flicker noise in lateral asymmetric channel MOSFETs

NASA Astrophysics Data System (ADS)

Agarwal, Harshit; Kushwaha, Pragya; Gupta, Chetan; Khandelwal, Sourabh; Hu, Chenming; Chauhan, Yogesh Singh

2016-01-01

In this paper, flicker noise behavior of lateral non-uniformly doped MOSFET is studied using impedance field method. Our study shows that Klaassen Prins (KP) method, which forms the basis of noise model in MOSFETs, underestimates flicker noise in such devices. The same KP method overestimates thermal noise by 2-3 orders of magnitude in similar devices as demonstrated in Roy et al. (2007). This apparent discrepancy between thermal and flicker noise behavior lies in origin of these noises, which leads to opposite trend of local noise power spectral density vs doping. We have modeled the physics behind such behavior, which also explain the trends observed in the measurements (Agarwal et al., 2015).

[Detection of Weak Speech Signals from Strong Noise Background Based on Adaptive Stochastic Resonance].

PubMed

Lu, Huanhuan; Wang, Fuzhong; Zhang, Huichun

2016-04-01

Traditional speech detection methods regard the noise as a jamming signal to filter,but under the strong noise background,these methods lost part of the original speech signal while eliminating noise.Stochastic resonance can use noise energy to amplify the weak signal and suppress the noise.According to stochastic resonance theory,a new method based on adaptive stochastic resonance to extract weak speech signals is proposed.This method,combined with twice sampling,realizes the detection of weak speech signals from strong noise.The parameters of the systema,b are adjusted adaptively by evaluating the signal-to-noise ratio of the output signal,and then the weak speech signal is optimally detected.Experimental simulation analysis showed that under the background of strong noise,the output signal-to-noise ratio increased from the initial value-7dB to about 0.86 dB,with the gain of signalto-noise ratio is 7.86 dB.This method obviously raises the signal-to-noise ratio of the output speech signals,which gives a new idea to detect the weak speech signals in strong noise environment.

A data-driven approach for denoising GNSS position time series

NASA Astrophysics Data System (ADS)

Li, Yanyan; Xu, Caijun; Yi, Lei; Fang, Rongxin

2017-12-01

Global navigation satellite system (GNSS) datasets suffer from common mode error (CME) and other unmodeled errors. To decrease the noise level in GNSS positioning, we propose a new data-driven adaptive multiscale denoising method in this paper. Both synthetic and real-world long-term GNSS datasets were employed to assess the performance of the proposed method, and its results were compared with those of stacking filtering, principal component analysis (PCA) and the recently developed multiscale multiway PCA. It is found that the proposed method can significantly eliminate the high-frequency white noise and remove the low-frequency CME. Furthermore, the proposed method is more precise for denoising GNSS signals than the other denoising methods. For example, in the real-world example, our method reduces the mean standard deviation of the north, east and vertical components from 1.54 to 0.26, 1.64 to 0.21 and 4.80 to 0.72 mm, respectively. Noise analysis indicates that for the original signals, a combination of power-law plus white noise model can be identified as the best noise model. For the filtered time series using our method, the generalized Gauss-Markov model is the best noise model with the spectral indices close to - 3, indicating that flicker walk noise can be identified. Moreover, the common mode error in the unfiltered time series is significantly reduced by the proposed method. After filtering with our method, a combination of power-law plus white noise model is the best noise model for the CMEs in the study region.

Automatic Assessment and Reduction of Noise using Edge Pattern Analysis in Non-Linear Image Enhancement

NASA Technical Reports Server (NTRS)

Jobson, Daniel J.; Rahman, Zia-Ur; Woodell, Glenn A.; Hines, Glenn D.

2004-01-01

Noise is the primary visibility limit in the process of non-linear image enhancement, and is no longer a statistically stable additive noise in the post-enhancement image. Therefore novel approaches are needed to both assess and reduce spatially variable noise at this stage in overall image processing. Here we will examine the use of edge pattern analysis both for automatic assessment of spatially variable noise and as a foundation for new noise reduction methods.

Use of Multiscale Entropy to Facilitate Artifact Detection in Electroencephalographic Signals

PubMed Central

Mariani, Sara; Borges, Ana F. T.; Henriques, Teresa; Goldberger, Ary L.; Costa, Madalena D.

2016-01-01

Electroencephalographic (EEG) signals present a myriad of challenges to analysis, beginning with the detection of artifacts. Prior approaches to noise detection have utilized multiple techniques, including visual methods, independent component analysis and wavelets. However, no single method is broadly accepted, inviting alternative ways to address this problem. Here, we introduce a novel approach based on a statistical physics method, multiscale entropy (MSE) analysis, which quantifies the complexity of a signal. We postulate that noise corrupted EEG signals have lower information content, and, therefore, reduced complexity compared with their noise free counterparts. We test the new method on an open-access database of EEG signals with and without added artifacts due to electrode motion. PMID:26738116

Range of sound levels in the outdoor environment

Treesearch

Lewis S. Goodfriend

1977-01-01

Current methods of measuring and rating noise in a metropolitan area are examined, including real-time spectrum analysis and sound-level integration, producing a single-number value representing the noise impact for each hour or each day. Methods of noise rating for metropolitan areas are reviewed, and the various measures from multidimensional rating methods such as...

Improving wavelet denoising based on an in-depth analysis of the camera color processing

NASA Astrophysics Data System (ADS)

Seybold, Tamara; Plichta, Mathias; Stechele, Walter

2015-02-01

While Denoising is an extensively studied task in signal processing research, most denoising methods are designed and evaluated using readily processed image data, e.g. the well-known Kodak data set. The noise model is usually additive white Gaussian noise (AWGN). This kind of test data does not correspond to nowadays real-world image data taken with a digital camera. Using such unrealistic data to test, optimize and compare denoising algorithms may lead to incorrect parameter tuning or suboptimal choices in research on real-time camera denoising algorithms. In this paper we derive a precise analysis of the noise characteristics for the different steps in the color processing. Based on real camera noise measurements and simulation of the processing steps, we obtain a good approximation for the noise characteristics. We further show how this approximation can be used in standard wavelet denoising methods. We improve the wavelet hard thresholding and bivariate thresholding based on our noise analysis results. Both the visual quality and objective quality metrics show the advantage of the proposed method. As the method is implemented using look-up-tables that are calculated before the denoising step, our method can be implemented with very low computational complexity and can process HD video sequences real-time in an FPGA.

Noise elimination algorithm for modal analysis

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

Bao, X. X., E-mail: baoxingxian@upc.edu.cn; Li, C. L.; Xiong, C. B.

2015-07-27

Modal analysis is an ongoing interdisciplinary physical issue. Modal parameters estimation is applied to determine the dynamic characteristics of structures under vibration excitation. Modal analysis is more challenging for the measured vibration response signals are contaminated with noise. This study develops a mathematical algorithm of structured low rank approximation combined with the complex exponential method to estimate the modal parameters. Physical experiments using a steel cantilever beam with ten accelerometers mounted, excited by an impulse load, demonstrate that this method can significantly eliminate noise from measured signals and accurately identify the modal frequencies and damping ratios. This study provides amore » fundamental mechanism of noise elimination using structured low rank approximation in physical fields.« less

SNR-weighted sinogram smoothing with improved noise-resolution properties for low-dose x-ray computed tomography

NASA Astrophysics Data System (ADS)

Li, Tianfang; Wang, Jing; Wen, Junhai; Li, Xiang; Lu, Hongbing; Hsieh, Jiang; Liang, Zhengrong

2004-05-01

To treat the noise in low-dose x-ray CT projection data more accurately, analysis of the noise properties of the data and development of a corresponding efficient noise treatment method are two major problems to be addressed. In order to obtain an accurate and realistic model to describe the x-ray CT system, we acquired thousands of repeated measurements on different phantoms at several fixed scan angles by a GE high-speed multi-slice spiral CT scanner. The collected data were calibrated and log-transformed by the sophisticated system software, which converts the detected photon energy into sinogram data that satisfies the Radon transform. From the analysis of these experimental data, a nonlinear relation between mean and variance for each datum of the sinogram was obtained. In this paper, we integrated this nonlinear relation into a penalized likelihood statistical framework for a SNR (signal-to-noise ratio) adaptive smoothing of noise in the sinogram. After the proposed preprocessing, the sinograms were reconstructed with unapodized FBP (filtered backprojection) method. The resulted images were evaluated quantitatively, in terms of noise uniformity and noise-resolution tradeoff, with comparison to other noise smoothing methods such as Hanning filter and Butterworth filter at different cutoff frequencies. Significant improvement on noise and resolution tradeoff and noise property was demonstrated.

Seismic facies analysis based on self-organizing map and empirical mode decomposition

NASA Astrophysics Data System (ADS)

Du, Hao-kun; Cao, Jun-xing; Xue, Ya-juan; Wang, Xing-jian

2015-01-01

Seismic facies analysis plays an important role in seismic interpretation and reservoir model building by offering an effective way to identify the changes in geofacies inter wells. The selections of input seismic attributes and their time window have an obvious effect on the validity of classification and require iterative experimentation and prior knowledge. In general, it is sensitive to noise when waveform serves as the input data to cluster analysis, especially with a narrow window. To conquer this limitation, the Empirical Mode Decomposition (EMD) method is introduced into waveform classification based on SOM. We first de-noise the seismic data using EMD and then cluster the data using 1D grid SOM. The main advantages of this method are resolution enhancement and noise reduction. 3D seismic data from the western Sichuan basin, China, are collected for validation. The application results show that seismic facies analysis can be improved and better help the interpretation. The powerful tolerance for noise makes the proposed method to be a better seismic facies analysis tool than classical 1D grid SOM method, especially for waveform cluster with a narrow window.

Spectral analysis methods for vehicle interior vibro-acoustics identification

NASA Astrophysics Data System (ADS)

Hosseini Fouladi, Mohammad; Nor, Mohd. Jailani Mohd.; Ariffin, Ahmad Kamal

2009-02-01

Noise has various effects on comfort, performance and health of human. Sound are analysed by human brain based on the frequencies and amplitudes. In a dynamic system, transmission of sound and vibrations depend on frequency and direction of the input motion and characteristics of the output. It is imperative that automotive manufacturers invest a lot of effort and money to improve and enhance the vibro-acoustics performance of their products. The enhancement effort may be very difficult and time-consuming if one relies only on 'trial and error' method without prior knowledge about the sources itself. Complex noise inside a vehicle cabin originated from various sources and travel through many pathways. First stage of sound quality refinement is to find the source. It is vital for automotive engineers to identify the dominant noise sources such as engine noise, exhaust noise and noise due to vibration transmission inside of vehicle. The purpose of this paper is to find the vibro-acoustical sources of noise in a passenger vehicle compartment. The implementation of spectral analysis method is much faster than the 'trial and error' methods in which, parts should be separated to measure the transfer functions. Also by using spectral analysis method, signals can be recorded in real operational conditions which conduce to more consistent results. A multi-channel analyser is utilised to measure and record the vibro-acoustical signals. Computational algorithms are also employed to identify contribution of various sources towards the measured interior signal. These achievements can be utilised to detect, control and optimise interior noise performance of road transport vehicles.

Phase noise in oscillators as differential-algebraic systems with colored noise sources

NASA Astrophysics Data System (ADS)

Demir, Alper

2004-05-01

Oscillators are key components of many kinds of systems, particularly electronic and opto-electronic systems. Undesired perturbations, i.e. noise, in practical systems adversely affect the spectral and timing properties of the signals generated by oscillators resulting in phase noise and timing jitter, which are key performance limiting factors, being major contributors to bit-error-rate (BER) of RF and possibly optical communication systems, and creating synchronization problems in clocked and sampled-data electronic systems. In this paper, we review our work on the theory and numerical methods for nonlinear perturbation and noise analysis of oscillators described by a system of differential-algebraic equations (DAEs) with white and colored noise sources. The bulk of the work reviewed in this paper first appeared in [1], then in [2] and [3]. Prior to the work mentioned above, we developed a theory and numerical methods for nonlinear perturbation and noise analysis of oscillators described by a system of ordinary differential equations (ODEs) with white noise sources only [4, 5]. In this paper, we also discuss some open problems and issues in the modeling and analysis of phase noise both in free running oscillators and in phase/injection-locked ones.

Analysis of Sampling Methodologies for Noise Pollution Assessment and the Impact on the Population.

PubMed

Rey Gozalo, Guillermo; Barrigón Morillas, Juan Miguel

2016-05-11

Today, noise pollution is an increasing environmental stressor. Noise maps are recognised as the main tool for assessing and managing environmental noise, but their accuracy largely depends on the sampling method used. The sampling methods most commonly used by different researchers (grid, legislative road types and categorisation methods) were analysed and compared using the city of Talca (Chile) as a test case. The results show that the stratification of sound values in road categories has a significantly lower prediction error and a higher capacity for discrimination and prediction than in the legislative road types used by the Ministry of Transport and Telecommunications in Chile. Also, the use of one or another method implies significant differences in the assessment of population exposure to noise pollution. Thus, the selection of a suitable method for performing noise maps through measurements is essential to achieve an accurate assessment of the impact of noise pollution on the population.

Measurement Of Trailing Edge Noise using Directional Array and Coherent Output Power Methods

NASA Technical Reports Server (NTRS)

Hutcheson, Florence V.; Brooks, Thomas F.

2002-01-01

The use of a directional array of microphones for the measurement of trailing edge (TE) noise is described. The capabilities of this method are evaluated via measurements of TE noise from a NACA 63-215 airfoil model and from a cylindrical rod. This TE noise measurement approach is compared to one that is based on the cross spectral analysis of output signals from a pair of microphones (COP method). Advantages and limitations of both methods are examined. It is shown that the microphone array can accurately measures TE noise and captures its two-dimensional characteristic over a large frequency range for any TE configuration as long as noise contamination from extraneous sources is within bounds. The COP method is shown to also accurately measure TE noise but over a more limited frequency range that narrows for increased TE thickness. Finally, the applicability and generality of an airfoil self-noise prediction method was evaluated via comparison to the experimental data obtained using the COP and array measurement methods. The predicted and experimental results are shown to agree over large frequency ranges.

A comparison of quantum limited dose and noise equivalent dose

NASA Astrophysics Data System (ADS)

Job, Isaias D.; Boyce, Sarah J.; Petrillo, Michael J.; Zhou, Kungang

2016-03-01

Quantum-limited-dose (QLD) and noise-equivalent-dose (NED) are performance metrics often used interchangeably. Although the metrics are related, they are not equivalent unless the treatment of electronic noise is carefully considered. These metrics are increasingly important to properly characterize the low-dose performance of flat panel detectors (FPDs). A system can be said to be quantum-limited when the Signal-to-noise-ratio (SNR) is proportional to the square-root of x-ray exposure. Recent experiments utilizing three methods to determine the quantum-limited dose range yielded inconsistent results. To investigate the deviation in results, generalized analytical equations are developed to model the image processing and analysis of each method. We test the generalized expression for both radiographic and fluoroscopic detectors. The resulting analysis shows that total noise content of the images processed by each method are inherently different based on their readout scheme. Finally, it will be shown that the NED is equivalent to the instrumentation-noise-equivalent-exposure (INEE) and furthermore that the NED is derived from the quantum-noise-only method of determining QLD. Future investigations will measure quantum-limited performance of radiographic panels with a modified readout scheme to allow for noise improvements similar to measurements performed with fluoroscopic detectors.

A research program to reduce interior noise in general aviation airplanes: Noise reduction through a cavity-backed flexible plate

NASA Technical Reports Server (NTRS)

Roskam, J.; Vandam, C. P. G.

1978-01-01

A prediction method is reported for noise reduction through a cavity-backed panel. The analysis takes into account only cavity modes in one direction. The results of this analysis were to find the effect of acoustic stiffness of a backing cavity on the panel behavior. The resulting changes in the noise reduction through the panel are significant.

A new multiscale noise tuning stochastic resonance for enhanced fault diagnosis in wind turbine drivetrains

NASA Astrophysics Data System (ADS)

Hu, Bingbing; Li, Bing

2016-02-01

It is very difficult to detect weak fault signatures due to the large amount of noise in a wind turbine system. Multiscale noise tuning stochastic resonance (MSTSR) has proved to be an effective way to extract weak signals buried in strong noise. However, the MSTSR method originally based on discrete wavelet transform (DWT) has disadvantages such as shift variance and the aliasing effects in engineering application. In this paper, the dual-tree complex wavelet transform (DTCWT) is introduced into the MSTSR method, which makes it possible to further improve the system output signal-to-noise ratio and the accuracy of fault diagnosis by the merits of DTCWT (nearly shift invariant and reduced aliasing effects). Moreover, this method utilizes the relationship between the two dual-tree wavelet basis functions, instead of matching the single wavelet basis function to the signal being analyzed, which may speed up the signal processing and be employed in on-line engineering monitoring. The proposed method is applied to the analysis of bearing outer ring and shaft coupling vibration signals carrying fault information. The results confirm that the method performs better in extracting the fault features than the original DWT-based MSTSR, the wavelet transform with post spectral analysis, and EMD-based spectral analysis methods.

An Integrated Low-Speed Performance and Noise Prediction Methodology for Subsonic Aircraft

NASA Technical Reports Server (NTRS)

Olson, E. D.; Mavris, D. N.

2000-01-01

An integrated methodology has been assembled to compute the engine performance, takeoff and landing trajectories, and community noise levels for a subsonic commercial aircraft. Where feasible, physics-based noise analysis methods have been used to make the results more applicable to newer, revolutionary designs and to allow for a more direct evaluation of new technologies. The methodology is intended to be used with approximation methods and risk analysis techniques to allow for the analysis of a greater number of variable combinations while retaining the advantages of physics-based analysis. Details of the methodology are described and limited results are presented for a representative subsonic commercial aircraft.

A new automated assessment method for contrast-detail images by applying support vector machine and its robustness to nonlinear image processing.

PubMed

Takei, Takaaki; Ikeda, Mitsuru; Imai, Kuniharu; Yamauchi-Kawaura, Chiyo; Kato, Katsuhiko; Isoda, Haruo

2013-09-01

The automated contrast-detail (C-D) analysis methods developed so-far cannot be expected to work well on images processed with nonlinear methods, such as noise reduction methods. Therefore, we have devised a new automated C-D analysis method by applying support vector machine (SVM), and tested for its robustness to nonlinear image processing. We acquired the CDRAD (a commercially available C-D test object) images at a tube voltage of 120 kV and a milliampere-second product (mAs) of 0.5-5.0. A partial diffusion equation based technique was used as noise reduction method. Three radiologists and three university students participated in the observer performance study. The training data for our SVM method was the classification data scored by the one radiologist for the CDRAD images acquired at 1.6 and 3.2 mAs and their noise-reduced images. We also compared the performance of our SVM method with the CDRAD Analyser algorithm. The mean C-D diagrams (that is a plot of the mean of the smallest visible hole diameter vs. hole depth) obtained from our devised SVM method agreed well with the ones averaged across the six human observers for both original and noise-reduced CDRAD images, whereas the mean C-D diagrams from the CDRAD Analyser algorithm disagreed with the ones from the human observers for both original and noise-reduced CDRAD images. In conclusion, our proposed SVM method for C-D analysis will work well for the images processed with the non-linear noise reduction method as well as for the original radiographic images.

Novel Signal Noise Reduction Method through Cluster Analysis, Applied to Photoplethysmography.

PubMed

Waugh, William; Allen, John; Wightman, James; Sims, Andrew J; Beale, Thomas A W

2018-01-01

Physiological signals can often become contaminated by noise from a variety of origins. In this paper, an algorithm is described for the reduction of sporadic noise from a continuous periodic signal. The design can be used where a sample of a periodic signal is required, for example, when an average pulse is needed for pulse wave analysis and characterization. The algorithm is based on cluster analysis for selecting similar repetitions or pulses from a periodic single. This method selects individual pulses without noise, returns a clean pulse signal, and terminates when a sufficiently clean and representative signal is received. The algorithm is designed to be sufficiently compact to be implemented on a microcontroller embedded within a medical device. It has been validated through the removal of noise from an exemplar photoplethysmography (PPG) signal, showing increasing benefit as the noise contamination of the signal increases. The algorithm design is generalised to be applicable for a wide range of physiological (physical) signals.

Stochastic modular analysis for gene circuits: interplay among retroactivity, nonlinearity, and stochasticity.

PubMed

Kim, Kyung Hyuk; Sauro, Herbert M

2015-01-01

This chapter introduces a computational analysis method for analyzing gene circuit dynamics in terms of modules while taking into account stochasticity, system nonlinearity, and retroactivity. (1) ANALOG ELECTRICAL CIRCUIT REPRESENTATION FOR GENE CIRCUITS: A connection between two gene circuit components is often mediated by a transcription factor (TF) and the connection signal is described by the TF concentration. The TF is sequestered to its specific binding site (promoter region) and regulates downstream transcription. This sequestration has been known to affect the dynamics of the TF by increasing its response time. The downstream effect-retroactivity-has been shown to be explicitly described in an electrical circuit representation, as an input capacitance increase. We provide a brief review on this topic. (2) MODULAR DESCRIPTION OF NOISE PROPAGATION: Gene circuit signals are noisy due to the random nature of biological reactions. The noisy fluctuations in TF concentrations affect downstream regulation. Thus, noise can propagate throughout the connected system components. This can cause different circuit components to behave in a statistically dependent manner, hampering a modular analysis. Here, we show that the modular analysis is still possible at the linear noise approximation level. (3) NOISE EFFECT ON MODULE INPUT-OUTPUT RESPONSE: We investigate how to deal with a module input-output response and its noise dependency. Noise-induced phenotypes are described as an interplay between system nonlinearity and signal noise. Lastly, we provide the comprehensive approach incorporating the above three analysis methods, which we call "stochastic modular analysis." This method can provide an analysis framework for gene circuit dynamics when the nontrivial effects of retroactivity, stochasticity, and nonlinearity need to be taken into account.

A Small Leak Detection Method Based on VMD Adaptive De-Noising and Ambiguity Correlation Classification Intended for Natural Gas Pipelines.

PubMed

Xiao, Qiyang; Li, Jian; Bai, Zhiliang; Sun, Jiedi; Zhou, Nan; Zeng, Zhoumo

2016-12-13

In this study, a small leak detection method based on variational mode decomposition (VMD) and ambiguity correlation classification (ACC) is proposed. The signals acquired from sensors were decomposed using the VMD, and numerous components were obtained. According to the probability density function (PDF), an adaptive de-noising algorithm based on VMD is proposed for noise component processing and de-noised components reconstruction. Furthermore, the ambiguity function image was employed for analysis of the reconstructed signals. Based on the correlation coefficient, ACC is proposed to detect the small leak of pipeline. The analysis of pipeline leakage signals, using 1 mm and 2 mm leaks, has shown that proposed detection method can detect a small leak accurately and effectively. Moreover, the experimental results have shown that the proposed method achieved better performances than support vector machine (SVM) and back propagation neural network (BP) methods.

A Small Leak Detection Method Based on VMD Adaptive De-Noising and Ambiguity Correlation Classification Intended for Natural Gas Pipelines

PubMed Central

Xiao, Qiyang; Li, Jian; Bai, Zhiliang; Sun, Jiedi; Zhou, Nan; Zeng, Zhoumo

2016-01-01

In this study, a small leak detection method based on variational mode decomposition (VMD) and ambiguity correlation classification (ACC) is proposed. The signals acquired from sensors were decomposed using the VMD, and numerous components were obtained. According to the probability density function (PDF), an adaptive de-noising algorithm based on VMD is proposed for noise component processing and de-noised components reconstruction. Furthermore, the ambiguity function image was employed for analysis of the reconstructed signals. Based on the correlation coefficient, ACC is proposed to detect the small leak of pipeline. The analysis of pipeline leakage signals, using 1 mm and 2 mm leaks, has shown that proposed detection method can detect a small leak accurately and effectively. Moreover, the experimental results have shown that the proposed method achieved better performances than support vector machine (SVM) and back propagation neural network (BP) methods. PMID:27983577

Evaluation and statistical judgement of neural responses to sinusoidal stimulation in cases with superimposed drift and noise.

PubMed

Jastreboff, P W

1979-06-01

Time histograms of neural responses evoked by sinuosidal stimulation often contain a slow drifting and an irregular noise which disturb Fourier analysis of these responses. Section 2 of this paper evaluates the extent to which a linear drift influences the Fourier analysis, and develops a combined Fourier and linear regression analysis for detecting and correcting for such a linear drift. Usefulness of this correcting method is demonstrated for the time histograms of actual eye movements and Purkinje cell discharges evoked by sinusoidal rotation of rabbits in the horizontal plane. In Sect. 3, the analysis of variance is adopted for estimating the probability of the random occurrence of the response curve extracted by Fourier analysis from noise. This method proved to be useful for avoiding false judgements as to whether the response curve was meaningful, particularly when the response was small relative to the contaminating noise.

SiPM electro-optical detection system noise suppression method

NASA Astrophysics Data System (ADS)

Bi, Xiangli; Yang, Suhui; Hu, Tao; Song, Yiheng

2014-11-01

In this paper, the single photon detection principle of Silicon Photomultipliers (SiPM) device is introduced. The main noise factors that infect the sensitivity of the electro-optical detection system are analyzed, including background light noise, detector dark noise, preamplifier noise and signal light noise etc. The Optical, electrical and thermodynamic methods are used to suppress the SiPM electro-optical detection system noise, which improved the response sensitivity of the detector. Using SiPM optoelectronic detector with a even high sensitivity, together with small field large aperture optical system, high cutoff narrow bandwidth filters, low-noise operational amplifier circuit, the modular design of functional circuit, semiconductor refrigeration technology, greatly improved the sensitivity of optical detection system, reduced system noise and achieved long-range detection of weak laser radiation signal. Theoretical analysis and experimental results show that the proposed methods are reasonable and efficient.

Improved nonlinear prediction method

NASA Astrophysics Data System (ADS)

Adenan, Nur Hamiza; Md Noorani, Mohd Salmi

2014-06-01

The analysis and prediction of time series data have been addressed by researchers. Many techniques have been developed to be applied in various areas, such as weather forecasting, financial markets and hydrological phenomena involving data that are contaminated by noise. Therefore, various techniques to improve the method have been introduced to analyze and predict time series data. In respect of the importance of analysis and the accuracy of the prediction result, a study was undertaken to test the effectiveness of the improved nonlinear prediction method for data that contain noise. The improved nonlinear prediction method involves the formation of composite serial data based on the successive differences of the time series. Then, the phase space reconstruction was performed on the composite data (one-dimensional) to reconstruct a number of space dimensions. Finally the local linear approximation method was employed to make a prediction based on the phase space. This improved method was tested with data series Logistics that contain 0%, 5%, 10%, 20% and 30% of noise. The results show that by using the improved method, the predictions were found to be in close agreement with the observed ones. The correlation coefficient was close to one when the improved method was applied on data with up to 10% noise. Thus, an improvement to analyze data with noise without involving any noise reduction method was introduced to predict the time series data.

Simulation of aerodynamic noise and vibration noise in hard disk drives

NASA Astrophysics Data System (ADS)

Zhu, Lei; Shen, Sheng-Nan; Li, Hui; Zhang, Guo-Qing; Cui, Fu-Hao

2018-05-01

Internal flow field characteristics of HDDs are usually influenced by the arm swing during seek operations. This, in turn, can affect aerodynamic noise and airflow-induced noise. In this paper, the dynamic mesh method is used to calculate the flow-induced vibration (FIV) by transient structure analysis and the boundary element method (BEM) is utilized to predict the vibration noise. Two operational states are considered: the arm is fixed and swinging over the disk. Both aerodynamic noise and vibration noise inside drives increase rapidly with increase in disk rotation and arm swing velocities. The largest aerodynamic noise source is always located near the arm and swung with the arm.

Aircraft Engine Noise Research and Testing at the NASA Glenn Research Center

NASA Technical Reports Server (NTRS)

Elliott, Dave

2015-01-01

The presentation will begin with a brief introduction to the NASA Glenn Research Center as well as an overview of how aircraft engine noise research fits within the organization. Some of the NASA programs and projects with noise content will be covered along with the associated goals of aircraft noise reduction. Topics covered within the noise research being presented will include noise prediction versus experimental results, along with engine fan, jet, and core noise. Details of the acoustic research conducted at NASA Glenn will include the test facilities available, recent test hardware, and data acquisition and analysis methods. Lastly some of the actual noise reduction methods investigated along with their results will be shown.

A Comparison of seismic instrument noise coherence analysis techniques

USGS Publications Warehouse

Ringler, A.T.; Hutt, C.R.; Evans, J.R.; Sandoval, L.D.

2011-01-01

The self-noise of a seismic instrument is a fundamental characteristic used to evaluate the quality of the instrument. It is important to be able to measure this self-noise robustly, to understand how differences among test configurations affect the tests, and to understand how different processing techniques and isolation methods (from nonseismic sources) can contribute to differences in results. We compare two popular coherence methods used for calculating incoherent noise, which is widely used as an estimate of instrument self-noise (incoherent noise and self-noise are not strictly identical but in observatory practice are approximately equivalent; Holcomb, 1989; Sleeman et al., 2006). Beyond directly comparing these two coherence methods on similar models of seismometers, we compare how small changes in test conditions can contribute to incoherent-noise estimates. These conditions include timing errors, signal-to-noise ratio changes (ratios between background noise and instrument incoherent noise), relative sensor locations, misalignment errors, processing techniques, and different configurations of sensor types.

Aircraft noise effects: An inter-disciplinary study of the effect of aircraft noise on man. Part 3: Supplementary analyses of the social-scientific portion of the study on aircraft noise conducted by the DFG

NASA Technical Reports Server (NTRS)

Schumer, R.

1980-01-01

Variables in a study of noise perception near the Munich-Reims airport are explained. The interactive effect of the stimulus (aircraft noise) and moderator (noise sensitivity) on the aircraft noise reaction (disturbance or annoyance) is considered. Methods employed to demonstrate that the moderator has a differencing effect on various stimulus levels are described. Results of the social-scientific portion of the aircraft noise project are compared with those of other survey studies on the problem of aircraft noise. Procedures for contrast group analysis and multiple classification analysis are examined with focus on some difficulties in their application.

The Traffic Noise Index: A Method of Controlling Noise Nuisance.

ERIC Educational Resources Information Center

Langdon, F. J.; Scholes, W. E.

This building research survey is an analysis of the social nuisance caused by urban motor ways and their noise. The Traffic Noise Index is used to indicate traffic noises and their effects on architectural designs and planning, while suggesting the need for more and better window insulation and acoustical barriers. Overall concern is for--(1)…

Image analysis methods for assessing levels of image plane nonuniformity and stochastic noise in a magnetic resonance image of a homogeneous phantom.

PubMed

Magnusson, P; Olsson, L E

2000-08-01

Magnetic response image plane nonuniformity and stochastic noise are properties that greatly influence the outcome of quantitative magnetic resonance imaging (MRI) evaluations such as gel dosimetry measurements using MRI. To study these properties, robust and accurate image analysis methods are required. New nonuniformity level assessment methods were designed, since previous methods were found to be insufficiently robust and accurate. The new and previously reported nonuniformity level assessment methods were analyzed with respect to, for example, insensitivity to stochastic noise; and previously reported stochastic noise level assessment methods with respect to insensitivity to nonuniformity. Using the same image data, different methods were found to assess significantly different levels of nonuniformity. Nonuniformity levels obtained using methods that count pixels in an intensity interval, and obtained using methods that use only intensity values, were found not to be comparable. The latter were found preferable, since they assess the quantity intrinsically sought. A new method which calculates a deviation image, with every pixel representing the deviation from a reference intensity, was least sensitive to stochastic noise. Furthermore, unlike any other analyzed method, it includes all intensity variations across the phantom area and allows for studies of nonuniformity shapes. This new method was designed for accurate studies of nonuniformities in gel dosimetry measurements, but could also be used with benefit in quality assurance and acceptance testing of MRI, scintillation camera, and computer tomography systems. The stochastic noise level was found to be greatly method dependent. Two methods were found to be insensitive to nonuniformity and also simple to use in practice. One method assesses the stochastic noise level as the average of the levels at five different positions within the phantom area, and the other assesses the stochastic noise in a region outside the phantom area.

Temporal Noise Analysis of Charge-Domain Sampling Readout Circuits for CMOS Image Sensors.

PubMed

Ge, Xiaoliang; Theuwissen, Albert J P

2018-02-27

This paper presents a temporal noise analysis of charge-domain sampling readout circuits for Complementary Metal-Oxide Semiconductor (CMOS) image sensors. In order to address the trade-off between the low input-referred noise and high dynamic range, a Gm-cell-based pixel together with a charge-domain correlated-double sampling (CDS) technique has been proposed to provide a way to efficiently embed a tunable conversion gain along the read-out path. Such readout topology, however, operates in a non-stationery large-signal behavior, and the statistical properties of its temporal noise are a function of time. Conventional noise analysis methods for CMOS image sensors are based on steady-state signal models, and therefore cannot be readily applied for Gm-cell-based pixels. In this paper, we develop analysis models for both thermal noise and flicker noise in Gm-cell-based pixels by employing the time-domain linear analysis approach and the non-stationary noise analysis theory, which help to quantitatively evaluate the temporal noise characteristic of Gm-cell-based pixels. Both models were numerically computed in MATLAB using design parameters of a prototype chip, and compared with both simulation and experimental results. The good agreement between the theoretical and measurement results verifies the effectiveness of the proposed noise analysis models.

Temporal Noise Analysis of Charge-Domain Sampling Readout Circuits for CMOS Image Sensors †

PubMed Central

Theuwissen, Albert J. P.

2018-01-01

This paper presents a temporal noise analysis of charge-domain sampling readout circuits for Complementary Metal-Oxide Semiconductor (CMOS) image sensors. In order to address the trade-off between the low input-referred noise and high dynamic range, a Gm-cell-based pixel together with a charge-domain correlated-double sampling (CDS) technique has been proposed to provide a way to efficiently embed a tunable conversion gain along the read-out path. Such readout topology, however, operates in a non-stationery large-signal behavior, and the statistical properties of its temporal noise are a function of time. Conventional noise analysis methods for CMOS image sensors are based on steady-state signal models, and therefore cannot be readily applied for Gm-cell-based pixels. In this paper, we develop analysis models for both thermal noise and flicker noise in Gm-cell-based pixels by employing the time-domain linear analysis approach and the non-stationary noise analysis theory, which help to quantitatively evaluate the temporal noise characteristic of Gm-cell-based pixels. Both models were numerically computed in MATLAB using design parameters of a prototype chip, and compared with both simulation and experimental results. The good agreement between the theoretical and measurement results verifies the effectiveness of the proposed noise analysis models. PMID:29495496

Aeroacoustic Prediction Codes

NASA Technical Reports Server (NTRS)

Gliebe, P; Mani, R.; Shin, H.; Mitchell, B.; Ashford, G.; Salamah, S.; Connell, S.; Huff, Dennis (Technical Monitor)

2000-01-01

This report describes work performed on Contract NAS3-27720AoI 13 as part of the NASA Advanced Subsonic Transport (AST) Noise Reduction Technology effort. Computer codes were developed to provide quantitative prediction, design, and analysis capability for several aircraft engine noise sources. The objective was to provide improved, physics-based tools for exploration of noise-reduction concepts and understanding of experimental results. Methods and codes focused on fan broadband and 'buzz saw' noise and on low-emissions combustor noise and compliment work done by other contractors under the NASA AST program to develop methods and codes for fan harmonic tone noise and jet noise. The methods and codes developed and reported herein employ a wide range of approaches, from the strictly empirical to the completely computational, with some being semiempirical analytical, and/or analytical/computational. Emphasis was on capturing the essential physics while still considering method or code utility as a practical design and analysis tool for everyday engineering use. Codes and prediction models were developed for: (1) an improved empirical correlation model for fan rotor exit flow mean and turbulence properties, for use in predicting broadband noise generated by rotor exit flow turbulence interaction with downstream stator vanes: (2) fan broadband noise models for rotor and stator/turbulence interaction sources including 3D effects, noncompact-source effects. directivity modeling, and extensions to the rotor supersonic tip-speed regime; (3) fan multiple-pure-tone in-duct sound pressure prediction methodology based on computational fluid dynamics (CFD) analysis; and (4) low-emissions combustor prediction methodology and computer code based on CFD and actuator disk theory. In addition. the relative importance of dipole and quadrupole source mechanisms was studied using direct CFD source computation for a simple cascadeigust interaction problem, and an empirical combustor-noise correlation model was developed from engine acoustic test results. This work provided several insights on potential approaches to reducing aircraft engine noise. Code development is described in this report, and those insights are discussed.

Assessment and control design for steam vent noise in an oil refinery.

PubMed

Monazzam, Mohammad Reza; Golmohammadi, Rostam; Nourollahi, Maryam; Momen Bellah Fard, Samaneh

2011-06-13

Noise is one of the most important harmful agents in work environment. Noise pollution in oil refinery industries is related to workers' health. This study aimed to determine the overall noise pollution of an oil refinery operation and its frequency analysis to determine the control plan for a vent noise in these industries. This experimental study performed in control unit of Tehran Oil Refinery in 2008. To determine the noise distributions, environmental noise measurements were carried out by lattice method according to basic information and technical process. The sound pressure level and frequency distribution was measured for each study sources subject separately was performed individually. According to the vent's specification, the measured steam noise characteristics reviewed and compared to the theoretical results of steam noise estimation. Eventually, a double expansion muffler was designed. Data analysis and graphical design were carried out using Excel software. The results of environmental noise measurements indicated that the level of sound pressure was above the national permitted level (85 dB (A)). The Mean level of sound pressure of the studied steam jet was 90.3 dB (L). The results of noise frequency analysis for the steam vents showed that the dominant frequency was 4000 Hz. To obtain 17 dB noise reductions, a double chamber aluminum muffler with 500 mm length and 200 mm diameter consisting pipe drilled was designed. The characteristics of steam vent noise were separated from other sources, a double expansion muffler was designed using a new method based on the level of steam noise, and principle sound frequency, a double expansion muffler was designed.

Noise removing in encrypted color images by statistical analysis

NASA Astrophysics Data System (ADS)

Islam, N.; Puech, W.

2012-03-01

Cryptographic techniques are used to secure confidential data from unauthorized access but these techniques are very sensitive to noise. A single bit change in encrypted data can have catastrophic impact over the decrypted data. This paper addresses the problem of removing bit error in visual data which are encrypted using AES algorithm in the CBC mode. In order to remove the noise, a method is proposed which is based on the statistical analysis of each block during the decryption. The proposed method exploits local statistics of the visual data and confusion/diffusion properties of the encryption algorithm to remove the errors. Experimental results show that the proposed method can be used at the receiving end for the possible solution for noise removing in visual data in encrypted domain.

Receiver function deconvolution using transdimensional hierarchical Bayesian inference

NASA Astrophysics Data System (ADS)

Kolb, J. M.; Lekić, V.

2014-06-01

Teleseismic waves can convert from shear to compressional (Sp) or compressional to shear (Ps) across impedance contrasts in the subsurface. Deconvolving the parent waveforms (P for Ps or S for Sp) from the daughter waveforms (S for Ps or P for Sp) generates receiver functions which can be used to analyse velocity structure beneath the receiver. Though a variety of deconvolution techniques have been developed, they are all adversely affected by background and signal-generated noise. In order to take into account the unknown noise characteristics, we propose a method based on transdimensional hierarchical Bayesian inference in which both the noise magnitude and noise spectral character are parameters in calculating the likelihood probability distribution. We use a reversible-jump implementation of a Markov chain Monte Carlo algorithm to find an ensemble of receiver functions whose relative fits to the data have been calculated while simultaneously inferring the values of the noise parameters. Our noise parametrization is determined from pre-event noise so that it approximates observed noise characteristics. We test the algorithm on synthetic waveforms contaminated with noise generated from a covariance matrix obtained from observed noise. We show that the method retrieves easily interpretable receiver functions even in the presence of high noise levels. We also show that we can obtain useful estimates of noise amplitude and frequency content. Analysis of the ensemble solutions produced by our method can be used to quantify the uncertainties associated with individual receiver functions as well as with individual features within them, providing an objective way for deciding which features warrant geological interpretation. This method should make possible more robust inferences on subsurface structure using receiver function analysis, especially in areas of poor data coverage or under noisy station conditions.

Noise Suppression Methods for Robust Speech Processing

DTIC Science & Technology

1981-04-01

1]. Techniques available for voice processor modification to account for noise contamination are being developed [4]. Preprocessor noise reduction...analysis window function. Principles governing discrete implementation of the transform pair are discussed, and relationships are formalized which specify

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

Measurement of Trailing Edge Noise Using Directional Array and Coherent Output Power Methods

NASA Technical Reports Server (NTRS)

Hutcheson, Florence V.; Brooks, Thomas F.

2002-01-01

The use of a directional (or phased) array of microphones for the measurement of trailing edge (TE) noise is described and tested. The capabilities of this method arc evaluated via measurements of TE noise from a NACA 63-215 airfoil model and from a cylindrical rod. This TE noise measurement approach is compared to one that is based on thc cross spectral analysis of output signals from a pair of microphones placed on opposite sides of an airframe model (COP method). Advantages and limitations of both methods arc examined. It is shown that the microphone array can accurately measures TE noise and captures its two-dimensional characteristic over a large frequency range for any TE configuration as long as noise contamination from extraneous sources is within bounds. The COP method is shown to also accurately measure TE noise but over a more limited frequency range that narrows for increased TE thickness. Finally, the applicability and generality of an airfoil self-noise prediction method was evaluated via comparison to the experimental data obtained using the COP and array measurement methods. The predicted and experimental results are shown to agree over large frequency ranges.

Acoustic prediction methods for the NASA generalized advanced propeller analysis system (GAPAS)

NASA Technical Reports Server (NTRS)

Padula, S. L.; Block, P. J. W.

1984-01-01

Classical methods of propeller performance analysis are coupled with state-of-the-art Aircraft Noise Prediction Program (ANOPP:) techniques to yield a versatile design tool, the NASA Generalized Advanced Propeller Analysis System (GAPAS) for the novel quiet and efficient propellers. ANOPP is a collection of modular specialized programs. GAPAS as a whole addresses blade geometry and aerodynamics, rotor performance and loading, and subsonic propeller noise.

Development of indirect EFBEM for radiating noise analysis including underwater problems

NASA Astrophysics Data System (ADS)

Kwon, Hyun-Wung; Hong, Suk-Yoon; Song, Jee-Hun

2013-09-01

For the analysis of radiating noise problems in medium-to-high frequency ranges, the Energy Flow Boundary Element Method (EFBEM) was developed. EFBEM is the analysis technique that applies the Boundary Element Method (BEM) to Energy Flow Analysis (EFA). The fundamental solutions representing spherical wave property for radiating noise problems in open field and considering the free surface effect in underwater are developed. Also the directivity factor is developed to express wave's directivity patterns in medium-to-high frequency ranges. Indirect EFBEM by using fundamental solutions and fictitious source was applied to open field and underwater noise problems successfully. Through numerical applications, the acoustic energy density distributions due to vibration of a simple plate model and a sphere model were compared with those of commercial code, and the comparison showed good agreement in the level and pattern of the energy density distributions.

Method of confidence domains in the analysis of noise-induced extinction for tritrophic population system

NASA Astrophysics Data System (ADS)

Bashkirtseva, Irina; Ryashko, Lev; Ryazanova, Tatyana

2017-09-01

A problem of the analysis of the noise-induced extinction in multidimensional population systems is considered. For the investigation of conditions of the extinction caused by random disturbances, a new approach based on the stochastic sensitivity function technique and confidence domains is suggested, and applied to tritrophic population model of interacting prey, predator and top predator. This approach allows us to analyze constructively the probabilistic mechanisms of the transition to the noise-induced extinction from both equilibrium and oscillatory regimes of coexistence. In this analysis, a method of principal directions for the reducing of the dimension of confidence domains is suggested. In the dispersion of random states, the principal subspace is defined by the ratio of eigenvalues of the stochastic sensitivity matrix. A detailed analysis of two scenarios of the noise-induced extinction in dependence on parameters of considered tritrophic system is carried out.

Read-noise characterization of focal plane array detectors via mean-variance analysis.

PubMed

Sperline, R P; Knight, A K; Gresham, C A; Koppenaal, D W; Hieftje, G M; Denton, M B

2005-11-01

Mean-variance analysis is described as a method for characterization of the read-noise and gain of focal plane array (FPA) detectors, including charge-coupled devices (CCDs), charge-injection devices (CIDs), and complementary metal-oxide-semiconductor (CMOS) multiplexers (infrared arrays). Practical FPA detector characterization is outlined. The nondestructive readout capability available in some CIDs and FPA devices is discussed as a means for signal-to-noise ratio improvement. Derivations of the equations are fully presented to unify understanding of this method by the spectroscopic community.

Investigation of noise in gear transmissions by the method of mathematical smoothing of experiments

NASA Technical Reports Server (NTRS)

Sheftel, B. T.; Lipskiy, G. K.; Ananov, P. P.; Chernenko, I. K.

1973-01-01

A rotatable central component smoothing method is used to analyze rotating gear noise spectra. A matrix is formulated in which the randomized rows correspond to various tests and the columns to factor values. Canonical analysis of the obtained regression equation permits the calculation of optimal speed and load at a previous assigned noise level.

[Extraction of evoked related potentials by using the combination of independent component analysis and wavelet analysis].

PubMed

Zou, Ling; Chen, Shuyue; Sun, Yuqiang; Ma, Zhenghua

2010-08-01

In this paper we present a new method of combining Independent Component Analysis (ICA) and Wavelet de-noising algorithm to extract Evoked Related Potentials (ERPs). First, the extended Infomax-ICA algorithm is used to analyze EEG signals and obtain the independent components (Ics); Then, the Wave Shrink (WS) method is applied to the demixed Ics as an intermediate step; the EEG data were rebuilt by using the inverse ICA based on the new Ics; the ERPs were extracted by using de-noised EEG data after being averaged several trials. The experimental results showed that the combined method and ICA method could remove eye artifacts and muscle artifacts mixed in the ERPs, while the combined method could retain the brain neural activity mixed in the noise Ics and could extract the weak ERPs efficiently from strong background artifacts.

Seismic noise attenuation using an online subspace tracking algorithm

NASA Astrophysics Data System (ADS)

Zhou, Yatong; Li, Shuhua; Zhang, Dong; Chen, Yangkang

2018-02-01

We propose a new low-rank based noise attenuation method using an efficient algorithm for tracking subspaces from highly corrupted seismic observations. The subspace tracking algorithm requires only basic linear algebraic manipulations. The algorithm is derived by analysing incremental gradient descent on the Grassmannian manifold of subspaces. When the multidimensional seismic data are mapped to a low-rank space, the subspace tracking algorithm can be directly applied to the input low-rank matrix to estimate the useful signals. Since the subspace tracking algorithm is an online algorithm, it is more robust to random noise than traditional truncated singular value decomposition (TSVD) based subspace tracking algorithm. Compared with the state-of-the-art algorithms, the proposed denoising method can obtain better performance. More specifically, the proposed method outperforms the TSVD-based singular spectrum analysis method in causing less residual noise and also in saving half of the computational cost. Several synthetic and field data examples with different levels of complexities demonstrate the effectiveness and robustness of the presented algorithm in rejecting different types of noise including random noise, spiky noise, blending noise, and coherent noise.

Radiation noise of the bearing applied to the ceramic motorized spindle based on the sub-source decomposition method

NASA Astrophysics Data System (ADS)

Bai, X. T.; Wu, Y. H.; Zhang, K.; Chen, C. Z.; Yan, H. P.

2017-12-01

This paper mainly focuses on the calculation and analysis on the radiation noise of the angular contact ball bearing applied to the ceramic motorized spindle. The dynamic model containing the main working conditions and structural parameters is established based on dynamic theory of rolling bearing. The sub-source decomposition method is introduced in for the calculation of the radiation noise of the bearing, and a comparative experiment is adopted to check the precision of the method. Then the comparison between the contribution of different components is carried out in frequency domain based on the sub-source decomposition method. The spectrum of radiation noise of different components under various rotation speeds are used as the basis of assessing the contribution of different eigenfrequencies on the radiation noise of the components, and the proportion of friction noise and impact noise is evaluated as well. The results of the research provide the theoretical basis for the calculation of bearing noise, and offers reference to the impact of different components on the radiation noise of the bearing under different rotation speed.

Speckle noise reduction technique for Lidar echo signal based on self-adaptive pulse-matching independent component analysis

NASA Astrophysics Data System (ADS)

Xu, Fan; Wang, Jiaxing; Zhu, Daiyin; Tu, Qi

2018-04-01

Speckle noise has always been a particularly tricky problem in improving the ranging capability and accuracy of Lidar system especially in harsh environment. Currently, effective speckle de-noising techniques are extremely scarce and should be further developed. In this study, a speckle noise reduction technique has been proposed based on independent component analysis (ICA). Since normally few changes happen in the shape of laser pulse itself, the authors employed the laser source as a reference pulse and executed the ICA decomposition to find the optimal matching position. In order to achieve the self-adaptability of algorithm, local Mean Square Error (MSE) has been defined as an appropriate criterion for investigating the iteration results. The obtained experimental results demonstrated that the self-adaptive pulse-matching ICA (PM-ICA) method could effectively decrease the speckle noise and recover the useful Lidar echo signal component with high quality. Especially, the proposed method achieves 4 dB more improvement of signal-to-noise ratio (SNR) than a traditional homomorphic wavelet method.

Understanding perception of active noise control system through multichannel EEG analysis.

PubMed

Bagha, Sangeeta; Tripathy, R K; Nanda, Pranati; Preetam, C; Das, Debi Prasad

2018-06-01

In this Letter, a method is proposed to investigate the effect of noise with and without active noise control (ANC) on multichannel electroencephalogram (EEG) signal. The multichannel EEG signal is recorded during different listening conditions such as silent, music, noise, ANC with background noise and ANC with both background noise and music. The multiscale analysis of EEG signal of each channel is performed using the discrete wavelet transform. The multivariate multiscale matrices are formulated based on the sub-band signals of each EEG channel. The singular value decomposition is applied to the multivariate matrices of multichannel EEG at significant scales. The singular value features at significant scales and the extreme learning machine classifier with three different activation functions are used for classification of multichannel EEG signal. The experimental results demonstrate that, for ANC with noise and ANC with noise and music classes, the proposed method has sensitivity values of 75.831% ( p < 0.001 ) and 99.31% ( p < 0.001 ), respectively. The method has an accuracy value of 83.22% for the classification of EEG signal with music and ANC with music as stimuli. The important finding of this study is that by the introduction of ANC, music can be better perceived by the human brain.

Noise Reduction in High-Throughput Gene Perturbation Screens

USDA-ARS?s Scientific Manuscript database

Motivation: Accurate interpretation of perturbation screens is essential for a successful functional investigation. However, the screened phenotypes are often distorted by noise, and their analysis requires specialized statistical analysis tools. The number and scope of statistical methods available...

Background Registration-Based Adaptive Noise Filtering of LWIR/MWIR Imaging Sensors for UAV Applications

PubMed Central

Kim, Byeong Hak; Kim, Min Young; Chae, You Seong

2017-01-01

Unmanned aerial vehicles (UAVs) are equipped with optical systems including an infrared (IR) camera such as electro-optical IR (EO/IR), target acquisition and designation sights (TADS), or forward looking IR (FLIR). However, images obtained from IR cameras are subject to noise such as dead pixels, lines, and fixed pattern noise. Nonuniformity correction (NUC) is a widely employed method to reduce noise in IR images, but it has limitations in removing noise that occurs during operation. Methods have been proposed to overcome the limitations of the NUC method, such as two-point correction (TPC) and scene-based NUC (SBNUC). However, these methods still suffer from unfixed pattern noise. In this paper, a background registration-based adaptive noise filtering (BRANF) method is proposed to overcome the limitations of conventional methods. The proposed BRANF method utilizes background registration processing and robust principle component analysis (RPCA). In addition, image quality verification methods are proposed that can measure the noise filtering performance quantitatively without ground truth images. Experiments were performed for performance verification with middle wave infrared (MWIR) and long wave infrared (LWIR) images obtained from practical military optical systems. As a result, it is found that the image quality improvement rate of BRANF is 30% higher than that of conventional NUC. PMID:29280970

Background Registration-Based Adaptive Noise Filtering of LWIR/MWIR Imaging Sensors for UAV Applications.

PubMed

Kim, Byeong Hak; Kim, Min Young; Chae, You Seong

2017-12-27

Unmanned aerial vehicles (UAVs) are equipped with optical systems including an infrared (IR) camera such as electro-optical IR (EO/IR), target acquisition and designation sights (TADS), or forward looking IR (FLIR). However, images obtained from IR cameras are subject to noise such as dead pixels, lines, and fixed pattern noise. Nonuniformity correction (NUC) is a widely employed method to reduce noise in IR images, but it has limitations in removing noise that occurs during operation. Methods have been proposed to overcome the limitations of the NUC method, such as two-point correction (TPC) and scene-based NUC (SBNUC). However, these methods still suffer from unfixed pattern noise. In this paper, a background registration-based adaptive noise filtering (BRANF) method is proposed to overcome the limitations of conventional methods. The proposed BRANF method utilizes background registration processing and robust principle component analysis (RPCA). In addition, image quality verification methods are proposed that can measure the noise filtering performance quantitatively without ground truth images. Experiments were performed for performance verification with middle wave infrared (MWIR) and long wave infrared (LWIR) images obtained from practical military optical systems. As a result, it is found that the image quality improvement rate of BRANF is 30% higher than that of conventional NUC.

Structural Noise and Acoustic Characteristics Improvement of Transport Power Plants

NASA Astrophysics Data System (ADS)

Chaynov, N. D.; Markov, V. A.; Savastenko, A. A.

2018-03-01

Noise reduction generated during the operation of various machines and mechanisms is an urgent task with regard to the power plants and, in particular, to internal combustion engines. Sound emission from the surfaces vibration of body parts is one of the main noise manifestations of the running engine and it is called a structural noise. The vibration defining of the outer surfaces of complex body parts and the calculation of their acoustic characteristics are determined with numerical methods. At the same time, realization of finite and boundary elements methods combination turned out to be very effective. The finite element method is used in calculating the structural elements vibrations, and the boundary elements method is used in the structural noise calculation. The main conditions of the methodology and the results of the structural noise analysis applied to a number of automobile engines are shown.

Two-Dimensional Fourier Transform Analysis of Helicopter Flyover Noise

NASA Technical Reports Server (NTRS)

SantaMaria, Odilyn L.; Farassat, F.; Morris, Philip J.

1999-01-01

A method to separate main rotor and tail rotor noise from a helicopter in flight is explored. Being the sum of two periodic signals of disproportionate, or incommensurate frequencies, helicopter noise is neither periodic nor stationary. The single Fourier transform divides signal energy into frequency bins of equal size. Incommensurate frequencies are therefore not adequately represented by any one chosen data block size. A two-dimensional Fourier analysis method is used to separate main rotor and tail rotor noise. The two-dimensional spectral analysis method is first applied to simulated signals. This initial analysis gives an idea of the characteristics of the two-dimensional autocorrelations and spectra. Data from a helicopter flight test is analyzed in two dimensions. The test aircraft are a Boeing MD902 Explorer (no tail rotor) and a Sikorsky S-76 (4-bladed tail rotor). The results show that the main rotor and tail rotor signals can indeed be separated in the two-dimensional Fourier transform spectrum. The separation occurs along the diagonals associated with the frequencies of interest. These diagonals are individual spectra containing only information related to one particular frequency.

Noise in Charge Amplifiers— A gm/ID Approach

NASA Astrophysics Data System (ADS)

Alvarez, Enrique; Avila, Diego; Campillo, Hernan; Dragone, Angelo; Abusleme, Angel

2012-10-01

Charge amplifiers represent the standard solution to amplify signals from capacitive detectors in high energy physics experiments. In a typical front-end, the noise due to the charge amplifier, and particularly from its input transistor, limits the achievable resolution. The classic approach to attenuate noise effects in MOSFET charge amplifiers is to use the maximum power available, to use a minimum-length input device, and to establish the input transistor width in order to achieve the optimal capacitive matching at the input node. These conclusions, reached by analysis based on simple noise models, lead to sub-optimal results. In this work, a new approach on noise analysis for charge amplifiers based on an extension of the gm/ID methodology is presented. This method combines circuit equations and results from SPICE simulations, both valid for all operation regions and including all noise sources. The method, which allows to find the optimal operation point of the charge amplifier input device for maximum resolution, shows that the minimum device length is not necessarily the optimal, that flicker noise is responsible for the non-monotonic noise versus current function, and provides a deeper insight on the noise limits mechanism from an alternative and more design-oriented point of view.

Development of a low cost method to estimate the seismic signature of a geothermal field form ambient noise analysis.

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

Tibuleac, Ileana

2016-06-30

A new, cost effective and non-invasive exploration method using ambient seismic noise has been tested at Soda Lake, NV, with promising results. The material included in this report demonstrates that, with the advantage of initial S-velocity models estimated from ambient noise surface waves, the seismic reflection survey, although with lower resolution, reproduces the results of the active survey when the ambient seismic noise is not contaminated by strong cultural noise. Ambient noise resolution is less at depth (below 1000m) compared to the active survey. In general, the results are promising and useful information can be recovered from ambient seismic noise,more » including dipping features and fault locations.« less

Near-field noise prediction for aircraft in cruising flight: Methods manual. [laminar flow control noise effects analysis

NASA Technical Reports Server (NTRS)

Tibbetts, J. G.

1979-01-01

Methods for predicting noise at any point on an aircraft while the aircraft is in a cruise flight regime are presented. Developed for use in laminar flow control (LFC) noise effects analyses, they can be used in any case where aircraft generated noise needs to be evaluated at a location on an aircraft while under high altitude, high speed conditions. For each noise source applicable to the LFC problem, a noise computational procedure is given in algorithm format, suitable for computerization. Three categories of noise sources are covered: (1) propulsion system, (2) airframe, and (3) LFC suction system. In addition, procedures are given for noise modifications due to source soundproofing and the shielding effects of the aircraft structure wherever needed. Sample cases, for each of the individual noise source procedures, are provided to familiarize the user with typical input and computed data.

Evaluation of Wavelet Denoising Methods for Small-Scale Joint Roughness Estimation Using Terrestrial Laser Scanning

NASA Astrophysics Data System (ADS)

Bitenc, M.; Kieffer, D. S.; Khoshelham, K.

2015-08-01

The precision of Terrestrial Laser Scanning (TLS) data depends mainly on the inherent random range error, which hinders extraction of small details from TLS measurements. New post processing algorithms have been developed that reduce or eliminate the noise and therefore enable modelling details at a smaller scale than one would traditionally expect. The aim of this research is to find the optimum denoising method such that the corrected TLS data provides a reliable estimation of small-scale rock joint roughness. Two wavelet-based denoising methods are considered, namely Discrete Wavelet Transform (DWT) and Stationary Wavelet Transform (SWT), in combination with different thresholding procedures. The question is, which technique provides a more accurate roughness estimates considering (i) wavelet transform (SWT or DWT), (ii) thresholding method (fixed-form or penalised low) and (iii) thresholding mode (soft or hard). The performance of denoising methods is tested by two analyses, namely method noise and method sensitivity to noise. The reference data are precise Advanced TOpometric Sensor (ATOS) measurements obtained on 20 × 30 cm rock joint sample, which are for the second analysis corrupted by different levels of noise. With such a controlled noise level experiments it is possible to evaluate the methods' performance for different amounts of noise, which might be present in TLS data. Qualitative visual checks of denoised surfaces and quantitative parameters such as grid height and roughness are considered in a comparative analysis of denoising methods. Results indicate that the preferred method for realistic roughness estimation is DWT with penalised low hard thresholding.

Comparative study of signalling methods for high-speed backplane transceiver

NASA Astrophysics Data System (ADS)

Wu, Kejun

2017-11-01

A combined analysis of transient simulation and statistical method is proposed for comparative study of signalling methods applied to high-speed backplane transceivers. This method enables fast and accurate signal-to-noise ratio and symbol error rate estimation of a serial link based on a four-dimension design space, including channel characteristics, noise scenarios, equalisation schemes, and signalling methods. The proposed combined analysis method chooses an efficient sampling size for performance evaluation. A comparative study of non-return-to-zero (NRZ), PAM-4, and four-phase shifted sinusoid symbol (PSS-4) using parameterised behaviour-level simulation shows PAM-4 and PSS-4 has substantial advantages over conventional NRZ in most of the cases. A comparison between PAM-4 and PSS-4 shows PAM-4 gets significant bit error rate degradation when noise level is enhanced.

Universal method for crosstalk noise and transmission loss analysis for N-port nonblocking optical router for photonic networks-on-chip

NASA Astrophysics Data System (ADS)

Xie, Yiyuan; Zhang, Zhendong; Song, Tingting; He, Chao; Li, Jiachao; Wang, Guijin

2016-05-01

Crosstalk noise and transmission loss are two key elements in determining the performance of optical routers. We propose a universal method for crosstalk noise and transmission loss analysis for the N-port nonblocking optical router used in photonic networks-on-chip. Utilizing this method, we study the crosstalk noise and transmission loss for the five-, six-, seven-, and eight-port optical routers. We ascertain that the crosstalk noise and transmission loss are different for different input-output pairs. For the five-port optical router, the maximum crosstalk noise ranges from 0 to -7.07 dBm, and the transmission loss ranges from -9.05 to -0.51 dB. Furthermore, based on the crosstalk noise and transmission loss, we analyze optical signal-to-noise ratio (OSNR) and bit error ratio (BER) for the five-, six-, seven-, and eight-port nonblocking optical routers. As the number of ports increases, the minimum average OSNR decreases and the average BER increases. In addition, in order to present the performance of the routers more visually, a fiber-optic communications system is designed to simulate the transmission processes of the signals of the different paths of the routers in Optisystem. The results show that the power amplitude of the input signal is obviously higher than the corresponding output signal. With this method, we can easily evaluate the transmission loss, crosstalk noise, OSNR, and BER of high-radix nonblocking optical routers and conveniently study the performance of the N-port optical router.

Least Squares Moving-Window Spectral Analysis.

PubMed

Lee, Young Jong

2017-08-01

Least squares regression is proposed as a moving-windows method for analysis of a series of spectra acquired as a function of external perturbation. The least squares moving-window (LSMW) method can be considered an extended form of the Savitzky-Golay differentiation for nonuniform perturbation spacing. LSMW is characterized in terms of moving-window size, perturbation spacing type, and intensity noise. Simulation results from LSMW are compared with results from other numerical differentiation methods, such as single-interval differentiation, autocorrelation moving-window, and perturbation correlation moving-window methods. It is demonstrated that this simple LSMW method can be useful for quantitative analysis of nonuniformly spaced spectral data with high frequency noise.

Application of wavelet multi-resolution analysis for correction of seismic acceleration records

NASA Astrophysics Data System (ADS)

Ansari, Anooshiravan; Noorzad, Assadollah; Zare, Mehdi

2007-12-01

During an earthquake, many stations record the ground motion, but only a few of them could be corrected using conventional high-pass and low-pass filtering methods and the others were identified as highly contaminated by noise and as a result useless. There are two major problems associated with these noisy records. First, since the signal to noise ratio (S/N) is low, it is not possible to discriminate between the original signal and noise either in the frequency domain or in the time domain. Consequently, it is not possible to cancel out noise using conventional filtering methods. The second problem is the non-stationary characteristics of the noise. In other words, in many cases the characteristics of the noise are varied over time and in these situations, it is not possible to apply frequency domain correction schemes. When correcting acceleration signals contaminated with high-level non-stationary noise, there is an important question whether it is possible to estimate the state of the noise in different bands of time and frequency. Wavelet multi-resolution analysis decomposes a signal into different time-frequency components, and besides introducing a suitable criterion for identification of the noise among each component, also provides the required mathematical tool for correction of highly noisy acceleration records. In this paper, the characteristics of the wavelet de-noising procedures are examined through the correction of selected real and synthetic acceleration time histories. It is concluded that this method provides a very flexible and efficient tool for the correction of very noisy and non-stationary records of ground acceleration. In addition, a two-step correction scheme is proposed for long period correction of the acceleration records. This method has the advantage of stable results in displacement time history and response spectrum.

Developments in ambient noise analysis for the characterization of dynamic response of slopes to seismic shaking

NASA Astrophysics Data System (ADS)

Del Gaudio, Vincenzo; Wasowski, Janusz

2016-04-01

In the last few decades, we have witnessed a growing awareness of the role of site dynamic response to seismic shaking in slope failures during earthquakes. Considering the time and costs involved in acquiring accelerometer data on landslide prone slopes, the analysis of ambient noise offers a profitable investigative alternative. Standard procedures of ambient noise analysis, according to the technique known as HVNR or Nakamura's method, were originally devised to interpret data under simple site conditions similar to 1D layering (flat horizontal layering infinitely extended). In such cases, conditions of site amplification, characterized by a strong impedance contrast between a soft surface layer and a stiff bedrock, result in a single pronounced isotropic maximum of spectral ratios between horizontal and vertical component of ambient noise. However, previous studies have shown that the dynamic response of slopes affected by landslides is rather complex, being characterized by multiple resonance peaks with directional variability, thus, the use of standard techniques can encounter difficulties in providing reliable information. A new approach of data analysis has recently been proposed to exploit the potential of information content of Rayleigh waves present in ambient noise, with regard to the identification of frequency and orientation of directional resonance. By exploiting ground motion ellipticity this approach can also provide information on vertical distribution of S-wave velocity, which controls site amplification factors. The method, based on the identification of Rayleigh wave packets from instantaneous polarization properties of ambient noise, was first tested using synthetic signals in order to optimize the data processing system. Then the improved processing scheme is adopted to re-process and re-interpret the ambient noise data acquired on landslide prone slopes around Caramanico Terme (central Italy), at sites monitored also with accelerometer stations. The comparison of ambient noise analysis results with the outcomes of accelerometer monitoring reveals potential and limits of the new method for the investigations on slope dynamic response.

Allowable SEM noise for unbiased LER measurement

NASA Astrophysics Data System (ADS)

Papavieros, George; Constantoudis, Vassilios; Gogolides, Evangelos

2018-03-01

Recently, a novel method for the calculation of unbiased Line Edge Roughness based on Power Spectral Density analysis has been proposed. In this paper first an alternative method is discussed and investigated, utilizing the Height-Height Correlation Function (HHCF) of edges. The HHCF-based method enables the unbiased determination of the whole triplet of LER parameters including besides rms the correlation length and roughness exponent. The key of both methods is the sensitivity of PSD and HHCF on noise at high frequencies and short distance respectively. Secondly, we elaborate a testbed of synthesized SEM images with controlled LER and noise to justify the effectiveness of the proposed unbiased methods. Our main objective is to find out the boundaries of the method in respect to noise levels and roughness characteristics, for which the method remains reliable, i.e the maximum amount of noise allowed, for which the output results cope with the controllable known inputs. At the same time, we will also set the extremes of roughness parameters for which the methods hold their accuracy.

A Study of Morrison's Iterative Noise Removal Method. Final Report M. S. Thesis

NASA Technical Reports Server (NTRS)

Ioup, G. E.; Wright, K. A. R.

1985-01-01

Morrison's iterative noise removal method is studied by characterizing its effect upon systems of differing noise level and response function. The nature of data acquired from a linear shift invariant instrument is discussed so as to define the relationship between the input signal, the instrument response function, and the output signal. Fourier analysis is introduced, along with several pertinent theorems, as a tool to more thorough understanding of the nature of and difficulties with deconvolution. In relation to such difficulties the necessity of a noise removal process is discussed. Morrison's iterative noise removal method and the restrictions upon its application are developed. The nature of permissible response functions is discussed, as is the choice of the response functions used.

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.

Determination of Rayleigh wave ellipticity across the Earthscope Transportable Array using single-station and array-based processing of ambient seismic noise

NASA Astrophysics Data System (ADS)

Workman, Eli; Lin, Fan-Chi; Koper, Keith D.

2017-01-01

We present a single station method for the determination of Rayleigh wave ellipticity, or Rayleigh wave horizontal to vertical amplitude ratio (H/V) using Frequency Dependent Polarization Analysis (FDPA). This procedure uses singular value decomposition of 3-by-3 spectral covariance matrices over 1-hr time windows to determine properties of the ambient seismic noise field such as particle motion and dominant wave-type. In FPDA, if the noise is mostly dominated by a primary singular value and the phase difference is roughly 90° between the major horizontal axis and the vertical axis of the corresponding singular vector, we infer that Rayleigh waves are dominant and measure an H/V ratio for that hour and frequency bin. We perform this analysis for all available data from the Earthscope Transportable Array between 2004 and 2014. We compare the observed Rayleigh wave H/V ratios with those previously measured by multicomponent, multistation noise cross-correlation (NCC), as well as classical noise spectrum H/V ratio analysis (NSHV). At 8 s the results from all three methods agree, suggesting that the ambient seismic noise field is Rayleigh wave dominated. Between 10 and 30 s, while the general pattern agrees well, the results from FDPA and NSHV are persistently slightly higher (˜2 per cent) and significantly higher (>20 per cent), respectively, than results from the array-based NCC. This is likely caused by contamination from other wave types (i.e. Love waves, body waves, and tilt noise) in the single station methods, but it could also reflect a small, persistent error in NCC. Additionally, we find that the single station method has difficulty retrieving robust Rayleigh wave H/V ratios within major sedimentary basins, such as the Williston Basin and Mississippi Embayment, where the noise field is likely dominated by reverberating Love waves and tilt noise.

Data Transmission Signal Design and Analysis

NASA Technical Reports Server (NTRS)

Moore, J. D.

1972-01-01

The error performances of several digital signaling methods are determined as a function of a specified signal-to-noise ratio. Results are obtained for Gaussian noise and impulse noise. Performance of a receiver for differentially encoded biphase signaling is obtained by extending the results of differential phase shift keying. The analysis presented obtains a closed-form answer through the use of some simplifying assumptions. The results give an insight into the analysis problem, however, the actual error performance may show a degradation because of the assumptions made in the analysis. Bipolar signaling decision-threshold selection is investigated. The optimum threshold depends on the signal-to-noise ratio and requires the use of an adaptive receiver.

Improved estimation of parametric images of cerebral glucose metabolic rate from dynamic FDG-PET using volume-wise principle component analysis

NASA Astrophysics Data System (ADS)

Dai, Xiaoqian; Tian, Jie; Chen, Zhe

2010-03-01

Parametric images can represent both spatial distribution and quantification of the biological and physiological parameters of tracer kinetics. The linear least square (LLS) method is a well-estimated linear regression method for generating parametric images by fitting compartment models with good computational efficiency. However, bias exists in LLS-based parameter estimates, owing to the noise present in tissue time activity curves (TTACs) that propagates as correlated error in the LLS linearized equations. To address this problem, a volume-wise principal component analysis (PCA) based method is proposed. In this method, firstly dynamic PET data are properly pre-transformed to standardize noise variance as PCA is a data driven technique and can not itself separate signals from noise. Secondly, the volume-wise PCA is applied on PET data. The signals can be mostly represented by the first few principle components (PC) and the noise is left in the subsequent PCs. Then the noise-reduced data are obtained using the first few PCs by applying 'inverse PCA'. It should also be transformed back according to the pre-transformation method used in the first step to maintain the scale of the original data set. Finally, the obtained new data set is used to generate parametric images using the linear least squares (LLS) estimation method. Compared with other noise-removal method, the proposed method can achieve high statistical reliability in the generated parametric images. The effectiveness of the method is demonstrated both with computer simulation and with clinical dynamic FDG PET study.

A Comparative Analysis of Pitch Detection Methods Under the Influence of Different Noise Conditions.

PubMed

Sukhostat, Lyudmila; Imamverdiyev, Yadigar

2015-07-01

Pitch is one of the most important components in various speech processing systems. The aim of this study was to evaluate different pitch detection methods in terms of various noise conditions. Prospective study. For evaluation of pitch detection algorithms, time-domain, frequency-domain, and hybrid methods were considered by using Keele and CSTR speech databases. Each of them has its own advantages and disadvantages. Experiments have shown that BaNa method achieves the highest pitch detection accuracy. The development of methods for pitch detection, which are robust to additive noise at different signal-to-noise ratio, is an important field of research with many opportunities for enhancement the modern methods. Copyright © 2015 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

Passive interior noise reduction analysis of King Air 350 turboprop aircraft using boundary element method/finite element method (BEM/FEM)

NASA Astrophysics Data System (ADS)

Dandaroy, Indranil; Vondracek, Joseph; Hund, Ron; Hartley, Dayton

2005-09-01

The objective of this study was to develop a vibro-acoustic computational model of the Raytheon King Air 350 turboprop aircraft with an intent to reduce propfan noise in the cabin. To develop the baseline analysis, an acoustic cavity model of the aircraft interior and a structural dynamics model of the aircraft fuselage were created. The acoustic model was an indirect boundary element method representation using SYSNOISE, while the structural model was a finite-element method normal modes representation in NASTRAN and subsequently imported to SYSNOISE. In the acoustic model, the fan excitation sources were represented employing the Ffowcs Williams-Hawkings equation. The acoustic and the structural models were fully coupled in SYSNOISE and solved to yield the baseline response of acoustic pressure in the aircraft interior and vibration on the aircraft structure due to fan noise. Various vibration absorbers, tuned to fundamental blade passage tone (100 Hz) and its first harmonic (200 Hz), were applied to the structural model to study their effect on cabin noise reduction. Parametric studies were performed to optimize the number and location of these passive devices. Effects of synchrophasing and absorptive noise treatments applied to the aircraft interior were also investigated for noise reduction.

Application of analysis techniques for low frequency interior noise and vibration of commercial aircraft

NASA Technical Reports Server (NTRS)

Landmann, A. E.; Tillema, H. F.; Macgregor, G. R.

1992-01-01

Finite element analysis (FEA), statistical energy analysis (SEA), and a power flow method (computer program PAIN) were used to assess low frequency interior noise associated with advanced propeller installations. FEA and SEA models were used to predict cabin noise and vibration and evaluate suppression concepts for structure-borne noise associated with the shaft rotational frequency and harmonics (less than 100 Hz). SEA and PAIN models were used to predict cabin noise and vibration and evaluate suppression concepts for airborne noise associated with engine radiated propeller tones. Both aft-mounted and wing-mounted propeller configurations were evaluated. Ground vibration test data from a 727 airplane modified to accept a propeller engine were used to compare with predictions for the aft-mounted propeller. Similar data from the 767 airplane was used for the wing-mounted comparisons.

Spectral Discrete Probability Density Function of Measured Wind Turbine Noise in the Far Field

PubMed Central

Ashtiani, Payam; Denison, Adelaide

2015-01-01

Of interest is the spectral character of wind turbine noise at typical residential set-back distances. In this paper, a spectral statistical analysis has been applied to immission measurements conducted at three locations. This method provides discrete probability density functions for the Turbine ONLY component of the measured noise. This analysis is completed for one-third octave sound levels, at integer wind speeds, and is compared to existing metrics for measuring acoustic comfort as well as previous discussions on low-frequency noise sources. PMID:25905097

Mapping underwater sound noise and assessing its sources by using a self-organizing maps method.

PubMed

Rako, Nikolina; Vilibić, Ivica; Mihanović, Hrvoje

2013-03-01

This study aims to provide an objective mapping of the underwater noise and its sources over an Adriatic coastal marine habitat by applying the self-organizing maps (SOM) method. Systematic sampling of sea ambient noise (SAN) was carried out at ten predefined acoustic stations between 2007 and 2009. Analyses of noise levels were performed for 1/3 octave band standard centered frequencies in terms of instantaneous sound pressure levels averaged over 300 s to calculate the equivalent continuous sound pressure levels. Data on vessels' presence, type, and distance from the monitoring stations were also collected at each acoustic station during the acoustic sampling. Altogether 69 noise surveys were introduced to the SOM predefined 2 × 2 array. The overall results of the analysis distinguished two dominant underwater soundscapes, associating them mainly to the seasonal changes in the nautical tourism and fishing activities within the study area and to the wind and wave action. The analysis identified recreational vessels as the dominant anthropogenic source of underwater noise, particularly during the tourist season. The method demonstrated to be an efficient tool in predicting the SAN levels based on the vessel distribution, indicating also the possibility of its wider implication for marine conservation.

Filtering of high noise breast thermal images using fast non-local means.

PubMed

Suganthi, S S; Ramakrishnan, S

2014-01-01

Analyses of breast thermograms are still a challenging task primarily due to the limitations such as low contrast, low signal to noise ratio and absence of clear edges. Therefore, always there is a requirement for preprocessing techniques before performing any quantitative analysis. In this work, a noise removal framework using fast non-local means algorithm, method noise and median filter was used to denoise breast thermograms. The images considered were subjected to Anscombe transformation to convert the distribution from Poisson to Gaussian. The pre-denoised image was obtained by subjecting the transformed image to fast non-local means filtering. The method noise which is the difference between the original and pre-denoised image was observed with the noise component merged in few structures and fine detail of the image. The image details presented in the method noise was extracted by smoothing the noise part using the median filter. The retrieved image part was added to the pre-denoised image to obtain the final denoised image. The performance of this technique was compared with that of Wiener and SUSAN filters. The results show that all the filters considered are able to remove the noise component. The performance of the proposed denoising framework is found to be good in preserving detail and removing noise. Further, the method noise is observed with negligible image details. Similarly, denoised image with no noise and smoothed edges are observed using Wiener filter and its method noise is contained with few structures and image details. The performance results of SUSAN filter is found to be blurred denoised image with little noise and also method noise with extensive structure and image details. Hence, it appears that the proposed denoising framework is able to preserve the edge information and generate clear image that could help in enhancing the diagnostic relevance of breast thermograms. In this paper, the introduction, objectives, materials and methods, results and discussion and conclusions are presented in detail.

Frequency domain analysis of errors in cross-correlations of ambient seismic noise

NASA Astrophysics Data System (ADS)

Liu, Xin; Ben-Zion, Yehuda; Zigone, Dimitri

2016-12-01

We analyse random errors (variances) in cross-correlations of ambient seismic noise in the frequency domain, which differ from previous time domain methods. Extending previous theoretical results on ensemble averaged cross-spectrum, we estimate confidence interval of stacked cross-spectrum of finite amount of data at each frequency using non-overlapping windows with fixed length. The extended theory also connects amplitude and phase variances with the variance of each complex spectrum value. Analysis of synthetic stationary ambient noise is used to estimate the confidence interval of stacked cross-spectrum obtained with different length of noise data corresponding to different number of evenly spaced windows of the same duration. This method allows estimating Signal/Noise Ratio (SNR) of noise cross-correlation in the frequency domain, without specifying filter bandwidth or signal/noise windows that are needed for time domain SNR estimations. Based on synthetic ambient noise data, we also compare the probability distributions, causal part amplitude and SNR of stacked cross-spectrum function using one-bit normalization or pre-whitening with those obtained without these pre-processing steps. Natural continuous noise records contain both ambient noise and small earthquakes that are inseparable from the noise with the existing pre-processing steps. Using probability distributions of random cross-spectrum values based on the theoretical results provides an effective way to exclude such small earthquakes, and additional data segments (outliers) contaminated by signals of different statistics (e.g. rain, cultural noise), from continuous noise waveforms. This technique is applied to constrain values and uncertainties of amplitude and phase velocity of stacked noise cross-spectrum at different frequencies, using data from southern California at both regional scale (˜35 km) and dense linear array (˜20 m) across the plate-boundary faults. A block bootstrap resampling method is used to account for temporal correlation of noise cross-spectrum at low frequencies (0.05-0.2 Hz) near the ocean microseismic peaks.

The Impact of Measurement Noise in GPA Diagnostic Analysis of a Gas Turbine Engine

NASA Astrophysics Data System (ADS)

Ntantis, Efstratios L.; Li, Y. G.

2013-12-01

The performance diagnostic analysis of a gas turbine is accomplished by estimating a set of internal engine health parameters from available sensor measurements. No physical measuring instruments however can ever completely eliminate the presence of measurement uncertainties. Sensor measurements are often distorted by noise and bias leading to inaccurate estimation results. This paper explores the impact of measurement noise on Gas Turbine GPA analysis. The analysis is demonstrated with a test case where gas turbine performance simulation and diagnostics code TURBOMATCH is used to build a performance model of a model engine similar to Rolls-Royce Trent 500 turbofan engine, and carry out the diagnostic analysis with the presence of different levels of measurement noise. Conclusively, to improve the reliability of the diagnostic results, a statistical analysis of the data scattering caused by sensor uncertainties is made. The diagnostic tool used to deal with the statistical analysis of measurement noise impact is a model-based method utilizing a non-linear GPA.

Development of Measurement Methods for Detection of Special Nuclear Materials using D-D Pulsed Neutron Source

NASA Astrophysics Data System (ADS)

Misawa, Tsuyoshi; Takahashi, Yoshiyuki; Yagi, Takahiro; Pyeon, Cheol Ho; Kimura, Masaharu; Masuda, Kai; Ohgaki, Hideaki

2015-10-01

For detection of hidden special nuclear materials (SNMs), we have developed an active neutron-based interrogation system combined with a D-D fusion pulsed neutron source and a neutron detection system. In the detection scheme, we have adopted new measurement techniques simultaneously; neutron noise analysis and neutron energy spectrum analysis. The validity of neutron noise analysis method has been experimentally studied in the Kyoto University Critical Assembly (KUCA), and was applied to a cargo container inspection system by simulation.

Readout Circuits for Noise Compensation in ISFET Sensory System

NASA Astrophysics Data System (ADS)

Das, M. P.; Bhuyan, M.; Talukdar, C.

2015-12-01

This paper presents two different noise reduction techniques for ion sensitive field effect transistor (ISFET) readout configuration and their comparison. The proposed circuit configurations are immune to the noise generated from the ISFET sensory system and particularly to the low frequency pH dependent 1/ f electrochemical noise. The methods used under this study are compensation of noise by differential OPAMP based and Wheatstone bridge circuit, where two identical commercial ISFET sensors were used. The statistical and frequency analysis of the data generated by this two methods were compared for different pH value ranging from pH 2 to 10 at room temperature, and it is found that the readout circuits are able to compensate the noise to a great extent.

Response analysis of a class of quasi-linear systems with fractional derivative excited by Poisson white noise

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

Yang, Yongge; Xu, Wei, E-mail: weixu@nwpu.edu.cn; Yang, Guidong

The Poisson white noise, as a typical non-Gaussian excitation, has attracted much attention recently. However, little work was referred to the study of stochastic systems with fractional derivative under Poisson white noise excitation. This paper investigates the stationary response of a class of quasi-linear systems with fractional derivative excited by Poisson white noise. The equivalent stochastic system of the original stochastic system is obtained. Then, approximate stationary solutions are obtained with the help of the perturbation method. Finally, two typical examples are discussed in detail to demonstrate the effectiveness of the proposed method. The analysis also shows that the fractionalmore » order and the fractional coefficient significantly affect the responses of the stochastic systems with fractional derivative.« less

Fast principal component analysis for stacking seismic data

NASA Astrophysics Data System (ADS)

Wu, Juan; Bai, Min

2018-04-01

Stacking seismic data plays an indispensable role in many steps of the seismic data processing and imaging workflow. Optimal stacking of seismic data can help mitigate seismic noise and enhance the principal components to a great extent. Traditional average-based seismic stacking methods cannot obtain optimal performance when the ambient noise is extremely strong. We propose a principal component analysis (PCA) algorithm for stacking seismic data without being sensitive to noise level. Considering the computational bottleneck of the classic PCA algorithm in processing massive seismic data, we propose an efficient PCA algorithm to make the proposed method readily applicable for industrial applications. Two numerically designed examples and one real seismic data are used to demonstrate the performance of the presented method.

2-COLOR Pupil Imaging Method to Detect Stellar Oscillations

NASA Astrophysics Data System (ADS)

Costantino, Sigismondi; Alessandro, Cacciani; Mauro, Dolci; Stuart, Jeffries; Eric, Fossat; Ludovico, Cesario; Paolo, Rapex; Luca, Bertello; Ferenc, Varadi; Wolfgang, Finsterle

Stellar intensity oscillations from the ground are strongly affected by atmospheric noise. For solar-type stars even Antarctic scintillation noise is still overwhelming. We proposed and tested a differential method that images on the same CCD detector two-color pupils of the telescope in order to compensate for intensity sky fluctuations guiding and saturation problems. SOHO data reveal that our method has an efficiency of 70% respect to the absolute amplitude variations. Using two instruments at Dome C and South Pole we can further minimize atmospheric color noise with cross-spectrum methods. This way we also decrease the likelihood of gaps in the data string due to bad weather. Observationally while waiting for the South Pole/Dome-C sites we are carrying on tests from available telescopes and Big Bear Mt. Wilson Teramo Milano. On the data analysis side we use the Random Lag Singular Cross-Spectrum Analysis which eliminates noise from the observed signal better than traditional Fourier transform. This method is also well-suited for extracting common oscillatory components from two or more observations including their relative phases as we are planning to do

Further studies of methods for reducing community noise around airports. [aircraft noise - aircraft engines

NASA Technical Reports Server (NTRS)

Petersen, R. H.; Barry, D. J.; Kline, D. M.

1975-01-01

A simplified method of analysis was used in which all flights at a 'simulated' airport were assumed to operate from one runway in a single direction. For this simulated airport, contours of noise exposure forecast were obtained and evaluated. A flight schedule of the simulated airport which is representative of the 23 major U. S. airports was used. The effect of banning night-time operations by four-engine, narrow-body aircraft in combination with other noise reduction options was studied. The reductions in noise which would occur of two- and three-engine, narrow-body aircraft equipped with a refanned engine was examined. A detailed comparison of the effects of engine cutback on takeoff versus the effects of retrofitting quiet nacelles for narrow-body aircraft was also examined. A method of presenting the effects of various noise reduction options was treated.

Noise Reduction Design of the Volute for a Centrifugal Compressor

NASA Astrophysics Data System (ADS)

Song, Zhen; Wen, Huabing; Hong, Liangxing; Jin, Yudong

2017-08-01

In order to effectively control the aerodynamic noise of a compressor, this paper takes into consideration a marine exhaust turbocharger compressor as a research object. According to the different design concept of volute section, tongue and exit cone, six different volute models were established. The finite volume method is used to calculate the flow field, whiles the finite element method is used for the acoustic calculation. Comparison and analysis of different structure designs from three aspects: noise level, isentropic efficiency and Static pressure recovery coefficient. The results showed that under the concept of volute section model 1 yielded the best result, under the concept of tongue analysis model 3 yielded the best result and finally under exit cone analysis model 6 yielded the best results.

Removal of Stationary Sinusoidal Noise from Random Vibration Signals.

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

Johnson, Brian; Cap, Jerome S.

In random vibration environments, sinusoidal line noise may appear in the vibration signal and can affect analysis of the resulting data. We studied two methods which remove stationary sine tones from random noise: a matrix inversion algorithm and a chirp-z transform algorithm. In addition, we developed new methods to determine the frequency of the tonal noise. The results show that both of the removal methods can eliminate sine tones in prefabricated random vibration data when the sine-to-random ratio is at least 0.25. For smaller ratios down to 0.02 only the matrix inversion technique can remove the tones, but the metricsmore » to evaluate its effectiveness also degrade. We also found that using fast Fourier transforms best identified the tonal noise, and determined that band-pass-filtering the signals prior to the process improved sine removal. When applied to actual vibration test data, the methods were not as effective at removing harmonic tones, which we believe to be a result of mixed-phase sinusoidal noise.« less

The Hilbert-Huang Transform-Based Denoising Method for the TEM Response of a PRBS Source Signal

NASA Astrophysics Data System (ADS)

Hai, Li; Guo-qiang, Xue; Pan, Zhao; Hua-sen, Zhong; Khan, Muhammad Younis

2016-08-01

The denoising process is critical in processing transient electromagnetic (TEM) sounding data. For the full waveform pseudo-random binary sequences (PRBS) response, an inadequate noise estimation may result in an erroneous interpretation. We consider the Hilbert-Huang transform (HHT) and its application to suppress the noise in the PRBS response. The focus is on the thresholding scheme to suppress the noise and the analysis of the signal based on its Hilbert time-frequency representation. The method first decomposes the signal into the intrinsic mode function, and then, inspired by the thresholding scheme in wavelet analysis; an adaptive and interval thresholding is conducted to set to zero all the components in intrinsic mode function which are lower than a threshold related to the noise level. The algorithm is based on the characteristic of the PRBS response. The HHT-based denoising scheme is tested on the synthetic and field data with the different noise levels. The result shows that the proposed method has a good capability in denoising and detail preservation.

A hybrid symplectic principal component analysis and central tendency measure method for detection of determinism in noisy time series with application to mechanomyography

NASA Astrophysics Data System (ADS)

Xie, Hong-Bo; Dokos, Socrates

2013-06-01

We present a hybrid symplectic geometry and central tendency measure (CTM) method for detection of determinism in noisy time series. CTM is effective for detecting determinism in short time series and has been applied in many areas of nonlinear analysis. However, its performance significantly degrades in the presence of strong noise. In order to circumvent this difficulty, we propose to use symplectic principal component analysis (SPCA), a new chaotic signal de-noising method, as the first step to recover the system dynamics. CTM is then applied to determine whether the time series arises from a stochastic process or has a deterministic component. Results from numerical experiments, ranging from six benchmark deterministic models to 1/f noise, suggest that the hybrid method can significantly improve detection of determinism in noisy time series by about 20 dB when the data are contaminated by Gaussian noise. Furthermore, we apply our algorithm to study the mechanomyographic (MMG) signals arising from contraction of human skeletal muscle. Results obtained from the hybrid symplectic principal component analysis and central tendency measure demonstrate that the skeletal muscle motor unit dynamics can indeed be deterministic, in agreement with previous studies. However, the conventional CTM method was not able to definitely detect the underlying deterministic dynamics. This result on MMG signal analysis is helpful in understanding neuromuscular control mechanisms and developing MMG-based engineering control applications.

A hybrid symplectic principal component analysis and central tendency measure method for detection of determinism in noisy time series with application to mechanomyography.

PubMed

Xie, Hong-Bo; Dokos, Socrates

2013-06-01

We present a hybrid symplectic geometry and central tendency measure (CTM) method for detection of determinism in noisy time series. CTM is effective for detecting determinism in short time series and has been applied in many areas of nonlinear analysis. However, its performance significantly degrades in the presence of strong noise. In order to circumvent this difficulty, we propose to use symplectic principal component analysis (SPCA), a new chaotic signal de-noising method, as the first step to recover the system dynamics. CTM is then applied to determine whether the time series arises from a stochastic process or has a deterministic component. Results from numerical experiments, ranging from six benchmark deterministic models to 1/f noise, suggest that the hybrid method can significantly improve detection of determinism in noisy time series by about 20 dB when the data are contaminated by Gaussian noise. Furthermore, we apply our algorithm to study the mechanomyographic (MMG) signals arising from contraction of human skeletal muscle. Results obtained from the hybrid symplectic principal component analysis and central tendency measure demonstrate that the skeletal muscle motor unit dynamics can indeed be deterministic, in agreement with previous studies. However, the conventional CTM method was not able to definitely detect the underlying deterministic dynamics. This result on MMG signal analysis is helpful in understanding neuromuscular control mechanisms and developing MMG-based engineering control applications.

Two-Dimensional Fourier Transform Applied to Helicopter Flyover Noise

NASA Technical Reports Server (NTRS)

Santa Maria, Odilyn L.

1999-01-01

A method to separate main rotor and tail rotor noise from a helicopter in flight is explored. Being the sum of two periodic signals of disproportionate, or incommensurate frequencies, helicopter noise is neither periodic nor stationary, but possibly harmonizable. The single Fourier transform divides signal energy into frequency bins of equal size. Incommensurate frequencies are therefore not adequately represented by any one chosen data block size. A two-dimensional Fourier analysis method is used to show helicopter noise as harmonizable. The two-dimensional spectral analysis method is first applied to simulated signals. This initial analysis gives an idea of the characteristics of the two-dimensional autocorrelations and spectra. Data from a helicopter flight test is analyzed in two dimensions. The test aircraft are a Boeing MD902 Explorer (no tail rotor) and a Sikorsky S-76 (4-bladed tail rotor). The results show that the main rotor and tail rotor signals can indeed be separated in the two-dimensional Fourier transform spectrum. The separation occurs along the diagonals associated with the frequencies of interest. These diagonals are individual spectra containing only information related to one particular frequency.

Interior Noise

NASA Technical Reports Server (NTRS)

Mixson, John S.; Wilby, John F.

1991-01-01

The generation and control of flight vehicle interior noise is discussed. Emphasis is placed on the mechanisms of transmission through airborne and structure-borne paths and the control of cabin noise by path modification. Techniques for identifying the relative contributions of the various source-path combinations are also discussed along with methods for the prediction of aircraft interior noise such as those based on the general modal theory and statistical energy analysis.

Methods for Detecting Low-Frequency Signals in the Presence of Strong Winds

DTIC Science & Technology

1990-05-01

34Two-Hydrophone Method of Eliminating the Effects of Nonacoustic Noise Interference in Measurements of Infra - sonic Ambient Noise Levels," J... Infrasonic Gradient Micro- phones and Windscreens," J. Acoustical Soc. Am., Vol 44 (November 1968), pp 1428-36. 9. M. Strasberg, "Dimensional Analysis of

Noise and linearity optimization methods for a 1.9GHz low noise amplifier.

PubMed

Guo, Wei; Huang, Da-Quan

2003-01-01

Noise and linearity performances are critical characteristics for radio frequency integrated circuits (RFICs), especially for low noise amplifiers (LNAs). In this paper, a detailed analysis of noise and linearity for the cascode architecture, a widely used circuit structure in LNA designs, is presented. The noise and the linearity improvement techniques for cascode structures are also developed and have been proven by computer simulating experiments. Theoretical analysis and simulation results showed that, for cascode structure LNAs, the first metallic oxide semiconductor field effect transistor (MOSFET) dominates the noise performance of the LNA, while the second MOSFET contributes more to the linearity. A conclusion is thus obtained that the first and second MOSFET of the LNA can be designed to optimize the noise performance and the linearity performance separately, without trade-offs. The 1.9GHz Complementary Metal-Oxide-Semiconductor (CMOS) LNA simulation results are also given as an application of the developed theory.

Measurement with verification of stationary signals and noise in extremely quiet environments: Measuring below the noise floor

PubMed Central

Ellingson, Roger M.; Gallun, Frederick J.; Bock, Guillaume

2015-01-01

It can be problematic to measure stationary acoustic sound pressure level in any environment when the target level approaches or lies below the minimum measureable sound pressure level of the measurement system itself. This minimum measureable level, referred to as the inherent measurement system noise floor, is generally established by noise emission characteristics of measurement system components such as microphones, preamplifiers, and other system circuitry. In this paper, methods are presented and shown accurate measuring stationary levels within 20 dB above and below this system noise floor. Methodology includes (1) measuring inherent measurement system noise, (2) subtractive energy based, inherent noise adjustment of levels affected by system noise floor, and (3) verifying accuracy of inherent noise adjustment technique. While generalizable to other purposes, the techniques presented here were specifically developed to quantify ambient noise levels in very quiet rooms used to evaluate free-field human hearing thresholds. Results obtained applying the methods to objectively measure and verify the ambient noise level in an extremely quiet room, using various measurement system noise floors and analysis bandwidths, are presented and discussed. The verified results demonstrate the adjustment method can accurately extend measurement range to 20 dB below the measurement system noise floor, and how measurement system frequency bandwidth can affect accuracy of reported noise levels. PMID:25786932

Determination of Rayleigh wave ellipticity using single-station and array-based processing of ambient seismic noise

NASA Astrophysics Data System (ADS)

Workman, Eli Joseph

We present a single-station method for the determination of Rayleigh wave ellipticity, or Rayleigh wave horizontal to vertical amplitude ratio (H/V) using Frequency Dependent Polarization Analysis (FDPA). This procedure uses singular value decomposition of 3-by-3 spectral covariance matrices over 1-hr time windows to determine properties of the ambient seismic noise field such as particle motion and dominant wave-type. In FPDA, if the noise is mostly dominated by a primary singular value and the phase difference is roughly 90° between the major horizontal axis and the vertical axis of the corresponding singular vector, we infer that Rayleigh waves are dominant and measure an H/V ratio for that hour and frequency bin. We perform this analysis for all available data from the Earthscope Transportable Array between 2004 and 2014. We compare the observed Rayleigh wave H/V ratios with those previously measured by multicomponent, multistation noise cross-correlation (NCC), as well as classical noise spectrum H/V ratio analysis (NSHV). At 8 sec the results from all three methods agree, suggesting that the ambient seismic noise field is Rayleigh wave dominated. Between 10 and 30 sec, while the general pattern agrees well, the results from FDPA and NSHV are persistently slightly higher ( 2%) and significantly higher (>20%), respectively, than results from the array-based NCC. This is likely caused by contamination from other wave types (i.e., Love waves, body waves, and tilt noise) in the single station methods, but it could also reflect a small, persistent error in NCC. Additionally, we find that the single station method has difficulty retrieving robust Rayleigh wave H/V ratios within major sedimentary basins, such as the Williston Basin and Mississippi Embayment, where the noise field is likely dominated by reverberating Love waves.

A Robust Deconvolution Method based on Transdimensional Hierarchical Bayesian Inference

NASA Astrophysics Data System (ADS)

Kolb, J.; Lekic, V.

2012-12-01

Analysis of P-S and S-P conversions allows us to map receiver side crustal and lithospheric structure. This analysis often involves deconvolution of the parent wave field from the scattered wave field as a means of suppressing source-side complexity. A variety of deconvolution techniques exist including damped spectral division, Wiener filtering, iterative time-domain deconvolution, and the multitaper method. All of these techniques require estimates of noise characteristics as input parameters. We present a deconvolution method based on transdimensional Hierarchical Bayesian inference in which both noise magnitude and noise correlation are used as parameters in calculating the likelihood probability distribution. Because the noise for P-S and S-P conversion analysis in terms of receiver functions is a combination of both background noise - which is relatively easy to characterize - and signal-generated noise - which is much more difficult to quantify - we treat measurement errors as an known quantity, characterized by a probability density function whose mean and variance are model parameters. This transdimensional Hierarchical Bayesian approach has been successfully used previously in the inversion of receiver functions in terms of shear and compressional wave speeds of an unknown number of layers [1]. In our method we used a Markov chain Monte Carlo (MCMC) algorithm to find the receiver function that best fits the data while accurately assessing the noise parameters. In order to parameterize the receiver function we model the receiver function as an unknown number of Gaussians of unknown amplitude and width. The algorithm takes multiple steps before calculating the acceptance probability of a new model, in order to avoid getting trapped in local misfit minima. Using both observed and synthetic data, we show that the MCMC deconvolution method can accurately obtain a receiver function as well as an estimate of the noise parameters given the parent and daughter components. Furthermore, we demonstrate that this new approach is far less susceptible to generating spurious features even at high noise levels. Finally, the method yields not only the most-likely receiver function, but also quantifies its full uncertainty. [1] Bodin, T., M. Sambridge, H. Tkalčić, P. Arroucau, K. Gallagher, and N. Rawlinson (2012), Transdimensional inversion of receiver functions and surface wave dispersion, J. Geophys. Res., 117, B02301

Noise Gating Solar Images

NASA Astrophysics Data System (ADS)

DeForest, Craig; Seaton, Daniel B.; Darnell, John A.

2017-08-01

I present and demonstrate a new, general purpose post-processing technique, "3D noise gating", that can reduce image noise by an order of magnitude or more without effective loss of spatial or temporal resolution in typical solar applications.Nearly all scientific images are, ultimately, limited by noise. Noise can be direct Poisson "shot noise" from photon counting effects, or introduced by other means such as detector read noise. Noise is typically represented as a random variable (perhaps with location- or image-dependent characteristics) that is sampled once per pixel or once per resolution element of an image sequence. Noise limits many aspects of image analysis, including photometry, spatiotemporal resolution, feature identification, morphology extraction, and background modeling and separation.Identifying and separating noise from image signal is difficult. The common practice of blurring in space and/or time works because most image "signal" is concentrated in the low Fourier components of an image, while noise is evenly distributed. Blurring in space and/or time attenuates the high spatial and temporal frequencies, reducing noise at the expense of also attenuating image detail. Noise-gating exploits the same property -- "coherence" -- that we use to identify features in images, to separate image features from noise.Processing image sequences through 3-D noise gating results in spectacular (more than 10x) improvements in signal-to-noise ratio, while not blurring bright, resolved features in either space or time. This improves most types of image analysis, including feature identification, time sequence extraction, absolute and relative photometry (including differential emission measure analysis), feature tracking, computer vision, correlation tracking, background modeling, cross-scale analysis, visual display/presentation, and image compression.I will introduce noise gating, describe the method, and show examples from several instruments (including SDO/AIA , SDO/HMI, STEREO/SECCHI, and GOES-R/SUVI) that explore the benefits and limits of the technique.

Data analysis and noise prediction for the QF-1B experimental fan stage

NASA Technical Reports Server (NTRS)

Bliss, D. B.; Chandiramani, K. L.; Piersol, A. G.

1976-01-01

The results of a fan noise data analysis and prediction effort using experimental data obtained from tests on the QF-1B research fan are described. Surface pressure measurements were made with flush mounted sensors installed on selected rotor blades and stator vanes and noise measurements were made by microphones located at the far field. Power spectral density analysis, time history studies, and calculation of coherence functions were made. The emphasis of these studies was on the characteristics of tones in the spectra. The amplitude behavior of spectral tones was found to have a large, often predominant, random component, suggesting that turbulent processes play an important role in the generation of tonal as well as broadband noise. Inputs from the data analysis were used in a prediction method which assumes that acoustic dipoles, produced by unsteady blade and van forces, are the important source of fan noise.

Improved NASA-ANOPP Noise Prediction Computer Code for Advanced Subsonic Propulsion Systems

NASA Technical Reports Server (NTRS)

Kontos, K. B.; Janardan, B. A.; Gliebe, P. R.

1996-01-01

Recent experience using ANOPP to predict turbofan engine flyover noise suggests that it over-predicts overall EPNL by a significant amount. An improvement in this prediction method is desired for system optimization and assessment studies of advanced UHB engines. An assessment of the ANOPP fan inlet, fan exhaust, jet, combustor, and turbine noise prediction methods is made using static engine component noise data from the CF6-8OC2, E(3), and QCSEE turbofan engines. It is shown that the ANOPP prediction results are generally higher than the measured GE data, and that the inlet noise prediction method (Heidmann method) is the most significant source of this overprediction. Fan noise spectral comparisons show that improvements to the fan tone, broadband, and combination tone noise models are required to yield results that more closely simulate the GE data. Suggested changes that yield improved fan noise predictions but preserve the Heidmann model structure are identified and described. These changes are based on the sets of engine data mentioned, as well as some CFM56 engine data that was used to expand the combination tone noise database. It should be noted that the recommended changes are based on an analysis of engines that are limited to single stage fans with design tip relative Mach numbers greater than one.

General aviation aircraft interior noise problem: Some suggested solutions

NASA Technical Reports Server (NTRS)

Roskam, J.; Navaneethan, R.

1984-01-01

Laboratory investigation of sound transmission through panels and the use of modern data analysis techniques applied to actual aircraft is used to determine methods to reduce general aviation interior noise. The experimental noise reduction characteristics of stiffened flat and curved panels with damping treatment are discussed. The experimental results of double-wall panels used in the general aviation industry are given. The effects of skin panel material, fiberglass insulation and trim panel material on the noise reduction characteristics of double-wall panels are investigated. With few modifications, the classical sound transmission theory can be used to design the interior noise control treatment of aircraft. Acoustic intensity and analysis procedures are included.

A numerical study of some potential sources of error in side-by-side seismometer evaluations

USGS Publications Warehouse

Holcomb, L. Gary

1990-01-01

This report presents the results of a series of computer simulations of potential errors in test data, which might be obtained when conducting side-by-side comparisons of seismometers. These results can be used as guides in estimating potential sources and magnitudes of errors one might expect when analyzing real test data. First, the derivation of a direct method for calculating the noise levels of two sensors in a side-by-side evaluation is repeated and extended slightly herein. This bulk of this derivation was presented previously (see Holcomb 1989); it is repeated here for easy reference.This method is applied to the analysis of a simulated test of two sensors in a side-by-side test in which the outputs of both sensors consist of white noise spectra with known signal-tonoise ratios (SNR's). This report extends this analysis to high SNR's to determine the limitations of the direct method for calculating the noise levels at signal-to-noise levels which are much higher than presented previously (see Holcomb 1989). Next, the method is used to analyze a simulated test of two sensors in a side-by-side test in which the outputs of both sensors consist of bandshaped noise spectra with known signal-tonoise ratios. This is a much more realistic representation of real world data because the earth's background spectrum is certainly not flat.Finally, the results of the analysis of simulated white and bandshaped side-by-side test data are used to assist in interpreting the analysis of the effects of simulated azimuthal misalignment in side-by-side sensor evaluations. A thorough understanding of azimuthal misalignment errors is important because of the physical impossibility of perfectly aligning two sensors in a real world situation. The analysis herein indicates that alignment errors place lower limits on the levels of system noise which can be resolved in a side-by-side measurement It also indicates that alignment errors are the source of the fact that real data noise spectra tend to follow the earth's background spectra in shape.

Statistics of baryon correlation functions in lattice QCD

NASA Astrophysics Data System (ADS)

Wagman, Michael L.; Savage, Martin J.; Nplqcd Collaboration

2017-12-01

A systematic analysis of the structure of single-baryon correlation functions calculated with lattice QCD is performed, with a particular focus on characterizing the structure of the noise associated with quantum fluctuations. The signal-to-noise problem in these correlation functions is shown, as long suspected, to result from a sign problem. The log-magnitude and complex phase are found to be approximately described by normal and wrapped normal distributions respectively. Properties of circular statistics are used to understand the emergence of a large time noise region where standard energy measurements are unreliable. Power-law tails in the distribution of baryon correlation functions, associated with stable distributions and "Lévy flights," are found to play a central role in their time evolution. A new method of analyzing correlation functions is considered for which the signal-to-noise ratio of energy measurements is constant, rather than exponentially degrading, with increasing source-sink separation time. This new method includes an additional systematic uncertainty that can be removed by performing an extrapolation, and the signal-to-noise problem reemerges in the statistics of this extrapolation. It is demonstrated that this new method allows accurate results for the nucleon mass to be extracted from the large-time noise region inaccessible to standard methods. The observations presented here are expected to apply to quantum Monte Carlo calculations more generally. Similar methods to those introduced here may lead to practical improvements in analysis of noisier systems.

The noise properties of 42 millisecond pulsars from the European Pulsar Timing Array and their impact on gravitational-wave searches

NASA Astrophysics Data System (ADS)

Caballero, R. N.; Lee, K. J.; Lentati, L.; Desvignes, G.; Champion, D. J.; Verbiest, J. P. W.; Janssen, G. H.; Stappers, B. W.; Kramer, M.; Lazarus, P.; Possenti, A.; Tiburzi, C.; Perrodin, D.; Osłowski, S.; Babak, S.; Bassa, C. G.; Brem, P.; Burgay, M.; Cognard, I.; Gair, J. R.; Graikou, E.; Guillemot, L.; Hessels, J. W. T.; Karuppusamy, R.; Lassus, A.; Liu, K.; McKee, J.; Mingarelli, C. M. F.; Petiteau, A.; Purver, M. B.; Rosado, P. A.; Sanidas, S.; Sesana, A.; Shaifullah, G.; Smits, R.; Taylor, S. R.; Theureau, G.; van Haasteren, R.; Vecchio, A.

2016-04-01

The sensitivity of Pulsar Timing Arrays to gravitational waves (GWs) depends on the noise present in the individual pulsar timing data. Noise may be either intrinsic or extrinsic to the pulsar. Intrinsic sources of noise will include rotational instabilities, for example. Extrinsic sources of noise include contributions from physical processes which are not sufficiently well modelled, for example, dispersion and scattering effects, analysis errors and instrumental instabilities. We present the results from a noise analysis for 42 millisecond pulsars (MSPs) observed with the European Pulsar Timing Array. For characterizing the low-frequency, stochastic and achromatic noise component, or `timing noise', we employ two methods, based on Bayesian and frequentist statistics. For 25 MSPs, we achieve statistically significant measurements of their timing noise parameters and find that the two methods give consistent results. For the remaining 17 MSPs, we place upper limits on the timing noise amplitude at the 95 per cent confidence level. We additionally place an upper limit on the contribution to the pulsar noise budget from errors in the reference terrestrial time standards (below 1 per cent), and we find evidence for a noise component which is present only in the data of one of the four used telescopes. Finally, we estimate that the timing noise of individual pulsars reduces the sensitivity of this data set to an isotropic, stochastic GW background by a factor of >9.1 and by a factor of >2.3 for continuous GWs from resolvable, inspiralling supermassive black hole binaries with circular orbits.

Simulation on a car interior aerodynamic noise control based on statistical energy analysis

NASA Astrophysics Data System (ADS)

Chen, Xin; Wang, Dengfeng; Ma, Zhengdong

2012-09-01

How to simulate interior aerodynamic noise accurately is an important question of a car interior noise reduction. The unsteady aerodynamic pressure on body surfaces is proved to be the key effect factor of car interior aerodynamic noise control in high frequency on high speed. In this paper, a detail statistical energy analysis (SEA) model is built. And the vibra-acoustic power inputs are loaded on the model for the valid result of car interior noise analysis. The model is the solid foundation for further optimization on car interior noise control. After the most sensitive subsystems for the power contribution to car interior noise are pointed by SEA comprehensive analysis, the sound pressure level of car interior aerodynamic noise can be reduced by improving their sound and damping characteristics. The further vehicle testing results show that it is available to improve the interior acoustic performance by using detailed SEA model, which comprised by more than 80 subsystems, with the unsteady aerodynamic pressure calculation on body surfaces and the materials improvement of sound/damping properties. It is able to acquire more than 2 dB reduction on the central frequency in the spectrum over 800 Hz. The proposed optimization method can be looked as a reference of car interior aerodynamic noise control by the detail SEA model integrated unsteady computational fluid dynamics (CFD) and sensitivity analysis of acoustic contribution.

Linnorm: improved statistical analysis for single cell RNA-seq expression data

PubMed Central

Yip, Shun H.; Wang, Panwen; Kocher, Jean-Pierre A.; Sham, Pak Chung

2017-01-01

Abstract Linnorm is a novel normalization and transformation method for the analysis of single cell RNA sequencing (scRNA-seq) data. Linnorm is developed to remove technical noises and simultaneously preserve biological variations in scRNA-seq data, such that existing statistical methods can be improved. Using real scRNA-seq data, we compared Linnorm with existing normalization methods, including NODES, SAMstrt, SCnorm, scran, DESeq and TMM. Linnorm shows advantages in speed, technical noise removal and preservation of cell heterogeneity, which can improve existing methods in the discovery of novel subtypes, pseudo-temporal ordering of cells, clustering analysis, etc. Linnorm also performs better than existing DEG analysis methods, including BASiCS, NODES, SAMstrt, Seurat and DESeq2, in false positive rate control and accuracy. PMID:28981748

Noise-aware dictionary-learning-based sparse representation framework for detection and removal of single and combined noises from ECG signal

PubMed Central

Ramkumar, Barathram; Sabarimalai Manikandan, M.

2017-01-01

Automatic electrocardiogram (ECG) signal enhancement has become a crucial pre-processing step in most ECG signal analysis applications. In this Letter, the authors propose an automated noise-aware dictionary learning-based generalised ECG signal enhancement framework which can automatically learn the dictionaries based on the ECG noise type for effective representation of ECG signal and noises, and can reduce the computational load of sparse representation-based ECG enhancement system. The proposed framework consists of noise detection and identification, noise-aware dictionary learning, sparse signal decomposition and reconstruction. The noise detection and identification is performed based on the moving average filter, first-order difference, and temporal features such as number of turning points, maximum absolute amplitude, zerocrossings, and autocorrelation features. The representation dictionary is learned based on the type of noise identified in the previous stage. The proposed framework is evaluated using noise-free and noisy ECG signals. Results demonstrate that the proposed method can significantly reduce computational load as compared with conventional dictionary learning-based ECG denoising approaches. Further, comparative results show that the method outperforms existing methods in automatically removing noises such as baseline wanders, power-line interference, muscle artefacts and their combinations without distorting the morphological content of local waves of ECG signal. PMID:28529758

Noise-aware dictionary-learning-based sparse representation framework for detection and removal of single and combined noises from ECG signal.

PubMed

Satija, Udit; Ramkumar, Barathram; Sabarimalai Manikandan, M

2017-02-01

Automatic electrocardiogram (ECG) signal enhancement has become a crucial pre-processing step in most ECG signal analysis applications. In this Letter, the authors propose an automated noise-aware dictionary learning-based generalised ECG signal enhancement framework which can automatically learn the dictionaries based on the ECG noise type for effective representation of ECG signal and noises, and can reduce the computational load of sparse representation-based ECG enhancement system. The proposed framework consists of noise detection and identification, noise-aware dictionary learning, sparse signal decomposition and reconstruction. The noise detection and identification is performed based on the moving average filter, first-order difference, and temporal features such as number of turning points, maximum absolute amplitude, zerocrossings, and autocorrelation features. The representation dictionary is learned based on the type of noise identified in the previous stage. The proposed framework is evaluated using noise-free and noisy ECG signals. Results demonstrate that the proposed method can significantly reduce computational load as compared with conventional dictionary learning-based ECG denoising approaches. Further, comparative results show that the method outperforms existing methods in automatically removing noises such as baseline wanders, power-line interference, muscle artefacts and their combinations without distorting the morphological content of local waves of ECG signal.

Modal parameter identification based on combining transmissibility functions and blind source separation techniques

NASA Astrophysics Data System (ADS)

Araújo, Iván Gómez; Sánchez, Jesús Antonio García; Andersen, Palle

2018-05-01

Transmissibility-based operational modal analysis is a recent and alternative approach used to identify the modal parameters of structures under operational conditions. This approach is advantageous compared with traditional operational modal analysis because it does not make any assumptions about the excitation spectrum (i.e., white noise with a flat spectrum). However, common methodologies do not include a procedure to extract closely spaced modes with low signal-to-noise ratios. This issue is relevant when considering that engineering structures generally have closely spaced modes and that their measured responses present high levels of noise. Therefore, to overcome these problems, a new combined method for modal parameter identification is proposed in this work. The proposed method combines blind source separation (BSS) techniques and transmissibility-based methods. Here, BSS techniques were used to recover source signals, and transmissibility-based methods were applied to estimate modal information from the recovered source signals. To achieve this combination, a new method to define a transmissibility function was proposed. The suggested transmissibility function is based on the relationship between the power spectral density (PSD) of mixed signals and the PSD of signals from a single source. The numerical responses of a truss structure with high levels of added noise and very closely spaced modes were processed using the proposed combined method to evaluate its ability to identify modal parameters in these conditions. Colored and white noise excitations were used for the numerical example. The proposed combined method was also used to evaluate the modal parameters of an experimental test on a structure containing closely spaced modes. The results showed that the proposed combined method is capable of identifying very closely spaced modes in the presence of noise and, thus, may be potentially applied to improve the identification of damping ratios.

Analysis of the iteratively regularized Gauss-Newton method under a heuristic rule

NASA Astrophysics Data System (ADS)

Jin, Qinian; Wang, Wei

2018-03-01

The iteratively regularized Gauss-Newton method is one of the most prominent regularization methods for solving nonlinear ill-posed inverse problems when the data is corrupted by noise. In order to produce a useful approximate solution, this iterative method should be terminated properly. The existing a priori and a posteriori stopping rules require accurate information on the noise level, which may not be available or reliable in practical applications. In this paper we propose a heuristic selection rule for this regularization method, which requires no information on the noise level. By imposing certain conditions on the noise, we derive a posteriori error estimates on the approximate solutions under various source conditions. Furthermore, we establish a convergence result without using any source condition. Numerical results are presented to illustrate the performance of our heuristic selection rule.

The higher mode of surface wave derived from ambient noise and preliminary application to estimating subsurface

NASA Astrophysics Data System (ADS)

Zhentao, Y.; Xiaofei, C.; Jiannan, W.

2016-12-01

The fundamental mode is the primary component of surface wave derived from ambient noise. It is the basis of the method of structure imaging from ambient noise (e.g. SPAC, Aki 1957; F-K, Lascoss 1968; MUSIC, Schmidt 1986). It is well known, however, that if the higher modes of surface wave can be identified from data and are incorporated in the inversion of dispersion curves, the uncertainty in inversion results will be greatly reduced (e.g., Tokimastu,1997). Actually, the ambient noise indeed contains the higher modes as well in its raw data of ambient noise. If we could extract the higher modes from ambient noise, the structure inversion method of ambient noise would be greatly improved. In the past decade, there are many studies to improve SPAC and analyses the relationship of fundamental mode and higher mode (Ohri et al 2002; Asten et al. 2006; Tashiaki Ykoi 2010 ;Tatsunori Ikeda 2012). In this study, we will present a new method of identifying higher modes from ambient noise data by reprocessing the "surface waves' phases" derived from the ambient noise through cross-correlation analysis, and show preliminary application in structure inversion.

Fractional domain varying-order differential denoising method

NASA Astrophysics Data System (ADS)

Zhang, Yan-Shan; Zhang, Feng; Li, Bing-Zhao; Tao, Ran

2014-10-01

Removal of noise is an important step in the image restoration process, and it remains a challenging problem in image processing. Denoising is a process used to remove the noise from the corrupted image, while retaining the edges and other detailed features as much as possible. Recently, denoising in the fractional domain is a hot research topic. The fractional-order anisotropic diffusion method can bring a less blocky effect and preserve edges in image denoising, a method that has received much interest in the literature. Based on this method, we propose a new method for image denoising, in which fractional-varying-order differential, rather than constant-order differential, is used. The theoretical analysis and experimental results show that compared with the state-of-the-art fractional-order anisotropic diffusion method, the proposed fractional-varying-order differential denoising model can preserve structure and texture well, while quickly removing noise, and yields good visual effects and better peak signal-to-noise ratio.

Signal-to-noise ratio application to seismic marker analysis and fracture detection

NASA Astrophysics Data System (ADS)

Xu, Hui-Qun; Gui, Zhi-Xian

2014-03-01

Seismic data with high signal-to-noise ratios (SNRs) are useful in reservoir exploration. To obtain high SNR seismic data, significant effort is required to achieve noise attenuation in seismic data processing, which is costly in materials, and human and financial resources. We introduce a method for improving the SNR of seismic data. The SNR is calculated by using the frequency domain method. Furthermore, we optimize and discuss the critical parameters and calculation procedure. We applied the proposed method on real data and found that the SNR is high in the seismic marker and low in the fracture zone. Consequently, this can be used to extract detailed information about fracture zones that are inferred by structural analysis but not observed in conventional seismic data.

Boundary layer noise subtraction in hydrodynamic tunnel using robust principal component analysis.

PubMed

Amailland, Sylvain; Thomas, Jean-Hugh; Pézerat, Charles; Boucheron, Romuald

2018-04-01

The acoustic study of propellers in a hydrodynamic tunnel is of paramount importance during the design process, but can involve significant difficulties due to the boundary layer noise (BLN). Indeed, advanced denoising methods are needed to recover the acoustic signal in case of poor signal-to-noise ratio. The technique proposed in this paper is based on the decomposition of the wall-pressure cross-spectral matrix (CSM) by taking advantage of both the low-rank property of the acoustic CSM and the sparse property of the BLN CSM. Thus, the algorithm belongs to the class of robust principal component analysis (RPCA), which derives from the widely used principal component analysis. If the BLN is spatially decorrelated, the proposed RPCA algorithm can blindly recover the acoustical signals even for negative signal-to-noise ratio. Unfortunately, in a realistic case, acoustic signals recorded in a hydrodynamic tunnel show that the noise may be partially correlated. A prewhitening strategy is then considered in order to take into account the spatially coherent background noise. Numerical simulations and experimental results show an improvement in terms of BLN reduction in the large hydrodynamic tunnel. The effectiveness of the denoising method is also investigated in the context of acoustic source localization.

Analysis of electrochemical noise (ECN) data in time and frequency domain for comparison corrosion inhibition of some azole compounds on Cu in 1.0 M H2SO4 solution

NASA Astrophysics Data System (ADS)

Ramezanzadeh, B.; Arman, S. Y.; Mehdipour, M.; Markhali, B. P.

2014-01-01

In this study, the corrosion inhibition properties of two similar heterocyclic compounds namely benzotriazole (BTA) and benzothiazole (BNS) inhibitors on copper in 1.0 M H2SO4 solution were studied by electrochemical techniques as well as surface analysis. The results showed that corrosion inhibition of copper largely depends on the molecular structure and concentration of the inhibitors. The effect of DC trend on the interpretation of electrochemical noise (ECN) results in time domain was evaluated by moving average removal (MAR) method. Accordingly, the impact of square and Hanning window functions as drift removal methods in frequency domain was studied. After DC trend removal, a good trend was observed between electrochemical noise (ECN) data and the results obtained from EIS and potentiodynamic polarization. Furthermore, the shot noise theory in frequency domain was applied to approach the charge of each electrochemical event (q) from the potential and current noise signals.

Methods of Stochastic Analysis of Complex Regimes in the 3D Hindmarsh-Rose Neuron Model

NASA Astrophysics Data System (ADS)

Bashkirtseva, Irina; Ryashko, Lev; Slepukhina, Evdokia

A problem of the stochastic nonlinear analysis of neuronal activity is studied by the example of the Hindmarsh-Rose (HR) model. For the parametric region of tonic spiking oscillations, it is shown that random noise transforms the spiking dynamic regime into the bursting one. This stochastic phenomenon is specified by qualitative changes in distributions of random trajectories and interspike intervals (ISIs). For a quantitative analysis of the noise-induced bursting, we suggest a constructive semi-analytical approach based on the stochastic sensitivity function (SSF) technique and the method of confidence domains that allows us to describe geometrically a distribution of random states around the deterministic attractors. Using this approach, we develop a new algorithm for estimation of critical values for the noise intensity corresponding to the qualitative changes in stochastic dynamics. We show that the obtained estimations are in good agreement with the numerical results. An interplay between noise-induced bursting and transitions from order to chaos is discussed.

Using Boosting Decision Trees in Gravitational Wave Searches triggered by Gamma-ray Bursts

NASA Astrophysics Data System (ADS)

Zuraw, Sarah; LIGO Collaboration

2015-04-01

The search for gravitational wave bursts requires the ability to distinguish weak signals from background detector noise. Gravitational wave bursts are characterized by their transient nature, making them particularly difficult to detect as they are similar to non-Gaussian noise fluctuations in the detector. The Boosted Decision Tree method is a powerful machine learning algorithm which uses Multivariate Analysis techniques to explore high-dimensional data sets in order to distinguish between gravitational wave signal and background detector noise. It does so by training with known noise events and simulated gravitational wave events. The method is tested using waveform models and compared with the performance of the standard gravitational wave burst search pipeline for Gamma-ray Bursts. It is shown that the method is able to effectively distinguish between signal and background events under a variety of conditions and over multiple Gamma-ray Burst events. This example demonstrates the usefulness and robustness of the Boosted Decision Tree and Multivariate Analysis techniques as a detection method for gravitational wave bursts. LIGO, UMass, PREP, NEGAP.

Characterization and simulation of noise in PET images reconstructed with OSEM: Development of a method for the generation of synthetic images.

PubMed

Castro, P; Huerga, C; Chamorro, P; Garayoa, J; Roch, M; Pérez, L

2018-04-17

The goals of the study are to characterize imaging properties in 2D PET images reconstructed with the iterative algorithm ordered-subset expectation maximization (OSEM) and to propose a new method for the generation of synthetic images. The noise is analyzed in terms of its magnitude, spatial correlation, and spectral distribution through standard deviation, autocorrelation function, and noise power spectrum (NPS), respectively. Their variations with position and activity level are also analyzed. This noise analysis is based on phantom images acquired from 18 F uniform distributions. Experimental recovery coefficients of hot spheres in different backgrounds are employed to study the spatial resolution of the system through point spread function (PSF). The NPS and PSF functions provide the baseline for the proposed simulation method: convolution with PSF as kernel and noise addition from NPS. The noise spectral analysis shows that the main contribution is of random nature. It is also proven that attenuation correction does not alter noise texture but it modifies its magnitude. Finally, synthetic images of 2 phantoms, one of them an anatomical brain, are quantitatively compared with experimental images showing a good agreement in terms of pixel values and pixel correlations. Thus, the contrast to noise ratio for the biggest sphere in the NEMA IEC phantom is 10.7 for the synthetic image and 8.8 for the experimental image. The properties of the analyzed OSEM-PET images can be described by NPS and PSF functions. Synthetic images, even anatomical ones, are successfully generated by the proposed method based on the NPS and PSF. Copyright © 2018 Sociedad Española de Medicina Nuclear e Imagen Molecular. Publicado por Elsevier España, S.L.U. All rights reserved.

Performance comparisons on spatial lattice algorithm and direct matrix inverse method with application to adaptive arrays processing

NASA Technical Reports Server (NTRS)

An, S. H.; Yao, K.

1986-01-01

Lattice algorithm has been employed in numerous adaptive filtering applications such as speech analysis/synthesis, noise canceling, spectral analysis, and channel equalization. In this paper the application to adaptive-array processing is discussed. The advantages are fast convergence rate as well as computational accuracy independent of the noise and interference conditions. The results produced by this technique are compared to those obtained by the direct matrix inverse method.

Dual-domain point diffraction interferometer

DOEpatents

Naulleau, Patrick P.; Goldberg, Kenneth Alan

2000-01-01

A hybrid spatial/temporal-domain point diffraction interferometer (referred to as the dual-domain PS/PDI) that is capable of suppressing the scattered-reference-light noise that hinders the conventional PS/PDI is provided. The dual-domain PS/PDI combines the separate noise-suppression capabilities of the widely-used phase-shifting and Fourier-transform fringe pattern analysis methods. The dual-domain PS/PDI relies on both a more restrictive implementation of the image plane PS/PDI mask and a new analysis method to be applied to the interferograms generated and recorded by the modified PS/PDI. The more restrictive PS/PDI mask guarantees the elimination of spatial-frequency crosstalk between the signal and the scattered-light noise arising from scattered-reference-light interfering with the test beam. The new dual-domain analysis method is then used to eliminate scattered-light noise arising from both the scattered-reference-light interfering with the test beam and the scattered-reference-light interfering with the "true" pinhole-diffracted reference light. The dual-domain analysis method has also been demonstrated to provide performance enhancement when using the non-optimized standard PS/PDI design. The dual-domain PS/PDI is essentially a three-tiered filtering system composed of lowpass spatial-filtering the test-beam electric field using the more restrictive PS/PDI mask, bandpass spatial-filtering the individual interferogram irradiance frames making up the phase-shifting series, and bandpass temporal-filtering the phase-shifting series as a whole.

Comparison of Predicted and Measured Attenuation of Turbine Noise from a Static Engine Test

NASA Technical Reports Server (NTRS)

Chien, Eugene W.; Ruiz, Marta; Yu, Jia; Morin, Bruce L.; Cicon, Dennis; Schwieger, Paul S.; Nark, Douglas M.

2007-01-01

Aircraft noise has become an increasing concern for commercial airlines. Worldwide demand for quieter aircraft is increasing, making the prediction of engine noise suppression one of the most important fields of research. The Low-Pressure Turbine (LPT) can be an important noise source during the approach condition for commercial aircraft. The National Aeronautics and Space Administration (NASA), Pratt & Whitney (P&W), and Goodrich Aerostructures (Goodrich) conducted a joint program to validate a method for predicting turbine noise attenuation. The method includes noise-source estimation, acoustic treatment impedance prediction, and in-duct noise propagation analysis. Two noise propagation prediction codes, Eversman Finite Element Method (FEM) code [1] and the CDUCT-LaRC [2] code, were used in this study to compare the predicted and the measured turbine noise attenuation from a static engine test. In this paper, the test setup, test configurations and test results are detailed in Section II. A description of the input parameters, including estimated noise modal content (in terms of acoustic potential), and acoustic treatment impedance values are provided in Section III. The prediction-to-test correlation study results are illustrated and discussed in Section IV and V for the FEM and the CDUCT-LaRC codes, respectively, and a summary of the results is presented in Section VI.

A Requirements-Driven Optimization Method for Acoustic Liners Using Analytic Derivatives

NASA Technical Reports Server (NTRS)

Berton, Jeffrey J.; Lopes, Leonard V.

2017-01-01

More than ever, there is flexibility and freedom in acoustic liner design. Subject to practical considerations, liner design variables may be manipulated to achieve a target attenuation spectrum. But characteristics of the ideal attenuation spectrum can be difficult to know. Many multidisciplinary system effects govern how engine noise sources contribute to community noise. Given a hardwall fan noise source to be suppressed, and using an analytical certification noise model to compute a community noise measure of merit, the optimal attenuation spectrum can be derived using multidisciplinary systems analysis methods. In a previous paper on this subject, a method deriving the ideal target attenuation spectrum that minimizes noise perceived by observers on the ground was described. A simple code-wrapping approach was used to evaluate a community noise objective function for an external optimizer. Gradients were evaluated using a finite difference formula. The subject of this paper is an application of analytic derivatives that supply precise gradients to an optimization process. Analytic derivatives improve the efficiency and accuracy of gradient-based optimization methods and allow consideration of more design variables. In addition, the benefit of variable impedance liners is explored using a multi-objective optimization.

Direct mapping of electrical noise sources in molecular wire-based devices

PubMed Central

Cho, Duckhyung; Lee, Hyungwoo; Shekhar, Shashank; Yang, Myungjae; Park, Jae Yeol; Hong, Seunghun

2017-01-01

We report a noise mapping strategy for the reliable identification and analysis of noise sources in molecular wire junctions. Here, different molecular wires were patterned on a gold substrate, and the current-noise map on the pattern was measured and analyzed, enabling the quantitative study of noise sources in the patterned molecular wires. The frequency spectra of the noise from the molecular wire junctions exhibited characteristic 1/f2 behavior, which was used to identify the electrical signals from molecular wires. This method was applied to analyze the molecular junctions comprising various thiol molecules on a gold substrate, revealing that the noise in the junctions mainly came from the fluctuation of the thiol bonds. Furthermore, we quantitatively compared the frequencies of such bond fluctuations in different molecular wire junctions and identified molecular wires with lower electrical noise, which can provide critical information for designing low-noise molecular electronic devices. Our method provides valuable insights regarding noise phenomena in molecular wires and can be a powerful tool for the development of molecular electronic devices. PMID:28233821

Direct mapping of electrical noise sources in molecular wire-based devices

NASA Astrophysics Data System (ADS)

Cho, Duckhyung; Lee, Hyungwoo; Shekhar, Shashank; Yang, Myungjae; Park, Jae Yeol; Hong, Seunghun

2017-02-01

We report a noise mapping strategy for the reliable identification and analysis of noise sources in molecular wire junctions. Here, different molecular wires were patterned on a gold substrate, and the current-noise map on the pattern was measured and analyzed, enabling the quantitative study of noise sources in the patterned molecular wires. The frequency spectra of the noise from the molecular wire junctions exhibited characteristic 1/f2 behavior, which was used to identify the electrical signals from molecular wires. This method was applied to analyze the molecular junctions comprising various thiol molecules on a gold substrate, revealing that the noise in the junctions mainly came from the fluctuation of the thiol bonds. Furthermore, we quantitatively compared the frequencies of such bond fluctuations in different molecular wire junctions and identified molecular wires with lower electrical noise, which can provide critical information for designing low-noise molecular electronic devices. Our method provides valuable insights regarding noise phenomena in molecular wires and can be a powerful tool for the development of molecular electronic devices.

Sensitivity analysis of gene ranking methods in phenotype prediction.

PubMed

deAndrés-Galiana, Enrique J; Fernández-Martínez, Juan L; Sonis, Stephen T

2016-12-01

It has become clear that noise generated during the assay and analytical processes has the ability to disrupt accurate interpretation of genomic studies. Not only does such noise impact the scientific validity and costs of studies, but when assessed in the context of clinically translatable indications such as phenotype prediction, it can lead to inaccurate conclusions that could ultimately impact patients. We applied a sequence of ranking methods to damp noise associated with microarray outputs, and then tested the utility of the approach in three disease indications using publically available datasets. This study was performed in three phases. We first theoretically analyzed the effect of noise in phenotype prediction problems showing that it can be expressed as a modeling error that partially falsifies the pathways. Secondly, via synthetic modeling, we performed the sensitivity analysis for the main gene ranking methods to different types of noise. Finally, we studied the predictive accuracy of the gene lists provided by these ranking methods in synthetic data and in three different datasets related to cancer, rare and neurodegenerative diseases to better understand the translational aspects of our findings. In the case of synthetic modeling, we showed that Fisher's Ratio (FR) was the most robust gene ranking method in terms of precision for all the types of noise at different levels. Significance Analysis of Microarrays (SAM) provided slightly lower performance and the rest of the methods (fold change, entropy and maximum percentile distance) were much less precise and accurate. The predictive accuracy of the smallest set of high discriminatory probes was similar for all the methods in the case of Gaussian and Log-Gaussian noise. In the case of class assignment noise, the predictive accuracy of SAM and FR is higher. Finally, for real datasets (Chronic Lymphocytic Leukemia, Inclusion Body Myositis and Amyotrophic Lateral Sclerosis) we found that FR and SAM provided the highest predictive accuracies with the smallest number of genes. Biological pathways were found with an expanded list of genes whose discriminatory power has been established via FR. We have shown that noise in expression data and class assignment partially falsifies the sets of discriminatory probes in phenotype prediction problems. FR and SAM better exploit the principle of parsimony and are able to find subsets with less number of high discriminatory genes. The predictive accuracy and the precision are two different metrics to select the important genes, since in the presence of noise the most predictive genes do not completely coincide with those that are related to the phenotype. Based on the synthetic results, FR and SAM are recommended to unravel the biological pathways that are involved in the disease development. Copyright © 2016 Elsevier Inc. All rights reserved.

Empirical mode decomposition of the ECG signal for noise removal

NASA Astrophysics Data System (ADS)

Khan, Jesmin; Bhuiyan, Sharif; Murphy, Gregory; Alam, Mohammad

2011-04-01

Electrocardiography is a diagnostic procedure for the detection and diagnosis of heart abnormalities. The electrocardiogram (ECG) signal contains important information that is utilized by physicians for the diagnosis and analysis of heart diseases. So good quality ECG signal plays a vital role for the interpretation and identification of pathological, anatomical and physiological aspects of the whole cardiac muscle. However, the ECG signals are corrupted by noise which severely limit the utility of the recorded ECG signal for medical evaluation. The most common noise presents in the ECG signal is the high frequency noise caused by the forces acting on the electrodes. In this paper, we propose a new ECG denoising method based on the empirical mode decomposition (EMD). The proposed method is able to enhance the ECG signal upon removing the noise with minimum signal distortion. Simulation is done on the MIT-BIH database to verify the efficacy of the proposed algorithm. Experiments show that the presented method offers very good results to remove noise from the ECG signal.

Ultrasensitive low noise voltage amplifier for spectral analysis.

PubMed

Giusi, G; Crupi, F; Pace, C

2008-08-01

Recently we have proposed several voltage noise measurement methods that allow, at least in principle, the complete elimination of the noise introduced by the measurement amplifier. The most severe drawback of these methods is that they require a multistep measurement procedure. Since environmental conditions may change in the different measurement steps, the final result could be affected by these changes. This problem is solved by the one-step voltage noise measurement methodology based on a novel amplifier topology proposed in this paper. Circuit implementations for the amplifier building blocks based on operational amplifiers are critically discussed. The proposed approach is validated through measurements performed on a prototype circuit.

Assessment of honking impact on traffic noise in urban traffic environment of Nagpur, India.

PubMed

Vijay, Ritesh; Sharma, Asheesh; Chakrabarti, Tapan; Gupta, Rajesh

2015-01-01

In context of increasing traffic noise in urban India, the objective of the research study is to assess noise due to heterogeneous traffic conditions and the impact of honking on it. Traffic volume, noise levels, honking, road geometry and vehicular speed were measured on national highway, major and minor roads in Nagpur, India. Initial study showed lack of correlation between traffic volume and equivalent noise due to some factors, later identified as honking, road geometry and vehicular speed. Further, frequency analysis of traffic noise showed that honking contributed an additional 2 to 5 dB (A) noise, which is quite significant. Vehicular speed was also found to increase traffic noise. Statistical method of analysis of variance (ANOVA) confirms that frequent honking (p < 0.01) and vehicular speed (p < 0.05) have substantial impact on traffic noise apart from traffic volume and type of road. The study suggests that honking must also be a component in traffic noise assessment and to identify and monitor "No Honking" zones in urban agglomerations.

Linnorm: improved statistical analysis for single cell RNA-seq expression data.

PubMed

Yip, Shun H; Wang, Panwen; Kocher, Jean-Pierre A; Sham, Pak Chung; Wang, Junwen

2017-12-15

Linnorm is a novel normalization and transformation method for the analysis of single cell RNA sequencing (scRNA-seq) data. Linnorm is developed to remove technical noises and simultaneously preserve biological variations in scRNA-seq data, such that existing statistical methods can be improved. Using real scRNA-seq data, we compared Linnorm with existing normalization methods, including NODES, SAMstrt, SCnorm, scran, DESeq and TMM. Linnorm shows advantages in speed, technical noise removal and preservation of cell heterogeneity, which can improve existing methods in the discovery of novel subtypes, pseudo-temporal ordering of cells, clustering analysis, etc. Linnorm also performs better than existing DEG analysis methods, including BASiCS, NODES, SAMstrt, Seurat and DESeq2, in false positive rate control and accuracy. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Improving MEG source localizations: an automated method for complete artifact removal based on independent component analysis.

PubMed

Mantini, D; Franciotti, R; Romani, G L; Pizzella, V

2008-03-01

The major limitation for the acquisition of high-quality magnetoencephalography (MEG) recordings is the presence of disturbances of physiological and technical origins: eye movements, cardiac signals, muscular contractions, and environmental noise are serious problems for MEG signal analysis. In the last years, multi-channel MEG systems have undergone rapid technological developments in terms of noise reduction, and many processing methods have been proposed for artifact rejection. Independent component analysis (ICA) has already shown to be an effective and generally applicable technique for concurrently removing artifacts and noise from the MEG recordings. However, no standardized automated system based on ICA has become available so far, because of the intrinsic difficulty in the reliable categorization of the source signals obtained with this technique. In this work, approximate entropy (ApEn), a measure of data regularity, is successfully used for the classification of the signals produced by ICA, allowing for an automated artifact rejection. The proposed method has been tested using MEG data sets collected during somatosensory, auditory and visual stimulation. It was demonstrated to be effective in attenuating both biological artifacts and environmental noise, in order to reconstruct clear signals that can be used for improving brain source localizations.

Detection and Classification of Motor Vehicle Noise in a Forested Landscape

NASA Astrophysics Data System (ADS)

Brown, Casey L.; Reed, Sarah E.; Dietz, Matthew S.; Fristrup, Kurt M.

2013-11-01

Noise emanating from human activity has become a common addition to natural soundscapes and has the potential to harm wildlife and erode human enjoyment of nature. In particular, motor vehicles traveling along roads and trails produce high levels of both chronic and intermittent noise, eliciting varied responses from a wide range of animal species. Anthropogenic noise is especially conspicuous in natural areas where ambient background sound levels are low. In this article, we present an acoustic method to detect and analyze motor vehicle noise. Our approach uses inexpensive consumer products to record sound, sound analysis software to automatically detect sound events within continuous recordings and measure their acoustic properties, and statistical classification methods to categorize sound events. We describe an application of this approach to detect motor vehicle noise on paved, gravel, and natural-surface roads, and off-road vehicle trails in 36 sites distributed throughout a national forest in the Sierra Nevada, CA, USA. These low-cost, unobtrusive methods can be used by scientists and managers to detect anthropogenic noise events for many potential applications, including ecological research, transportation and recreation planning, and natural resource management.

Predicted changes in advanced turboprop noise with shaft angle of attack

NASA Technical Reports Server (NTRS)

Padula, S. L.; Block, P. J. W.

1984-01-01

Advanced turboprop blade designs and new propeller installation schemes motivated an effort to include unsteady loading effects in existing propeller noise prediction computer programs. The present work validates the prediction capability while studing the effects of shaft inclination on the radiated sound field. Classical methods of propeller performance analysis supply the time-dependent blade loading needed to calculate noise. Polar plots of the sound pressure level (SPL) of the first four harmonics and overall SPL are indicative of the change in directivity pattern as a function of propeller angle of attack. Noise predictions are compared with newly available wind tunnel data and the accuracy and applicability of the prediction method are discussed. It is concluded that unsteady blade loading caused by inclining the propeller with respect to the flow changes the directionality and the intensity of the radiated noise. These changes are well modeled by the present quasi-steady prediction method.

Power Spectral Density Error Analysis of Spectral Subtraction Type of Speech Enhancement Methods

NASA Astrophysics Data System (ADS)

Händel, Peter

2006-12-01

A theoretical framework for analysis of speech enhancement algorithms is introduced for performance assessment of spectral subtraction type of methods. The quality of the enhanced speech is related to physical quantities of the speech and noise (such as stationarity time and spectral flatness), as well as to design variables of the noise suppressor. The derived theoretical results are compared with the outcome of subjective listening tests as well as successful design strategies, performed by independent research groups.

Landing Gear Noise Prediction and Analysis for Tube-and-Wing and Hybrid-Wing-Body Aircraft

NASA Technical Reports Server (NTRS)

Guo, Yueping; Burley, Casey L.; Thomas, Russell H.

2016-01-01

Improvements and extensions to landing gear noise prediction methods are developed. New features include installation effects such as reflection from the aircraft, gear truck angle effect, local flow calculation at the landing gear locations, gear size effect, and directivity for various gear designs. These new features have not only significantly improved the accuracy and robustness of the prediction tools, but also have enabled applications to unconventional aircraft designs and installations. Systematic validations of the improved prediction capability are then presented, including parametric validations in functional trends as well as validations in absolute amplitudes, covering a wide variety of landing gear designs, sizes, and testing conditions. The new method is then applied to selected concept aircraft configurations in the portfolio of the NASA Environmentally Responsible Aviation Project envisioned for the timeframe of 2025. The landing gear noise levels are on the order of 2 to 4 dB higher than previously reported predictions due to increased fidelity in accounting for installation effects and gear design details. With the new method, it is now possible to reveal and assess the unique noise characteristics of landing gear systems for each type of aircraft. To address the inevitable uncertainties in predictions of landing gear noise models for future aircraft, an uncertainty analysis is given, using the method of Monte Carlo simulation. The standard deviation of the uncertainty in predicting the absolute level of landing gear noise is quantified and determined to be 1.4 EPNL dB.

An improved algorithm of laser spot center detection in strong noise background

NASA Astrophysics Data System (ADS)

Zhang, Le; Wang, Qianqian; Cui, Xutai; Zhao, Yu; Peng, Zhong

2018-01-01

Laser spot center detection is demanded in many applications. The common algorithms for laser spot center detection such as centroid and Hough transform method have poor anti-interference ability and low detection accuracy in the condition of strong background noise. In this paper, firstly, the median filtering was used to remove the noise while preserving the edge details of the image. Secondly, the binarization of the laser facula image was carried out to extract target image from background. Then the morphological filtering was performed to eliminate the noise points inside and outside the spot. At last, the edge of pretreated facula image was extracted and the laser spot center was obtained by using the circle fitting method. In the foundation of the circle fitting algorithm, the improved algorithm added median filtering, morphological filtering and other processing methods. This method could effectively filter background noise through theoretical analysis and experimental verification, which enhanced the anti-interference ability of laser spot center detection and also improved the detection accuracy.

A Multi Directional Perfect Reconstruction Filter Bank Designed with 2-D Eigenfilter Approach: Application to Ultrasound Speckle Reduction.

PubMed

Nagare, Mukund B; Patil, Bhushan D; Holambe, Raghunath S

2017-02-01

B-Mode ultrasound images are degraded by inherent noise called Speckle, which creates a considerable impact on image quality. This noise reduces the accuracy of image analysis and interpretation. Therefore, reduction of speckle noise is an essential task which improves the accuracy of the clinical diagnostics. In this paper, a Multi-directional perfect-reconstruction (PR) filter bank is proposed based on 2-D eigenfilter approach. The proposed method used for the design of two-dimensional (2-D) two-channel linear-phase FIR perfect-reconstruction filter bank. In this method, the fan shaped, diamond shaped and checkerboard shaped filters are designed. The quadratic measure of the error function between the passband and stopband of the filter has been used an objective function. First, the low-pass analysis filter is designed and then the PR condition has been expressed as a set of linear constraints on the corresponding synthesis low-pass filter. Subsequently, the corresponding synthesis filter is designed using the eigenfilter design method with linear constraints. The newly designed 2-D filters are used in translation invariant pyramidal directional filter bank (TIPDFB) for reduction of speckle noise in ultrasound images. The proposed 2-D filters give better symmetry, regularity and frequency selectivity of the filters in comparison to existing design methods. The proposed method is validated on synthetic and real ultrasound data which ensures improvement in the quality of ultrasound images and efficiently suppresses the speckle noise compared to existing methods.

A Requirements-Driven Optimization Method for Acoustic Treatment Design

NASA Technical Reports Server (NTRS)

Berton, Jeffrey J.

2016-01-01

Acoustic treatment designers have long been able to target specific noise sources inside turbofan engines. Facesheet porosity and cavity depth are key design variables of perforate-over-honeycomb liners that determine levels of noise suppression as well as the frequencies at which suppression occurs. Layers of these structures can be combined to create a robust attenuation spectrum that covers a wide range of frequencies. Looking to the future, rapidly-emerging additive manufacturing technologies are enabling new liners with multiple degrees of freedom, and new adaptive liners with variable impedance are showing promise. More than ever, there is greater flexibility and freedom in liner design. Subject to practical considerations, liner design variables may be manipulated to achieve a target attenuation spectrum. But characteristics of the ideal attenuation spectrum can be difficult to know. Many multidisciplinary system effects govern how engine noise sources contribute to community noise. Given a hardwall fan noise source to be suppressed, and using an analytical certification noise model to compute a community noise measure of merit, the optimal attenuation spectrum can be derived using multidisciplinary systems analysis methods. The subject of this paper is an analytical method that derives the ideal target attenuation spectrum that minimizes noise perceived by observers on the ground.

Acoustic resonance of outer-rotor brushless dc motor for air-conditioner fan

NASA Astrophysics Data System (ADS)

Lee, Hong-Joo; Chung, Shi-Uk; Hwang, Sang-Moon

2008-04-01

Generation of acoustic noise in electric motor is an interacting combination of mechanical and electromagnetic sources. In this paper, a brushless dc motor for air-conditioner fan is analyzed by finite element method to identify noise source, and the analysis results are verified by experiments, and sensitivity analysis is performed by design of experiments.

Applications of fractional lower order S transform time frequency filtering algorithm to machine fault diagnosis

PubMed Central

Wang, Haibin; Zha, Daifeng; Li, Peng; Xie, Huicheng; Mao, Lili

2017-01-01

Stockwell transform(ST) time-frequency representation(ST-TFR) is a time frequency analysis method which combines short time Fourier transform with wavelet transform, and ST time frequency filtering(ST-TFF) method which takes advantage of time-frequency localized spectra can separate the signals from Gaussian noise. The ST-TFR and ST-TFF methods are used to analyze the fault signals, which is reasonable and effective in general Gaussian noise cases. However, it is proved that the mechanical bearing fault signal belongs to Alpha(α) stable distribution process(1 < α < 2) in this paper, even the noise also is α stable distribution in some special cases. The performance of ST-TFR method will degrade under α stable distribution noise environment, following the ST-TFF method fail. Hence, a new fractional lower order ST time frequency representation(FLOST-TFR) method employing fractional lower order moment and ST and inverse FLOST(IFLOST) are proposed in this paper. A new FLOST time frequency filtering(FLOST-TFF) algorithm based on FLOST-TFR method and IFLOST is also proposed, whose simplified method is presented in this paper. The discrete implementation of FLOST-TFF algorithm is deduced, and relevant steps are summarized. Simulation results demonstrate that FLOST-TFR algorithm is obviously better than the existing ST-TFR algorithm under α stable distribution noise, which can work better under Gaussian noise environment, and is robust. The FLOST-TFF method can effectively filter out α stable distribution noise, and restore the original signal. The performance of FLOST-TFF algorithm is better than the ST-TFF method, employing which mixed MSEs are smaller when α and generalized signal noise ratio(GSNR) change. Finally, the FLOST-TFR and FLOST-TFF methods are applied to analyze the outer race fault signal and extract their fault features under α stable distribution noise, where excellent performances can be shown. PMID:28406916

Preprocessing with image denoising and histogram equalization for endoscopy image analysis using texture analysis.

PubMed

Hiroyasu, Tomoyuki; Hayashinuma, Katsutoshi; Ichikawa, Hiroshi; Yagi, Nobuaki

2015-08-01

A preprocessing method for endoscopy image analysis using texture analysis is proposed. In a previous study, we proposed a feature value that combines a co-occurrence matrix and a run-length matrix to analyze the extent of early gastric cancer from images taken with narrow-band imaging endoscopy. However, the obtained feature value does not identify lesion zones correctly due to the influence of noise and halation. Therefore, we propose a new preprocessing method with a non-local means filter for de-noising and contrast limited adaptive histogram equalization. We have confirmed that the pattern of gastric mucosa in images can be improved by the proposed method. Furthermore, the lesion zone is shown more correctly by the obtained color map.

A hybrid spatial-spectral denoising method for infrared hyperspectral images using 2DPCA

NASA Astrophysics Data System (ADS)

Huang, Jun; Ma, Yong; Mei, Xiaoguang; Fan, Fan

2016-11-01

The traditional noise reduction methods for 3-D infrared hyperspectral images typically operate independently in either the spatial or spectral domain, and such methods overlook the relationship between the two domains. To address this issue, we propose a hybrid spatial-spectral method in this paper to link both domains. First, principal component analysis and bivariate wavelet shrinkage are performed in the 2-D spatial domain. Second, 2-D principal component analysis transformation is conducted in the 1-D spectral domain to separate the basic components from detail ones. The energy distribution of noise is unaffected by orthogonal transformation; therefore, the signal-to-noise ratio of each component is used as a criterion to determine whether a component should be protected from over-denoising or denoised with certain 1-D denoising methods. This study implements the 1-D wavelet shrinking threshold method based on Stein's unbiased risk estimator, and the quantitative results on publicly available datasets demonstrate that our method can improve denoising performance more effectively than other state-of-the-art methods can.

Applied Chaos Level Test for Validation of Signal Conditions Underlying Optimal Performance of Voice Classification Methods.

PubMed

Liu, Boquan; Polce, Evan; Sprott, Julien C; Jiang, Jack J

2018-05-17

The purpose of this study is to introduce a chaos level test to evaluate linear and nonlinear voice type classification method performances under varying signal chaos conditions without subjective impression. Voice signals were constructed with differing degrees of noise to model signal chaos. Within each noise power, 100 Monte Carlo experiments were applied to analyze the output of jitter, shimmer, correlation dimension, and spectrum convergence ratio. The computational output of the 4 classifiers was then plotted against signal chaos level to investigate the performance of these acoustic analysis methods under varying degrees of signal chaos. A diffusive behavior detection-based chaos level test was used to investigate the performances of different voice classification methods. Voice signals were constructed by varying the signal-to-noise ratio to establish differing signal chaos conditions. Chaos level increased sigmoidally with increasing noise power. Jitter and shimmer performed optimally when the chaos level was less than or equal to 0.01, whereas correlation dimension was capable of analyzing signals with chaos levels of less than or equal to 0.0179. Spectrum convergence ratio demonstrated proficiency in analyzing voice signals with all chaos levels investigated in this study. The results of this study corroborate the performance relationships observed in previous studies and, therefore, demonstrate the validity of the validation test method. The presented chaos level validation test could be broadly utilized to evaluate acoustic analysis methods and establish the most appropriate methodology for objective voice analysis in clinical practice.

Restoration for Noise Removal in Quantum Images

NASA Astrophysics Data System (ADS)

Liu, Kai; Zhang, Yi; Lu, Kai; Wang, Xiaoping

2017-09-01

Quantum computation has become increasingly attractive in the past few decades due to its extraordinary performance. As a result, some studies focusing on image representation and processing via quantum mechanics have been done. However, few of them have considered the quantum operations for images restoration. To address this problem, three noise removal algorithms are proposed in this paper based on the novel enhanced quantum representation model, oriented to two kinds of noise pollution (Salt-and-Pepper noise and Gaussian noise). For the first algorithm Q-Mean, it is designed to remove the Salt-and-Pepper noise. The noise points are extracted through comparisons with the adjacent pixel values, after which the restoration operation is finished by mean filtering. As for the second method Q-Gauss, a special mask is applied to weaken the Gaussian noise pollution. The third algorithm Q-Adapt is effective for the source image containing unknown noise. The type of noise can be judged through the quantum statistic operations for the color value of the whole image, and then different noise removal algorithms are used to conduct image restoration respectively. Performance analysis reveals that our methods can offer high restoration quality and achieve significant speedup through inherent parallelism of quantum computation.

Analysis of radiometric signal in sedimentating suspension flow in open channel

NASA Astrophysics Data System (ADS)

Zych, Marcin; Hanus, Robert; Petryka, Leszek; Świsulski, Dariusz; Doktor, Marek; Mastej, Wojciech

2015-05-01

The article discusses issues related to the estimation of the sedimentating solid particles average flow velocity in an open channel using radiometric methods. Due to the composition of the compound, which formed water and diatomite, received data have a very weak signal to noise ratio. In the process analysis the known determining of the solid phase transportation time delay the classical cross-correlation function is the most reliable method. The use of advanced frequency analysis based on mutual spectral density function and wavelet transform of recorded signals allows a reduction of the noise contribution.

Noise models for low counting rate coherent diffraction imaging.

PubMed

Godard, Pierre; Allain, Marc; Chamard, Virginie; Rodenburg, John

2012-11-05

Coherent diffraction imaging (CDI) is a lens-less microscopy method that extracts the complex-valued exit field from intensity measurements alone. It is of particular importance for microscopy imaging with diffraction set-ups where high quality lenses are not available. The inversion scheme allowing the phase retrieval is based on the use of an iterative algorithm. In this work, we address the question of the choice of the iterative process in the case of data corrupted by photon or electron shot noise. Several noise models are presented and further used within two inversion strategies, the ordered subset and the scaled gradient. Based on analytical and numerical analysis together with Monte-Carlo studies, we show that any physical interpretations drawn from a CDI iterative technique require a detailed understanding of the relationship between the noise model and the used inversion method. We observe that iterative algorithms often assume implicitly a noise model. For low counting rates, each noise model behaves differently. Moreover, the used optimization strategy introduces its own artefacts. Based on this analysis, we develop a hybrid strategy which works efficiently in the absence of an informed initial guess. Our work emphasises issues which should be considered carefully when inverting experimental data.

A technique for setting analytical thresholds in massively parallel sequencing-based forensic DNA analysis

PubMed Central

2017-01-01

Amplicon (targeted) sequencing by massively parallel sequencing (PCR-MPS) is a potential method for use in forensic DNA analyses. In this application, PCR-MPS may supplement or replace other instrumental analysis methods such as capillary electrophoresis and Sanger sequencing for STR and mitochondrial DNA typing, respectively. PCR-MPS also may enable the expansion of forensic DNA analysis methods to include new marker systems such as single nucleotide polymorphisms (SNPs) and insertion/deletions (indels) that currently are assayable using various instrumental analysis methods including microarray and quantitative PCR. Acceptance of PCR-MPS as a forensic method will depend in part upon developing protocols and criteria that define the limitations of a method, including a defensible analytical threshold or method detection limit. This paper describes an approach to establish objective analytical thresholds suitable for multiplexed PCR-MPS methods. A definition is proposed for PCR-MPS method background noise, and an analytical threshold based on background noise is described. PMID:28542338

A technique for setting analytical thresholds in massively parallel sequencing-based forensic DNA analysis.

PubMed

Young, Brian; King, Jonathan L; Budowle, Bruce; Armogida, Luigi

2017-01-01

Amplicon (targeted) sequencing by massively parallel sequencing (PCR-MPS) is a potential method for use in forensic DNA analyses. In this application, PCR-MPS may supplement or replace other instrumental analysis methods such as capillary electrophoresis and Sanger sequencing for STR and mitochondrial DNA typing, respectively. PCR-MPS also may enable the expansion of forensic DNA analysis methods to include new marker systems such as single nucleotide polymorphisms (SNPs) and insertion/deletions (indels) that currently are assayable using various instrumental analysis methods including microarray and quantitative PCR. Acceptance of PCR-MPS as a forensic method will depend in part upon developing protocols and criteria that define the limitations of a method, including a defensible analytical threshold or method detection limit. This paper describes an approach to establish objective analytical thresholds suitable for multiplexed PCR-MPS methods. A definition is proposed for PCR-MPS method background noise, and an analytical threshold based on background noise is described.

Analysis of signal-dependent sensor noise on JPEG 2000-compressed Sentinel-2 multi-spectral images

NASA Astrophysics Data System (ADS)

Uss, M.; Vozel, B.; Lukin, V.; Chehdi, K.

2017-10-01

The processing chain of Sentinel-2 MultiSpectral Instrument (MSI) data involves filtering and compression stages that modify MSI sensor noise. As a result, noise in Sentinel-2 Level-1C data distributed to users becomes processed. We demonstrate that processed noise variance model is bivariate: noise variance depends on image intensity (caused by signal-dependency of photon counting detectors) and signal-to-noise ratio (SNR; caused by filtering/compression). To provide information on processed noise parameters, which is missing in Sentinel-2 metadata, we propose to use blind noise parameter estimation approach. Existing methods are restricted to univariate noise model. Therefore, we propose extension of existing vcNI+fBm blind noise parameter estimation method to multivariate noise model, mvcNI+fBm, and apply it to each band of Sentinel-2A data. Obtained results clearly demonstrate that noise variance is affected by filtering/compression for SNR less than about 15. Processed noise variance is reduced by a factor of 2 - 5 in homogeneous areas as compared to noise variance for high SNR values. Estimate of noise variance model parameters are provided for each Sentinel-2A band. Sentinel-2A MSI Level-1C noise models obtained in this paper could be useful for end users and researchers working in a variety of remote sensing applications.

A method for calculating strut and splitter plate noise in exit ducts: Theory and verification

NASA Technical Reports Server (NTRS)

Fink, M. R.

1978-01-01

Portions of a four-year analytical and experimental investigation relative to noise radiation from engine internal components in turbulent flow are summarized. Spectra measured for such airfoils over a range of chord, thickness ratio, flow velocity, and turbulence level were compared with predictions made by an available rigorous thin-airfoil analytical method. This analysis included the effects of flow compressibility and source noncompactness. Generally good agreement was obtained. This noise calculation method for isolated airfoils in turbulent flow was combined with a method for calculating transmission of sound through a subsonic exit duct and with an empirical far-field directivity shape. These three elements were checked separately and were individually shown to give close agreement with data. This combination provides a method for predicting engine internally generated aft-radiated noise from radial struts and stators, and annular splitter rings. Calculated sound power spectra, directivity, and acoustic pressure spectra were compared with the best available data. These data were for noise caused by a fan exit duct annular splitter ring, larger-chord stator blades, and turbine exit struts.

Analysis of crackling noise using the maximum-likelihood method: Power-law mixing and exponential damping.

PubMed

Salje, Ekhard K H; Planes, Antoni; Vives, Eduard

2017-10-01

Crackling noise can be initiated by competing or coexisting mechanisms. These mechanisms can combine to generate an approximate scale invariant distribution that contains two or more contributions. The overall distribution function can be analyzed, to a good approximation, using maximum-likelihood methods and assuming that it follows a power law although with nonuniversal exponents depending on a varying lower cutoff. We propose that such distributions are rather common and originate from a simple superposition of crackling noise distributions or exponential damping.

Rotor Broadband Noise Prediction with Comparison to Model Data

NASA Technical Reports Server (NTRS)

Brooks, Thomas F.; Burley, Casey L.

2001-01-01

This paper reports an analysis and prediction development of rotor broadband noise. The two primary components of this noise are Blade-Wake Interaction (BWI) noise, due to the blades' interaction with the turbulent wakes of the preceding blades, and "Self" noise, due to the development and shedding of turbulence within the blades' boundary layers. Emphasized in this report is the new code development for Self noise. The analysis and validation employs data from the HART program, a model BO-105 rotor wind tunnel test conducted in the German-Dutch Wind Tunnel (DNW). The BWI noise predictions are based on measured pressure response coherence functions using cross-spectral methods. The Self noise predictions are based on previously reported semiempirical modeling of Self noise obtained from isolated airfoil sections and the use of CAMRAD.Modl to define rotor performance and local blade segment flow conditions. Both BWI and Self noise from individual blade segments are Doppler shifted and summed at the observer positions. Prediction comparisons with measurements show good agreement for a range of rotor operating conditions from climb to steep descent. The broadband noise predictions, along with those of harmonic and impulsive Blade-Vortex Interaction (BVI) noise predictions, demonstrate a significant advance in predictive capability for main rotor noise.

Aircraft Conceptual Design and Risk Analysis Using Physics-Based Noise Prediction

NASA Technical Reports Server (NTRS)

Olson, Erik D.; Mavris, Dimitri N.

2006-01-01

An approach was developed which allows for design studies of commercial aircraft using physics-based noise analysis methods while retaining the ability to perform the rapid trade-off and risk analysis studies needed at the conceptual design stage. A prototype integrated analysis process was created for computing the total aircraft EPNL at the Federal Aviation Regulations Part 36 certification measurement locations using physics-based methods for fan rotor-stator interaction tones and jet mixing noise. The methodology was then used in combination with design of experiments to create response surface equations (RSEs) for the engine and aircraft performance metrics, geometric constraints and take-off and landing noise levels. In addition, Monte Carlo analysis was used to assess the expected variability of the metrics under the influence of uncertainty, and to determine how the variability is affected by the choice of engine cycle. Finally, the RSEs were used to conduct a series of proof-of-concept conceptual-level design studies demonstrating the utility of the approach. The study found that a key advantage to using physics-based analysis during conceptual design lies in the ability to assess the benefits of new technologies as a function of the design to which they are applied. The greatest difficulty in implementing physics-based analysis proved to be the generation of design geometry at a sufficient level of detail for high-fidelity analysis.

A median-Gaussian filtering framework for Moiré pattern noise removal from X-ray microscopy image.

PubMed

Wei, Zhouping; Wang, Jian; Nichol, Helen; Wiebe, Sheldon; Chapman, Dean

2012-02-01

Moiré pattern noise in Scanning Transmission X-ray Microscopy (STXM) imaging introduces significant errors in qualitative and quantitative image analysis. Due to the complex origin of the noise, it is difficult to avoid Moiré pattern noise during the image data acquisition stage. In this paper, we introduce a post-processing method for filtering Moiré pattern noise from STXM images. This method includes a semi-automatic detection of the spectral peaks in the Fourier amplitude spectrum by using a local median filter, and elimination of the spectral noise peaks using a Gaussian notch filter. The proposed median-Gaussian filtering framework shows good results for STXM images with the size of power of two, if such parameters as threshold, sizes of the median and Gaussian filters, and size of the low frequency window, have been properly selected. Copyright © 2011 Elsevier Ltd. All rights reserved.

A Real-Time De-Noising Algorithm for E-Noses in a Wireless Sensor Network

PubMed Central

Qu, Jianfeng; Chai, Yi; Yang, Simon X.

2009-01-01

A wireless e-nose network system is developed for the special purpose of monitoring odorant gases and accurately estimating odor strength in and around livestock farms. This system is to simultaneously acquire accurate odor strength values remotely at various locations, where each node is an e-nose that includes four metal-oxide semiconductor (MOS) gas sensors. A modified Kalman filtering technique is proposed for collecting raw data and de-noising based on the output noise characteristics of those gas sensors. The measurement noise variance is obtained in real time by data analysis using the proposed slip windows average method. The optimal system noise variance of the filter is obtained by using the experiments data. The Kalman filter theory on how to acquire MOS gas sensors data is discussed. Simulation results demonstrate that the proposed method can adjust the Kalman filter parameters and significantly reduce the noise from the gas sensors. PMID:22399946

A Wiener-Wavelet-Based filter for de-noising satellite soil moisture retrievals

NASA Astrophysics Data System (ADS)

Massari, Christian; Brocca, Luca; Ciabatta, Luca; Moramarco, Tommaso; Su, Chun-Hsu; Ryu, Dongryeol; Wagner, Wolfgang

2014-05-01

The reduction of noise in microwave satellite soil moisture (SM) retrievals is of paramount importance for practical applications especially for those associated with the study of climate changes, droughts, floods and other related hydrological processes. So far, Fourier based methods have been used for de-noising satellite SM retrievals by filtering either the observed emissivity time series (Du, 2012) or the retrieved SM observations (Su et al. 2013). This contribution introduces an alternative approach based on a Wiener-Wavelet-Based filtering (WWB) technique, which uses the Entropy-Based Wavelet de-noising method developed by Sang et al. (2009) to design both a causal and a non-causal version of the filter. WWB is used as a post-retrieval processing tool to enhance the quality of observations derived from the i) Advanced Microwave Scanning Radiometer for the Earth observing system (AMSR-E), ii) the Advanced SCATterometer (ASCAT), and iii) the Soil Moisture and Ocean Salinity (SMOS) satellite. The method is tested on three pilot sites located in Spain (Remedhus Network), in Greece (Hydrological Observatory of Athens) and in Australia (Oznet network), respectively. Different quantitative criteria are used to judge the goodness of the de-noising technique. Results show that WWB i) is able to improve both the correlation and the root mean squared differences between satellite retrievals and in situ soil moisture observations, and ii) effectively separates random noise from deterministic components of the retrieved signals. Moreover, the use of WWB de-noised data in place of raw observations within a hydrological application confirms the usefulness of the proposed filtering technique. Du, J. (2012), A method to improve satellite soil moisture retrievals based on Fourier analysis, Geophys. Res. Lett., 39, L15404, doi:10.1029/ 2012GL052435 Su,C.-H.,D.Ryu, A. W. Western, and W. Wagner (2013), De-noising of passive and active microwave satellite soil moisture time series, Geophys. Res. Lett., 40,3624-3630, doi:10.1002/grl.50695. Sang Y.-F., D. Wang, J.-C. Wu, Q.-P. Zhu, and L. Wang (2009), Entropy-Based Wavelet De-noising Method for Time Series Analysis, Entropy, 11, pp. 1123-1148, doi:10.3390/e11041123.

Should helicopter noise be measured differently from other aircraft noise? A review of the psychoacoustic literature

NASA Technical Reports Server (NTRS)

Molino, J. A.

1982-01-01

A review of 34 studies indicates that several factors or variables might be important in providing a psychoacoustic foundation for measurements of the noise from helicopters. These factors are phase relations, tail rotor noise, repetition rate, crest level, and generic differences between conventional aircraft and helicopters. Particular attention was given to the impulsive noise known as blade slap. Analysis of the evidence for and against each factor reveals that, for the present state of scientific knowledge, none of these factors should be regarded as the basis for a significant noise measurement correction due to impulsive blade slap. The current method of measuring effective perceived noise level for conventional aircraft appears to be adequate for measuring helicopter noise as well.

Development of an Empirical Methods for Predicting Jet Mixing Noise of Cold Flow Rectangular Jets

NASA Technical Reports Server (NTRS)

Russell, James W.

1999-01-01

This report presents an empirical method for predicting the jet mixing noise levels of cold flow rectangular jets. The report presents a detailed analysis of the methodology used in development of the prediction method. The empirical correlations used are based on narrow band acoustic data for cold flow rectangular model nozzle tests conducted in the NASA Langley Jet Noise Laboratory. There were 20 separate nozzle test operating conditions. For each operating condition 60 Hz bandwidth microphone measurements were made over a frequency range from 0 to 60,000 Hz. Measurements were performed at 16 polar directivity angles ranging from 45 degrees to 157.5 degrees. At each polar directivity angle, measurements were made at 9 azimuth directivity angles. The report shows the methods employed to remove screech tones and shock noise from the data in order to obtain the jet mixing noise component. The jet mixing noise was defined in terms of one third octave band spectral content, polar and azimuth directivity, and overall power level. Empirical correlations were performed over the range of test conditions to define each of these jet mixing noise parameters as a function of aspect ratio, jet velocity, and polar and azimuth directivity angles. The report presents the method for predicting the overall power level, the average polar directivity, the azimuth directivity and the location and shape of the spectra for jet mixing noise of cold flow rectangular jets.

Experimental and numerical analysis on noise reduction in a multi-blade centrifugal fan

NASA Astrophysics Data System (ADS)

Chen, X. J.; Y Cao, T.; Su, J.; Qin, G. L.

2013-12-01

In this work, analysis on noise source and reduction in a multi-blade centrifugal fan used for air-conditioners was carried out by experimental and numerical methods. Firstly, an experimental system using microphone mounted on volute surface for measuring surface pressure fluctuations of volute was designed and introduced, then surface pressure fluctuations of the whole volute for a multi-blade centrifugal fan were measured by this system, and the inlet noise for this fan was also obtained. And then, based on the experimental results, the aerodynamic noise source of the studied fan was analysed. The surface pressure fluctuations of the volute showed that there were largest surface pressure fluctuations near the volute tongue, and peaks appeared at the Blade Passing Frequency (BPF). The spectra of fan inlet noise showed that the peaks also appeared at BPF, and noise levels in a wide range of frequency were also larger. Secondly, the internal flow of the fan was simulated by commercial software under the same conditions with the experiment, and then the fluid flow and acoustic power field were obtained and discussed. The contours of acoustic power level showed that the larger noise was generated at the impeller area close to the outlet of scroll and at the volute tongue, which is same as that from experiment. Based on all of the results, we can find that the vortex noise is an important part of fan noise for the studied fan, and the rotation noise also cannot be neglected. Finally, several reduction methods that are thought to be effective based on experimental and numerical results were suggested.

Leak Detection in Spacecraft Using a 64-Element Multiplexed Passive Array to Monitor Structure-Borne Noise

NASA Astrophysics Data System (ADS)

Holland, Stephen D.; Song, Jun-Ho; Chimenti, D. E.; Roberts, Ron

2006-03-01

We demonstrate an array sensor method intended to locate leaks in manned spacecraft using leak-generated, structure-borne ultrasonic noise. We have developed and tested a method for sensing and processing leak noise to reveal the leak location involving the use of a 64-element phased-array. Cross-correlations of ultrasonic noise waveforms from a leak into vacuum have been used with a phased-array analysis to find the direction from the sensor to the leak. This method measures the propagation of guided ultrasonic Lamb waves passing under the PZT array sensor in the spacecraft skin structure. This paper will describe the custom-designed array with integrated electronics, as well as the performance of the array in prototype applications. We show that this method can be used to successfully locate leaks to within a few millimeters on a 0.6-m square aluminum plate.

Probabilistic density function method for nonlinear dynamical systems driven by colored noise

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

Barajas-Solano, David A.; Tartakovsky, Alexandre M.

2016-05-01

We present a probability density function (PDF) method for a system of nonlinear stochastic ordinary differential equations driven by colored noise. The method provides an integro-differential equation for the temporal evolution of the joint PDF of the system's state, which we close by means of a modified Large-Eddy-Diffusivity-type closure. Additionally, we introduce the generalized local linearization (LL) approximation for deriving a computable PDF equation in the form of the second-order partial differential equation (PDE). We demonstrate the proposed closure and localization accurately describe the dynamics of the PDF in phase space for systems driven by noise with arbitrary auto-correlation time.more » We apply the proposed PDF method to the analysis of a set of Kramers equations driven by exponentially auto-correlated Gaussian colored noise to study the dynamics and stability of a power grid.« less

Statistical Analysis of the Random Telegraph Noise in a 1.1 μm Pixel, 8.3 MP CMOS Image Sensor Using On-Chip Time Constant Extraction Method.

PubMed

Chao, Calvin Yi-Ping; Tu, Honyih; Wu, Thomas Meng-Hsiu; Chou, Kuo-Yu; Yeh, Shang-Fu; Yin, Chin; Lee, Chih-Lin

2017-11-23

A study of the random telegraph noise (RTN) of a 1.1 μm pitch, 8.3 Mpixel CMOS image sensor (CIS) fabricated in a 45 nm backside-illumination (BSI) technology is presented in this paper. A noise decomposition scheme is used to pinpoint the noise source. The long tail of the random noise (RN) distribution is directly linked to the RTN from the pixel source follower (SF). The full 8.3 Mpixels are classified into four categories according to the observed RTN histogram peaks. A theoretical formula describing the RTN as a function of the time difference between the two phases of the correlated double sampling (CDS) is derived and validated by measured data. An on-chip time constant extraction method is developed and applied to the RTN analysis. The effects of readout circuit bandwidth on the settling ratios of the RTN histograms are investigated and successfully accounted for in a simulation using a RTN behavior model.

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).

Signal-to-noise contribution of principal component loads in reconstructed near-infrared Raman tissue spectra.

PubMed

Grimbergen, M C M; van Swol, C F P; Kendall, C; Verdaasdonk, R M; Stone, N; Bosch, J L H R

2010-01-01

The overall quality of Raman spectra in the near-infrared region, where biological samples are often studied, has benefited from various improvements to optical instrumentation over the past decade. However, obtaining ample spectral quality for analysis is still challenging due to device requirements and short integration times required for (in vivo) clinical applications of Raman spectroscopy. Multivariate analytical methods, such as principal component analysis (PCA) and linear discriminant analysis (LDA), are routinely applied to Raman spectral datasets to develop classification models. Data compression is necessary prior to discriminant analysis to prevent or decrease the degree of over-fitting. The logical threshold for the selection of principal components (PCs) to be used in discriminant analysis is likely to be at a point before the PCs begin to introduce equivalent signal and noise and, hence, include no additional value. Assessment of the signal-to-noise ratio (SNR) at a certain peak or over a specific spectral region will depend on the sample measured. Therefore, the mean SNR over the whole spectral region (SNR(msr)) is determined in the original spectrum as well as for spectra reconstructed from an increasing number of principal components. This paper introduces a method of assessing the influence of signal and noise from individual PC loads and indicates a method of selection of PCs for LDA. To evaluate this method, two data sets with different SNRs were used. The sets were obtained with the same Raman system and the same measurement parameters on bladder tissue collected during white light cystoscopy (set A) and fluorescence-guided cystoscopy (set B). This method shows that the mean SNR over the spectral range in the original Raman spectra of these two data sets is related to the signal and noise contribution of principal component loads. The difference in mean SNR over the spectral range can also be appreciated since fewer principal components can reliably be used in the low SNR data set (set B) compared to the high SNR data set (set A). Despite the fact that no definitive threshold could be found, this method may help to determine the cutoff for the number of principal components used in discriminant analysis. Future analysis of a selection of spectral databases using this technique will allow optimum thresholds to be selected for different applications and spectral data quality levels.

Antigen-antibody biorecognition events as discriminated by noise analysis of force spectroscopy curves.

PubMed

Bizzarri, Anna Rita; Cannistraro, Salvatore

2014-08-22

Atomic force spectroscopy is able to extract kinetic and thermodynamic parameters of biomolecular complexes provided that the registered unbinding force curves could be reliably attributed to the rupture of the specific complex interactions. To this aim, a commonly used strategy is based on the analysis of the stretching features of polymeric linkers which are suitably introduced in the biomolecule-substrate immobilization procedure. Alternatively, we present a method to select force curves corresponding to specific biorecognition events, which relies on a careful analysis of the force fluctuations of the biomolecule-functionalized cantilever tip during its approach to the partner molecules immobilized on a substrate. In the low frequency region, a characteristic 1/f (α) noise with α equal to one (flickering noise) is found to replace white noise in the cantilever fluctuation power spectrum when, and only when, a specific biorecognition process between the partners occurs. The method, which has been validated on a well-characterized antigen-antibody complex, represents a fast, yet reliable alternative to the use of linkers which may involve additional surface chemistry and reproducibility concerns.

Prediction of light aircraft interior noise

NASA Technical Reports Server (NTRS)

Howlett, J. T.; Morales, D. A.

1976-01-01

At the present time, predictions of aircraft interior noise depend heavily on empirical correction factors derived from previous flight measurements. However, to design for acceptable interior noise levels and to optimize acoustic treatments, analytical techniques which do not depend on empirical data are needed. This paper describes a computerized interior noise prediction method for light aircraft. An existing analytical program (developed for commercial jets by Cockburn and Jolly in 1968) forms the basis of some modal analysis work which is described. The accuracy of this modal analysis technique for predicting low-frequency coupled acoustic-structural natural frequencies is discussed along with trends indicating the effects of varying parameters such as fuselage length and diameter, structural stiffness, and interior acoustic absorption.

Improving label-free detection of circulating melanoma cells by photoacoustic flow cytometry

NASA Astrophysics Data System (ADS)

Zhou, Huan; Wang, Qiyan; Pang, Kai; Zhou, Quanyu; Yang, Ping; He, Hao; Wei, Xunbin

2018-02-01

Melanoma is a kind of a malignant tumor of melanocytes with the properties of high mortality and high metastasis rate. The circulating melanoma cells with the high content of melanin can be detected by light absorption to diagnose and treat cancer at an early stage. Compared with conventional detection methods such as in vivo flow cytometry (IVFC) based on fluorescence, the in vivo photoacoustic flow cytometry (PAFC) utilizes melanin cells as biomarkers to collect the photoacoustic (PA) signals without toxic fluorescent dyes labeling in a non-invasive way. The information of target tumor cells is helpful for data analysis and cell counting. However, the raw signals in PAFC system contain numerous noises such as environmental noise, device noise and in vivo motion noise. Conventional denoising algorithms such as wavelet denoising (WD) method and means filter (MF) method are based on the local information to extract the data of clinical interest, which remove the subtle feature and leave many noises. To address the above questions, the nonlocal means (NLM) method based on nonlocal data has been proposed to suppress the noise in PA signals. Extensive experiments on in vivo PA signals from the mice with the injection of B16F10 cells in caudal vein have been conducted. All the results indicate that the NLM method has superior noise reduction performance and subtle information reservation.

Measurements of Reynolds stress profiles in unstratified tidal flow

USGS Publications Warehouse

Stacey, M.T.; Monismith, Stephen G.; Burau, J.R.

1999-01-01

In this paper we present a method for measuring profiles of turbulence quantities using a broadband acoustic doppler current profiler (ADCP). The method follows previous work on the continental shelf and extends the analysis to develop estimates of the errors associated with the estimation methods. ADCP data was collected in an unstratified channel and the results of the analysis are compared to theory. This comparison shows that the method provides an estimate of the Reynolds stresses, which is unbiased by Doppler noise, and an estimate of the turbulent kinetic energy (TKE) which is biased by an amount proportional to the Doppler noise. The noise in each of these quantities as well as the bias in the TKE match well with the theoretical values produced by the error analysis. The quantification of profiles of Reynolds stresses simultaneous with the measurement of mean velocity profiles allows for extensive analysis of the turbulence of the flow. In this paper, we examine the relation between the turbulence and the mean flow through the calculation of u*, the friction velocity, and Cd, the coefficient of drag. Finally, we calculate quantities of particular interest in turbulence modeling and analysis, the characteristic lengthscales, including a lengthscale which represents the stream-wise scale of the eddies which dominate the Reynolds stresses. Copyright 1999 by the American Geophysical Union.

Noise suppression methods for robust speech processing

NASA Astrophysics Data System (ADS)

Boll, S. F.; Ravindra, H.; Randall, G.; Armantrout, R.; Power, R.

1980-05-01

Robust speech processing in practical operating environments requires effective environmental and processor noise suppression. This report describes the technical findings and accomplishments during this reporting period for the research program funded to develop real time, compressed speech analysis synthesis algorithms whose performance in invariant under signal contamination. Fulfillment of this requirement is necessary to insure reliable secure compressed speech transmission within realistic military command and control environments. Overall contributions resulting from this research program include the understanding of how environmental noise degrades narrow band, coded speech, development of appropriate real time noise suppression algorithms, and development of speech parameter identification methods that consider signal contamination as a fundamental element in the estimation process. This report describes the current research and results in the areas of noise suppression using the dual input adaptive noise cancellation using the short time Fourier transform algorithms, articulation rate change techniques, and a description of an experiment which demonstrated that the spectral subtraction noise suppression algorithm can improve the intelligibility of 2400 bps, LPC 10 coded, helicopter speech by 10.6 point.

Noise analysis in numerical modeling of crossed fields microwave tubes

NASA Astrophysics Data System (ADS)

BłaŻejewicz, Mariusz; Woźniak, Martyna; Szkop, Emil; RóŻycki, Andrzej; Rychlewski, Michał; Baczewski, Dariusz; Laskowski, Dariusz

2018-04-01

One of the most important parameters that characterize microwave tubes with crossed fields, both amplifiers (CFA), and generating tubes like magnetrons is the noise level. This type of tubes are characterized by relatively high noise levels, which is the main factor limiting their current use in radar transmitters. The main source of noise in microwave tubes of this type is the dispersion of the energy of electrons that are in phase with the spatial wave of the electromagnetic field propagating in the delay line (in case of an amplitron) or in the resonant structure (in case of a magnetron).The results of the research presented in the article concern the technique of determination of Signal to Noise Ratio (SNR) based on the analysis of results obtained during the numerical simulations of the effect of electric charge on a high frequency electromagnetic field. Signal to noise ratio was determined by analysing in-phase and quadrature data recorded in the high frequency simulation. In order to assess the accuracy of the method under investigation, the results from the noise analysis obtained from numerical calculations were compared with the results obtained from real tube measurements performed by a spectrum analyser. On the basis of the research, it appears that performing analysis of noise generated in the interaction area may be useful for preliminary evaluation of the tube at the design stage.

Initial Results from SQUID Sensor: Analysis and Modeling for the ELF/VLF Atmospheric Noise.

PubMed

Hao, Huan; Wang, Huali; Chen, Liang; Wu, Jun; Qiu, Longqing; Rong, Liangliang

2017-02-14

In this paper, the amplitude probability density (APD) of the wideband extremely low frequency (ELF) and very low frequency (VLF) atmospheric noise is studied. The electromagnetic signals from the atmosphere, referred to herein as atmospheric noise, was recorded by a mobile low-temperature superconducting quantum interference device (SQUID) receiver under magnetically unshielded conditions. In order to eliminate the adverse effect brought by the geomagnetic activities and powerline, the measured field data was preprocessed to suppress the baseline wandering and harmonics by symmetric wavelet transform and least square methods firstly. Then statistical analysis was performed for the atmospheric noise on different time and frequency scales. Finally, the wideband ELF/VLF atmospheric noise was analyzed and modeled separately. Experimental results show that, Gaussian model is appropriate to depict preprocessed ELF atmospheric noise by a hole puncher operator. While for VLF atmospheric noise, symmetric α -stable (S α S) distribution is more accurate to fit the heavy-tail of the envelope probability density function (pdf).

Initial Results from SQUID Sensor: Analysis and Modeling for the ELF/VLF Atmospheric Noise

PubMed Central

Hao, Huan; Wang, Huali; Chen, Liang; Wu, Jun; Qiu, Longqing; Rong, Liangliang

2017-01-01

In this paper, the amplitude probability density (APD) of the wideband extremely low frequency (ELF) and very low frequency (VLF) atmospheric noise is studied. The electromagnetic signals from the atmosphere, referred to herein as atmospheric noise, was recorded by a mobile low-temperature superconducting quantum interference device (SQUID) receiver under magnetically unshielded conditions. In order to eliminate the adverse effect brought by the geomagnetic activities and powerline, the measured field data was preprocessed to suppress the baseline wandering and harmonics by symmetric wavelet transform and least square methods firstly. Then statistical analysis was performed for the atmospheric noise on different time and frequency scales. Finally, the wideband ELF/VLF atmospheric noise was analyzed and modeled separately. Experimental results show that, Gaussian model is appropriate to depict preprocessed ELF atmospheric noise by a hole puncher operator. While for VLF atmospheric noise, symmetric α-stable (SαS) distribution is more accurate to fit the heavy-tail of the envelope probability density function (pdf). PMID:28216590

Change detection for synthetic aperture radar images based on pattern and intensity distinctiveness analysis

NASA Astrophysics Data System (ADS)

Wang, Xiao; Gao, Feng; Dong, Junyu; Qi, Qiang

2018-04-01

Synthetic aperture radar (SAR) image is independent on atmospheric conditions, and it is the ideal image source for change detection. Existing methods directly analysis all the regions in the speckle noise contaminated difference image. The performance of these methods is easily affected by small noisy regions. In this paper, we proposed a novel change detection framework for saliency-guided change detection based on pattern and intensity distinctiveness analysis. The saliency analysis step can remove small noisy regions, and therefore makes the proposed method more robust to the speckle noise. In the proposed method, the log-ratio operator is first utilized to obtain a difference image (DI). Then, the saliency detection method based on pattern and intensity distinctiveness analysis is utilized to obtain the changed region candidates. Finally, principal component analysis and k-means clustering are employed to analysis pixels in the changed region candidates. Thus, the final change map can be obtained by classifying these pixels into changed or unchanged class. The experiment results on two real SAR images datasets have demonstrated the effectiveness of the proposed method.

Noise removal using factor analysis of dynamic structures: application to cardiac gated studies.

PubMed

Bruyant, P P; Sau, J; Mallet, J J

1999-10-01

Factor analysis of dynamic structures (FADS) facilitates the extraction of relevant data, usually with physiologic meaning, from a dynamic set of images. The result of this process is a set of factor images and curves plus some residual activity. The set of factor images and curves can be used to retrieve the original data with reduced noise using an inverse factor analysis process (iFADS). This improvement in image quality is expected because the inverse process does not use the residual activity, assumed to be made of noise. The goal of this work is to quantitate and assess the efficiency of this method on gated cardiac images. A computer simulation of a planar cardiac gated study was performed. The simulated images were added with noise and processed by the FADS-iFADS program. The signal-to-noise ratios (SNRs) were compared between original and processed data. Planar gated cardiac studies from 10 patients were tested. The data processed by FADS-iFADS were subtracted to the original data. The result of the substraction was studied to evaluate its noisy nature. The SNR is about five times greater after the FADS-iFADS process. The difference between original and processed data is noise only, i.e., processed data equals original data minus some white noise. The FADS-iFADS process is successful in the removal of an important part of the noise and therefore is a tool to improve the image quality of cardiac images. This tool does not decrease the spatial resolution (compared with smoothing filters) and does not lose details (compared with frequential filters). Once the number of factors is chosen, this method is not operator dependent.

DC/DC Converter Stability Testing Study

NASA Technical Reports Server (NTRS)

Wang, Bright L.

2008-01-01

This report presents study results on hybrid DC/DC converter stability testing methods. An input impedance measurement method and a gain/phase margin measurement method were evaluated to be effective to determine front-end oscillation and feedback loop oscillation. In particular, certain channel power levels of converter input noises have been found to have high degree correlation with the gain/phase margins. It becomes a potential new method to evaluate stability levels of all type of DC/DC converters by utilizing the spectral analysis on converter input noises.

A complex noise reduction method for improving visualization of SD-OCT skin biomedical images

NASA Astrophysics Data System (ADS)

Myakinin, Oleg O.; Zakharov, Valery P.; Bratchenko, Ivan A.; Kornilin, Dmitry V.; Khramov, Alexander G.

2014-05-01

In this paper we consider the original method of solving noise reduction problem for visualization's quality improvement of SD-OCT skin and tumors biomedical images. The principal advantages of OCT are high resolution and possibility of in vivo analysis. We propose a two-stage algorithm: 1) process of raw one-dimensional A-scans of SD-OCT and 2) remove a noise from the resulting B(C)-scans. The general mathematical methods of SD-OCT are unstable: if the noise of the CCD is 1.6% of the dynamic range then result distortions are already 25-40% of the dynamic range. We use at the first stage a resampling of A-scans and simple linear filters to reduce the amount of data and remove the noise of the CCD camera. The efficiency, improving productivity and conservation of the axial resolution when using this approach are showed. At the second stage we use an effective algorithms based on Hilbert-Huang Transform for more accurately noise peaks removal. The effectiveness of the proposed approach for visualization of malignant and benign skin tumors (melanoma, BCC etc.) and a significant improvement of SNR level for different methods of noise reduction are showed. Also in this study we consider a modification of this method depending of a specific hardware and software features of used OCT setup. The basic version does not require any hardware modifications of existing equipment. The effectiveness of proposed method for 3D visualization of tissues can simplify medical diagnosis in oncology.

Robust gene selection methods using weighting schemes for microarray data analysis.

PubMed

Kang, Suyeon; Song, Jongwoo

2017-09-02

A common task in microarray data analysis is to identify informative genes that are differentially expressed between two different states. Owing to the high-dimensional nature of microarray data, identification of significant genes has been essential in analyzing the data. However, the performances of many gene selection techniques are highly dependent on the experimental conditions, such as the presence of measurement error or a limited number of sample replicates. We have proposed new filter-based gene selection techniques, by applying a simple modification to significance analysis of microarrays (SAM). To prove the effectiveness of the proposed method, we considered a series of synthetic datasets with different noise levels and sample sizes along with two real datasets. The following findings were made. First, our proposed methods outperform conventional methods for all simulation set-ups. In particular, our methods are much better when the given data are noisy and sample size is small. They showed relatively robust performance regardless of noise level and sample size, whereas the performance of SAM became significantly worse as the noise level became high or sample size decreased. When sufficient sample replicates were available, SAM and our methods showed similar performance. Finally, our proposed methods are competitive with traditional methods in classification tasks for microarrays. The results of simulation study and real data analysis have demonstrated that our proposed methods are effective for detecting significant genes and classification tasks, especially when the given data are noisy or have few sample replicates. By employing weighting schemes, we can obtain robust and reliable results for microarray data analysis.

Quantifying the similarity of seismic polarizations

NASA Astrophysics Data System (ADS)

Jones, Joshua P.; Eaton, David W.; Caffagni, Enrico

2016-02-01

Assessing the similarities of seismic attributes can help identify tremor, low signal-to-noise (S/N) signals and converted or reflected phases, in addition to diagnosing site noise and sensor misalignment in arrays. Polarization analysis is a widely accepted method for studying the orientation and directional characteristics of seismic phases via computed attributes, but similarity is ordinarily discussed using qualitative comparisons with reference values or known seismic sources. Here we introduce a technique for quantitative polarization similarity that uses weighted histograms computed in short, overlapping time windows, drawing on methods adapted from the image processing and computer vision literature. Our method accounts for ambiguity in azimuth and incidence angle and variations in S/N ratio. Measuring polarization similarity allows easy identification of site noise and sensor misalignment and can help identify coherent noise and emergent or low S/N phase arrivals. Dissimilar azimuths during phase arrivals indicate misaligned horizontal components, dissimilar incidence angles during phase arrivals indicate misaligned vertical components and dissimilar linear polarization may indicate a secondary noise source. Using records of the Mw = 8.3 Sea of Okhotsk earthquake, from Canadian National Seismic Network broad-band sensors in British Columbia and Yukon Territory, Canada, and a vertical borehole array at Hoadley gas field, central Alberta, Canada, we demonstrate that our method is robust to station spacing. Discrete wavelet analysis extends polarization similarity to the time-frequency domain in a straightforward way. Time-frequency polarization similarities of borehole data suggest that a coherent noise source may have persisted above 8 Hz several months after peak resource extraction from a `flowback' type hydraulic fracture.

3D shallow velocity model in the area of Pozzo Pitarrone, NE flank of Mt. Etna Volcano, by using SPAC array method.

NASA Astrophysics Data System (ADS)

Zuccarello, Luciano; Paratore, Mario; La Rocca, Mario; Ferrari, Ferruccio; Messina, Alfio; Contrafatto, Danilo; Galluzzo, Danilo; Rapisarda, Salvatore

2016-04-01

In volcanic environment the propagation of seismic signals through the shallowest layers is strongly affected by lateral heterogeneity, attenuation, scattering, and interaction with the free surface. Therefore tracing a seismic ray from the recording site back to the source is a complex matter, with obvious implications for the source location. For this reason the knowledge of the shallow velocity structure may improve the location of shallow volcano-tectonic earthquakes and volcanic tremor, thus contributing to improve the monitoring of volcanic activity. This work focuses on the analysis of seismic noise and volcanic tremor recorded in 2014 by a temporary array installed around Pozzo Pitarrone, NE flank of Mt. Etna. Several methods permit a reliable estimation of the shear wave velocity in the shallowest layers through the analysis of stationary random wavefield like the seismic noise. We have applied the single station HVSR method and SPAC array method to seismic noise to investigate the local shallow structure. The inversion of dispersion curves produced a shear wave velocity model of the area reliable down to depth of about 130 m. We also applied the Beam Forming array method in the 0.5 Hz - 4 Hz frequency range to both seismic noise and volcanic tremor. The apparent velocity of coherent tremor signals fits quite well the dispersion curve estimated from the analysis of seismic noise, thus giving a further constrain on the estimated velocity model. Moreover, taking advantage of a borehole station installed at 130 m depth in the same area of the array, we obtained a direct estimate of the P-wave velocity by comparing the borehole recordings of local earthquakes with the same event recorded at surface. Further insight on the P-wave velocity in the upper 130 m layer comes from the surface reflected wave visible in some cases at the borehole station. From this analysis we obtained an average P-wave velocity of about 1.2 km/s, in good agreement with the shear wave velocity found from the analysis of seismic noise. To better constrain the inversion we used the HVSR computed at each array station, which also give a lateral extension to the final 3D velocity model. The obtained results indicate that site effects in the investigate area are quite homogeneous among the array stations.

Opportunities for Environmental Noise Mapping in Saudi Arabia: A Case of Traffic Noise Annoyance in an Urban Area in Jeddah City.

PubMed

Zytoon, Mohamed A

2016-05-13

As the traffic and other environmental noise generating activities are growing in The Kingdom of Saudi Arabia (KSA), adverse health and other impacts are expected to develop. The management of such problem involves many actions, of which noise mapping has been proven to be a helpful approach. The objective of the current study was to test the adequacy of the available data in KSA municipalities for generating urban noise maps and to verify the applicability of available environmental noise mapping and noise annoyance models for KSA. Therefore, noise maps were produced for Al-Fayha District in Jeddah City, KSA using commercially available noise mapping software and applying the French national computation method "NMPB" for traffic noise. Most of the data required for traffic noise prediction and annoyance analysis were available, either in the Municipality GIS department or in other governmental authorities. The predicted noise levels during the three time periods, i.e., daytime, evening, and nighttime, were found higher than the maximum recommended levels established in KSA environmental noise standards. Annoyance analysis revealed that high percentages of the District inhabitants were highly annoyed, depending on the type of planning zone and period of interest. These results reflect the urgent need to consider environmental noise reduction in KSA national plans. The accuracy of the predicted noise levels and the availability of most of the necessary data should encourage further studies on the use of noise mapping as part of noise reduction plans.

Structural health monitoring using DOG multi-scale space: an approach for analyzing damage characteristics

NASA Astrophysics Data System (ADS)

Guo, Tian; Xu, Zili

2018-03-01

Measurement noise is inevitable in practice; thus, it is difficult to identify defects, cracks or damage in a structure while suppressing noise simultaneously. In this work, a novel method is introduced to detect multiple damage in noisy environments. Based on multi-scale space analysis for discrete signals, a method for extracting damage characteristics from the measured displacement mode shape is illustrated. Moreover, the proposed method incorporates a data fusion algorithm to further eliminate measurement noise-based interference. The effectiveness of the method is verified by numerical and experimental methods applied to different structural types. The results demonstrate that there are two advantages to the proposed method. First, damage features are extracted by the difference of the multi-scale representation; this step is taken such that the interference of noise amplification can be avoided. Second, a data fusion technique applied to the proposed method provides a global decision, which retains the damage features while maximally eliminating the uncertainty. Monte Carlo simulations are utilized to validate that the proposed method has a higher accuracy in damage detection.

Human voice quality measurement in noisy environments.

PubMed

Ueng, Shyh-Kuang; Luo, Cheng-Ming; Tsai, Tsung-Yu; Yeh, Hsuan-Chen

2015-01-01

Computerized acoustic voice measurement is essential for the diagnosis of vocal pathologies. Previous studies showed that ambient noises have significant influences on the accuracy of voice quality assessment. This paper presents a voice quality assessment system that can accurately measure qualities of voice signals, even though the input voice data are contaminated by low-frequency noises. The ambient noises in our living rooms and laboratories are collected and the frequencies of these noises are analyzed. Based on the analysis, a filter is designed to reduce noise level of the input voice signal. Then, improved numerical algorithms are employed to extract voice parameters from the voice signal to reveal the health of the voice signal. Compared with MDVP and Praat, the proposed method outperforms these two widely used programs in measuring fundamental frequency and harmonic-to-noise ratio, and its performance is comparable to these two famous programs in computing jitter and shimmer. The proposed voice quality assessment method is resistant to low-frequency noises and it can measure human voice quality in environments filled with noises from air-conditioners, ceiling fans and cooling fans of computers.

Improved Line Tracing Methods for Removal of Bad Streaks Noise in CCD Line Array Image—A Case Study with GF-1 Images

PubMed Central

Wang, Bo; Bao, Jianwei; Wang, Shikui; Wang, Houjun; Sheng, Qinghong

2017-01-01

Remote sensing images could provide us with tremendous quantities of large-scale information. Noise artifacts (stripes), however, made the images inappropriate for vitalization and batch process. An effective restoration method would make images ready for further analysis. In this paper, a new method is proposed to correct the stripes and bad abnormal pixels in charge-coupled device (CCD) linear array images. The method involved a line tracing method, limiting the location of noise to a rectangular region, and corrected abnormal pixels with the Lagrange polynomial algorithm. The proposed detection and restoration method were applied to Gaofen-1 satellite (GF-1) images, and the performance of this method was evaluated by omission ratio and false detection ratio, which reached 0.6% and 0%, respectively. This method saved 55.9% of the time, compared with traditional method. PMID:28441754

Synchronized and noise-robust audio recordings during realtime magnetic resonance imaging scans.

PubMed

Bresch, Erik; Nielsen, Jon; Nayak, Krishna; Narayanan, Shrikanth

2006-10-01

This letter describes a data acquisition setup for recording, and processing, running speech from a person in a magnetic resonance imaging (MRI) scanner. The main focus is on ensuring synchronicity between image and audio acquisition, and in obtaining good signal to noise ratio to facilitate further speech analysis and modeling. A field-programmable gate array based hardware design for synchronizing the scanner image acquisition to other external data such as audio is described. The audio setup itself features two fiber optical microphones and a noise-canceling filter. Two noise cancellation methods are described including a novel approach using a pulse sequence specific model of the gradient noise of the MRI scanner. The setup is useful for scientific speech production studies. Sample results of speech and singing data acquired and processed using the proposed method are given.

Synchronized and noise-robust audio recordings during realtime magnetic resonance imaging scans (L)

PubMed Central

Bresch, Erik; Nielsen, Jon; Nayak, Krishna; Narayanan, Shrikanth

2007-01-01

This letter describes a data acquisition setup for recording, and processing, running speech from a person in a magnetic resonance imaging (MRI) scanner. The main focus is on ensuring synchronicity between image and audio acquisition, and in obtaining good signal to noise ratio to facilitate further speech analysis and modeling. A field-programmable gate array based hardware design for synchronizing the scanner image acquisition to other external data such as audio is described. The audio setup itself features two fiber optical microphones and a noise-canceling filter. Two noise cancellation methods are described including a novel approach using a pulse sequence specific model of the gradient noise of the MRI scanner. The setup is useful for scientific speech production studies. Sample results of speech and singing data acquired and processed using the proposed method are given. PMID:17069275

Probabilistic solutions of nonlinear oscillators excited by combined colored and white noise excitations

NASA Astrophysics Data System (ADS)

Siu-Siu, Guo; Qingxuan, Shi

2017-03-01

In this paper, single-degree-of-freedom (SDOF) systems combined to Gaussian white noise and Gaussian/non-Gaussian colored noise excitations are investigated. By expressing colored noise excitation as a second-order filtered white noise process and introducing colored noise as an additional state variable, the equation of motion for SDOF system under colored noise is then transferred artificially to multi-degree-of-freedom (MDOF) system under white noise excitations with four-coupled first-order differential equations. As a consequence, corresponding Fokker-Planck-Kolmogorov (FPK) equation governing the joint probabilistic density function (PDF) of state variables increases to 4-dimension (4-D). Solution procedure and computer programme become much more sophisticated. The exponential-polynomial closure (EPC) method, widely applied for cases of SDOF systems under white noise excitations, is developed and improved for cases of systems under colored noise excitations and for solving the complex 4-D FPK equation. On the other hand, Monte Carlo simulation (MCS) method is performed to test the approximate EPC solutions. Two examples associated with Gaussian and non-Gaussian colored noise excitations are considered. Corresponding band-limited power spectral densities (PSDs) for colored noise excitations are separately given. Numerical studies show that the developed EPC method provides relatively accurate estimates of the stationary probabilistic solutions, especially the ones in the tail regions of the PDFs. Moreover, statistical parameter of mean-up crossing rate (MCR) is taken into account, which is important for reliability and failure analysis. Hopefully, our present work could provide insights into the investigation of structures under random loadings.

Linear approximations of global behaviors in nonlinear systems with moderate or strong noise

NASA Astrophysics Data System (ADS)

Liang, Junhao; Din, Anwarud; Zhou, Tianshou

2018-03-01

While many physical or chemical systems can be modeled by nonlinear Langevin equations (LEs), dynamical analysis of these systems is challenging in the cases of moderate and strong noise. Here we develop a linear approximation scheme, which can transform an often intractable LE into a linear set of binomial moment equations (BMEs). This scheme provides a feasible way to capture nonlinear behaviors in the sense of probability distribution and is effective even when the noise is moderate or big. Based on BMEs, we further develop a noise reduction technique, which can effectively handle tough cases where traditional small-noise theories are inapplicable. The overall method not only provides an approximation-based paradigm to analysis of the local and global behaviors of nonlinear noisy systems but also has a wide range of applications.

Mining knowledge in noisy audio data

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

Czyzewski, A.

1996-12-31

This paper demonstrates a KDD method applied to audio data analysis, particularly, it presents possibilities which result from replacing traditional methods of analysis and acoustic signal processing by KDD algorithms when restoring audio recordings affected by strong noise.

Further development of the sound intensity method of measuring tire noise performance of in-situ pavements.

DOT National Transportation Integrated Search

2006-01-01

Through analysis of earlier research and some recent on-road testing it is demonstrated that, with : adequate precaution, accurate measurement of tire/pavement noise using on-board sound : intensity (SI) can be accomplished with two intensity probes ...

Method for removal of random noise in eddy-current testing system

DOEpatents

Levy, Arthur J.

1995-01-01

Eddy-current response voltages, generated during inspection of metallic structures for anomalies, are often replete with noise. Therefore, analysis of the inspection data and results is difficult or near impossible, resulting in inconsistent or unreliable evaluation of the structure. This invention processes the eddy-current response voltage, removing the effect of random noise, to allow proper identification of anomalies within and associated with the structure.

Optimization and Comparison of Different Digital Mammographic Tomosynthesis Reconstruction Methods

DTIC Science & Technology

2007-04-01

physical measurements of impulse response analysis, modulation transfer function (MTF) and noise power spectrum (NPS). (Months 5- 12). 1.2.1. Simulate...added: projection images with simulated impulse and the 1/r2 shading difference. Other system blur and noise issues were not addressed in this paper...spectrum (NPS), Noise -equivalent quanta (NEQ), impulse response, Back Projection (BP) 1. INTRODUCTION Digital breast tomosynthesis is a new

Optimization and Comparison of Different Digital Mammographic Tomosynthesis Reconstruction Methods

DTIC Science & Technology

2008-04-01

physical measurements of impulse response analysis, modulation transfer function (MTF) and noise power spectrum (NPS). (Months 5- 12). This task has...and 2 impulse -added: projection images with simulated impulse and the I /r2 shading difference. Other system blur and noise issues are not...blur, and suppressed high frequency noise . Point-by-point BP rather than traditional SAA should be considered as the basis of further deblurring

Automated filtering of common-mode artifacts in multichannel physiological recordings.

PubMed

Kelly, John W; Siewiorek, Daniel P; Smailagic, Asim; Wang, Wei

2013-10-01

The removal of spatially correlated noise is an important step in processing multichannel recordings. Here, a technique termed the adaptive common average reference (ACAR) is presented as an effective and simple method for removing this noise. The ACAR is based on a combination of the well-known common average reference (CAR) and an adaptive noise canceling (ANC) filter. In a convergent process, the CAR provides a reference to an ANC filter, which in turn provides feedback to enhance the CAR. This method was effective on both simulated and real data, outperforming the standard CAR when the amplitude or polarity of the noise changes across channels. In many cases, the ACAR even outperformed independent component analysis. On 16 channels of simulated data, the ACAR was able to attenuate up to approximately 290 dB of noise and could improve signal quality if the original SNR was as high as 5 dB. With an original SNR of 0 dB, the ACAR improved signal quality with only two data channels and performance improved as the number of channels increased. It also performed well under many different conditions for the structure of the noise and signals. Analysis of contaminated electrocorticographic recordings further showed the effectiveness of the ACAR.

Automated Filtering of Common Mode Artifacts in Multi-Channel Physiological Recordings

PubMed Central

Kelly, John W.; Siewiorek, Daniel P.; Smailagic, Asim; Wang, Wei

2014-01-01

The removal of spatially correlated noise is an important step in processing multi-channel recordings. Here, a technique termed the adaptive common average reference (ACAR) is presented as an effective and simple method for removing this noise. The ACAR is based on a combination of the well-known common average reference (CAR) and an adaptive noise canceling (ANC) filter. In a convergent process, the CAR provides a reference to an ANC filter, which in turn provides feedback to enhance the CAR. This method was effective on both simulated and real data, outperforming the standard CAR when the amplitude or polarity of the noise changes across channels. In many cases the ACAR even outperformed independent component analysis (ICA). On 16 channels of simulated data the ACAR was able to attenuate up to approximately 290 dB of noise and could improve signal quality if the original SNR was as high as 5 dB. With an original SNR of 0 dB, the ACAR improved signal quality with only two data channels and performance improved as the number of channels increased. It also performed well under many different conditions for the structure of the noise and signals. Analysis of contaminated electrocorticographic (ECoG) recordings further showed the effectiveness of the ACAR. PMID:23708770

Airframe noise of the DC-9

NASA Technical Reports Server (NTRS)

Bauer, A. B.; Munson, A. G.

1977-01-01

Airframe noise measurements are reported for the DC-9-31 aircraft flown at several speeds and with a number of flap, landing gear, and slat extension configurations. The data are corrected for atmospheric attenuation and spherical divergence, and are presented for an overhead position normalized to a 1-meter height. The sound pressure levels are found to vary approximately as the fifth power of flight velocity. Both lift and drag dipoles exist as a significant part of the airframe noise. The data are compared with airframe noise predictions using the drag element and the data analysis methods. Although some of the predictions are very good, further work is needed to refine these methods, particularly for the gear-down and flaps-down configurations.

Delving into α-stable distribution in noise suppression for seizure detection from scalp EEG

NASA Astrophysics Data System (ADS)

Wang, Yueming; Qi, Yu; Wang, Yiwen; Lei, Zhen; Zheng, Xiaoxiang; Pan, Gang

2016-10-01

Objective. There is serious noise in EEG caused by eye blink and muscle activities. The noise exhibits similar morphologies to epileptic seizure signals, leading to relatively high false alarms in most existing seizure detection methods. The objective in this paper is to develop an effective noise suppression method in seizure detection and explore the reason why it works. Approach. Based on a state-space model containing a non-linear observation function and multiple features as the observations, this paper delves deeply into the effect of the α-stable distribution in the noise suppression for seizure detection from scalp EEG. Compared with the Gaussian distribution, the α-stable distribution is asymmetric and has relatively heavy tails. These properties make it more powerful in modeling impulsive noise in EEG, which usually can not be handled by the Gaussian distribution. Specially, we give a detailed analysis in the state estimation process to show the reason why the α-stable distribution can suppress the impulsive noise. Main results. To justify each component in our model, we compare our method with 4 different models with different settings on a collected 331-hour epileptic EEG data. To show the superiority of our method, we compare it with the existing approaches on both our 331-hour data and 892-hour public data. The results demonstrate that our method is most effective in both the detection rate and the false alarm. Significance. This is the first attempt to incorporate the α-stable distribution to a state-space model for noise suppression in seizure detection and achieves the state-of-the-art performance.

High lateral resolution exploration using surface waves from noise records

NASA Astrophysics Data System (ADS)

Chávez-García, Francisco José Yokoi, Toshiaki

2016-04-01

Determination of the shear-wave velocity structure at shallow depths is a constant necessity in engineering or environmental projects. Given the sensitivity of Rayleigh waves to shear-wave velocity, subsoil structure exploration using surface waves is frequently used. Methods such as the spectral analysis of surface waves (SASW) or multi-channel analysis of surface waves (MASW) determine phase velocity dispersion from surface waves generated by an active source recorded on a line of geophones. Using MASW, it is important that the receiver array be as long as possible to increase the precision at low frequencies. However, this implies that possible lateral variations are discarded. Hayashi and Suzuki (2004) proposed a different way of stacking shot gathers to increase lateral resolution. They combined strategies used in MASW with the common mid-point (CMP) summation currently used in reflection seismology. In their common mid-point with cross-correlation method (CMPCC), they cross-correlate traces sharing CMP locations before determining phase velocity dispersion. Another recent approach to subsoil structure exploration is based on seismic interferometry. It has been shown that cross-correlation of a diffuse field, such as seismic noise, allows the estimation of the Green's Function between two receivers. Thus, a virtual-source seismic section may be constructed from the cross-correlation of seismic noise records obtained in a line of receivers. In this paper, we use the seismic interferometry method to process seismic noise records obtained in seismic refraction lines of 24 geophones, and analyse the results using CMPCC to increase the lateral resolution of the results. Cross-correlation of the noise records allows reconstructing seismic sections with virtual sources at each receiver location. The Rayleigh wave component of the Green's Functions is obtained with a high signal-to-noise ratio. Using CMPCC analysis of the virtual-source seismic lines, we are able to identify lateral variations of phase velocity inside the seismic line, and increase the lateral resolution compared with results of conventional analysis.

Filtration of human EEG recordings from physiological artifacts with empirical mode method

NASA Astrophysics Data System (ADS)

Grubov, Vadim V.; Runnova, Anastasiya E.; Khramova, Marina V.

2017-03-01

In the paper we propose the new method for dealing with noise and physiological artifacts in experimental human EEG recordings. The method is based on analysis of EEG signals with empirical mode decomposition (Hilbert-Huang transform). We consider noises and physiological artifacts on EEG as specific oscillatory patterns that cause problems during EEG analysis and can be detected with additional signals recorded simultaneously with EEG (ECG, EMG, EOG, etc.) We introduce the algorithm of the method with following steps: empirical mode decomposition of EEG signal, choosing of empirical modes with artifacts, removing empirical modes with artifacts, reconstruction of the initial EEG signal. We test the method on filtration of experimental human EEG signals from eye-moving artifacts and show high efficiency of the method.

Multi-channel Analysis of Passive Surface Waves (MAPS)

NASA Astrophysics Data System (ADS)

Xia, J.; Cheng, F. Mr; Xu, Z.; Wang, L.; Shen, C.; Liu, R.; Pan, Y.; Mi, B.; Hu, Y.

2017-12-01

Urbanization is an inevitable trend in modernization of human society. In the end of 2013 the Chinese Central Government launched a national urbanization plan—"Three 100 Million People", which aggressively and steadily pushes forward urbanization. Based on the plan, by 2020, approximately 100 million people from rural areas will permanently settle in towns, dwelling conditions of about 100 million people in towns and villages will be improved, and about 100 million people in the central and western China will permanently settle in towns. China's urbanization process will run at the highest speed in the urbanization history of China. Environmentally friendly, non-destructive and non-invasive geophysical assessment method has played an important role in the urbanization process in China. Because human noise and electromagnetic field due to industrial life, geophysical methods already used in urban environments (gravity, magnetics, electricity, seismic) face great challenges. But humanity activity provides an effective source of passive seismic methods. Claerbout pointed out that wavefileds that are received at one point with excitation at the other point can be reconstructed by calculating the cross-correlation of noise records at two surface points. Based on this idea (cross-correlation of two noise records) and the virtual source method, we proposed Multi-channel Analysis of Passive Surface Waves (MAPS). MAPS mainly uses traffic noise recorded with a linear receiver array. Because Multi-channel Analysis of Surface Waves can produces a shear (S) wave velocity model with high resolution in shallow part of the model, MPAS combines acquisition and processing of active source and passive source data in a same flow, which does not require to distinguish them. MAPS is also of ability of real-time quality control of noise recording that is important for near-surface applications in urban environment. The numerical and real-world examples demonstrated that MAPS can be used for accurate and fast imaging of high-frequency surface wave energy, and some examples also show that high quality imaging similar to those with active sources can be generated only by the use of a few minutes of noise. The use of cultural noise in town, MAPS can image S-wave velocity structure from the ground surface to hundreds of meters depth.

Dual-tree complex wavelet transform and SVD based acoustic noise reduction and its application in leak detection for natural gas pipeline

NASA Astrophysics Data System (ADS)

Yu, Xuchao; Liang, Wei; Zhang, Laibin; Jin, Hao; Qiu, Jingwei

2016-05-01

During the last decades, leak detection for natural gas pipeline has become one of the paramount concerns of pipeline operators and researchers across the globe. However, acoustic wave method has been proved to be an effective way to identify and localize leakage for gas pipeline. Considering the fact that noises inevitably exist in the acoustic signals collected, noise reduction should be enforced on the signals for subsequent data mining and analysis. Thus, an integrated acoustic noise reduction method based on DTCWT and SVD is proposed in this study. The method is put forward based on the idea that noise reduction strategy should match the characteristics of the noisy signal. According to previous studies, it is known that the energy of acoustic signals collected under leaking condition is mainly concentrated in low-frequency portion (0-100 Hz). And ultralow-frequency component (0-5 Hz), which is taken as the characteristic frequency band in this study, can propagate a relatively longer distance and be captured by sensors. Therefore, in order to filter the noises and to reserve the characteristic frequency band, DTCWT is taken as the core to conduct multilevel decomposition and refining for acoustic signals and SVD is employed to eliminate noises in non-characteristic bands. Both simulation and field experiments show that DTCWT-SVD is an excellent method for acoustic noise reduction. At the end of this study, application in leakage localization shows that it becomes much easier and a little more accurate to estimate the location of leak hole after noise reduction by DTCWT-SVD.

A novel rail defect detection method based on undecimated lifting wavelet packet transform and Shannon entropy-improved adaptive line enhancer

NASA Astrophysics Data System (ADS)

Hao, Qiushi; Zhang, Xin; Wang, Yan; Shen, Yi; Makis, Viliam

2018-07-01

Acoustic emission (AE) technology is sensitive to subliminal rail defects, however strong wheel-rail contact rolling noise under high-speed condition has gravely impeded detecting of rail defects using traditional denoising methods. In this context, the paper develops an adaptive detection method for rail cracks, which combines multiresolution analysis with an improved adaptive line enhancer (ALE). To obtain elaborate multiresolution information of transient crack signals with low computational cost, lifting scheme-based undecimated wavelet packet transform is adopted. In order to feature the impulsive property of crack signals, a Shannon entropy-improved ALE is proposed as a signal enhancing approach, where Shannon entropy is introduced to improve the cost function. Then a rail defect detection plan based on the proposed method for high-speed condition is put forward. From theoretical analysis and experimental verification, it is demonstrated that the proposed method has superior performance in enhancing the rail defect AE signal and reducing the strong background noise, offering an effective multiresolution approach for rail defect detection under high-speed and strong-noise condition.

Analysis of acoustic and entropy disturbances in a hypersonic wind tunnel

NASA Astrophysics Data System (ADS)

Schilden, Thomas; Schröder, Wolfgang; Ali, Syed Raza Christopher; Schreyer, Anne-Marie; Wu, Jie; Radespiel, Rolf

2016-05-01

The tunnel noise in a Mach 5.9 Ludwieg tube is determined by two methods, a newly developed cone-probe-DNS method and a reliable hot-wire-Pitot-probe method. The new method combines pressure and heat flux measurements using a cone probe and direct numerical simulation (DNS). The modal analysis is based on transfer functions obtained by the DNS to link the measured quantities to the tunnel noise. The measurements are performed for several unit-Reynolds numbers in the range of 5 ṡ 106 ≤ Re/m ≤ 16 ṡ 106 and probe positions to identify the sensitivities of tunnel noise. The DNS solutions show similar response mechanisms of the cone probe to incident acoustic and entropy waves which leads to high condition numbers of the transfer matrix such that a unique relationship between response and source mechanism can be only determined by neglecting the contribution of the non-acoustic modes to the pressure and heat flux fluctuations. The results of the cone-probe-DNS method are compared to a modal analysis based on the hot-wire-Pitot-probe method which provides reliable results in the frequency range less than 50 kHz. In this low frequency range the findings of the two different mode analyses agree well. At higher frequencies, the newly developed cone-probe-DNS method is still valid. The tunnel noise is dominated by the acoustic mode, since the entropy mode is lower by one order of magnitude and the vorticity mode can be neglected. The acoustic mode is approximately 0.5% at 30 kHz and the cone-probe-DNS data illustrate the acoustic mode to decrease and to asymptotically approach 0.2%.

Analysis of Subway Interior Noise at Peak Commuter Time

PubMed Central

Lee, Donguk; Kim, Gibbeum; Han, Woojae

2017-01-01

Background and Objectives Although mass transit systems are convenient and efficient for urban people, little attention has been paid to the potential hearing hazard from their noise. The purpose of the current study was to measure and analyze levels of subway interior noise at peak commuter times and to provide information about commuters’ daily dose of noise exposure. Materials and Methods To measure the subway interior noise, nine subway lines inside Seoul (i.e., lines 1-9) and six lines surrounding the capital city area (i.e., Central, Bundang, Sinbundang, Incheon, Gyeongui, and Gyeongchun) were chosen. The noise was measured and recorded by a sound level meter for two-hour periods in the morning and evening. Results 1) In the LZeq analysis, the average noise level of all 15 lines was 72.78 dB; the maximum and minimum noise levels were 78.34 and 62.46 dB, respectively. The average noise level of the nine lines inside Seoul was 73.45 dB, which was 1.68-dB louder than that of the six lines surrounding the capital city area. 2) Based on the LZeq analysis of 33 measured frequencies, 12.5 Hz was the highest frequency and 20,000 Hz was the lowest. 3) There was no remarkable difference in the level of subway interior noise between morning and evening peak commuter times. Conclusions We concluded that the level of subway interior noise was not loud enough for commuters to incur noise-induced hearing loss. Regardless, environmental noise control efforts in the subway system might be needed for commuters who take a subway every day. PMID:28704890

Prediction and Reduction of Noise in Pneumatic Bleed Valves

NASA Astrophysics Data System (ADS)

Taghavi Nezhad, Shervin

This study investigates numerically the fluid mechanics and acoustics of pneumatic bleed valves used in turbofan engines. The goal is to characterized the fundamental processes of noise generation and devise strategies for noise reduction. Three different methods are employed for both analysis and redesign of the bleed valve to reduce noise. The bleed valve noise problem is carefully divided into multiple smaller problems. For large separations and tonal noises, the unsteady Reynolds-Averaged Navier-Stokes (URANS) method is utilized. This method is also applied in the re-designing of the bleed valve geometry. For the bleed valve muffler, which is comprised of perforated plates and a honeycomb, a Reynolds-Averaged Navier-Stokes (RANS) method combined with a simplified acoustic analogy is used. The original muffler design is modified to improve noise attenuation. Finally, for sound scattering through perforated plates, a fully implicit linearized Euler solver is developed. The problem of sound interaction with perforated plates is studied from two perspectives. In the first study the effect of high--speed mean flow is considered and it is shown that at Strouhal numbers of around 0.2-0.25 there is an increase in transmitted incident sound. In the second part, the interaction of holes in two--dimensional perforated plates is investigated using three different configurations. The study demonstrates that the hole interaction has a significant impact on sound attenuation, especially at high frequencies.

Single neuron computation: from dynamical system to feature detector.

PubMed

Hong, Sungho; Agüera y Arcas, Blaise; Fairhall, Adrienne L

2007-12-01

White noise methods are a powerful tool for characterizing the computation performed by neural systems. These methods allow one to identify the feature or features that a neural system extracts from a complex input and to determine how these features are combined to drive the system's spiking response. These methods have also been applied to characterize the input-output relations of single neurons driven by synaptic inputs, simulated by direct current injection. To interpret the results of white noise analysis of single neurons, we would like to understand how the obtained feature space of a single neuron maps onto the biophysical properties of the membrane, in particular, the dynamics of ion channels. Here, through analysis of a simple dynamical model neuron, we draw explicit connections between the output of a white noise analysis and the underlying dynamical system. We find that under certain assumptions, the form of the relevant features is well defined by the parameters of the dynamical system. Further, we show that under some conditions, the feature space is spanned by the spike-triggered average and its successive order time derivatives.

On signals faint and sparse: The ACICA algorithm for blind de-trending of exoplanetary transits with low signal-to-noise

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

Waldmann, I. P., E-mail: ingo@star.ucl.ac.uk

2014-01-01

Independent component analysis (ICA) has recently been shown to be a promising new path in data analysis and de-trending of exoplanetary time series signals. Such approaches do not require or assume any prior or auxiliary knowledge about the data or instrument in order to de-convolve the astrophysical light curve signal from instrument or stellar systematic noise. These methods are often known as 'blind-source separation' (BSS) algorithms. Unfortunately, all BSS methods suffer from an amplitude and sign ambiguity of their de-convolved components, which severely limits these methods in low signal-to-noise (S/N) observations where their scalings cannot be determined otherwise. Here wemore » present a novel approach to calibrate ICA using sparse wavelet calibrators. The Amplitude Calibrated Independent Component Analysis (ACICA) allows for the direct retrieval of the independent components' scalings and the robust de-trending of low S/N data. Such an approach gives us an unique and unprecedented insight in the underlying morphology of a data set, which makes this method a powerful tool for exoplanetary data de-trending and signal diagnostics.« less

Some propulsion system noise data handling conventions and computer programs used at the Lewis Research Center

NASA Technical Reports Server (NTRS)

Montegani, F. J.

1974-01-01

Methods of handling one-third-octave band noise data originating from the outdoor full-scale fan noise facility and the engine acoustic facility at the Lewis Research Center are presented. Procedures for standardizing, retrieving, extrapolating, and reporting these data are explained. Computer programs are given which are used to accomplish these and other noise data analysis tasks. This information is useful as background for interpretation of data from these facilities appearing in NASA reports and can aid data exchange by promoting standardization.

Opportunities for Environmental Noise Mapping in Saudi Arabia: A Case of Traffic Noise Annoyance in an Urban Area in Jeddah City

PubMed Central

Zytoon, Mohamed A.

2016-01-01

As the traffic and other environmental noise generating activities are growing in The Kingdom of Saudi Arabia (KSA), adverse health and other impacts are expected to develop. The management of such problem involves many actions, of which noise mapping has been proven to be a helpful approach. The objective of the current study was to test the adequacy of the available data in KSA municipalities for generating urban noise maps and to verify the applicability of available environmental noise mapping and noise annoyance models for KSA. Therefore, noise maps were produced for Al-Fayha District in Jeddah City, KSA using commercially available noise mapping software and applying the French national computation method “NMPB” for traffic noise. Most of the data required for traffic noise prediction and annoyance analysis were available, either in the Municipality GIS department or in other governmental authorities. The predicted noise levels during the three time periods, i.e., daytime, evening, and nighttime, were found higher than the maximum recommended levels established in KSA environmental noise standards. Annoyance analysis revealed that high percentages of the District inhabitants were highly annoyed, depending on the type of planning zone and period of interest. These results reflect the urgent need to consider environmental noise reduction in KSA national plans. The accuracy of the predicted noise levels and the availability of most of the necessary data should encourage further studies on the use of noise mapping as part of noise reduction plans. PMID:27187438

Phase noise analysis of voltage controlled oscillator used in cesium atomic clock

NASA Astrophysics Data System (ADS)

Zhi, Menghui; Tang, Liang; Qiao, Donghai

2017-03-01

Coherent population trapping (CPT) cesium frequency standard plays a significant role in precision guidance of missile and global positioning system (GPS). Low noise 4.596 GHz voltage controlled oscillator (VCO) is an indispensable part of microwave signal source in cesium frequency standard. Low-phase noise is also the most important and difficult performance indicator of VCO. Starting from phase noise analysis method proposed by Leeson, the formulas about the relationship between phase noise of output signal of oscillator feedback model and phase fluctuation spectrum of amplifier, phase noise of oscillator are derived in this paper. Finally, the asymptote model of microwave oscillator is proposed based on the formula derivation. The experiment shows that when the reverse bias voltage of variode is 1.8 V, the designed oscillation frequency of VCO is 4.596 GHz, the power is -1 dBm and the DC power consumption is 19.6 mW. The tendency of phase noise simulation curve and actual test curve conform to asymptote model. The phase noise in 1 and 10 kHz is, respectively, -60.86 and -86.58 dBc/Hz. The significance of the paper lies in determining the main factors influencing oscillator phase noise and providing guiding direction for the design of low-phase noise VCO.

Fluctuation-Enhanced Sensing for Biological Agent Detection and Identification

DTIC Science & Technology

2009-01-01

method for bacterium detection published earlier; sensing and evaluating the odors of microbes ; and spectral and amplitude distribution analysis of noise...REPORT TYPE 3. DATES COVERED 00-00-2009 to 00-00-2009 4. TITLE AND SUBTITLE Fluctuation-Enhanced Sensing for Biological Agent Detection and...evaluating the odors of microbes ; and spectral and amplitude distribution analysis of noise in light scattering to identify spores based on their

Unsupervised seismic facies analysis with spatial constraints using regularized fuzzy c-means

NASA Astrophysics Data System (ADS)

Song, Chengyun; Liu, Zhining; Cai, Hanpeng; Wang, Yaojun; Li, Xingming; Hu, Guangmin

2017-12-01

Seismic facies analysis techniques combine classification algorithms and seismic attributes to generate a map that describes main reservoir heterogeneities. However, most of the current classification algorithms only view the seismic attributes as isolated data regardless of their spatial locations, and the resulting map is generally sensitive to noise. In this paper, a regularized fuzzy c-means (RegFCM) algorithm is used for unsupervised seismic facies analysis. Due to the regularized term of the RegFCM algorithm, the data whose adjacent locations belong to same classification will play a more important role in the iterative process than other data. Therefore, this method can reduce the effect of seismic data noise presented in discontinuous regions. The synthetic data with different signal/noise values are used to demonstrate the noise tolerance ability of the RegFCM algorithm. Meanwhile, the fuzzy factor, the neighbour window size and the regularized weight are tested using various values, to provide a reference of how to set these parameters. The new approach is also applied to a real seismic data set from the F3 block of the Netherlands. The results show improved spatial continuity, with clear facies boundaries and channel morphology, which reveals that the method is an effective seismic facies analysis tool.

Vibration and acoustic noise emitted by dry-type air-core reactors under PWM voltage excitation

NASA Astrophysics Data System (ADS)

Li, Jingsong; Wang, Shanming; Hong, Jianfeng; Yang, Zhanlu; Jiang, Shengqian; Xia, Shichong

2018-05-01

According to coupling way between the magnetic field and the structural order, structure mode is discussed by engaging finite element (FE) method and both natural frequency and modal shape for a dry-type air-core reactor (DAR) are obtained in this paper. On the basis of harmonic response analysis, electromagnetic force under PWM (Pulse Width Modulation) voltage excitation is mapped with the structure mesh, the vibration spectrum is gained and the consequences represents that the whole structure vibration predominates in the radial direction, with less axial vibration. Referring to the test standard of reactor noise, the rules of emitted noise of the DAR are measured and analyzed at chosen switching frequency matches the sample resonant frequency and the methods of active vibration and noise reduction are put forward. Finally, the low acoustic noise emission of a prototype DAR is verified by measurement.

High-order noise analysis for low dose iterative image reconstruction methods: ASIR, IRIS, and MBAI

NASA Astrophysics Data System (ADS)

Do, Synho; Singh, Sarabjeet; Kalra, Mannudeep K.; Karl, W. Clem; Brady, Thomas J.; Pien, Homer

2011-03-01

Iterative reconstruction techniques (IRTs) has been shown to suppress noise significantly in low dose CT imaging. However, medical doctors hesitate to accept this new technology because visual impression of IRT images are different from full-dose filtered back-projection (FBP) images. Most common noise measurements such as the mean and standard deviation of homogeneous region in the image that do not provide sufficient characterization of noise statistics when probability density function becomes non-Gaussian. In this study, we measure L-moments of intensity values of images acquired at 10% of normal dose and reconstructed by IRT methods of two state-of-art clinical scanners (i.e., GE HDCT and Siemens DSCT flash) by keeping dosage level identical to each other. The high- and low-dose scans (i.e., 10% of high dose) were acquired from each scanner and L-moments of noise patches were calculated for the comparison.

Consideration of some factors affecting low-frequency fuselage noise transmission for propeller aircraft

NASA Technical Reports Server (NTRS)

Mixson, J. S.; Roussos, L. A.

1986-01-01

Possible reasons for disagreement between measured and predicted trends of sidewall noise transmission at low frequency are investigated using simplified analysis methods. An analytical model combining incident plane acoustic waves with an infinite flat panel is used to study the effects of sound incidence angle, plate structural properties, frequency, absorption, and the difference between noise reduction and transmission loss. Analysis shows that these factors have significant effects on noise transmission but they do not account for the differences between measured and predicted trends at low frequencies. An analytical model combining an infinite flat plate with a normally incident acoustic wave having exponentially decaying magnitude along one coordinate is used to study the effect of a localized source distribution such as is associated with propeller noise. Results show that the localization brings the predicted low-frequency trend of noise transmission into better agreement with measured propeller results. This effect is independent of low-frequency stiffness effects that have been previously reported to be associated with boundary conditions.

A general procedure to generate models for urban environmental-noise pollution using feature selection and machine learning methods.

PubMed

Torija, Antonio J; Ruiz, Diego P

2015-02-01

The prediction of environmental noise in urban environments requires the solution of a complex and non-linear problem, since there are complex relationships among the multitude of variables involved in the characterization and modelling of environmental noise and environmental-noise magnitudes. Moreover, the inclusion of the great spatial heterogeneity characteristic of urban environments seems to be essential in order to achieve an accurate environmental-noise prediction in cities. This problem is addressed in this paper, where a procedure based on feature-selection techniques and machine-learning regression methods is proposed and applied to this environmental problem. Three machine-learning regression methods, which are considered very robust in solving non-linear problems, are used to estimate the energy-equivalent sound-pressure level descriptor (LAeq). These three methods are: (i) multilayer perceptron (MLP), (ii) sequential minimal optimisation (SMO), and (iii) Gaussian processes for regression (GPR). In addition, because of the high number of input variables involved in environmental-noise modelling and estimation in urban environments, which make LAeq prediction models quite complex and costly in terms of time and resources for application to real situations, three different techniques are used to approach feature selection or data reduction. The feature-selection techniques used are: (i) correlation-based feature-subset selection (CFS), (ii) wrapper for feature-subset selection (WFS), and the data reduction technique is principal-component analysis (PCA). The subsequent analysis leads to a proposal of different schemes, depending on the needs regarding data collection and accuracy. The use of WFS as the feature-selection technique with the implementation of SMO or GPR as regression algorithm provides the best LAeq estimation (R(2)=0.94 and mean absolute error (MAE)=1.14-1.16 dB(A)). Copyright © 2014 Elsevier B.V. All rights reserved.

Estimation of background noise level on seismic station using statistical analysis for improved analysis accuracy

NASA Astrophysics Data System (ADS)

Han, S. M.; Hahm, I.

2015-12-01

We evaluated the background noise level of seismic stations in order to collect the observation data of high quality and produce accurate seismic information. Determining of the background noise level was used PSD (Power Spectral Density) method by McNamara and Buland (2004) in this study. This method that used long-term data is influenced by not only innate electronic noise of sensor and a pulse wave resulting from stabilizing but also missing data and controlled by the specified frequency which is affected by the irregular signals without site characteristics. It is hard and inefficient to implement process that filters out the abnormal signal within the automated system. To solve these problems, we devised a method for extracting the data which normally distributed with 90 to 99% confidence intervals at each period. The availability of the method was verified using 62-seismic stations with broadband and short-period sensors operated by the KMA (Korea Meteorological Administration). Evaluation standards were NHNM (New High Noise Model) and NLNM (New Low Noise Model) published by the USGS (United States Geological Survey). It was designed based on the western United States. However, Korean Peninsula surrounded by the ocean on three sides has a complicated geological structure and a high population density. So, we re-designed an appropriate model in Korean peninsula by statistically combined result. The important feature is that secondary-microseism peak appeared at a higher frequency band. Acknowledgements: This research was carried out as a part of "Research for the Meteorological and Earthquake Observation Technology and Its Application" supported by the 2015 National Institute of Meteorological Research (NIMR) in the Korea Meteorological Administration.

Validation of finite element and boundary element methods for predicting structural vibration and radiated noise

NASA Technical Reports Server (NTRS)

Seybert, A. F.; Wu, X. F.; Oswald, Fred B.

1992-01-01

Analytical and experimental validation of methods to predict structural vibration and radiated noise are presented. A rectangular box excited by a mechanical shaker was used as a vibrating structure. Combined finite element method (FEM) and boundary element method (BEM) models of the apparatus were used to predict the noise radiated from the box. The FEM was used to predict the vibration, and the surface vibration was used as input to the BEM to predict the sound intensity and sound power. Vibration predicted by the FEM model was validated by experimental modal analysis. Noise predicted by the BEM was validated by sound intensity measurements. Three types of results are presented for the total radiated sound power: (1) sound power predicted by the BEM modeling using vibration data measured on the surface of the box; (2) sound power predicted by the FEM/BEM model; and (3) sound power measured by a sound intensity scan. The sound power predicted from the BEM model using measured vibration data yields an excellent prediction of radiated noise. The sound power predicted by the combined FEM/BEM model also gives a good prediction of radiated noise except for a shift of the natural frequencies that are due to limitations in the FEM model.

Spectral reconstruction analysis for enhancing signal-to-noise in time-resolved spectroscopies

NASA Astrophysics Data System (ADS)

Wilhelm, Michael J.; Smith, Jonathan M.; Dai, Hai-Lung

2015-09-01

We demonstrate a new spectral analysis for the enhancement of the signal-to-noise ratio (SNR) in time-resolved spectroscopies. Unlike the simple linear average which produces a single representative spectrum with enhanced SNR, this Spectral Reconstruction analysis (SRa) improves the SNR (by a factor of ca. 0 . 6 √{ n } ) for all n experimentally recorded time-resolved spectra. SRa operates by eliminating noise in the temporal domain, thereby attenuating noise in the spectral domain, as follows: Temporal profiles at each measured frequency are fit to a generic mathematical function that best represents the temporal evolution; spectra at each time are then reconstructed with data points from the fitted profiles. The SRa method is validated with simulated control spectral data sets. Finally, we apply SRa to two distinct experimentally measured sets of time-resolved IR emission spectra: (1) UV photolysis of carbonyl cyanide and (2) UV photolysis of vinyl cyanide.

Vibration and noise analysis of a gear transmission system

NASA Technical Reports Server (NTRS)

Choy, F. K.; Qian, W.; Zakrajsek, J. J.; Oswald, F. B.

1993-01-01

This paper presents a comprehensive procedure to predict both the vibration and noise generated by a gear transmission system under normal operating conditions. The gearbox vibrations were obtained from both numerical simulation and experimental studies using a gear noise test rig. In addition, the noise generated by the gearbox vibrations was recorded during the experimental testing. A numerical method was used to develop linear relationships between the gearbox vibration and the generated noise. The hypercoherence function is introduced to correlate the nonlinear relationship between the fundamental noise frequency and its harmonics. A numerical procedure was developed using both the linear and nonlinear relationships generated from the experimental data to predict noise resulting from the gearbox vibrations. The application of this methodology is demonstrated by comparing the numerical and experimental results from the gear noise test rig.

On the Performance of T2∗ Correction Methods for Quantification of Hepatic Fat Content

PubMed Central

Reeder, Scott B.; Bice, Emily K.; Yu, Huanzhou; Hernando, Diego; Pineda, Angel R.

2014-01-01

Nonalcoholic fatty liver disease is the most prevalent chronic liver disease in Western societies. MRI can quantify liver fat, the hallmark feature of nonalcoholic fatty liver disease, so long as multiple confounding factors including T2∗ decay are addressed. Recently developed MRI methods that correct for T2∗ to improve the accuracy of fat quantification either assume a common T2∗ (single- T2∗) for better stability and noise performance or independently estimate the T2∗ for water and fat (dual- T2∗) for reduced bias, but with noise performance penalty. In this study, the tradeoff between bias and variance for different T2∗ correction methods is analyzed using the Cramér-Rao bound analysis for biased estimators and is validated using Monte Carlo experiments. A noise performance metric for estimation of fat fraction is proposed. Cramér-Rao bound analysis for biased estimators was used to compute the metric at different echo combinations. Optimization was performed for six echoes and typical T2∗ values. This analysis showed that all methods have better noise performance with very short first echo times and echo spacing of ∼π/2 for single- T2∗ correction, and ∼2π/3 for dual- T2∗ correction. Interestingly, when an echo spacing and first echo shift of ∼π/2 are used, methods without T2∗ correction have less than 5% bias in the estimates of fat fraction. PMID:21661045

On the Uncertainty in Single Molecule Fluorescent Lifetime and Energy Emission Measurements

NASA Technical Reports Server (NTRS)

Brown, Emery N.; Zhang, Zhenhua; McCollom, Alex D.

1996-01-01

Time-correlated single photon counting has recently been combined with mode-locked picosecond pulsed excitation to measure the fluorescent lifetimes and energy emissions of single molecules in a flow stream. Maximum likelihood (ML) and least squares methods agree and are optimal when the number of detected photons is large, however, in single molecule fluorescence experiments the number of detected photons can be less than 20, 67 percent of those can be noise, and the detection time is restricted to 10 nanoseconds. Under the assumption that the photon signal and background noise are two independent inhomogeneous Poisson processes, we derive the exact joint arrival time probability density of the photons collected in a single counting experiment performed in the presence of background noise. The model obviates the need to bin experimental data for analysis, and makes it possible to analyze formally the effect of background noise on the photon detection experiment using both ML or Bayesian methods. For both methods we derive the joint and marginal probability densities of the fluorescent lifetime and fluorescent emission. The ML and Bayesian methods are compared in an analysis of simulated single molecule fluorescence experiments of Rhodamine 110 using different combinations of expected background noise and expected fluorescence emission. While both the ML or Bayesian procedures perform well for analyzing fluorescence emissions, the Bayesian methods provide more realistic measures of uncertainty in the fluorescent lifetimes. The Bayesian methods would be especially useful for measuring uncertainty in fluorescent lifetime estimates in current single molecule flow stream experiments where the expected fluorescence emission is low. Both the ML and Bayesian algorithms can be automated for applications in molecular biology.

A novel transmitter IQ imbalance and phase noise suppression method utilizing pilots in PDM CO-OFDM system

NASA Astrophysics Data System (ADS)

Zhang, Haoyuan; Ma, Xiurong; Li, Pengru

2018-04-01

In this paper, we develop a novel pilot structure to suppress transmitter in-phase and quadrature (Tx IQ) imbalance, phase noise and channel distortion for polarization division multiplexed (PDM) coherent optical orthogonal frequency division multiplexing (CO-OFDM) systems. Compared with the conventional approach, our method not only significantly improves the system tolerance of IQ imbalance as well as phase noise, but also provides higher transmission speed. Numerical simulations of PDM CO-OFDM system is used to validate the theoretical analysis under the simulation conditions: the amplitude mismatch 3 dB, the phase mismatch 15°, the transmission bit rate 100 Gb/s and 560 km standard signal-mode fiber transmission. Moreover, the proposed method is 63% less complex than the compared method.

Evaluation of an urban traffic Noise-Exposed population based on points of interest and noise maps: The case of Guangzhou.

PubMed

Wang, Haibo; Chen, Hanjie; Cai, Ming

2018-08-01

The primary objective of this study was to develop an evaluation method for assessing an urban traffic noise-exposed population and apply it in the main urban area of Guangzhou. The method based on points of interest (POIs) and noise map is realized in several steps. First, after regionalizing based on road networks and executing a cluster analysis for regions according to the properties of POIs, the environmental noise functional regions (NFRs) of the urban area are presented. Then, surrounding POIs are used to infer the type of buildings, and according to the attraction of different building types and the whole population of the region, the population distribution at the building level is calculated. Finally, with the help of a noise map, an evaluation method for assessing an urban traffic noise-exposed population is proposed. The method is applied in the main urban area of Guangzhou, and the results reveal the followings. 1) At daytime and nighttime, 23.63% and 30.53% of the population, respectively, experience noise levels that exceed the noise standards. The per capita noise exposure value at daytime and nighttime is 0.9 dB and 2.0 dB, respectively. 2) The percentages of the exposed population of Yuexiu District were 28.89% at daytime and 35.65% at nighttime, which are the largest, followed by the exposed population percentages of Liwan, Haizhu, and Tianhe Districts. 3) From the view of different classes of NFRs, the percentages of the exposed population of Class 1 and Class 4 are larger than the percentages of the exposed population from the other classes, especially at nighttime (48.24% of Class 1 and 40.79% of Class 4). 4) Although there are masses of people affected by traffic noise, a large percentage of them (85%) experience not more than 5 dB of traffic noise superscale. Copyright © 2018 Elsevier Ltd. All rights reserved.

Efficient thermal noise removal of Sentinel-1 image and its impacts on sea ice applications

NASA Astrophysics Data System (ADS)

Park, Jeong-Won; Korosov, Anton; Babiker, Mohamed

2017-04-01

Wide swath SAR observation from several spaceborne SAR missions played an important role in studying sea ice in the polar region. Sentinel 1A and 1B are producing dual-polarization observation data with the highest temporal resolution ever. For a proper use of dense time-series, radiometric properties must be qualified. Thermal noise is often neglected in many sea ice applications, but is impacting seriously the utility of dual-polarization SAR data. Sentinel-1 TOPSAR image intensity is disturbed by additive thermal noise particularly in cross-polarization channel. Although ESA provides calibrated noise vectors for noise power subtraction, residual noise contribution is significant considering relatively narrow backscattering distribution of cross-polarization channel. In this study, we investigate the noise characteristics and propose an efficient method for noise reduction based on three types of correction: azimuth de-scalloping, noise scaling, and inter-swath power balancing. The core idea is to find optimum correction coefficients resulting in the most noise-uncorrelated gentle backscatter profile over homogeneous region and to combine them with scalloping gain for reconstruction of complete two-dimensional noise field. Denoising is accomplished by subtracting the reconstructed noise field from the original image. The resulting correction coefficients determined by extensive experiments showed different noise characteristics for different Instrument Processing Facility (IPF) versions of Level 1 product generation. Even after thermal noise subtraction, the image still suffers from residual noise, which distorts local statistics. Since this residual noise depends on local signal-to-noise ratio, it can be compensated by variance normalization with coefficients determined from an empirical model. Denoising improved not only visual interpretability but also performances in SAR intensity-based sea ice applications. Results from two applications showed the effectiveness of the proposed method: feature tracking based sea ice drift and texture analysis based sea ice classification. For feature tracking, large spatial asymmetry of keypoint distribution caused by higher noise level in the nearest subswath was decresed so that the matched features to be selected evenly in space. For texture analysis, inter-subswath texture differences caused by different noise equivalent sigma zero were normalized so that the texture features estimated in any subswath have similar value with those in other subswaths.

Noise correlation in PET, CT, SPECT and PET/CT data evaluated using autocorrelation function: a phantom study on data, reconstructed using FBP and OSEM.

PubMed

Razifar, Pasha; Sandström, Mattias; Schnieder, Harald; Långström, Bengt; Maripuu, Enn; Bengtsson, Ewert; Bergström, Mats

2005-08-25

Positron Emission Tomography (PET), Computed Tomography (CT), PET/CT and Single Photon Emission Tomography (SPECT) are non-invasive imaging tools used for creating two dimensional (2D) cross section images of three dimensional (3D) objects. PET and SPECT have the potential of providing functional or biochemical information by measuring distribution and kinetics of radiolabelled molecules, whereas CT visualizes X-ray density in tissues in the body. PET/CT provides fused images representing both functional and anatomical information with better precision in localization than PET alone. Images generated by these types of techniques are generally noisy, thereby impairing the imaging potential and affecting the precision in quantitative values derived from the images. It is crucial to explore and understand the properties of noise in these imaging techniques. Here we used autocorrelation function (ACF) specifically to describe noise correlation and its non-isotropic behaviour in experimentally generated images of PET, CT, PET/CT and SPECT. Experiments were performed using phantoms with different shapes. In PET and PET/CT studies, data were acquired in 2D acquisition mode and reconstructed by both analytical filter back projection (FBP) and iterative, ordered subsets expectation maximisation (OSEM) methods. In the PET/CT studies, different magnitudes of X-ray dose in the transmission were employed by using different mA settings for the X-ray tube. In the CT studies, data were acquired using different slice thickness with and without applied dose reduction function and the images were reconstructed by FBP. SPECT studies were performed in 2D, reconstructed using FBP and OSEM, using post 3D filtering. ACF images were generated from the primary images, and profiles across the ACF images were used to describe the noise correlation in different directions. The variance of noise across the images was visualised as images and with profiles across these images. The most important finding was that the pattern of noise correlation is rotation symmetric or isotropic, independent of object shape in PET and PET/CT images reconstructed using the iterative method. This is, however, not the case in FBP images when the shape of phantom is not circular. Also CT images reconstructed using FBP show the same non-isotropic pattern independent of slice thickness and utilization of care dose function. SPECT images show an isotropic correlation of the noise independent of object shape or applied reconstruction algorithm. Noise in PET/CT images was identical independent of the applied X-ray dose in the transmission part (CT), indicating that the noise from transmission with the applied doses does not propagate into the PET images showing that the noise from the emission part is dominant. The results indicate that in human studies it is possible to utilize a low dose in transmission part while maintaining the noise behaviour and the quality of the images. The combined effect of noise correlation for asymmetric objects and a varying noise variance across the image field significantly complicates the interpretation of the images when statistical methods are used, such as with statistical estimates of precision in average values, use of statistical parametric mapping methods and principal component analysis. Hence it is recommended that iterative reconstruction methods are used for such applications. However, it is possible to calculate the noise analytically in images reconstructed by FBP, while it is not possible to do the same calculation in images reconstructed by iterative methods. Therefore for performing statistical methods of analysis which depend on knowing the noise, FBP would be preferred.

SNDR Limits of Oscillator-Based Sensor Readout Circuits.

PubMed

Cardes, Fernando; Quintero, Andres; Gutierrez, Eric; Buffa, Cesare; Wiesbauer, Andreas; Hernandez, Luis

2018-02-03

This paper analyzes the influence of phase noise and distortion on the performance of oscillator-based sensor data acquisition systems. Circuit noise inherent to the oscillator circuit manifests as phase noise and limits the SNR. Moreover, oscillator nonlinearity generates distortion for large input signals. Phase noise analysis of oscillators is well known in the literature, but the relationship between phase noise and the SNR of an oscillator-based sensor is not straightforward. This paper proposes a model to estimate the influence of phase noise in the performance of an oscillator-based system by reflecting the phase noise to the oscillator input. The proposed model is based on periodic steady-state analysis tools to predict the SNR of the oscillator. The accuracy of this model has been validated by both simulation and experiment in a 130 nm CMOS prototype. We also propose a method to estimate the SNDR and the dynamic range of an oscillator-based readout circuit that improves by more than one order of magnitude the simulation time compared to standard time domain simulations. This speed up enables the optimization and verification of this kind of systems with iterative algorithms.

Optimized signal detection and analysis methods for in vivo photoacoustic flow cytometry

NASA Astrophysics Data System (ADS)

Wang, Qiyan; Zhou, Quanyu; Yang, Ping; Wang, Xiaoling; Niu, Zhenyu; Suo, Yuanzhen; He, Hao; Gao, Wenyuan; Tang, Shuo; Wei, Xunbin

2017-02-01

Melanoma is known as a malignant tumor of melanocytes, which usually appear in the blood circulation at the metastasis stage of cancer. Thus the detection of circulating melanoma cells is useful for early diagnosis and therapy of cancer. Here we have developed an in vivo photoacoustic flow cytometry (PAFC) based on the photoacoustic effect to detect melanoma cells. However, the raw signals we obtain from the target cells contain noises such as environmental sonic noises and electronic noises. Therefore we apply correlation comparison and feature separation methods to the detection and verification of the in vivo signals. Due to similar shape and structure of cells, the photoacoustic signals usually have similar vibration mode. By analyzing the correlations and the signal features in time domain and frequency domain, we are able to provide a method for separating photoacoustic signals generated by target cells from background noises. The method introduced here has proved to optimize the signal acquisition and signal processing, which can improve the detection accuracy in PAFC.

Acoustic methodology review

NASA Technical Reports Server (NTRS)

Schlegel, R. G.

1982-01-01

It is important for industry and NASA to assess the status of acoustic design technology for predicting and controlling helicopter external noise in order for a meaningful research program to be formulated which will address this problem. The prediction methodologies available to the designer and the acoustic engineer are three-fold. First is what has been described as a first principle analysis. This analysis approach attempts to remove any empiricism from the analysis process and deals with a theoretical mechanism approach to predicting the noise. The second approach attempts to combine first principle methodology (when available) with empirical data to formulate source predictors which can be combined to predict vehicle levels. The third is an empirical analysis, which attempts to generalize measured trends into a vehicle noise prediction method. This paper will briefly address each.

An image-processing method to detect sub-optical features based on understanding noise in intensity measurements.

PubMed

Bhatia, Tripta

2018-07-01

Accurate quantitative analysis of image data requires that we distinguish between fluorescence intensity (true signal) and the noise inherent to its measurements to the extent possible. We image multilamellar membrane tubes and beads that grow from defects in the fluid lamellar phase of the lipid 1,2-dioleoyl-sn-glycero-3-phosphocholine dissolved in water and water-glycerol mixtures by using fluorescence confocal polarizing microscope. We quantify image noise and determine the noise statistics. Understanding the nature of image noise also helps in optimizing image processing to detect sub-optical features, which would otherwise remain hidden. We use an image-processing technique "optimum smoothening" to improve the signal-to-noise ratio of features of interest without smearing their structural details. A high SNR renders desired positional accuracy with which it is possible to resolve features of interest with width below optical resolution. Using optimum smoothening, the smallest and the largest core diameter detected is of width [Formula: see text] and [Formula: see text] nm, respectively, discussed in this paper. The image-processing and analysis techniques and the noise modeling discussed in this paper can be used for detailed morphological analysis of features down to sub-optical length scales that are obtained by any kind of fluorescence intensity imaging in the raster mode.

A direct method for calculating instrument noise levels in side-by-side seismometer evaluations

USGS Publications Warehouse

Holcomb, L. Gary

1989-01-01

The subject of determining the inherent system noise levels present in modem broadband closed loop seismic sensors has been an evolving topic ever since closed loop systems became available. Closed loop systems are unique in that the system noise can not be determined via a blocked mass test as in older conventional open loop seismic sensors. Instead, most investigators have resorted to performing measurements on two or more systems operating in close proximity to one another and to analyzing the outputs of these systems with respect to one another to ascertain their relative noise levels.The analysis of side-by-side relative performance is inherently dependent on the accuracy of the mathematical modeling of the test configuration. This report presents a direct approach to extracting the system noise levels of two linear systems with a common coherent input signal. The mathematical solution to the problem is incredibly simple; however the practical application of the method encounters some difficulties. Examples of expected accuracies are presented as derived by simulating real systems performance using computer generated random noise. In addition, examples of the performance of the method when applied to real experimental test data are shown.

Spatio-temporal diffusion of dynamic PET images

NASA Astrophysics Data System (ADS)

Tauber, C.; Stute, S.; Chau, M.; Spiteri, P.; Chalon, S.; Guilloteau, D.; Buvat, I.

2011-10-01

Positron emission tomography (PET) images are corrupted by noise. This is especially true in dynamic PET imaging where short frames are required to capture the peak of activity concentration after the radiotracer injection. High noise results in a possible bias in quantification, as the compartmental models used to estimate the kinetic parameters are sensitive to noise. This paper describes a new post-reconstruction filter to increase the signal-to-noise ratio in dynamic PET imaging. It consists in a spatio-temporal robust diffusion of the 4D image based on the time activity curve (TAC) in each voxel. It reduces the noise in homogeneous areas while preserving the distinct kinetics in regions of interest corresponding to different underlying physiological processes. Neither anatomical priors nor the kinetic model are required. We propose an automatic selection of the scale parameter involved in the diffusion process based on a robust statistical analysis of the distances between TACs. The method is evaluated using Monte Carlo simulations of brain activity distributions. We demonstrate the usefulness of the method and its superior performance over two other post-reconstruction spatial and temporal filters. Our simulations suggest that the proposed method can be used to significantly increase the signal-to-noise ratio in dynamic PET imaging.

A semi-learning algorithm for noise rejection: an fNIRS study on ADHD children

NASA Astrophysics Data System (ADS)

Sutoko, Stephanie; Funane, Tsukasa; Katura, Takusige; Sato, Hiroki; Kiguchi, Masashi; Maki, Atsushi; Monden, Yukifumi; Nagashima, Masako; Yamagata, Takanori; Dan, Ippeita

2017-02-01

In pediatrics studies, the quality of functional near infrared spectroscopy (fNIRS) signals is often reduced by motion artifacts. These artifacts likely mislead brain functionality analysis, causing false discoveries. While noise correction methods and their performance have been investigated, these methods require several parameter assumptions that apparently result in noise overfitting. In contrast, the rejection of noisy signals serves as a preferable method because it maintains the originality of the signal waveform. Here, we describe a semi-learning algorithm to detect and eliminate noisy signals. The algorithm dynamically adjusts noise detection according to the predetermined noise criteria, which are spikes, unusual activation values (averaged amplitude signals within the brain activation period), and high activation variances (among trials). Criteria were sequentially organized in the algorithm and orderly assessed signals based on each criterion. By initially setting an acceptable rejection rate, particular criteria causing excessive data rejections are neglected, whereas others with tolerable rejections practically eliminate noises. fNIRS data measured during the attention response paradigm (oddball task) in children with attention deficit/hyperactivity disorder (ADHD) were utilized to evaluate and optimize the algorithm's performance. This algorithm successfully substituted the visual noise identification done in the previous studies and consistently found significantly lower activation of the right prefrontal and parietal cortices in ADHD patients than in typical developing children. Thus, we conclude that the semi-learning algorithm confers more objective and standardized judgment for noise rejection and presents a promising alternative to visual noise rejection

Accuracy Maximization Analysis for Sensory-Perceptual Tasks: Computational Improvements, Filter Robustness, and Coding Advantages for Scaled Additive Noise

PubMed Central

Burge, Johannes

2017-01-01

Accuracy Maximization Analysis (AMA) is a recently developed Bayesian ideal observer method for task-specific dimensionality reduction. Given a training set of proximal stimuli (e.g. retinal images), a response noise model, and a cost function, AMA returns the filters (i.e. receptive fields) that extract the most useful stimulus features for estimating a user-specified latent variable from those stimuli. Here, we first contribute two technical advances that significantly reduce AMA’s compute time: we derive gradients of cost functions for which two popular estimators are appropriate, and we implement a stochastic gradient descent (AMA-SGD) routine for filter learning. Next, we show how the method can be used to simultaneously probe the impact on neural encoding of natural stimulus variability, the prior over the latent variable, noise power, and the choice of cost function. Then, we examine the geometry of AMA’s unique combination of properties that distinguish it from better-known statistical methods. Using binocular disparity estimation as a concrete test case, we develop insights that have general implications for understanding neural encoding and decoding in a broad class of fundamental sensory-perceptual tasks connected to the energy model. Specifically, we find that non-orthogonal (partially redundant) filters with scaled additive noise tend to outperform orthogonal filters with constant additive noise; non-orthogonal filters and scaled additive noise can interact to sculpt noise-induced stimulus encoding uncertainty to match task-irrelevant stimulus variability. Thus, we show that some properties of neural response thought to be biophysical nuisances can confer coding advantages to neural systems. Finally, we speculate that, if repurposed for the problem of neural systems identification, AMA may be able to overcome a fundamental limitation of standard subunit model estimation. As natural stimuli become more widely used in the study of psychophysical and neurophysiological performance, we expect that task-specific methods for feature learning like AMA will become increasingly important. PMID:28178266

Method of calibrating an interferometer and reducing its systematic noise

NASA Technical Reports Server (NTRS)

Hammer, Philip D. (Inventor)

1997-01-01

Methods of operation and data analysis for an interferometer so as to eliminate the errors contributed by non-responsive or unstable pixels, interpixel gain variations that drift over time, and spurious noise that would otherwise degrade the operation of the interferometer are disclosed. The methods provide for either online or post-processing calibration. The methods apply prescribed reversible transformations that exploit the physical properties of interferograms obtained from said interferometer to derive a calibration reference signal for subsequent treatment of said interferograms for interpixel gain variations. A self-consistent approach for treating bad pixels is incorporated into the methods.

3D seismic data de-noising and reconstruction using Multichannel Time Slice Singular Spectrum Analysis

NASA Astrophysics Data System (ADS)

Rekapalli, Rajesh; Tiwari, R. K.; Sen, Mrinal K.; Vedanti, Nimisha

2017-05-01

Noises and data gaps complicate the seismic data processing and subsequently cause difficulties in the geological interpretation. We discuss a recent development and application of the Multi-channel Time Slice Singular Spectrum Analysis (MTSSSA) for 3D seismic data de-noising in time domain. In addition, L1 norm based simultaneous data gap filling of 3D seismic data using MTSSSA also discussed. We discriminated the noises from single individual time slices of 3D volumes by analyzing Eigen triplets of the trajectory matrix. We first tested the efficacy of the method on 3D synthetic seismic data contaminated with noise and then applied to the post stack seismic reflection data acquired from the Sleipner CO2 storage site (pre and post CO2 injection) from Norway. Our analysis suggests that the MTSSSA algorithm is efficient to enhance the S/N for better identification of amplitude anomalies along with simultaneous data gap filling. The bright spots identified in the de-noised data indicate upward migration of CO2 towards the top of the Utsira formation. The reflections identified applying MTSSSA to pre and post injection data correlate well with the geology of the Southern Viking Graben (SVG).

Statistical model based iterative reconstruction (MBIR) in clinical CT systems: Experimental assessment of noise performance

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

Li, Ke; Tang, Jie; Chen, Guang-Hong, E-mail: gchen7@wisc.edu

Purpose: To reduce radiation dose in CT imaging, the statistical model based iterative reconstruction (MBIR) method has been introduced for clinical use. Based on the principle of MBIR and its nonlinear nature, the noise performance of MBIR is expected to be different from that of the well-understood filtered backprojection (FBP) reconstruction method. The purpose of this work is to experimentally assess the unique noise characteristics of MBIR using a state-of-the-art clinical CT system. Methods: Three physical phantoms, including a water cylinder and two pediatric head phantoms, were scanned in axial scanning mode using a 64-slice CT scanner (Discovery CT750 HD,more » GE Healthcare, Waukesha, WI) at seven different mAs levels (5, 12.5, 25, 50, 100, 200, 300). At each mAs level, each phantom was repeatedly scanned 50 times to generate an image ensemble for noise analysis. Both the FBP method with a standard kernel and the MBIR method (Veo{sup ®}, GE Healthcare, Waukesha, WI) were used for CT image reconstruction. Three-dimensional (3D) noise power spectrum (NPS), two-dimensional (2D) NPS, and zero-dimensional NPS (noise variance) were assessed both globally and locally. Noise magnitude, noise spatial correlation, noise spatial uniformity and their dose dependence were examined for the two reconstruction methods. Results: (1) At each dose level and at each frequency, the magnitude of the NPS of MBIR was smaller than that of FBP. (2) While the shape of the NPS of FBP was dose-independent, the shape of the NPS of MBIR was strongly dose-dependent; lower dose lead to a “redder” NPS with a lower mean frequency value. (3) The noise standard deviation (σ) of MBIR and dose were found to be related through a power law of σ ∝ (dose){sup −β} with the component β ≈ 0.25, which violated the classical σ ∝ (dose){sup −0.5} power law in FBP. (4) With MBIR, noise reduction was most prominent for thin image slices. (5) MBIR lead to better noise spatial uniformity when compared with FBP. (6) A composite image generated from two MBIR images acquired at two different dose levels (D1 and D2) demonstrated lower noise than that of an image acquired at a dose level of D1+D2. Conclusions: The noise characteristics of the MBIR method are significantly different from those of the FBP method. The well known tradeoff relationship between CT image noise and radiation dose has been modified by MBIR to establish a more gradual dependence of noise on dose. Additionally, some other CT noise properties that had been well understood based on the linear system theory have also been altered by MBIR. Clinical CT scan protocols that had been optimized based on the classical CT noise properties need to be carefully re-evaluated for systems equipped with MBIR in order to maximize the method's potential clinical benefits in dose reduction and/or in CT image quality improvement.« less

Characterizing noise in nonhuman vocalizations: Acoustic analysis and human perception of barks by coyotes and dogs

NASA Astrophysics Data System (ADS)

Riede, Tobias; Mitchell, Brian R.; Tokuda, Isao; Owren, Michael J.

2005-07-01

Measuring noise as a component of mammalian vocalizations is of interest because of its potential relevance to the communicative function. However, methods for characterizing and quantifying noise are less well established than methods applicable to harmonically structured aspects of signals. Using barks of coyotes and domestic dogs, we compared six acoustic measures and studied how they are related to human perception of noisiness. Measures of harmonic-to-noise-ratio (HNR), percent voicing, and shimmer were found to be the best predictors of perceptual rating by human listeners. Both acoustics and perception indicated that noisiness was similar across coyote and dog barks, but within each species there was significant variation among the individual vocalizers. The advantages and disadvantages of the various measures are discussed.

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.

A Comparison of Two Balance Calibration Model Building Methods

NASA Technical Reports Server (NTRS)

DeLoach, Richard; Ulbrich, Norbert

2007-01-01

Simulated strain-gage balance calibration data is used to compare the accuracy of two balance calibration model building methods for different noise environments and calibration experiment designs. The first building method obtains a math model for the analysis of balance calibration data after applying a candidate math model search algorithm to the calibration data set. The second building method uses stepwise regression analysis in order to construct a model for the analysis. Four balance calibration data sets were simulated in order to compare the accuracy of the two math model building methods. The simulated data sets were prepared using the traditional One Factor At a Time (OFAT) technique and the Modern Design of Experiments (MDOE) approach. Random and systematic errors were introduced in the simulated calibration data sets in order to study their influence on the math model building methods. Residuals of the fitted calibration responses and other statistical metrics were compared in order to evaluate the calibration models developed with different combinations of noise environment, experiment design, and model building method. Overall, predicted math models and residuals of both math model building methods show very good agreement. Significant differences in model quality were attributable to noise environment, experiment design, and their interaction. Generally, the addition of systematic error significantly degraded the quality of calibration models developed from OFAT data by either method, but MDOE experiment designs were more robust with respect to the introduction of a systematic component of the unexplained variance.

A full-spectrum analysis of high-speed train interior noise under multi-physical-field coupling excitations

NASA Astrophysics Data System (ADS)

Zheng, Xu; Hao, Zhiyong; Wang, Xu; Mao, Jie

2016-06-01

High-speed-railway-train interior noise at low, medium, and high frequencies could be simulated by finite element analysis (FEA) or boundary element analysis (BEA), hybrid finite element analysis-statistical energy analysis (FEA-SEA) and statistical energy analysis (SEA), respectively. First, a new method named statistical acoustic energy flow (SAEF) is proposed, which can be applied to the full-spectrum HST interior noise simulation (including low, medium, and high frequencies) with only one model. In an SAEF model, the corresponding multi-physical-field coupling excitations are firstly fully considered and coupled to excite the interior noise. The interior noise attenuated by sound insulation panels of carriage is simulated through modeling the inflow acoustic energy from the exterior excitations into the interior acoustic cavities. Rigid multi-body dynamics, fast multi-pole BEA, and large-eddy simulation with indirect boundary element analysis are first employed to extract the multi-physical-field excitations, which include the wheel-rail interaction forces/secondary suspension forces, the wheel-rail rolling noise, and aerodynamic noise, respectively. All the peak values and their frequency bands of the simulated acoustic excitations are validated with those from the noise source identification test. Besides, the measured equipment noise inside equipment compartment is used as one of the excitation sources which contribute to the interior noise. Second, a full-trimmed FE carriage model is firstly constructed, and the simulated modal shapes and frequencies agree well with the measured ones, which has validated the global FE carriage model as well as the local FE models of the aluminum alloy-trim composite panel. Thus, the sound transmission loss model of any composite panel has indirectly been validated. Finally, the SAEF model of the carriage is constructed based on the accurate FE model and stimulated by the multi-physical-field excitations. The results show that the trend of the simulated 1/3 octave band sound pressure spectrum agrees well with that of the on-site-measured one. The deviation between the simulated and measured overall sound pressure level (SPL) is 2.6 dB(A) and well controlled below the engineering tolerance limit, which has validated the SAEF model in the full-spectrum analysis of the high speed train interior noise.

Analysis on spectra of hydroacoustic field in sonar cavity of the sandwich elastic wall structure

NASA Astrophysics Data System (ADS)

Xuetao, W.; Rui, H.; Weike, W.

2017-09-01

In this paper, the characteristics of the mechanical self - noise in sonar array cavity are studied by using the elastic flatbed - filled rectangular cavity parameterization model. Firstly, the analytic derivation of the vibration differential equation of the single layer, sandwich elastic wall plate structure and internal fluid coupling is carried out, and the modal method is used to solve it. Finally, the spectral characteristics of the acoustic field of rectangular cavity of different elastic wallboard materials are simulated and analyzed, which provides a theoretical reference for the prediction and control of sonar mechanical self-noise. In this paper, the sandwich board as control inside the dome background noise of a potential means were discussed, the dome background noise of qualitative prediction analysis and control has important theoretical significance.

Digital Signal Processing Methods for Ultrasonic Echoes.

PubMed

Sinding, Kyle; Drapaca, Corina; Tittmann, Bernhard

2016-04-28

Digital signal processing has become an important component of data analysis needed in industrial applications. In particular, for ultrasonic thickness measurements the signal to noise ratio plays a major role in the accurate calculation of the arrival time. For this application a band pass filter is not sufficient since the noise level cannot be significantly decreased such that a reliable thickness measurement can be performed. This paper demonstrates the abilities of two regularization methods - total variation and Tikhonov - to filter acoustic and ultrasonic signals. Both of these methods are compared to a frequency based filtering for digitally produced signals as well as signals produced by ultrasonic transducers. This paper demonstrates the ability of the total variation and Tikhonov filters to accurately recover signals from noisy acoustic signals faster than a band pass filter. Furthermore, the total variation filter has been shown to reduce the noise of a signal significantly for signals with clear ultrasonic echoes. Signal to noise ratios have been increased over 400% by using a simple parameter optimization. While frequency based filtering is efficient for specific applications, this paper shows that the reduction of noise in ultrasonic systems can be much more efficient with regularization methods.

Application of the Radon-FCL approach to seismic random noise suppression and signal preservation

NASA Astrophysics Data System (ADS)

Meng, Fanlei; Li, Yue; Liu, Yanping; Tian, Yanan; Wu, Ning

2016-08-01

The fractal conservation law (FCL) is a linear partial differential equation that is modified by an anti-diffusive term of lower order. The analysis indicated that this algorithm could eliminate high frequencies and preserve or amplify low/medium-frequencies. Thus, this method is quite suitable for the simultaneous noise suppression and enhancement or preservation of seismic signals. However, the conventional FCL filters seismic data only along the time direction, thereby ignoring the spatial coherence between neighbouring traces, which leads to the loss of directional information. Therefore, we consider the development of the conventional FCL into the time-space domain and propose a Radon-FCL approach. We applied a Radon transform to implement the FCL method in this article; performing FCL filtering in the Radon domain achieves a higher level of noise attenuation. Using this method, seismic reflection events can be recovered with the sacrifice of fewer frequency components while effectively attenuating more random noise than conventional FCL filtering. Experiments using both synthetic and common shot point data demonstrate the advantages of the Radon-FCL approach versus the conventional FCL method with regard to both random noise attenuation and seismic signal preservation.

ERP denoising in multichannel EEG data using contrasts between signal and noise subspaces.

PubMed

Ivannikov, Andriy; Kalyakin, Igor; Hämäläinen, Jarmo; Leppänen, Paavo H T; Ristaniemi, Tapani; Lyytinen, Heikki; Kärkkäinen, Tommi

2009-06-15

In this paper, a new method intended for ERP denoising in multichannel EEG data is discussed. The denoising is done by separating ERP/noise subspaces in multidimensional EEG data by a linear transformation and the following dimension reduction by ignoring noise components during inverse transformation. The separation matrix is found based on the assumption that ERP sources are deterministic for all repetitions of the same type of stimulus within the experiment, while the other noise sources do not obey the determinancy property. A detailed derivation of the technique is given together with the analysis of the results of its application to a real high-density EEG data set. The interpretation of the results and the performance of the proposed method under conditions, when the basic assumptions are violated - e.g. the problem is underdetermined - are also discussed. Moreover, we study how the factors of the number of channels and trials used by the method influence the effectiveness of ERP/noise subspaces separation. In addition, we explore also the impact of different data resampling strategies on the performance of the considered algorithm. The results can help in determining the optimal parameters of the equipment/methods used to elicit and reliably estimate ERPs.

Noise studies of communication systems using the SYSTID computer aided analysis program

NASA Technical Reports Server (NTRS)

Tranter, W. H.; Dawson, C. T.

1973-01-01

SYSTID computer aided design is a simple program for simulating data systems and communication links. A trial of the efficiency of the method was carried out by simulating a linear analog communication system to determine its noise performance and by comparing the SYSTID result with the result arrived at by theoretical calculation. It is shown that the SYSTID program is readily applicable to the analysis of these types of systems.

A temporal and spatial analysis of anthropogenic noise sources affecting SNMR

NASA Astrophysics Data System (ADS)

Dalgaard, E.; Christiansen, P.; Larsen, J. J.; Auken, E.

2014-11-01

One of the biggest challenges when using the surface nuclear magnetic resonance (SNMR) method in urban areas is a relatively low signal level compared to a high level of background noise. To understand the temporal and spatial behavior of anthropogenic noise sources like powerlines and electric fences, we have developed a multichannel instrument, noiseCollector (nC), which measures the full noise spectrum up to 10 kHz. Combined with advanced signal processing we can interpret the noise as seen by a SNMR instrument and also obtain insight into the more fundamental behavior of the noise. To obtain a specified acceptable noise level for a SNMR sounding the stack size can be determined by quantifying the different noise sources. Two common noise sources, electromagnetic fields stemming from powerlines and fences are analyzed and show a 1/r2 dependency in agreement with theoretical relations. A typical noise map, obtained with the nC instrument prior to a SNMR field campaign, clearly shows the location of noise sources, and thus we can efficiently determine the optimal location for the SNMR sounding from a noise perspective.

Sample-based engine noise synthesis using an enhanced pitch-synchronous overlap-and-add method.

PubMed

Jagla, Jan; Maillard, Julien; Martin, Nadine

2012-11-01

An algorithm for the real time synthesis of internal combustion engine noise is presented. Through the analysis of a recorded engine noise signal of continuously varying engine speed, a dataset of sound samples is extracted allowing the real time synthesis of the noise induced by arbitrary evolutions of engine speed. The sound samples are extracted from a recording spanning the entire engine speed range. Each sample is delimitated such as to contain the sound emitted during one cycle of the engine plus the necessary overlap to ensure smooth transitions during the synthesis. The proposed approach, an extension of the PSOLA method introduced for speech processing, takes advantage of the specific periodicity of engine noise signals to locate the extraction instants of the sound samples. During the synthesis stage, the sound samples corresponding to the target engine speed evolution are concatenated with an overlap and add algorithm. It is shown that this method produces high quality audio restitution with a low computational load. It is therefore well suited for real time applications.

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.

Background noise analysis in urban airport surroundings of Brazilian cities, Congonhas Airport, São Paulo

PubMed Central

Scatolini, Fabio; Alves, Cláudio Jorge Pinto

2016-01-01

ABSTRACT OBJECTIVE To perform a quantitative analysis of the background noise at Congonhas Airport surroundings based on large sampling and measurements with no interruption. METHODS Measuring sites were chosen from 62 and 72 DNL (day-night-level) noise contours, in urban sites compatible with residential use. Fifteen sites were monitored for at least 168 hours without interruption or seven consecutive days. Data compilation was based on cross-reference between noise measurements and air traffic control records, and results were validated by airport meteorological reports. Preliminary diagnoses were established using the standard NBR-13368. Background noise values were calculated based on the Sound Exposure Level (SEL). Statistic parameters were calculated in one-hour intervals. RESULTS Only four of the fifteen sites assessed presented aircraft operations as a clear cause for the noise annoyance. Even so, it is possible to detect background noise levels above regulation limits during periods of low airport activity or when it closes at night. CONCLUSIONS All the sites monitored showed background noise levels above regulation limits between 7:00 and 21:00. In the intervals between 6:00-6:59 and 21:00-22:59 the noise data, when analyzed with the current airport operational characteristics, still allow the development of additional mitigating measures. PMID:28099658

Evaluation of analysis techniques for low frequency interior noise and vibration of commercial aircraft

NASA Technical Reports Server (NTRS)

Landmann, A. E.; Tillema, H. F.; Marshall, S. E.

1989-01-01

The application of selected analysis techniques to low frequency cabin noise associated with advanced propeller engine installations is evaluated. Three design analysis techniques were chosen for evaluation including finite element analysis, statistical energy analysis (SEA), and a power flow method using element of SEA (computer program Propeller Aircraft Interior Noise). An overview of the three procedures is provided. Data from tests of a 727 airplane (modified to accept a propeller engine) were used to compare with predictions. Comparisons of predicted and measured levels at the end of the first year's effort showed reasonable agreement leading to the conclusion that each technique had value for propeller engine noise predictions on large commercial transports. However, variations in agreement were large enough to remain cautious and to lead to recommendations for further work with each technique. Assessment of the second year's results leads to the conclusion that the selected techniques can accurately predict trends and can be useful to a designer, but that absolute level predictions remain unreliable due to complexity of the aircraft structure and low modal densities.

Limits on the prediction of helicopter rotor noise using thickness and loading sources: Validation of helicopter noise prediction techniques

NASA Technical Reports Server (NTRS)

Succi, G. P.

1983-01-01

The techniques of helicopter rotor noise prediction attempt to describe precisely the details of the noise field and remove the empiricisms and restrictions inherent in previous methods. These techniques require detailed inputs of the rotor geometry, operating conditions, and blade surface pressure distribution. The Farassat noise prediction techniques was studied, and high speed helicopter noise prediction using more detailed representations of the thickness and loading noise sources was investigated. These predictions were based on the measured blade surface pressures on an AH-1G rotor and compared to the measured sound field. Although refinements in the representation of the thickness and loading noise sources improve the calculation, there are still discrepancies between the measured and predicted sound field. Analysis of the blade surface pressure data indicates shocks on the blades, which are probably responsible for these discrepancies.

Noise abatement technology options for conventional turboprop airplanes. Final report

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

Galloway, W.J.; Wilby, J.F.

1981-06-01

The practical application of noise control technology to new and derivative conventional turboprop airplanes likely to come into service in the 1980's has been analyzed with a view to determining noise control cost/benefits. The analysis identifies feasible noise control methods, applies them to four study airplanes, and presents the noise reductions in terms of the equivalent perceived noise level at takeoff, sideline and approach locations, and the effect on the area within selected EPNL contours. Noise reductions of up to 8.3 dB for takeoff and 10.7 dB for approach are calculated for the study airplanes but, for most cases, themore » changes are less than 5 dB. Weight and cost increases associated with the noise control treatments are determined under the assumption there they are no changes to airplane performance or fuel consumption.« less

Experimental validation of finite element and boundary element methods for predicting structural vibration and radiated noise

NASA Technical Reports Server (NTRS)

Seybert, A. F.; Wu, T. W.; Wu, X. F.

1994-01-01

This research report is presented in three parts. In the first part, acoustical analyses were performed on modes of vibration of the housing of a transmission of a gear test rig developed by NASA. The modes of vibration of the transmission housing were measured using experimental modal analysis. The boundary element method (BEM) was used to calculate the sound pressure and sound intensity on the surface of the housing and the radiation efficiency of each mode. The radiation efficiency of each of the transmission housing modes was then compared to theoretical results for a finite baffled plate. In the second part, analytical and experimental validation of methods to predict structural vibration and radiated noise are presented. A rectangular box excited by a mechanical shaker was used as a vibrating structure. Combined finite element method (FEM) and boundary element method (BEM) models of the apparatus were used to predict the noise level radiated from the box. The FEM was used to predict the vibration, while the BEM was used to predict the sound intensity and total radiated sound power using surface vibration as the input data. Vibration predicted by the FEM model was validated by experimental modal analysis; noise predicted by the BEM was validated by measurements of sound intensity. Three types of results are presented for the total radiated sound power: sound power predicted by the BEM model using vibration data measured on the surface of the box; sound power predicted by the FEM/BEM model; and sound power measured by an acoustic intensity scan. In the third part, the structure used in part two was modified. A rib was attached to the top plate of the structure. The FEM and BEM were then used to predict structural vibration and radiated noise respectively. The predicted vibration and radiated noise were then validated through experimentation.

Adaptive photoacoustic imaging quality optimization with EMD and reconstruction

NASA Astrophysics Data System (ADS)

Guo, Chengwen; Ding, Yao; Yuan, Jie; Xu, Guan; Wang, Xueding; Carson, Paul L.

2016-10-01

Biomedical photoacoustic (PA) signal is characterized with extremely low signal to noise ratio which will yield significant artifacts in photoacoustic tomography (PAT) images. Since PA signals acquired by ultrasound transducers are non-linear and non-stationary, traditional data analysis methods such as Fourier and wavelet method cannot give useful information for further research. In this paper, we introduce an adaptive method to improve the quality of PA imaging based on empirical mode decomposition (EMD) and reconstruction. Data acquired by ultrasound transducers are adaptively decomposed into several intrinsic mode functions (IMFs) after a sifting pre-process. Since noise is randomly distributed in different IMFs, depressing IMFs with more noise while enhancing IMFs with less noise can effectively enhance the quality of reconstructed PAT images. However, searching optimal parameters by means of brute force searching algorithms will cost too much time, which prevent this method from practical use. To find parameters within reasonable time, heuristic algorithms, which are designed for finding good solutions more efficiently when traditional methods are too slow, are adopted in our method. Two of the heuristic algorithms, Simulated Annealing Algorithm, a probabilistic method to approximate the global optimal solution, and Artificial Bee Colony Algorithm, an optimization method inspired by the foraging behavior of bee swarm, are selected to search optimal parameters of IMFs in this paper. The effectiveness of our proposed method is proved both on simulated data and PA signals from real biomedical tissue, which might bear the potential for future clinical PA imaging de-noising.

Detecting and quantifying stellar magnetic fields. Sparse Stokes profile approximation using orthogonal matching pursuit

NASA Astrophysics Data System (ADS)

Carroll, T. A.; Strassmeier, K. G.

2014-03-01

Context. In recent years, we have seen a rapidly growing number of stellar magnetic field detections for various types of stars. Many of these magnetic fields are estimated from spectropolarimetric observations (Stokes V) by using the so-called center-of-gravity (COG) method. Unfortunately, the accuracy of this method rapidly deteriorates with increasing noise and thus calls for a more robust procedure that combines signal detection and field estimation. Aims: We introduce an estimation method that provides not only the effective or mean longitudinal magnetic field from an observed Stokes V profile but also uses the net absolute polarization of the profile to obtain an estimate of the apparent (i.e., velocity resolved) absolute longitudinal magnetic field. Methods: By combining the COG method with an orthogonal-matching-pursuit (OMP) approach, we were able to decompose observed Stokes profiles with an overcomplete dictionary of wavelet-basis functions to reliably reconstruct the observed Stokes profiles in the presence of noise. The elementary wave functions of the sparse reconstruction process were utilized to estimate the effective longitudinal magnetic field and the apparent absolute longitudinal magnetic field. A multiresolution analysis complements the OMP algorithm to provide a robust detection and estimation method. Results: An extensive Monte-Carlo simulation confirms the reliability and accuracy of the magnetic OMP approach where a mean error of under 2% is found. Its full potential is obtained for heavily noise-corrupted Stokes profiles with signal-to-noise variance ratios down to unity. In this case a conventional COG method yields a mean error for the effective longitudinal magnetic field of up to 50%, whereas the OMP method gives a maximum error of 18%. It is, moreover, shown that even in the case of very small residual noise on a level between 10-3 and 10-5, a regime reached by current multiline reconstruction techniques, the conventional COG method incorrectly interprets a large portion of the residual noise as a magnetic field, with values of up to 100 G. The magnetic OMP method, on the other hand, remains largely unaffected by the noise, regardless of the noise level the maximum error is no greater than 0.7 G.

Active Control of Fan Noise: Feasibility Study. Volume 5; Numerical Computation of Acoustic Mode Reflection Coefficients for an Unflanged Cylindrical Duct

NASA Technical Reports Server (NTRS)

Kraft, R. E.

1996-01-01

A computational method to predict modal reflection coefficients in cylindrical ducts has been developed based on the work of Homicz, Lordi, and Rehm, which uses the Wiener-Hopf method to account for the boundary conditions at the termination of a thin cylindrical pipe. The purpose of this study is to develop a computational routine to predict the reflection coefficients of higher order acoustic modes impinging on the unflanged termination of a cylindrical duct. This effort was conducted wider Task Order 5 of the NASA Lewis LET Program, Active Noise Control of aircraft Engines: Feasibility Study, and will be used as part of the development of an integrated source noise, acoustic propagation, ANC actuator coupling, and control system algorithm simulation. The reflection coefficient prediction will be incorporated into an existing cylindrical duct modal analysis to account for the reflection of modes from the duct termination. This will provide a more accurate, rapid computation design tool for evaluating the effect of reflected waves on active noise control systems mounted in the duct, as well as providing a tool for the design of acoustic treatment in inlet ducts. As an active noise control system design tool, the method can be used preliminary to more accurate but more numerically intensive acoustic propagation models such as finite element methods. The resulting computer program has been shown to give reasonable results, some examples of which are presented. Reliable data to use for comparison is scarce, so complete checkout is difficult, and further checkout is needed over a wider range of system parameters. In future efforts the method will be adapted as a subroutine to the GEAE segmented cylindrical duct modal analysis program.

Schenberg microwave cabling seismic isolation.

NASA Astrophysics Data System (ADS)

Bortoli, F. S.; Frajuca, C.; Aguiar, O. D.

2018-02-01

SCHENBERG is a resonant-mass gravitational wave detector with a frequency about 3.2 kHz. Its spherical antenna, weighing 1.15 metric ton, is connected to the external world by a system which must attenuate seismic noise. When a gravitational wave passes the antenna vibrates, its motion is monitored by transducers. These parametric transducers uses microwaves carried by coaxial cables that are also connected to the external world, they also carry seismic noise. In this analysis the system was modeled using finite element method. This work shows that the addition of masses along these cables can decrease this noise, so that this noise is below the thermal noise of the detector when operating at 50 mK.

Unified aeroacoustics analysis for high speed turboprop aerodynamics and noise. Volume 5: Propagation of propeller tone noise through a fuselage boundary layer

NASA Technical Reports Server (NTRS)

Magliozzi, B.; Hanson, D. B.

1991-01-01

An analysis of tone noise propagation through a boundary layer and fuselage scattering effects was derived. This analysis is a three dimensional and the complete wave field is solved by matching analytical expressions for the incident and scattered waves in the outer flow to a numerical solution in the boundary layer flow. The outer wave field is constructed analytically from an incident wave appropriate to the source and a scattered wave in the standard Hankel function form. For the incident wave, an existing function - domain propeller noise radiation theory is used. In the boundary layer region, the wave equation is solved by numerical methods. The theoretical analysis is embodied in a computer program which allows the calculation of correction factors for the fuselage scattering and boundary layer refraction effects. The effects are dependent on boundary layer profile, flight speed, and frequency. Corrections can be derived for any point on the fuselage, including those on the opposite side from the source. The theory was verified using limited cases and by comparing calculations with available measurements from JetStar tests of model prop-fans. For the JetStar model scale, the boundary layer refraction effects produce moderate fuselage pressure reinforcements aft of and near the plane of rotation and significant attenuation forward of the plane of rotation at high flight speeds. At lower flight speeds, the calculated boundary layer effects result in moderate amplification over the fuselage area of interest. Apparent amplification forward of the plane of rotation is a result of effective changes in the source directivity due to boundary layer refraction effects. Full scale effects are calculated to be moderate, providing fuselage pressure amplification of about 5 dB at the peak noise location. Evaluation using available noise measurements was made under high-speed, high-altitude flight conditions. Comparisons of calculations made of free field noise, using a current frequency-domain propeller noise prediction method, and fuselage effects using this new procedure show good agreement with fuselage measurements over a wide range of flight speeds and frequencies. Correction factors for the JetStar measurements made on the fuselage are provided in an Appendix.

Use of local noise power spectrum and wavelet analysis in quantitative image quality assurance for EPIDs

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

Lee, Soyoung

Purpose: To investigate the use of local noise power spectrum (NPS) to characterize image noise and wavelet analysis to isolate defective pixels and inter-subpanel flat-fielding artifacts for quantitative quality assurance (QA) of electronic portal imaging devices (EPIDs). Methods: A total of 93 image sets including custom-made bar-pattern images and open exposure images were collected from four iViewGT a-Si EPID systems over three years. Global quantitative metrics such as modulation transform function (MTF), NPS, and detective quantum efficiency (DQE) were computed for each image set. Local NPS was also calculated for individual subpanels by sampling region of interests within each subpanelmore » of the EPID. The 1D NPS, obtained by radially averaging the 2D NPS, was fitted to a power-law function. The r-square value of the linear regression analysis was used as a singular metric to characterize the noise properties of individual subpanels of the EPID. The sensitivity of the local NPS was first compared with the global quantitative metrics using historical image sets. It was then compared with two commonly used commercial QA systems with images collected after applying two different EPID calibration methods (single-level gain and multilevel gain). To detect isolated defective pixels and inter-subpanel flat-fielding artifacts, Haar wavelet transform was applied on the images. Results: Global quantitative metrics including MTF, NPS, and DQE showed little change over the period of data collection. On the contrary, a strong correlation between the local NPS (r-square values) and the variation of the EPID noise condition was observed. The local NPS analysis indicated image quality improvement with the r-square values increased from 0.80 ± 0.03 (before calibration) to 0.85 ± 0.03 (after single-level gain calibration) and to 0.96 ± 0.03 (after multilevel gain calibration), while the commercial QA systems failed to distinguish the image quality improvement between the two calibration methods. With wavelet analysis, defective pixels and inter-subpanel flat-fielding artifacts were clearly identified as spikes after thresholding the inversely transformed images. Conclusions: The proposed local NPS (r-square values) showed superior sensitivity to the noise level variations of individual subpanels compared with global quantitative metrics such as MTF, NPS, and DQE. Wavelet analysis was effective in detecting isolated defective pixels and inter-subpanel flat-fielding artifacts. The proposed methods are promising for the early detection of imaging artifacts of EPIDs.« less

Preconditioned alternating direction method of multipliers for inverse problems with constraints

NASA Astrophysics Data System (ADS)

Jiao, Yuling; Jin, Qinian; Lu, Xiliang; Wang, Weijie

2017-02-01

We propose a preconditioned alternating direction method of multipliers (ADMM) to solve linear inverse problems in Hilbert spaces with constraints, where the feature of the sought solution under a linear transformation is captured by a possibly non-smooth convex function. During each iteration step, our method avoids solving large linear systems by choosing a suitable preconditioning operator. In case the data is given exactly, we prove the convergence of our preconditioned ADMM without assuming the existence of a Lagrange multiplier. In case the data is corrupted by noise, we propose a stopping rule using information on noise level and show that our preconditioned ADMM is a regularization method; we also propose a heuristic rule when the information on noise level is unavailable or unreliable and give its detailed analysis. Numerical examples are presented to test the performance of the proposed method.

Method for detecting the signature of noise-induced structures in spatiotemporal data sets: an application to excitable media

NASA Astrophysics Data System (ADS)

Huett, Marc-Thorsten

2003-05-01

We formulate mathematical tools for analyzing spatiotemporal data sets. The tools are based on nearest-neighbor considerations similar to cellular automata. One of the analysis tools allows for reconstructing the noise intensity in a data set and is an appropriate method for detecting a variety of noise-induced phenomena in spatiotemporal data. The functioning of these methods is illustrated on sample data generated with the forest fire model and with networks of nonlinear oscillators. It is seen that these methods allow the characterization of spatiotemporal stochastic resonance (STSR) in experimental data. Application of these tools to biological spatiotemporal patterns is discussed. For one specific example, the slime mold Dictyostelium discoideum, it is seen, how transitions between different patterns are clearly marked by changes in the spatiotemporal observables.

Statistical model based iterative reconstruction (MBIR) in clinical CT systems: experimental assessment of noise performance.

PubMed

Li, Ke; Tang, Jie; Chen, Guang-Hong

2014-04-01

To reduce radiation dose in CT imaging, the statistical model based iterative reconstruction (MBIR) method has been introduced for clinical use. Based on the principle of MBIR and its nonlinear nature, the noise performance of MBIR is expected to be different from that of the well-understood filtered backprojection (FBP) reconstruction method. The purpose of this work is to experimentally assess the unique noise characteristics of MBIR using a state-of-the-art clinical CT system. Three physical phantoms, including a water cylinder and two pediatric head phantoms, were scanned in axial scanning mode using a 64-slice CT scanner (Discovery CT750 HD, GE Healthcare, Waukesha, WI) at seven different mAs levels (5, 12.5, 25, 50, 100, 200, 300). At each mAs level, each phantom was repeatedly scanned 50 times to generate an image ensemble for noise analysis. Both the FBP method with a standard kernel and the MBIR method (Veo(®), GE Healthcare, Waukesha, WI) were used for CT image reconstruction. Three-dimensional (3D) noise power spectrum (NPS), two-dimensional (2D) NPS, and zero-dimensional NPS (noise variance) were assessed both globally and locally. Noise magnitude, noise spatial correlation, noise spatial uniformity and their dose dependence were examined for the two reconstruction methods. (1) At each dose level and at each frequency, the magnitude of the NPS of MBIR was smaller than that of FBP. (2) While the shape of the NPS of FBP was dose-independent, the shape of the NPS of MBIR was strongly dose-dependent; lower dose lead to a "redder" NPS with a lower mean frequency value. (3) The noise standard deviation (σ) of MBIR and dose were found to be related through a power law of σ ∝ (dose)(-β) with the component β ≈ 0.25, which violated the classical σ ∝ (dose)(-0.5) power law in FBP. (4) With MBIR, noise reduction was most prominent for thin image slices. (5) MBIR lead to better noise spatial uniformity when compared with FBP. (6) A composite image generated from two MBIR images acquired at two different dose levels (D1 and D2) demonstrated lower noise than that of an image acquired at a dose level of D1+D2. The noise characteristics of the MBIR method are significantly different from those of the FBP method. The well known tradeoff relationship between CT image noise and radiation dose has been modified by MBIR to establish a more gradual dependence of noise on dose. Additionally, some other CT noise properties that had been well understood based on the linear system theory have also been altered by MBIR. Clinical CT scan protocols that had been optimized based on the classical CT noise properties need to be carefully re-evaluated for systems equipped with MBIR in order to maximize the method's potential clinical benefits in dose reduction and/or in CT image quality improvement. © 2014 American Association of Physicists in Medicine.

Rank estimation and the multivariate analysis of in vivo fast-scan cyclic voltammetric data

PubMed Central

Keithley, Richard B.; Carelli, Regina M.; Wightman, R. Mark

2010-01-01

Principal component regression has been used in the past to separate current contributions from different neuromodulators measured with in vivo fast-scan cyclic voltammetry. Traditionally, a percent cumulative variance approach has been used to determine the rank of the training set voltammetric matrix during model development, however this approach suffers from several disadvantages including the use of arbitrary percentages and the requirement of extreme precision of training sets. Here we propose that Malinowski’s F-test, a method based on a statistical analysis of the variance contained within the training set, can be used to improve factor selection for the analysis of in vivo fast-scan cyclic voltammetric data. These two methods of rank estimation were compared at all steps in the calibration protocol including the number of principal components retained, overall noise levels, model validation as determined using a residual analysis procedure, and predicted concentration information. By analyzing 119 training sets from two different laboratories amassed over several years, we were able to gain insight into the heterogeneity of in vivo fast-scan cyclic voltammetric data and study how differences in factor selection propagate throughout the entire principal component regression analysis procedure. Visualizing cyclic voltammetric representations of the data contained in the retained and discarded principal components showed that using Malinowski’s F-test for rank estimation of in vivo training sets allowed for noise to be more accurately removed. Malinowski’s F-test also improved the robustness of our criterion for judging multivariate model validity, even though signal-to-noise ratios of the data varied. In addition, pH change was the majority noise carrier of in vivo training sets while dopamine prediction was more sensitive to noise. PMID:20527815

RNA-seq mixology: designing realistic control experiments to compare protocols and analysis methods

PubMed Central

Holik, Aliaksei Z.; Law, Charity W.; Liu, Ruijie; Wang, Zeya; Wang, Wenyi; Ahn, Jaeil; Asselin-Labat, Marie-Liesse; Smyth, Gordon K.

2017-01-01

Abstract Carefully designed control experiments provide a gold standard for benchmarking different genomics research tools. A shortcoming of many gene expression control studies is that replication involves profiling the same reference RNA sample multiple times. This leads to low, pure technical noise that is atypical of regular studies. To achieve a more realistic noise structure, we generated a RNA-sequencing mixture experiment using two cell lines of the same cancer type. Variability was added by extracting RNA from independent cell cultures and degrading particular samples. The systematic gene expression changes induced by this design allowed benchmarking of different library preparation kits (standard poly-A versus total RNA with Ribozero depletion) and analysis pipelines. Data generated using the total RNA kit had more signal for introns and various RNA classes (ncRNA, snRNA, snoRNA) and less variability after degradation. For differential expression analysis, voom with quality weights marginally outperformed other popular methods, while for differential splicing, DEXSeq was simultaneously the most sensitive and the most inconsistent method. For sample deconvolution analysis, DeMix outperformed IsoPure convincingly. Our RNA-sequencing data set provides a valuable resource for benchmarking different protocols and data pre-processing workflows. The extra noise mimics routine lab experiments more closely, ensuring any conclusions are widely applicable. PMID:27899618

Prediction and analysis of infra and low-frequency noise of upwind horizontal axis wind turbine using statistical wind speed model

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

Lee, Gwang-Se; Cheong, Cheolung, E-mail: ccheong@pusan.ac.kr

Despite increasing concern about low-frequency noise of modern large horizontal-axis wind turbines (HAWTs), few studies have focused on its origin or its prediction methods. In this paper, infra- and low-frequency (the ILF) wind turbine noise are closely examined and an efficient method is developed for its prediction. Although most previous studies have assumed that the ILF noise consists primarily of blade passing frequency (BPF) noise components, these tonal noise components are seldom identified in the measured noise spectrum, except for the case of downwind wind turbines. In reality, since modern HAWTs are very large, during rotation, a single blade ofmore » the turbine experiences inflow with variation in wind speed in time as well as in space, breaking periodic perturbations of the BPF. Consequently, this transforms acoustic contributions at the BPF harmonics into broadband noise components. In this study, the ILF noise of wind turbines is predicted by combining Lowson’s acoustic analogy with the stochastic wind model, which is employed to reproduce realistic wind speed conditions. In order to predict the effects of these wind conditions on pressure variation on the blade surface, unsteadiness in the incident wind speed is incorporated into the XFOIL code by varying incident flow velocities on each blade section, which depend on the azimuthal locations of the rotating blade. The calculated surface pressure distribution is subsequently used to predict acoustic pressure at an observing location by using Lowson’s analogy. These predictions are compared with measured data, which ensures that the present method can reproduce the broadband characteristics of the measured low-frequency noise spectrum. Further investigations are carried out to characterize the IFL noise in terms of pressure loading on blade surface, narrow-band noise spectrum and noise maps around the turbine.« less

Noise-induced hearing loss: a military perspective.

PubMed

Pfannenstiel, Travis J

2014-10-01

To summarize relevant literature occurring over the past 12-18 months forwarding understanding of noise-induced hearing loss in relation to military service. Hearing loss prior to entry into military service is highly predictive of subsequent hearing loss and hearing loss disability. Tightly controlled organic solvent exposure may not be a significant risk factor for noise-induced hearing loss. Increasingly detailed analysis of high intensity noise, impulse and blast noise exposures, and the methods used to mitigate these exposures are leading to breakthroughs in understanding and predicting hearing loss in military service. Prevention, mitigation, treatment, and prediction of the effects of hazardous noise exposure in military service continue to require a multidisciplinary team of individuals from around the world fully aware of the detrimental effect to service members and their societies of hearing loss disability.

Improved Denoising via Poisson Mixture Modeling of Image Sensor Noise.

PubMed

Zhang, Jiachao; Hirakawa, Keigo

2017-04-01

This paper describes a study aimed at comparing the real image sensor noise distribution to the models of noise often assumed in image denoising designs. A quantile analysis in pixel, wavelet transform, and variance stabilization domains reveal that the tails of Poisson, signal-dependent Gaussian, and Poisson-Gaussian models are too short to capture real sensor noise behavior. A new Poisson mixture noise model is proposed to correct the mismatch of tail behavior. Based on the fact that noise model mismatch results in image denoising that undersmoothes real sensor data, we propose a mixture of Poisson denoising method to remove the denoising artifacts without affecting image details, such as edge and textures. Experiments with real sensor data verify that denoising for real image sensor data is indeed improved by this new technique.

MSSA de-noising of horizon time structure to improve the curvature attribute analysis

NASA Astrophysics Data System (ADS)

Tiwari, R. K.; Rekapalli, R.; Vedanti, N.

2017-12-01

Although the seismic attributes are useful for identifying sub-surface structural features like faults, fractures, lineaments and sharp stratigraphy etc., the different kinds of noises arising from unknown physical sources during the data acquisition and processing creates acute problems in physical interpretation of complex crustal structures. Hence, we propose to study effect of noise on curvature attribute analysis of seismic time structure data. We propose here Multichannel Singular Spectrum Analysis (MSSA) de-noising algorithm as a pre filtering scheme to reduce effect of noise. To demonstrate the procedure, first, we compute the most positive and negative curvature on a synthetic time structure with surface features resembling anticlines, synclines and faults and then adding the known percentage of noise. We noticed that the curvatures estimated from the noisy data reveal considerable deviations from the curvature of pure synthetic data. This suggests that there is a strong impact of noise on the curvature estimates. Further, we have employed 2D median filter and MSSA methods to filter the noisy time structure and then computed the curvatures. The comparisons of curvatures estimated from de-noised data suggest that the results obtained from MSSA de-noised data match well with the curvatures of pure synthetic data. Finally, we present an example of real data analysis from Utsira Top (UT) horizon of Southern Viking Graben, Norway to identify the time-lapse changes in UT horizon after CO2 injection. We applied the MSSA de-noising algorithm on UT horizon time structure and amplitude data of pre and post CO2 injection. Our analyses suggest modest but clearly visible, structural changes in the UT horizon after CO2 injection at a few locations, which seem to be associated with the locations of change in seismic amplitudes. Thus, the results from both the synthetic and real field data suggest that the MSSA based de-noising algorithm is robust for filtering the horizon time structures for accurate curvature attributes analysis and better interpretation of structural changes in geological features. Key Words: Curvature attributes, MSSA, Seismic Horizon, 2D-median filter, Utsira Horizon.

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.

Fetal Heart Sounds Detection Using Wavelet Transform and Fractal Dimension

PubMed Central

Koutsiana, Elisavet; Hadjileontiadis, Leontios J.; Chouvarda, Ioanna; Khandoker, Ahsan H.

2017-01-01

Phonocardiography is a non-invasive technique for the detection of fetal heart sounds (fHSs). In this study, analysis of fetal phonocardiograph (fPCG) signals, in order to achieve fetal heartbeat segmentation, is proposed. The proposed approach (namely WT–FD) is a wavelet transform (WT)-based method that combines fractal dimension (FD) analysis in the WT domain for the extraction of fHSs from the underlying noise. Its adoption in this field stems from its successful use in the fields of lung and bowel sounds de-noising analysis. The efficiency of the WT–FD method in fHS extraction has been evaluated with 19 simulated fHS signals, created for the present study, with additive noise up to (3 dB), along with the simulated fPCGs database available at PhysioBank. Results have shown promising performance in the identification of the correct location and morphology of the fHSs, reaching an overall accuracy of 89% justifying the efficacy of the method. The WT–FD approach effectively extracts the fHS signals from the noisy background, paving the way for testing it in real fHSs and clearly contributing to better evaluation of the fetal heart functionality. PMID:28944222

Unified Aeroacoustics Analysis for High Speed Turboprop Aerodynamics and Noise. Volume 1; Development of Theory for Blade Loading, Wakes, and Noise

NASA Technical Reports Server (NTRS)

Hanson, D. B.

1991-01-01

A unified theory for the aerodynamics and noise of advanced turboprops are presented. Aerodynamic topics include calculation of performance, blade load distribution, and non-uniform wake flow fields. Blade loading can be steady or unsteady due to fixed distortion, counter-rotating wakes, or blade vibration. The aerodynamic theory is based on the pressure potential method and is therefore basically linear. However, nonlinear effects associated with finite axial induction and blade vortex flow are included via approximate methods. Acoustic topics include radiation of noise caused by blade thickness, steady loading (including vortex lift), and unsteady loading. Shielding of the fuselage by its boundary layer and the wing are treated in separate analyses that are compatible but not integrated with the aeroacoustic theory for rotating blades.

Investigation of noise properties in grating-based x-ray phase tomography with reverse projection method

NASA Astrophysics Data System (ADS)

Bao, Yuan; Wang, Yan; Gao, Kun; Wang, Zhi-Li; Zhu, Pei-Ping; Wu, Zi-Yu

2015-10-01

The relationship between noise variance and spatial resolution in grating-based x-ray phase computed tomography (PCT) imaging is investigated with reverse projection extraction method, and the noise variances of the reconstructed absorption coefficient and refractive index decrement are compared. For the differential phase contrast method, the noise variance in the differential projection images follows the same inverse-square law with spatial resolution as in conventional absorption-based x-ray imaging projections. However, both theoretical analysis and simulations demonstrate that in PCT the noise variance of the reconstructed refractive index decrement scales with spatial resolution follows an inverse linear relationship at fixed slice thickness, while the noise variance of the reconstructed absorption coefficient conforms with the inverse cubic law. The results indicate that, for the same noise variance level, PCT imaging may enable higher spatial resolution than conventional absorption computed tomography (ACT), while ACT benefits more from degraded spatial resolution. This could be a useful guidance in imaging the inner structure of the sample in higher spatial resolution. Project supported by the National Basic Research Program of China (Grant No. 2012CB825800), the Science Fund for Creative Research Groups, the Knowledge Innovation Program of the Chinese Academy of Sciences (Grant Nos. KJCX2-YW-N42 and Y4545320Y2), the National Natural Science Foundation of China (Grant Nos. 11475170, 11205157, 11305173, 11205189, 11375225, 11321503, 11179004, and U1332109).

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).

A passive noise control approach utilizing air gaps with fibrous materials in the textile industry.

PubMed

Monazzam-Esmaeelpour, Mohammad Reza; Hashemi, Zahra; Golmohammadi, Rostam; Zaredar, Narges

2014-01-01

Noise pollution is currently a major risk factor in industries in both developed and developing countries.The present study assessed noise pollution in the knitting industry in Iran in 2009 and presented a control method to reduce the rate of noise generation. The overall noise level was estimated using the network environmental noise assessment method in Sina Poud textile mill in Hamadan. Then, frequency analysis was performed at indicator target stations in the linear network. Finally, a suitable absorbent was recommended for the ceilings, walls, and aerial panels at three phases according to the results found for the sound source and destination environment. The results showed that the highest sound pressure level was 98.5 dB and the lowest was 95.1 dB. The dominant frequency for the industry was 500 Hz. The highest and lowest sound suppression was achieved by intervention at 4000 Hz equivalent to 14.6 dB and 250 Hz in the textile industry. When noise control at the source is not available or insufficient because of the wide distribution of the acoustic field in the workplace, the best option is to increase the absorptive surface of the workplace using adsorbents such as polystyrene.

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.

Experimental characterization of turbulent inflow noise on a full-scale wind turbine

NASA Astrophysics Data System (ADS)

Buck, Steven; Oerlemans, Stefan; Palo, Scott

2016-12-01

An extensive experimental campaign was conducted on a 108-m diameter 2.3-MW wind turbine in order to assess the effect of inflow turbulence conditions on wind turbine acoustics. Over 50 h of continuous acoustic data was acquired at power-generating wind speeds. Twelve precision microphones were used, arranged in a one rotor radius ring about the turbine tower in order to assess the directivity of the noise emission. Turbine operational and atmospheric conditions were gathered simultaneously with acoustics measurements. The testing and analysis constitute perhaps the most thorough experimental characterization of turbulent inflow noise from a wind turbine to date. Turbulence intensities typically varied between 10 percent and 35 percent, and wind speeds covered most of the operational range of the wind turbine, from cut-on to well above its rated power. A method was developed for using blade-mounted accelerometers for determining the turbulence conditions in the immediate vicinity of the blades, which are the primary turbulence noise generating bodies. The method uses the blades' vibrational energy within a specified frequency range to estimate the overall turbulence conditions by assuming a von Kármán turbulence spectrum. Using this method, a clear positive correlation is shown between turbulence intensity and noise levels. The turbulence noise is dominant at low frequencies and is primarily observed in the upwind and downwind directions. Low frequency noise increases by as much as 6 dB for the range of turbulence conditions measured. Comparisons are made between the measured turbine noise directivity and theory using a simple acoustic model of the turbine as three point-sources. Strong agreement is found between the theoretical leading edge noise directivity model and the measured low frequency noise directivity.

Precomputing Process Noise Covariance for Onboard Sequential Filters

NASA Technical Reports Server (NTRS)

Olson, Corwin G.; Russell, Ryan P.; Carpenter, J. Russell

2017-01-01

Process noise is often used in estimation filters to account for unmodeled and mismodeled accelerations in the dynamics. The process noise covariance acts to inflate the state covariance over propagation intervals, increasing the uncertainty in the state. In scenarios where the acceleration errors change significantly over time, the standard process noise covariance approach can fail to provide effective representation of the state and its uncertainty. Consider covariance analysis techniques provide a method to precompute a process noise covariance profile along a reference trajectory using known model parameter uncertainties. The process noise covariance profile allows significantly improved state estimation and uncertainty representation over the traditional formulation. As a result, estimation performance on par with the consider filter is achieved for trajectories near the reference trajectory without the additional computational cost of the consider filter. The new formulation also has the potential to significantly reduce the trial-and-error tuning currently required of navigation analysts. A linear estimation problem as described in several previous consider covariance analysis studies is used to demonstrate the effectiveness of the precomputed process noise covariance, as well as a nonlinear descent scenario at the asteroid Bennu with optical navigation.

Precomputing Process Noise Covariance for Onboard Sequential Filters

NASA Technical Reports Server (NTRS)

Olson, Corwin G.; Russell, Ryan P.; Carpenter, J. Russell

2017-01-01

Process noise is often used in estimation filters to account for unmodeled and mismodeled accelerations in the dynamics. The process noise covariance acts to inflate the state covariance over propagation intervals, increasing the uncertainty in the state. In scenarios where the acceleration errors change significantly over time, the standard process noise covariance approach can fail to provide effective representation of the state and its uncertainty. Consider covariance analysis techniques provide a method to precompute a process noise covariance profile along a reference trajectory, using known model parameter uncertainties. The process noise covariance profile allows significantly improved state estimation and uncertainty representation over the traditional formulation. As a result, estimation performance on par with the consider filter is achieved for trajectories near the reference trajectory without the additional computational cost of the consider filter. The new formulation also has the potential to significantly reduce the trial-and-error tuning currently required of navigation analysts. A linear estimation problem as described in several previous consider covariance analysis publications is used to demonstrate the effectiveness of the precomputed process noise covariance, as well as a nonlinear descent scenario at the asteroid Bennu with optical navigation.

SNDR Limits of Oscillator-Based Sensor Readout Circuits

PubMed Central

Buffa, Cesare; Wiesbauer, Andreas; Hernandez, Luis

2018-01-01

This paper analyzes the influence of phase noise and distortion on the performance of oscillator-based sensor data acquisition systems. Circuit noise inherent to the oscillator circuit manifests as phase noise and limits the SNR. Moreover, oscillator nonlinearity generates distortion for large input signals. Phase noise analysis of oscillators is well known in the literature, but the relationship between phase noise and the SNR of an oscillator-based sensor is not straightforward. This paper proposes a model to estimate the influence of phase noise in the performance of an oscillator-based system by reflecting the phase noise to the oscillator input. The proposed model is based on periodic steady-state analysis tools to predict the SNR of the oscillator. The accuracy of this model has been validated by both simulation and experiment in a 130 nm CMOS prototype. We also propose a method to estimate the SNDR and the dynamic range of an oscillator-based readout circuit that improves by more than one order of magnitude the simulation time compared to standard time domain simulations. This speed up enables the optimization and verification of this kind of systems with iterative algorithms. PMID:29401646

Including the effect of motion artifacts in noise and performance analysis of dual-energy contrast-enhanced mammography

NASA Astrophysics Data System (ADS)

Allec, N.; Abbaszadeh, S.; Scott, C. C.; Lewin, J. M.; Karim, K. S.

2012-12-01

In contrast-enhanced mammography (CEM), the dual-energy dual-exposure technique, which can leverage existing conventional mammography infrastructure, relies on acquiring the low- and high-energy images using two separate exposures. The finite time between image acquisition leads to motion artifacts in the combined image. Motion artifacts can lead to greater anatomical noise in the combined image due to increased mismatch of the background tissue in the images to be combined, however the impact has not yet been quantified. In this study we investigate a method to include motion artifacts in the dual-energy noise and performance analysis. The motion artifacts are included via an extended cascaded systems model. To validate the model, noise power spectra of a previous dual-energy clinical study are compared to that of the model. The ideal observer detectability is used to quantify the effect of motion artifacts on tumor detectability. It was found that the detectability can be significantly degraded when motion is present (e.g., detectability of 2.5 mm radius tumor decreased by approximately a factor of 2 for translation motion on the order of 1000 μm). The method presented may be used for a more comprehensive theoretical noise and performance analysis and fairer theoretical performance comparison between dual-exposure techniques, where motion artifacts are present, and single-exposure techniques, where low- and high-energy images are acquired simultaneously and motion artifacts are absent.

Including the effect of motion artifacts in noise and performance analysis of dual-energy contrast-enhanced mammography.

PubMed

Allec, N; Abbaszadeh, S; Scott, C C; Lewin, J M; Karim, K S

2012-12-21

In contrast-enhanced mammography (CEM), the dual-energy dual-exposure technique, which can leverage existing conventional mammography infrastructure, relies on acquiring the low- and high-energy images using two separate exposures. The finite time between image acquisition leads to motion artifacts in the combined image. Motion artifacts can lead to greater anatomical noise in the combined image due to increased mismatch of the background tissue in the images to be combined, however the impact has not yet been quantified. In this study we investigate a method to include motion artifacts in the dual-energy noise and performance analysis. The motion artifacts are included via an extended cascaded systems model. To validate the model, noise power spectra of a previous dual-energy clinical study are compared to that of the model. The ideal observer detectability is used to quantify the effect of motion artifacts on tumor detectability. It was found that the detectability can be significantly degraded when motion is present (e.g., detectability of 2.5 mm radius tumor decreased by approximately a factor of 2 for translation motion on the order of 1000 μm). The method presented may be used for a more comprehensive theoretical noise and performance analysis and fairer theoretical performance comparison between dual-exposure techniques, where motion artifacts are present, and single-exposure techniques, where low- and high-energy images are acquired simultaneously and motion artifacts are absent.

Open Rotor Computational Aeroacoustic Analysis with an Immersed Boundary Method

NASA Technical Reports Server (NTRS)

Brehm, Christoph; Barad, Michael F.; Kiris, Cetin C.

2016-01-01

Reliable noise prediction capabilities are essential to enable novel fuel efficient open rotor designs that can meet the community and cabin noise standards. Toward this end, immersed boundary methods have reached a level of maturity where more and more complex flow problems can be tackled with this approach. This paper demonstrates that our higher-order immersed boundary method provides the ability for aeroacoustic analysis of wake-dominated flow fields generated by a contra-rotating open rotor. This is the first of a kind aeroacoustic simulation of an open rotor propulsion system employing an immersed boundary method. In addition to discussing the methodologies of how to apply the immersed boundary method to this moving boundary problem, we will provide a detailed validation of the aeroacoustic analysis approach employing the Launch Ascent and Vehicle Aerodynamics (LAVA) solver. Two free-stream Mach numbers with M=0.2 and M=0.78 are considered in this analysis that are based on the nominally take-off and cruise flow conditions. The simulation data is compared to available experimental data and other computational results employing more conventional CFD methods. Spectral analysis is used to determine the dominant wave propagation pattern in the acoustic near-field.

Noise reduction efforts for the ALS infrared beamlines

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

Scarvie, Tom; Andresen, Nord; Baptiste, Ken

2003-08-10

The quality of infrared microscopy and spectroscopy data collected at synchrotron based sources is strongly dependent on signal-to-noise. We have successfully identified and suppressed several noise sources affecting Beamlines 1.4.2, 1.4.3, and 1.4.4 at the Advanced Light Source (ALS), resulting in a significant increase in the quality of FTIR spectra obtained. In this paper, we present our methods of noise source analysis, the negative effect of noise on the infrared beam quality, and the techniques used to reduce the noise. These include reducing the phase noise in the storage ring radio-frequency (RF) system, installing an active mirror feedback system, analyzingmore » and changing physical mounts to better isolate portions of the beamline optics from low-frequency environmental noise, and modifying the input signals to the main ALS RF system. We also discuss the relationship between electron beam energy oscillations at a point of dispersion and infrared beamline noise.« less

Noise Reduction Efforts for the ALS Infrared Beamlines

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

Scarvie, Tom; Andresen, Nord; Baptiste, Ken

2004-05-12

The quality of infrared microscopy and spectroscopy data collected at synchrotron based sources is strongly dependent on signal-to-noise. We have successfully identified and suppressed several noise sources affecting Beamlines 1.4.2, 1.4.3, and 1.4.4 at the Advanced Light Source (ALS), resulting in a significant increase in the quality of FTIR spectra obtained. In this paper, we present our methods of noise source analysis, the negative effect of noise on the infrared beam quality, and the techniques used to reduce the noise. These include reducing the phase noise in the storage ring radio-frequency (RF) system, installing an active mirror feedback system, analyzingmore » and changing physical mounts to better isolate portions of the beamline optics from low-frequency environmental noise, and modifying the input signals to the main ALS RF system. We also discuss the relationship between electron beam energy oscillations at a point of dispersion and infrared beamline noise.« less

Patient-specific estimation of spatially variant image noise for a pinhole cardiac SPECT camera.

PubMed

Cuddy-Walsh, Sarah G; Wells, R Glenn

2018-05-01

New single photon emission computed tomography (SPECT) cameras using fixed pinhole collimation are increasingly popular. Pinhole collimators are known to have variable sensitivity with distance and angle from the pinhole aperture. It follows that pinhole SPECT systems will also have spatially variant sensitivity and hence spatially variant image noise. The objective of this study was to develop and validate a rapid method for analytically estimating a map of the noise magnitude in a reconstructed image using data from a single clinical acquisition. The projected voxel (PV) noise estimation method uses a modified forward projector with attenuation effects to estimate the number of photons detected from each voxel in the field-of-view. We approximate the noise for each voxel as the standard deviation of a Poisson distribution with a mean equal to the number of detected photons. An empirical formula is used to address scaling discrepancies caused by image reconstruction. Calibration coefficients are determined for the PV method by comparing it with noise measured from a nonparametrically bootstrapped set of images of a spherical uniformly filled Tc-99m water phantom. Validation studies compare PV noise estimates with bootstrapped measured noise for 31 patient images (5 min, 340 MBq, 99m Tc-tetrofosmin rest study). Bland-Altman analysis shows R 2 correlations ≥70% between the PV-estimated and -measured image noise. For the 31 patient cardiac images, the PV noise estimate has an average bias of 0.1% compared to bootstrapped noise and have a coefficient of variation (CV) ≤ 17%. The bootstrap approach to noise measurement requires 5 h of computation for each image, whereas the PV noise estimate requires only 64 s. In cardiac images, image noise due to attenuation and camera sensitivity varies on average from 4% at the apex to 9% in the basal posterior region of the heart. The standard deviation between 15 healthy patient study images (including physiological variability in the population) ranges from 6% to 16.5% over the length of the heart. The PV method provides a rapid estimate for spatially variant patient-specific image noise magnitude in a pinhole-collimated dedicated cardiac SPECT camera with a bias of -0.3% and better than 83% precision. © 2018 American Association of Physicists in Medicine.

Broadband FBG resonator seismometer: principle, key technique, self-noise, and seismic response analysis.

PubMed

Huang, Wenzhu; Zhang, Wentao; Luo, Yingbo; Li, Li; Liu, Wenyi; Li, Fang

2018-04-16

A broadband optical fiber seismometer based on FBG resonator is proposed for earthquake monitoring. The principle and key technique, high-resolution ultralow-frequency wavelength interrogation by dual-laser swept frequency and beat frequency method, are discussed and analyzed. From the simulation and test results, the seismometer works at broadband range from 0.01 Hz to 10 Hz with a sensitivity of better than 330 pm/g and the wavelength resolution of the interrogation system is better than 0.001 pm/√Hz from 0.1 Hz to 10 Hz. A three-channel correlation method is used to measure the self-noise of the seismometer. It reaches a noise level of 2.7 × 10 -7 ms -2 /√Hz@0.1 Hz, which is lower than the earth's background noise (the new high noise model, NHNM). An earthquake monitoring experiment is conducted in a low noise seismic station. The recorded seismic waves are analyzed, which suggests that the proposed seismometer has the ability to record the close microearthquake and distant great earthquake with a high signal-noise ratio (SNR). This is the first time that a FBG-based middle-long period seismometer with lower self-noise than NHNM and large dynamic range (100 dB) is reported.

Properties of Noise Cross-Correlation Functions Obtained from a Distributed Acoustic Sensing Array at Garner Valley, California

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

Zeng, Xiangfang; Lancelle, Chelsea; Thurber, Clifford

A field test that was conducted at Garner Valley, California, on 11 and 12 September 2013 using distributed acoustic sensing (DAS) to sense ground vibrations provided a continuous overnight record of ambient noise. Furthermore, the energy of ambient noise was concentrated between 5 and 25 Hz, which falls into the typical traffic noise frequency band. A standard procedure (Bensen et al., 2007) was adopted to calculate noise cross-correlation functions (NCFs) for 1-min intervals. The 1-min-long NCFs were stacked using the time–frequency domain phase-weighted-stacking method, which significantly improves signal quality. The obtained NCFs were asymmetrical, which was a result of themore » nonuniform distributed noise sources. A precursor appeared on NCFs along one segment, which was traced to a strong localized noise source or a scatterer at a nearby road intersection. NCF for the radial component of two surface accelerometers along a DAS profile gave similar results to those from DAS channels. Here, we calculated the phase velocity dispersion from DAS NCFs using the multichannel analysis of surface waves technique, and the result agrees with active-source results. We then conclude that ambient noise sources and the high spatial sampling of DAS can provide the same subsurface information as traditional active-source methods.« less

Properties of Noise Cross-Correlation Functions Obtained from a Distributed Acoustic Sensing Array at Garner Valley, California

DOE PAGES

Zeng, Xiangfang; Lancelle, Chelsea; Thurber, Clifford; ...

2017-01-31

A field test that was conducted at Garner Valley, California, on 11 and 12 September 2013 using distributed acoustic sensing (DAS) to sense ground vibrations provided a continuous overnight record of ambient noise. Furthermore, the energy of ambient noise was concentrated between 5 and 25 Hz, which falls into the typical traffic noise frequency band. A standard procedure (Bensen et al., 2007) was adopted to calculate noise cross-correlation functions (NCFs) for 1-min intervals. The 1-min-long NCFs were stacked using the time–frequency domain phase-weighted-stacking method, which significantly improves signal quality. The obtained NCFs were asymmetrical, which was a result of themore » nonuniform distributed noise sources. A precursor appeared on NCFs along one segment, which was traced to a strong localized noise source or a scatterer at a nearby road intersection. NCF for the radial component of two surface accelerometers along a DAS profile gave similar results to those from DAS channels. Here, we calculated the phase velocity dispersion from DAS NCFs using the multichannel analysis of surface waves technique, and the result agrees with active-source results. We then conclude that ambient noise sources and the high spatial sampling of DAS can provide the same subsurface information as traditional active-source methods.« less

Distinguishing short duration noise transients in LIGO data to improve the PyCBC search for gravitational waves from high mass binary black hole mergers

NASA Astrophysics Data System (ADS)

Nitz, Alexander H.

2018-02-01

‘Blip glitches’ are a type of short duration transient noise in LIGO data. The cause for the majority of these is currently unknown. Short duration transient noise creates challenges for searches of the highest mass binary black hole systems, as standard methods of applying signal consistency, which look for consistency in the accumulated signal-to-noise of the candidate event, are unable to distinguish many blip glitches from short duration gravitational-wave signals due to similarities in their time and frequency evolution. We demonstrate a straightforward method, employed during Advanced LIGO’s second observing run, including the period of joint observation with the Virgo observatory, to separate the majority of this transient noise from potential gravitational-wave sources. This yields a  ∼20% improvement in the detection rate of high mass binary black hole mergers (> 60 Mȯ ) for the PyCBC analysis.

Simultaneous digital super-resolution and nonuniformity correction for infrared imaging systems.

PubMed

Meza, Pablo; Machuca, Guillermo; Torres, Sergio; Martin, Cesar San; Vera, Esteban

2015-07-20

In this article, we present a novel algorithm to achieve simultaneous digital super-resolution and nonuniformity correction from a sequence of infrared images. We propose to use spatial regularization terms that exploit nonlocal means and the absence of spatial correlation between the scene and the nonuniformity noise sources. We derive an iterative optimization algorithm based on a gradient descent minimization strategy. Results from infrared image sequences corrupted with simulated and real fixed-pattern noise show a competitive performance compared with state-of-the-art methods. A qualitative analysis on the experimental results obtained with images from a variety of infrared cameras indicates that the proposed method provides super-resolution images with significantly less fixed-pattern noise.

Component Analysis of Remanent Magnetization Curves: A Revisit with a New Model Distribution

NASA Astrophysics Data System (ADS)

Zhao, X.; Suganuma, Y.; Fujii, M.

2017-12-01

Geological samples often consist of several magnetic components that have distinct origins. As the magnetic components are often indicative of their underlying geological and environmental processes, it is therefore desirable to identify individual components to extract associated information. This component analysis can be achieved using the so-called unmixing method, which fits a mixture model of certain end-member model distribution to the measured remanent magnetization curve. In earlier studies, the lognormal, skew generalized Gaussian and skewed Gaussian distributions have been used as the end-member model distribution in previous studies, which are performed on the gradient curve of remanent magnetization curves. However, gradient curves are sensitive to measurement noise as the differentiation of the measured curve amplifies noise, which could deteriorate the component analysis. Though either smoothing or filtering can be applied to reduce the noise before differentiation, their effect on biasing component analysis is vaguely addressed. In this study, we investigated a new model function that can be directly applied to the remanent magnetization curves and therefore avoid the differentiation. The new model function can provide more flexible shape than the lognormal distribution, which is a merit for modeling the coercivity distribution of complex magnetic component. We applied the unmixing method both to model and measured data, and compared the results with those obtained using other model distributions to better understand their interchangeability, applicability and limitation. The analyses on model data suggest that unmixing methods are inherently sensitive to noise, especially when the number of component is over two. It is, therefore, recommended to verify the reliability of component analysis by running multiple analyses with synthetic noise. Marine sediments and seafloor rocks are analyzed with the new model distribution. Given the same component number, the new model distribution can provide closer fits than the lognormal distribution evidenced by reduced residuals. Moreover, the new unmixing protocol is automated so that the users are freed from the labor of providing initial guesses for the parameters, which is also helpful to improve the subjectivity of component analysis.

Deterministic analysis of extrinsic and intrinsic noise in an epidemiological model.

PubMed

Bayati, Basil S

2016-05-01

We couple a stochastic collocation method with an analytical expansion of the canonical epidemiological master equation to analyze the effects of both extrinsic and intrinsic noise. It is shown that depending on the distribution of the extrinsic noise, the master equation yields quantitatively different results compared to using the expectation of the distribution for the stochastic parameter. This difference is incident to the nonlinear terms in the master equation, and we show that the deviation away from the expectation of the extrinsic noise scales nonlinearly with the variance of the distribution. The method presented here converges linearly with respect to the number of particles in the system and exponentially with respect to the order of the polynomials used in the stochastic collocation calculation. This makes the method presented here more accurate than standard Monte Carlo methods, which suffer from slow, nonmonotonic convergence. In epidemiological terms, the results show that extrinsic fluctuations should be taken into account since they effect the speed of disease breakouts and that the gamma distribution should be used to model the basic reproductive number.

Characterization of chaotic attractors under noise: A recurrence network perspective

NASA Astrophysics Data System (ADS)

Jacob, Rinku; Harikrishnan, K. P.; Misra, R.; Ambika, G.

2016-12-01

We undertake a detailed numerical investigation to understand how the addition of white and colored noise to a chaotic time series changes the topology and the structure of the underlying attractor reconstructed from the time series. We use the methods and measures of recurrence plot and recurrence network generated from the time series for this analysis. We explicitly show that the addition of noise obscures the property of recurrence of trajectory points in the phase space which is the hallmark of every dynamical system. However, the structure of the attractor is found to be robust even upto high noise levels of 50%. An advantage of recurrence network measures over the conventional nonlinear measures is that they can be applied on short and non stationary time series data. By using the results obtained from the above analysis, we go on to analyse the light curves from a dominant black hole system and show that the recurrence network measures are capable of identifying the nature of noise contamination in a time series.

Selective Weighted Least Squares Method for Fourier Transform Infrared Quantitative Analysis.

PubMed

Wang, Xin; Li, Yan; Wei, Haoyun; Chen, Xia

2017-06-01

Classical least squares (CLS) regression is a popular multivariate statistical method used frequently for quantitative analysis using Fourier transform infrared (FT-IR) spectrometry. Classical least squares provides the best unbiased estimator for uncorrelated residual errors with zero mean and equal variance. However, the noise in FT-IR spectra, which accounts for a large portion of the residual errors, is heteroscedastic. Thus, if this noise with zero mean dominates in the residual errors, the weighted least squares (WLS) regression method described in this paper is a better estimator than CLS. However, if bias errors, such as the residual baseline error, are significant, WLS may perform worse than CLS. In this paper, we compare the effect of noise and bias error in using CLS and WLS in quantitative analysis. Results indicated that for wavenumbers with low absorbance, the bias error significantly affected the error, such that the performance of CLS is better than that of WLS. However, for wavenumbers with high absorbance, the noise significantly affected the error, and WLS proves to be better than CLS. Thus, we propose a selective weighted least squares (SWLS) regression that processes data with different wavenumbers using either CLS or WLS based on a selection criterion, i.e., lower or higher than an absorbance threshold. The effects of various factors on the optimal threshold value (OTV) for SWLS have been studied through numerical simulations. These studies reported that: (1) the concentration and the analyte type had minimal effect on OTV; and (2) the major factor that influences OTV is the ratio between the bias error and the standard deviation of the noise. The last part of this paper is dedicated to quantitative analysis of methane gas spectra, and methane/toluene mixtures gas spectra as measured using FT-IR spectrometry and CLS, WLS, and SWLS. The standard error of prediction (SEP), bias of prediction (bias), and the residual sum of squares of the errors (RSS) from the three quantitative analyses were compared. In methane gas analysis, SWLS yielded the lowest SEP and RSS among the three methods. In methane/toluene mixture gas analysis, a modification of the SWLS has been presented to tackle the bias error from other components. The SWLS without modification presents the lowest SEP in all cases but not bias and RSS. The modification of SWLS reduced the bias, which showed a lower RSS than CLS, especially for small components.

Comparison of modal analysis results of laser vibrometry and nearfield acoustical holography measurements of an aluminum plate

NASA Astrophysics Data System (ADS)

Potter, Jennifer L.

2011-12-01

Noise and vibration has long been sought to be reduced in major industries: automotive, aerospace and marine to name a few. Products must be tested and pass certain levels of federally regulated standards before entering the market. Vibration measurements are commonly acquired using accelerometers; however limitations of this method create a need for alternative solutions. Two methods for non-contact vibration measurements are compared: Laser Vibrometry, which directly measures the surface velocity of the aluminum plate, and Nearfield Acoustic Holography (NAH), which measures sound pressure in the nearfield, and using Green's Functions, reconstructs the surface velocity at the plate. The surface velocity from each method is then used in modal analysis to determine the comparability of frequency, damping and mode shapes. Frequency and mode shapes are also compared to an FEA model. Laser Vibrometry is a proven, direct method for determining surface velocity and subsequently calculating modal analysis results. NAH is an effective method in locating noise sources, especially those that are not well separated spatially. Little work has been done in incorporating NAH into modal analysis.

R2C: improving ab initio residue contact map prediction using dynamic fusion strategy and Gaussian noise filter.

PubMed

Yang, Jing; Jin, Qi-Yu; Zhang, Biao; Shen, Hong-Bin

2016-08-15

Inter-residue contacts in proteins dictate the topology of protein structures. They are crucial for protein folding and structural stability. Accurate prediction of residue contacts especially for long-range contacts is important to the quality of ab inito structure modeling since they can enforce strong restraints to structure assembly. In this paper, we present a new Residue-Residue Contact predictor called R2C that combines machine learning-based and correlated mutation analysis-based methods, together with a two-dimensional Gaussian noise filter to enhance the long-range residue contact prediction. Our results show that the outputs from the machine learning-based method are concentrated with better performance on short-range contacts; while for correlated mutation analysis-based approach, the predictions are widespread with higher accuracy on long-range contacts. An effective query-driven dynamic fusion strategy proposed here takes full advantages of the two different methods, resulting in an impressive overall accuracy improvement. We also show that the contact map directly from the prediction model contains the interesting Gaussian noise, which has not been discovered before. Different from recent studies that tried to further enhance the quality of contact map by removing its transitive noise, we designed a new two-dimensional Gaussian noise filter, which was especially helpful for reinforcing the long-range residue contact prediction. Tested on recent CASP10/11 datasets, the overall top L/5 accuracy of our final R2C predictor is 17.6%/15.5% higher than the pure machine learning-based method and 7.8%/8.3% higher than the correlated mutation analysis-based approach for the long-range residue contact prediction. http://www.csbio.sjtu.edu.cn/bioinf/R2C/Contact:hbshen@sjtu.edu.cn Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Selection of Variables in Cluster Analysis: An Empirical Comparison of Eight Procedures

ERIC Educational Resources Information Center

Steinley, Douglas; Brusco, Michael J.

2008-01-01

Eight different variable selection techniques for model-based and non-model-based clustering are evaluated across a wide range of cluster structures. It is shown that several methods have difficulties when non-informative variables (i.e., random noise) are included in the model. Furthermore, the distribution of the random noise greatly impacts the…

Can weekly noise levels of urban road traffic, as predominant noise source, estimate annual ones?

PubMed

Prieto Gajardo, Carlos; Barrigón Morillas, Juan Miguel; Rey Gozalo, Guillermo; Vílchez-Gómez, Rosendo

2016-11-01

The effects of noise pollution on human quality of life and health were recognised by the World Health Organisation a long time ago. There is a crucial dilemma for the study of urban noise when one is looking for proven methodologies that can allow, on the one hand, an increase in the quality of predictions, and on the other hand, saving resources in the spatial and temporal sampling. The temporal structure of urban noise is studied in this work from a different point of view. This methodology, based on Fourier analysis, is applied to several measurements of urban noise, mainly from road traffic and one-week long, carried out in two cities located on different continents and with different sociological life styles (Cáceres, Spain and Talca, Chile). Its capacity to predict annual noise levels from weekly measurements is studied. The relation between this methodology and the categorisation method is also analysed.

Mapping Urban Environmental Noise Using Smartphones.

PubMed

Zuo, Jinbo; Xia, Hao; Liu, Shuo; Qiao, Yanyou

2016-10-13

Noise mapping is an effective method of visualizing and accessing noise pollution. In this paper, a noise-mapping method based on smartphones to effectively and easily measure environmental noise is proposed. By using this method, a noise map of an entire area can be created using limited measurement data. To achieve the measurement with certain precision, a set of methods was designed to calibrate the smartphones. Measuring noise with mobile phones is different from the traditional static observations. The users may be moving at any time. Therefore, a method of attaching an additional microphone with a windscreen is proposed to reduce the wind effect. However, covering an entire area is impossible. Therefore, an interpolation method is needed to achieve full coverage of the area. To reduce the influence of spatial heterogeneity and improve the precision of noise mapping, a region-based noise-mapping method is proposed in this paper, which is based on the distribution of noise in different region types tagged by volunteers, to interpolate and combine them to create a noise map. To validate the effect of the method, a comparison of the interpolation results was made to analyse our method and the ordinary Kriging method. The result shows that our method is more accurate in reflecting the local distribution of noise and has better interpolation precision. We believe that the proposed noise-mapping method is a feasible and low-cost noise-mapping solution.

Mapping Urban Environmental Noise Using Smartphones

PubMed Central

Zuo, Jinbo; Xia, Hao; Liu, Shuo; Qiao, Yanyou

2016-01-01

Noise mapping is an effective method of visualizing and accessing noise pollution. In this paper, a noise-mapping method based on smartphones to effectively and easily measure environmental noise is proposed. By using this method, a noise map of an entire area can be created using limited measurement data. To achieve the measurement with certain precision, a set of methods was designed to calibrate the smartphones. Measuring noise with mobile phones is different from the traditional static observations. The users may be moving at any time. Therefore, a method of attaching an additional microphone with a windscreen is proposed to reduce the wind effect. However, covering an entire area is impossible. Therefore, an interpolation method is needed to achieve full coverage of the area. To reduce the influence of spatial heterogeneity and improve the precision of noise mapping, a region-based noise-mapping method is proposed in this paper, which is based on the distribution of noise in different region types tagged by volunteers, to interpolate and combine them to create a noise map. To validate the effect of the method, a comparison of the interpolation results was made to analyse our method and the ordinary Kriging method. The result shows that our method is more accurate in reflecting the local distribution of noise and has better interpolation precision. We believe that the proposed noise-mapping method is a feasible and low-cost noise-mapping solution. PMID:27754359

The prediction of airborne and structure-borne noise potential for a tire

NASA Astrophysics Data System (ADS)

Sakamoto, Nicholas Y.

Tire/pavement interaction noise is a major component of both exterior pass-by noise and vehicle interior noise. The current testing methods for ranking tires from loud to quiet require expensive equipment, multiple tires, and/or long experimental set-up and run times. If a laboratory based off-vehicle test could be used to identify the airborne and structure-borne potential of a tire from its dynamic characteristics, a relative ranking of a large group of tires could be performed at relatively modest expense. This would provide a smaller sample set of tires for follow-up testing and thus save expense for automobile OEMs. The focus of this research was identifying key noise features from a tire/pavement experiment. These results were compared against a stationary tire test in which the natural response of the tire to a forced input was measured. Since speed was identified as having some effect on the noise, an input function was also developed to allow the tires to be ranked at an appropriate speed. A relative noise model was used on a second sample set of tires to verify if the ranking could be used against interior vehicle measurements. While overall level analysis of the specified spectrum had mixed success, important noise generating features were identified, and the methods used could be improved to develop a standard off-vehicle test to predict a tire's noise potential.

Generalized Linear Covariance Analysis

NASA Technical Reports Server (NTRS)

Carpenter, James R.; Markley, F. Landis

2014-01-01

This talk presents a comprehensive approach to filter modeling for generalized covariance analysis of both batch least-squares and sequential estimators. We review and extend in two directions the results of prior work that allowed for partitioning of the state space into solve-for'' and consider'' parameters, accounted for differences between the formal values and the true values of the measurement noise, process noise, and textita priori solve-for and consider covariances, and explicitly partitioned the errors into subspaces containing only the influence of the measurement noise, process noise, and solve-for and consider covariances. In this work, we explicitly add sensitivity analysis to this prior work, and relax an implicit assumption that the batch estimator's epoch time occurs prior to the definitive span. We also apply the method to an integrated orbit and attitude problem, in which gyro and accelerometer errors, though not estimated, influence the orbit determination performance. We illustrate our results using two graphical presentations, which we call the variance sandpile'' and the sensitivity mosaic,'' and we compare the linear covariance results to confidence intervals associated with ensemble statistics from a Monte Carlo analysis.

Precision and Accuracy in PDV and VISAR

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

Ambrose, W. P.

2017-08-22

This is a technical report discussing our current level of understanding of a wide and varying distribution of uncertainties in velocity results from Photonic Doppler Velocimetry in its application to gas gun experiments. Using propagation of errors methods with statistical averaging of photon number fluctuation in the detected photocurrent and subsequent addition of electronic recording noise, we learn that the velocity uncertainty in VISAR can be written in closed form. For PDV, the non-linear frequency transform and peak fitting methods employed make propagation of errors estimates notoriously more difficult to write down in closed form expect in the limit ofmore » constant velocity and low time resolution (large analysis-window width). An alternative method of error propagation in PDV is to use Monte Carlo methods with a simulation of the time domain signal based on results from the spectral domain. A key problem for Monte Carlo estimation for an experiment is a correct estimate of that portion of the time-domain noise associated with the peak-fitting region-of-interesting in the spectral domain. Using short-time Fourier transformation spectral analysis and working with the phase dependent real and imaginary parts allows removal of amplitude-noise cross terms that invariably show up when working with correlation-based methods or FFT power spectra. Estimation of the noise associated with a given spectral region of interest is then possible. At this level of progress, we learn that Monte Carlo trials with random recording noise and initial (uncontrolled) phase yields velocity uncertainties that are not as large as those observed. In a search for additional noise sources, a speckleinterference modulation contribution with off axis rays was investigated, and was found to add a velocity variation beyond that from the recording noise (due to random interference between off axis rays), but in our experiments the speckle modulation precision was not as important as the recording noise precision. But from these investigations we do appreciate that the velocity-uncertainty itself has a wide distribution of values that varies with signal-amplitude modulation (is not a single value). To provide a rough rule of thumb for the velocity uncertainty, we computed the average of the relative standard deviation distributions from 60 recorded traces (with distributions of uncertainties roughly between 0.1 % to 1 % in each trace) and found a mean of the distribution of uncertainties for our experiments is not better than 0.4 % at an analysis window width of 5 ns (although for brief intervals it can be as good as 0.1 %). Further imagination and testing may be needed to reveal other possible hydrodynamics-related sources of velocity error in PDV.« less

Fringe-projection profilometry based on two-dimensional empirical mode decomposition.

PubMed

Zheng, Suzhen; Cao, Yiping

2013-11-01

In 3D shape measurement, because deformed fringes often contain low-frequency information degraded with random noise and background intensity information, a new fringe-projection profilometry is proposed based on 2D empirical mode decomposition (2D-EMD). The fringe pattern is first decomposed into numbers of intrinsic mode functions by 2D-EMD. Because the method has partial noise reduction, the background components can be removed to obtain the fundamental components needed to perform Hilbert transformation to retrieve the phase information. The 2D-EMD can effectively extract the modulation phase of a single direction fringe and an inclined fringe pattern because it is a full 2D analysis method and considers the relationship between adjacent lines of a fringe patterns. In addition, as the method does not add noise repeatedly, as does ensemble EMD, the data processing time is shortened. Computer simulations and experiments prove the feasibility of this method.

A novel Kalman filter based video image processing scheme for two-photon fluorescence microscopy

NASA Astrophysics Data System (ADS)

Sun, Wenqing; Huang, Xia; Li, Chunqiang; Xiao, Chuan; Qian, Wei

2016-03-01

Two-photon fluorescence microscopy (TPFM) is a perfect optical imaging equipment to monitor the interaction between fast moving viruses and hosts. However, due to strong unavoidable background noises from the culture, videos obtained by this technique are too noisy to elaborate this fast infection process without video image processing. In this study, we developed a novel scheme to eliminate background noises, recover background bacteria images and improve video qualities. In our scheme, we modified and implemented the following methods for both host and virus videos: correlation method, round identification method, tree-structured nonlinear filters, Kalman filters, and cell tracking method. After these procedures, most of noises were eliminated and host images were recovered with their moving directions and speed highlighted in the videos. From the analysis of the processed videos, 93% bacteria and 98% viruses were correctly detected in each frame on average.

Automated image quality assessment for chest CT scans.

PubMed

Reeves, Anthony P; Xie, Yiting; Liu, Shuang

2018-02-01

Medical image quality needs to be maintained at standards sufficient for effective clinical reading. Automated computer analytic methods may be applied to medical images for quality assessment. For chest CT scans in a lung cancer screening context, an automated quality assessment method is presented that characterizes image noise and image intensity calibration. This is achieved by image measurements in three automatically segmented homogeneous regions of the scan: external air, trachea lumen air, and descending aorta blood. Profiles of CT scanner behavior are also computed. The method has been evaluated on both phantom and real low-dose chest CT scans and results show that repeatable noise and calibration measures may be realized by automated computer algorithms. Noise and calibration profiles show relevant differences between different scanners and protocols. Automated image quality assessment may be useful for quality control for lung cancer screening and may enable performance improvements to automated computer analysis methods. © 2017 American Association of Physicists in Medicine.

Validation of helicopter noise prediction techniques

NASA Technical Reports Server (NTRS)

Succi, G. P.

1981-01-01

The current techniques of helicopter rotor noise prediction attempt to describe the details of the noise field precisely and remove the empiricisms and restrictions inherent in previous methods. These techniques require detailed inputs of the rotor geometry, operating conditions, and blade surface pressure distribution. The purpose of this paper is to review those techniques in general and the Farassat/Nystrom analysis in particular. The predictions of the Farassat/Nystrom noise computer program, using both measured and calculated blade surface pressure data, are compared to measured noise level data. This study is based on a contract from NASA to Bolt Beranek and Newman Inc. with measured data from the AH-1G Helicopter Operational Loads Survey flight test program supplied by Bell Helicopter Textron.

Single Photon Counting Performance and Noise Analysis of CMOS SPAD-Based Image Sensors.

PubMed

Dutton, Neale A W; Gyongy, Istvan; Parmesan, Luca; Henderson, Robert K

2016-07-20

SPAD-based solid state CMOS image sensors utilising analogue integrators have attained deep sub-electron read noise (DSERN) permitting single photon counting (SPC) imaging. A new method is proposed to determine the read noise in DSERN image sensors by evaluating the peak separation and width (PSW) of single photon peaks in a photon counting histogram (PCH). The technique is used to identify and analyse cumulative noise in analogue integrating SPC SPAD-based pixels. The DSERN of our SPAD image sensor is exploited to confirm recent multi-photon threshold quanta image sensor (QIS) theory. Finally, various single and multiple photon spatio-temporal oversampling techniques are reviewed.

Nonlocal maximum likelihood estimation method for denoising multiple-coil magnetic resonance images.

PubMed

Rajan, Jeny; Veraart, Jelle; Van Audekerke, Johan; Verhoye, Marleen; Sijbers, Jan

2012-12-01

Effective denoising is vital for proper analysis and accurate quantitative measurements from magnetic resonance (MR) images. Even though many methods were proposed to denoise MR images, only few deal with the estimation of true signal from MR images acquired with phased-array coils. If the magnitude data from phased array coils are reconstructed as the root sum of squares, in the absence of noise correlations and subsampling, the data is assumed to follow a non central-χ distribution. However, when the k-space is subsampled to increase the acquisition speed (as in GRAPPA like methods), noise becomes spatially varying. In this note, we propose a method to denoise multiple-coil acquired MR images. Both the non central-χ distribution and the spatially varying nature of the noise is taken into account in the proposed method. Experiments were conducted on both simulated and real data sets to validate and to demonstrate the effectiveness of the proposed method. Copyright © 2012 Elsevier Inc. All rights reserved.

A surface acoustic wave response detection method for passive wireless torque sensor

NASA Astrophysics Data System (ADS)

Fan, Yanping; Kong, Ping; Qi, Hongli; Liu, Hongye; Ji, Xiaojun

2018-01-01

This paper presents an effective surface acoustic wave (SAW) response detection method for the passive wireless SAW torque sensor to improve the measurement accuracy. An analysis was conducted on the relationship between the response energy-entropy and the bandwidth of SAW resonator (SAWR). A self-correlation method was modified to suppress the blurred white noise and highlight the attenuation characteristic of wireless SAW response. The SAW response was detected according to both the variation and the duration of energy-entropy ascension of an acquired RF signal. Numerical simulation results showed that the SAW response can be detected even when the signal-to-noise ratio (SNR) is 6dB. The proposed SAW response detection method was evaluated with several experiments at different conditions. The SAW response can be well distinguished from the sinusoidal signal and the noise. The performance of the SAW torque measurement system incorporating the detection method was tested. The obtained repeatability error was 0.23% and the linearity was 0.9934, indicating the validity of the detection method.

Noise, sampling, and the number of projections in cone-beam CT with a flat-panel detector

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

Zhao, Z.; Gang, G. J.; Siewerdsen, J. H., E-mail: jeff.siewerdsen@jhu.edu

2014-06-15

Purpose: To investigate the effect of the number of projection views on image noise in cone-beam CT (CBCT) with a flat-panel detector. Methods: This fairly fundamental consideration in CBCT system design and operation was addressed experimentally (using a phantom presenting a uniform medium as well as statistically motivated “clutter”) and theoretically (using a cascaded systems model describing CBCT noise) to elucidate the contributing factors of quantum noise (σ{sub Q}), electronic noise (σ{sub E}), and view aliasing (σ{sub view}). Analysis included investigation of the noise, noise-power spectrum, and modulation transfer function as a function of the number of projections (N{sub proj}),more » dose (D{sub tot}), and voxel size (b{sub vox}). Results: The results reveal a nonmonotonic relationship between image noise andN{sub proj} at fixed total dose: for the CBCT system considered, noise decreased with increasing N{sub proj} due to reduction of view sampling effects in the regime N{sub proj} <∼200, above which noise increased with N{sub proj} due to increased electronic noise. View sampling effects were shown to depend on the heterogeneity of the object in a direct analytical relationship to power-law anatomical clutter of the form κ/f {sup β}—and a general model of individual noise components (σ{sub Q}, σ{sub E}, and σ{sub view}) demonstrated agreement with measurements over a broad range in N{sub proj}, D{sub tot}, and b{sub vox}. Conclusions: The work elucidates fairly basic elements of CBCT noise in a manner that demonstrates the role of distinct noise components (viz., quantum, electronic, and view sampling noise). For configurations fairly typical of CBCT with a flat-panel detector (FPD), the analysis reveals a “sweet spot” (i.e., minimum noise) in the rangeN{sub proj} ∼ 250–350, nearly an order of magnitude lower in N{sub proj} than typical of multidetector CT, owing to the relatively high electronic noise in FPDs. The analysis explicitly relates view aliasing and quantum noise in a manner that includes aspects of the object (“clutter”) and imaging chain (including nonidealities of detector blur and electronic noise) to provide a more rigorous basis for commonly held intuition and heurism in CBCT system design and operation.« less

Comparison of DIGE and post-stained gel electrophoresis with both traditional and SameSpots analysis for quantitative proteomics.

PubMed

Karp, Natasha A; Feret, Renata; Rubtsov, Denis V; Lilley, Kathryn S

2008-03-01

2-DE is an important tool in quantitative proteomics. Here, we compare the deep purple (DP) system with DIGE using both a traditional and the SameSpots approach to gel analysis. Missing values in the traditional approach were found to be a significant issue for both systems. SameSpots attempts to address the missing value problem. SameSpots was found to increase the proportion of low volume data for DP but not for DIGE. For all the analysis methods applied in this study, the assumptions of parametric tests were met. Analysis of the same images gave significantly lower noise with SameSpots (over traditional) for DP, but no difference for DIGE. We propose that SameSpots gave lower noise with DP due to the stabilisation of the spot area by the common spot outline, but this was not seen with DIGE due to the co-detection process which stabilises the area selected. For studies where measurement of small abundance changes is required, a cost-benefit analysis highlights that DIGE was significantly cheaper regardless of the analysis methods. For studies analysing large changes, DP with SameSpots could be an effective alternative to DIGE but this will be dependent on the biological noise of the system under investigation.

A dual estimate method for aeromagnetic compensation

NASA Astrophysics Data System (ADS)

Ma, Ming; Zhou, Zhijian; Cheng, Defu

2017-11-01

Scalar aeromagnetic surveys have played a vital role in prospecting. However, before analysis of the surveys’ aeromagnetic data is possible, the aircraft’s magnetic interference should be removed. The extensively adopted linear model for aeromagnetic compensation is computationally efficient but faces an underfitting problem. On the other hand, the neural model proposed by Williams is more powerful at fitting but always suffers from an overfitting problem. This paper starts off with an analysis of these two models and then proposes a dual estimate method to combine them together to improve accuracy. This method is based on an unscented Kalman filter, but a gradient descent method is implemented over the iteration so that the parameters of the linear model are adjustable during flight. The noise caused by the neural model’s overfitting problem is suppressed by introducing an observation noise.

Noise power spectrum of the fixed pattern noise in digital radiography detectors

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

Kim, Dong Sik, E-mail: dskim@hufs.ac.kr; Kim, Eun

Purpose: The fixed pattern noise in radiography image detectors is caused by various sources. Multiple readout circuits with gate drivers and charge amplifiers are used to efficiently acquire the pixel voltage signals. However, the multiple circuits are not identical and thus yield nonuniform system gains. Nonuniform sensitivities are also produced from local variations in the charge collection elements. Furthermore, in phosphor-based detectors, the optical scattering at the top surface of the columnar CsI growth, the grain boundaries, and the disorder structure causes spatial sensitivity variations. These nonuniform gains or sensitivities cause fixed pattern noise and degrade the detector performance, evenmore » though the noise problem can be partially alleviated by using gain correction techniques. Hence, in order to develop good detectors, comparative analysis of the energy spectrum of the fixed pattern noise is important. Methods: In order to observe the energy spectrum of the fixed pattern noise, a normalized noise power spectrum (NNPS) of the fixed pattern noise is considered in this paper. Since the fixed pattern noise is mainly caused by the nonuniform gains, we call the spectrum the gain NNPS. We first asymptotically observe the gain NNPS and then formulate two relationships to calculate the gain NNPS based on a nonuniform-gain model. Since the gain NNPS values are quite low compared to the usual NNPS, measuring such a low NNPS value is difficult. By using the average of the uniform exposure images, a robust measuring method for the gain NNPS is proposed in this paper. Results: By using the proposed measuring method, the gain NNPS curves of several prototypes of general radiography and mammography detectors were measured to analyze their fixed pattern noise properties. We notice that a direct detector, which is based on the a-Se photoconductor, showed lower gain NNPS than the indirect-detector case, which is based on the CsI scintillator. By comparing the gain NNPS curves of the indirect detectors, we could analyze the scintillator properties depending on the techniques for the scintillator surface processing. Conclusions: A robust measuring method for the NNPS of the fixed pattern noise of a radiography detector is proposed in this paper. The method can measure a stable gain NNPS curve, even though the fixed pattern noise level is quite low. From the measured gain NNPS curves, we can compare and analyze the detector properties in terms of producing the fixed pattern noise.« less

Chaos in brake squeal noise

NASA Astrophysics Data System (ADS)

Oberst, S.; Lai, J. C. S.

2011-02-01

Brake squeal has become an increasing concern to the automotive industry because of warranty costs and the requirement for continued interior vehicle noise reduction. Most research has been directed to either analytical and experimental studies of brake squeal mechanisms or the prediction of brake squeal propensity using finite element methods. By comparison, there is a lack of systematic analysis of brake squeal data obtained from a noise dynamometer. It is well known that brake squeal is a nonlinear transient phenomenon and a number of studies using analytical and experimental models of brake systems (e.g., pin-on-disc) indicate that it could be treated as a chaotic phenomenon. Data obtained from a full brake system on a noise dynamometer were examined with nonlinear analysis techniques. The application of recurrence plots reveals chaotic structures even in noisy data from the squealing events. By separating the time series into different regimes, lower dimensional attractors are isolated and quantified by dynamic invariants such as correlation dimension estimates or Lyapunov exponents. Further analysis of the recurrence plot of squealing events by means of recurrence quantification analysis measures reveals different regimes of laminar and random behaviour, periodicity and chaos-forming recurrent transitions. These results help to classify brake squeal mechanisms and to enhance understanding of friction-related noise phenomena.

Removal of intensity bias in magnitude spin-echo MRI images by nonlinear diffusion filtering

NASA Astrophysics Data System (ADS)

Samsonov, Alexei A.; Johnson, Chris R.

2004-05-01

MRI data analysis is routinely done on the magnitude part of complex images. While both real and imaginary image channels contain Gaussian noise, magnitude MRI data are characterized by Rice distribution. However, conventional filtering methods often assume image noise to be zero mean and Gaussian distributed. Estimation of an underlying image using magnitude data produces biased result. The bias may lead to significant image errors, especially in areas of low signal-to-noise ratio (SNR). The incorporation of the Rice PDF into a noise filtering procedure can significantly complicate the method both algorithmically and computationally. In this paper, we demonstrate that inherent image phase smoothness of spin-echo MRI images could be utilized for separate filtering of real and imaginary complex image channels to achieve unbiased image denoising. The concept is demonstrated with a novel nonlinear diffusion filtering scheme developed for complex image filtering. In our proposed method, the separate diffusion processes are coupled through combined diffusion coefficients determined from the image magnitude. The new method has been validated with simulated and real MRI data. The new method has provided efficient denoising and bias removal in conventional and black-blood angiography MRI images obtained using fast spin echo acquisition protocols.

Determining cantilever stiffness from thermal noise.

PubMed

Lübbe, Jannis; Temmen, Matthias; Rahe, Philipp; Kühnle, Angelika; Reichling, Michael

2013-01-01

We critically discuss the extraction of intrinsic cantilever properties, namely eigenfrequency f n , quality factor Q n and specifically the stiffness k n of the nth cantilever oscillation mode from thermal noise by an analysis of the power spectral density of displacement fluctuations of the cantilever in contact with a thermal bath. The practical applicability of this approach is demonstrated for several cantilevers with eigenfrequencies ranging from 50 kHz to 2 MHz. As such an analysis requires a sophisticated spectral analysis, we introduce a new method to determine k n from a spectral analysis of the demodulated oscillation signal of the excited cantilever that can be performed in the frequency range of 10 Hz to 1 kHz regardless of the eigenfrequency of the cantilever. We demonstrate that the latter method is in particular useful for noncontact atomic force microscopy (NC-AFM) where the required simple instrumentation for spectral analysis is available in most experimental systems.

Stochastic resonance in a fractional oscillator driven by multiplicative quadratic noise

NASA Astrophysics Data System (ADS)

Ren, Ruibin; Luo, Maokang; Deng, Ke

2017-02-01

Stochastic resonance of a fractional oscillator subject to an external periodic field as well as to multiplicative and additive noise is investigated. The fluctuations of the eigenfrequency are modeled as the quadratic function of the trichotomous noise. Applying the moment equation method and Shapiro-Loginov formula, we obtain the exact expression of the complex susceptibility and related stability criteria. Theoretical analysis and numerical simulations indicate that the spectral amplification (SPA) depends non-monotonicly both on the external driving frequency and the parameters of the quadratic noise. In addition, the investigations into fractional stochastic systems have suggested that both the noise parameters and the memory effect can induce the phenomenon of stochastic multi-resonance (SMR), which is previously reported and believed to be absent in the case of the multiplicative noise with only a linear term.

Intrinsic noise analysis and stochastic simulation on transforming growth factor beta signal pathway

NASA Astrophysics Data System (ADS)

Wang, Lu; Ouyang, Qi

2010-10-01

A typical biological cell lives in a small volume at room temperature; the noise effect on the cell signal transduction pathway may play an important role in its dynamics. Here, using the transforming growth factor-β signal transduction pathway as an example, we report our stochastic simulations of the dynamics of the pathway and introduce a linear noise approximation method to calculate the transient intrinsic noise of pathway components. We compare the numerical solutions of the linear noise approximation with the statistic results of chemical Langevin equations, and find that they are quantitatively in agreement with the other. When transforming growth factor-β dose decreases to a low level, the time evolution of noise fluctuation of nuclear Smad2—Smad4 complex indicates the abnormal enhancement in the transient signal activation process.

Towards a general framework for including noise impacts in LCA.

PubMed

Cucurachi, Stefano; Heijungs, Reinout; Ohlau, Katrin

Several damages have been associated with the exposure of human beings to noise. These include auditory effects, i.e., hearing impairment, but also non-auditory physiological ones such as hypertension and ischemic heart disease, or psychological ones such as annoyance, depression, sleep disturbance, limited performance of cognitive tasks or inadequate cognitive development. Noise can also interfere with intended activities, both in daytime and nighttime. ISO 14'040 also indicated the necessity of introducing noise, together with other less developed impact categories, in a complete LCA study, possibly changing the results of many LCA studies already available. The attempts available in the literature focused on the integration of transportation noise in LCA. Although being considered the most frequent source of intrusive impact, transportation noise is not the only type of noise that can have a malign impact on public health. Several other sources of noise such as industrial or occupational need to be taken into account to have a complete consideration of noise into LCA. Major life cycle inventories (LCI) typically do not contain data on noise emissions yet and characterisation factors are not yet clearly defined. The aim of the present paper is to briefly review what is already available in the field and propose a new framework for the consideration of human health impacts of any type of noise that could be of interest in the LCA practice, providing indications for the introduction of noise in LCI and analysing what data is already available and, in the form of a research agenda, what other resources would be needed to reach a complete coverage of the problem. The literature production related to the impacts of noise on human health has been analysed, with considerations of impacts caused by transportation noise as well as occupational and industrial noise. The analysis of the specialist medical literature allowed for a better understanding of how to deal with the epidemiological findings from an LCA perspective and identify areas still missing dose-response relations. A short review of the state-of-science in the field of noise and LCA is presented with an expansion to other contributions in the field subsequent to the comprehensive work by Althaus et al. (2009a; 2009b). Focusing on the analogy between toxicological analysis of pollutants and noise impact evaluation, an alternative approach is suggested, which is oriented to the consideration of any type of noise in LCA and not solely of transportation noise. A multi-step framework is presented as a method for the inclusion of noise impacts on human health in LCA. A theoretical structural framework for the inclusion of noise impacts in LCA is provided as a basis for future modelling expansions in the field. Rather than evaluating traffic/transportation noise, the method focuses on the consideration of the noise level and its impact on human health, regardless of the source producing the noise in an analogous manner as considered in the fields of toxicology and common noise evaluation practices combined. The resulting framework will constitute the basis for the development of a more detailed mathematical model for the inclusion of noise in LCA. The toxicological background and the experience of the analysis of the release of chemicals in LCA seem to provide sufficient ground for the inclusion of noise in LCA: taken into account the physical differences and the uniqueness of noise as an impact, the procedure applied to the release of chemicals during a product life cycle is key for a valuable inclusion of noise in the LCA logic. It is fundamental for the development of research in the field of LCA and noise to consider any type of noise. Further studies are needed to contribute to the inclusion of noise sources and noise impacts in LCA. In this paper, a structure is proposed that will be expanded and adapted in the future and which forms the basic framework for the successive modelling phase.

Hybrid Analysis of Engine Core Noise

NASA Astrophysics Data System (ADS)

O'Brien, Jeffrey; Kim, Jeonglae; Ihme, Matthias

2015-11-01

Core noise, or the noise generated within an aircraft engine, is becoming an increasing concern for the aviation industry as other noise sources are progressively reduced. The prediction of core noise generation and propagation is especially challenging for computationalists since it involves extensive multiphysics including chemical reaction and moving blades in addition to the aerothermochemical effects of heated jets. In this work, a representative engine flow path is constructed using experimentally verified geometries to simulate the physics of core noise. A combustor, single-stage turbine, nozzle and jet are modeled in separate calculations using appropriate high fidelity techniques including LES, actuator disk theory and Ffowcs-Williams Hawkings surfaces. A one way coupling procedure is developed for passing fluctuations downstream through the flowpath. This method effectively isolates the core noise from other acoustic sources, enables straightforward study of the interaction between core noise and jet exhaust, and allows for simple distinction between direct and indirect noise. The impact of core noise on the farfield jet acoustics is studied extensively and the relative efficiency of different disturbance types and shapes is examined in detail.

Background noise spectra of global seismic stations

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

Wada, M.M.; Claassen, J.P.

1996-08-01

Over an extended period of time station noise spectra were collected from various sources for use in estimating the detection and location performance of global networks of seismic stations. As the database of noise spectra enlarged and duplicate entries became available, an effort was mounted to more carefully select station noise spectra while discarding others. This report discusses the methodology and criteria by which the noise spectra were selected. It also identifies and illustrates the station noise spectra which survived the selection process and which currently contribute to the modeling efforts. The resulting catalog of noise statistics not only benefitsmore » those who model network performance but also those who wish to select stations on the basis of their noise level as may occur in designing networks or in selecting seismological data for analysis on the basis of station noise level. In view of the various ways by which station noise were estimated by the different contributors, it is advisable that future efforts which predict network performance have available station noise data and spectral estimation methods which are compatible with the statistics underlying seismic noise. This appropriately requires (1) averaging noise over seasonal and/or diurnal cycles, (2) averaging noise over time intervals comparable to those employed by actual detectors, and (3) using logarithmic measures of the noise.« less

Integral-equation based methods for parameter estimation in output pulses of radiation detectors: Application in nuclear medicine and spectroscopy

NASA Astrophysics Data System (ADS)

Mohammadian-Behbahani, Mohammad-Reza; Saramad, Shahyar

2018-04-01

Model based analysis methods are relatively new approaches for processing the output data of radiation detectors in nuclear medicine imaging and spectroscopy. A class of such methods requires fast algorithms for fitting pulse models to experimental data. In order to apply integral-equation based methods for processing the preamplifier output pulses, this article proposes a fast and simple method for estimating the parameters of the well-known bi-exponential pulse model by solving an integral equation. The proposed method needs samples from only three points of the recorded pulse as well as its first and second order integrals. After optimizing the sampling points, the estimation results were calculated and compared with two traditional integration-based methods. Different noise levels (signal-to-noise ratios from 10 to 3000) were simulated for testing the functionality of the proposed method, then it was applied to a set of experimental pulses. Finally, the effect of quantization noise was assessed by studying different sampling rates. Promising results by the proposed method endorse it for future real-time applications.

3-component beamforming analysis of ambient seismic noise field for Love and Rayleigh wave source directions

NASA Astrophysics Data System (ADS)

Juretzek, Carina; Hadziioannou, Céline

2014-05-01

Our knowledge about common and different origins of Love and Rayleigh waves observed in the microseism band of the ambient seismic noise field is still limited, including the understanding of source locations and source mechanisms. Multi-component array methods are suitable to address this issue. In this work we use a 3-component beamforming algorithm to obtain source directions and polarization states of the ambient seismic noise field within the primary and secondary microseism bands recorded at the Gräfenberg array in southern Germany. The method allows to distinguish between different polarized waves present in the seismic noise field and estimates Love and Rayleigh wave source directions and their seasonal variations using one year of array data. We find mainly coinciding directions for the strongest acting sources of both wave types at the primary microseism and different source directions at the secondary microseism.

A Ffowcs Williams and Hawkings formulation for hydroacoustic analysis of propeller sheet cavitation

NASA Astrophysics Data System (ADS)

Testa, C.; Ianniello, S.; Salvatore, F.

2018-01-01

A novel hydroacoustic formulation for the prediction of tonal noise emitted by marine propellers in presence of unsteady sheet cavitation, is presented. The approach is based on the standard Ffowcs Williams and Hawkings equation and the use of transpiration (velocity and acceleration) terms, accounting for the time evolution of the vapour cavity attached on the blade surface. Drawbacks and potentialities of the method are tested on a marine propeller operating in a nonhomogeneous onset flow, by exploiting the hydrodynamic data from a potential-based panel method equipped with a sheet cavitation model and comparing the noise predictions with those carried out by an alternative numerical approach, documented in literature. It is shown that the proposed formulation yields a one-to-one correlation between emitted noise and sheet cavitation dynamics, carrying out accurate predictions in terms of noise magnitude and directivity.

The correlation between acoustic and magnetic properties in the long working metal boiler drum with the parameters of the electron microscope

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

Ababkov, Nikolai, E-mail: n.ababkov@rambler.ru; Smirnov, Alexander, E-mail: galvas.kem@gmail.com

The present paper presents comparative analysis of measurement results of acoustic and magnetic properties in long working metal of boiler drums and the results obtained by methods of electronic microscopy. The structure of the metal sample from the fracture zone to the base metal (metal working sample long) and the center of the base metal before welding (weld metal sample) was investigated by electron microscopy. Studies performed by spectral acoustic, magnetic noise and electron microscopic methods were conducted on the same plots and the same samples of long working and weld metal of high-pressure boiler drums. The analysis of researchmore » results showed high sensitivity of spectral-acoustic and magnetic-noise methods to definition changes of microstructure parameters. Practical application of spectral-acoustic and magnetic noise NDT method is possible for the detection of irregularities and changes in structural and phase state of the long working and weld metal of boiler drums, made of a special molybdenum steel (such as 20M). The above technique can be used to evaluate the structure and physical-mechanical properties of the long working metal of boiler drums in the energy sector.« less

Noise produced by turbulent flow into a rotor: Theory manual for noise calculation

NASA Technical Reports Server (NTRS)

Amiet, R. K.

1989-01-01

An analysis is presented for the calculation of noise produced by turbulent flow into a helicopter rotor. The method is based on the analysis of Amiet for the sound produced by an airfoil moving in rectilinear motion through a turbulent flow field. The rectilinear motion results are used in a quasi-steady manner to calculate the instantaneous spectrum of the rotor noise at any given rotor position; the overall spectrum is then found by averaging the instantaneous spectrum over all rotor azimuth angles. Account is taken of the fact that the rotor spends different amounts of retarded time at different rotor positions. Blade to blade correlation is included in the analysis, leading to harmonics of blade passing frequency. The spectrum of the turbulence entering the rotor is calculated by applying rapid distortion theory to an isotropic turbulence spectrum, assuming that the turbulence is stretched as it is pulled into the rotor. The inputs to the program are obtained from the atmospheric turbulence model and mean flow distortion calculation, described in another volume of this set of reports. The analytical basis is provided for a module which was incorporated in NASA's ROTONET helicopter noise prediction program.

Assessment of NASA's Aircraft Noise Prediction Capability

NASA Technical Reports Server (NTRS)

Dahl, Milo D. (Editor)

2012-01-01

A goal of NASA s Fundamental Aeronautics Program is the improvement of aircraft noise prediction. This document provides an assessment, conducted from 2006 to 2009, on the current state of the art for aircraft noise prediction by carefully analyzing the results from prediction tools and from the experimental databases to determine errors and uncertainties and compare results to validate the predictions. The error analysis is included for both the predictions and the experimental data and helps identify where improvements are required. This study is restricted to prediction methods and databases developed or sponsored by NASA, although in many cases they represent the current state of the art for industry. The present document begins with an introduction giving a general background for and a discussion on the process of this assessment followed by eight chapters covering topics at both the system and the component levels. The topic areas, each with multiple contributors, are aircraft system noise, engine system noise, airframe noise, fan noise, liner physics, duct acoustics, jet noise, and propulsion airframe aeroacoustics.

How to deal with the high condition number of the noise covariance matrix of gravity field functionals synthesised from a satellite-only global gravity field model?

NASA Astrophysics Data System (ADS)

Klees, R.; Slobbe, D. C.; Farahani, H. H.

2018-03-01

The posed question arises for instance in regional gravity field modelling using weighted least-squares techniques if the gravity field functionals are synthesised from the spherical harmonic coefficients of a satellite-only global gravity model (GGM), and are used as one of the noisy datasets. The associated noise covariance matrix, appeared to be extremely ill-conditioned with a singular value spectrum that decayed gradually to zero without any noticeable gap. We analysed three methods to deal with the ill-conditioned noise covariance matrix: Tihonov regularisation of the noise covariance matrix in combination with the standard formula for the weighted least-squares estimator, a formula of the weighted least-squares estimator, which does not involve the inverse noise covariance matrix, and an estimator based on Rao's unified theory of least-squares. Our analysis was based on a numerical experiment involving a set of height anomalies synthesised from the GGM GOCO05s, which is provided with a full noise covariance matrix. We showed that the three estimators perform similar, provided that the two regularisation parameters each method knows were chosen properly. As standard regularisation parameter choice rules do not apply here, we suggested a new parameter choice rule, and demonstrated its performance. Using this rule, we found that the differences between the three least-squares estimates were within noise. For the standard formulation of the weighted least-squares estimator with regularised noise covariance matrix, this required an exceptionally strong regularisation, much larger than one expected from the condition number of the noise covariance matrix. The preferred method is the inversion-free formulation of the weighted least-squares estimator, because of its simplicity with respect to the choice of the two regularisation parameters.

Gden: An indicator for European noise maps comparison and to support action plans.

PubMed

Licitra, Gaetano; Ascari, Elena

2014-06-01

Ten years after the approval of the Environmental Noise Directive 2002/49/EC (END) a large experience have been acquired to develop noise maps and action plans: the Noise Observation and Information Service for Europe maintained by the European Environment Agency (EEA) on behalf of the European Commission contains all data delivered in accordance with the END by Members States within the first round of implementation of the END. This large database should be useful to evaluate the pollution of Europe and to guide policy makers to establish best practices. However, local procedures and national methods do not permit a direct comparison of data reported. A comparison within agglomerations in EU is here carried out in order to find suitable indicators to identify most polluted cities despite different methods used. Critical and quiet areas have been assessed in action plans, but national laws and requirements are various, as different indicators used for their identification. The analysis was performed on noise exposure classes distribution, grouping them together using Gden and Gnight indicators to offer a new tool for presenting noise maps of the cities to the public permitting their comparison and for drawing detailed action plans. Strong relationship between these indicators and highly annoyed and highly sleep-disturbed people percentages are obtained. Furthermore, a comparison between Gden and Qcity Noise Scoring for local hot spot identification is carried out for the agglomeration of Pisa, where different transportation noise sources are present. The final goal is to define faster methods for suitable indicators calculation in hot spot identifications. © 2013 Elsevier B.V. All rights reserved.

The Augmented Lagrange Multipliers Method for Matrix Completion from Corrupted Samplings with Application to Mixed Gaussian-Impulse Noise Removal

PubMed Central

Meng, Fan; Yang, Xiaomei; Zhou, Chenghu

2014-01-01

This paper studies the problem of the restoration of images corrupted by mixed Gaussian-impulse noise. In recent years, low-rank matrix reconstruction has become a research hotspot in many scientific and engineering domains such as machine learning, image processing, computer vision and bioinformatics, which mainly involves the problem of matrix completion and robust principal component analysis, namely recovering a low-rank matrix from an incomplete but accurate sampling subset of its entries and from an observed data matrix with an unknown fraction of its entries being arbitrarily corrupted, respectively. Inspired by these ideas, we consider the problem of recovering a low-rank matrix from an incomplete sampling subset of its entries with an unknown fraction of the samplings contaminated by arbitrary errors, which is defined as the problem of matrix completion from corrupted samplings and modeled as a convex optimization problem that minimizes a combination of the nuclear norm and the -norm in this paper. Meanwhile, we put forward a novel and effective algorithm called augmented Lagrange multipliers to exactly solve the problem. For mixed Gaussian-impulse noise removal, we regard it as the problem of matrix completion from corrupted samplings, and restore the noisy image following an impulse-detecting procedure. Compared with some existing methods for mixed noise removal, the recovery quality performance of our method is dominant if images possess low-rank features such as geometrically regular textures and similar structured contents; especially when the density of impulse noise is relatively high and the variance of Gaussian noise is small, our method can outperform the traditional methods significantly not only in the simultaneous removal of Gaussian noise and impulse noise, and the restoration ability for a low-rank image matrix, but also in the preservation of textures and details in the image. PMID:25248103

Numerical method for high accuracy index of refraction estimation for spectro-angular surface plasmon resonance systems.

PubMed

Alleyne, Colin J; Kirk, Andrew G; Chien, Wei-Yin; Charette, Paul G

2008-11-24

An eigenvector analysis based algorithm is presented for estimating refractive index changes from 2-D reflectance/dispersion images obtained with spectro-angular surface plasmon resonance systems. High resolution over a large dynamic range can be achieved simultaneously. The method performs well in simulations with noisy data maintaining an error of less than 10(-8) refractive index units with up to six bits of noise on 16 bit quantized image data. Experimental measurements show that the method results in a much higher signal to noise ratio than the standard 1-D weighted centroid dip finding algorithm.

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.

Robustifying blind image deblurring methods by simple filters

NASA Astrophysics Data System (ADS)

Liu, Yan; Zeng, Xiangrong; Huangpeng, Qizi; Fan, Jun; Zhou, Jinglun; Feng, Jing

2016-07-01

The state-of-the-art blind image deblurring (BID) methods are sensitive to noise, and most of them can deal with only small levels of Gaussian noise. In this paper, we use simple filters to present a robust BID framework which is able to robustify exiting BID methods to high-level Gaussian noise or/and Non-Gaussian noise. Experiments on images in presence of Gaussian noise, impulse noise (salt-and-pepper noise and random-valued noise) and mixed Gaussian-impulse noise, and a real-world blurry and noisy image show that the proposed method can faster estimate sharper kernels and better images, than that obtained by other methods.

Relative velocity change measurement based on seismic noise analysis in exploration geophysics

NASA Astrophysics Data System (ADS)

Corciulo, M.; Roux, P.; Campillo, M.; Dubuq, D.

2011-12-01

Passive monitoring techniques based on noise cross-correlation analysis are still debated in exploration geophysics even if recent studies showed impressive performance in seismology at larger scale. Time evolution of complex geological structure using noise data includes localization of noise sources and measurement of relative velocity variations. Monitoring relative velocity variations only requires the measurement of phase shifts of seismic noise cross-correlation functions computed for successive time recordings. The existing algorithms, such as the Stretching and the Doublet, classically need great efforts in terms of computation time, making them not practical when continuous dataset on dense arrays are acquired. We present here an innovative technique for passive monitoring based on the measure of the instantaneous phase of noise-correlated signals. The Instantaneous Phase Variation (IPV) technique aims at cumulating the advantages of the Stretching and Doublet methods while proposing a faster measurement of the relative velocity change. The IPV takes advantage of the Hilbert transform to compute in the time domain the phase difference between two noise correlation functions. The relative velocity variation is measured through the slope of the linear regression of the phase difference curve as a function of correlation time. The large amount of noise correlation functions, classically available at exploration scale on dense arrays, allows for a statistical analysis that further improves the precision of the estimation of the velocity change. In this work, numerical tests first aim at comparing the IPV performance to the Stretching and Doublet techniques in terms of accuracy, robustness and computation time. Then experimental results are presented using a seismic noise dataset with five days of continuous recording on 397 geophones spread on a ~1 km-squared area.

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.

Analysis of helicopter position determination methods

DOT National Transportation Integrated Search

1992-01-01

The Federal Aviation Administration (FAA), along with members of the helicopter industry, is continually searching for methods to reduce the cost and effort required for helicopter noise certification. In September 1992, the FAA adopted Appendix J of...

Robust and transferable quantification of NMR spectral quality using IROC analysis

NASA Astrophysics Data System (ADS)

Zambrello, Matthew A.; Maciejewski, Mark W.; Schuyler, Adam D.; Weatherby, Gerard; Hoch, Jeffrey C.

2017-12-01

Non-Fourier methods are increasingly utilized in NMR spectroscopy because of their ability to handle nonuniformly-sampled data. However, non-Fourier methods present unique challenges due to their nonlinearity, which can produce nonrandom noise and render conventional metrics for spectral quality such as signal-to-noise ratio unreliable. The lack of robust and transferable metrics (i.e. applicable to methods exhibiting different nonlinearities) has hampered comparison of non-Fourier methods and nonuniform sampling schemes, preventing the identification of best practices. We describe a novel method, in situ receiver operating characteristic analysis (IROC), for characterizing spectral quality based on the Receiver Operating Characteristic curve. IROC utilizes synthetic signals added to empirical data as "ground truth", and provides several robust scalar-valued metrics for spectral quality. This approach avoids problems posed by nonlinear spectral estimates, and provides a versatile quantitative means of characterizing many aspects of spectral quality. We demonstrate applications to parameter optimization in Fourier and non-Fourier spectral estimation, critical comparison of different methods for spectrum analysis, and optimization of nonuniform sampling schemes. The approach will accelerate the discovery of optimal approaches to nonuniform sampling experiment design and non-Fourier spectrum analysis for multidimensional NMR.

On Correlated-noise Analyses Applied to Exoplanet Light Curves

NASA Astrophysics Data System (ADS)

Cubillos, Patricio; Harrington, Joseph; Loredo, Thomas J.; Lust, Nate B.; Blecic, Jasmina; Stemm, Madison

2017-01-01

Time-correlated noise is a significant source of uncertainty when modeling exoplanet light-curve data. A correct assessment of correlated noise is fundamental to determine the true statistical significance of our findings. Here, we review three of the most widely used correlated-noise estimators in the exoplanet field, the time-averaging, residual-permutation, and wavelet-likelihood methods. We argue that the residual-permutation method is unsound in estimating the uncertainty of parameter estimates. We thus recommend to refrain from this method altogether. We characterize the behavior of the time averaging’s rms-versus-bin-size curves at bin sizes similar to the total observation duration, which may lead to underestimated uncertainties. For the wavelet-likelihood method, we note errors in the published equations and provide a list of corrections. We further assess the performance of these techniques by injecting and retrieving eclipse signals into synthetic and real Spitzer light curves, analyzing the results in terms of the relative-accuracy and coverage-fraction statistics. Both the time-averaging and wavelet-likelihood methods significantly improve the estimate of the eclipse depth over a white-noise analysis (a Markov-chain Monte Carlo exploration assuming uncorrelated noise). However, the corrections are not perfect when retrieving the eclipse depth from Spitzer data sets, these methods covered the true (injected) depth within the 68% credible region in only ˜45%-65% of the trials. Lastly, we present our open-source model-fitting tool, Multi-Core Markov-Chain Monte Carlo (MC3). This package uses Bayesian statistics to estimate the best-fitting values and the credible regions for the parameters for a (user-provided) model. MC3 is a Python/C code, available at https://github.com/pcubillos/MCcubed.

Denoising of Raman spectroscopy for biological samples based on empirical mode decomposition

NASA Astrophysics Data System (ADS)

León-Bejarano, Fabiola; Ramírez-Elías, Miguel; Mendez, Martin O.; Dorantes-Méndez, Guadalupe; Rodríguez-Aranda, Ma. Del Carmen; Alba, Alfonso

Raman spectroscopy of biological samples presents undesirable noise and fluorescence generated by the biomolecular excitation. The reduction of these types of noise is a fundamental task to obtain the valuable information of the sample under analysis. This paper proposes the application of the empirical mode decomposition (EMD) for noise elimination. EMD is a parameter-free and adaptive signal processing method useful for the analysis of nonstationary signals. EMD performance was compared with the commonly used Vancouver algorithm (VRA) through artificial data (Teflon), synthetic (Vitamin E and paracetamol) and biological (Mouse brain and human nails) Raman spectra. The correlation coefficient (ρ) was used as performance measure. Results on synthetic data showed a better performance of EMD (ρ=0.52) at high noise levels compared with VRA (ρ=0.19). The methods with simulated fluorescence added to artificial material exhibited a similar shape of fluorescence in both cases (ρ=0.95 for VRA and ρ=0.93 for EMD). For synthetic data, Raman spectra of vitamin E were used and the results showed a good performance comparing both methods (ρ=0.95 for EMD and ρ=0.99 for VRA). Finally, in biological data, EMD and VRA displayed a similar behavior (ρ=0.85 for EMD and ρ=0.96 for VRA), but with the advantage that EMD maintains small amplitude Raman peaks. The results suggest that EMD could be an effective method for denoising biological Raman spectra, EMD is able to retain information and correctly eliminates the fluorescence without parameter tuning.

Investigation of dynamic noise affecting geodynamics information in a tethered subsatellite

NASA Technical Reports Server (NTRS)

Gullahorn, G. E.

1985-01-01

Work performed as part of an investigation of noise affecting instrumentation in a tethered subsatellite, was studied. The following specific topics were addressed during the reporting period: a method for stabilizing the subsatellite against the rotational effects of atmospheric perturbation was developed; a variety of analytic studies of tether dynamics aimed at elucidating dynamic noise processes were performed; a novel mechanism for coupling longitudinal and latitudinal oscillations of the tether was discovered, and random vibration analysis for modeling the tethered subsatellite under atmospheric perturbation were studied.

Baseline measurement of the noise generated by a short-to-medium range jet transport flying standard ILS approaches and level flyovers

NASA Technical Reports Server (NTRS)

Hastings, E. C., Jr.; Shanks, R. E.; Mueller, A. W.

1975-01-01

The results of baseline noise flight tests are presented. Data are given for a point 1.85 kilometers (1.0 nautical mile) from the runway threshold, and experimental results of level flyover noise at altitudes of 122 meters (400 feet) and 610 meters (2,000 feet) are also shown for several different power levels. The experimental data are compared with data from other sources and reasonable agreement is noted. A description of the test technique, instrumentation, and data analysis methods is included.

Reducing Modeling Error of Graphical Methods for Estimating Volume of Distribution Measurements in PIB-PET study

PubMed Central

Guo, Hongbin; Renaut, Rosemary A; Chen, Kewei; Reiman, Eric M

2010-01-01

Graphical analysis methods are widely used in positron emission tomography quantification because of their simplicity and model independence. But they may, particularly for reversible kinetics, lead to bias in the estimated parameters. The source of the bias is commonly attributed to noise in the data. Assuming a two-tissue compartmental model, we investigate the bias that originates from modeling error. This bias is an intrinsic property of the simplified linear models used for limited scan durations, and it is exaggerated by random noise and numerical quadrature error. Conditions are derived under which Logan's graphical method either over- or under-estimates the distribution volume in the noise-free case. The bias caused by modeling error is quantified analytically. The presented analysis shows that the bias of graphical methods is inversely proportional to the dissociation rate. Furthermore, visual examination of the linearity of the Logan plot is not sufficient for guaranteeing that equilibrium has been reached. A new model which retains the elegant properties of graphical analysis methods is presented, along with a numerical algorithm for its solution. We perform simulations with the fibrillar amyloid β radioligand [11C] benzothiazole-aniline using published data from the University of Pittsburgh and Rotterdam groups. The results show that the proposed method significantly reduces the bias due to modeling error. Moreover, the results for data acquired over a 70 minutes scan duration are at least as good as those obtained using existing methods for data acquired over a 90 minutes scan duration. PMID:20493196

The Effect of Nondeterministic Parameters on Shock-Associated Noise Prediction Modeling

NASA Technical Reports Server (NTRS)

Dahl, Milo D.; Khavaran, Abbas

2010-01-01

Engineering applications for aircraft noise prediction contain models for physical phenomenon that enable solutions to be computed quickly. These models contain parameters that have an uncertainty not accounted for in the solution. To include uncertainty in the solution, nondeterministic computational methods are applied. Using prediction models for supersonic jet broadband shock-associated noise, fixed model parameters are replaced by probability distributions to illustrate one of these methods. The results show the impact of using nondeterministic parameters both on estimating the model output uncertainty and on the model spectral level prediction. In addition, a global sensitivity analysis is used to determine the influence of the model parameters on the output, and to identify the parameters with the least influence on model output.

Noise-induced extinction for a ratio-dependent predator-prey model with strong Allee effect in prey

NASA Astrophysics Data System (ADS)

Mandal, Partha Sarathi

2018-04-01

In this paper, we study a stochastically forced ratio-dependent predator-prey model with strong Allee effect in prey population. In the deterministic case, we show that the model exhibits the stable interior equilibrium point or limit cycle corresponding to the co-existence of both species. We investigate a probabilistic mechanism of the noise-induced extinction in a zone of stable interior equilibrium point. Computational methods based on the stochastic sensitivity function technique are applied for the analysis of the dispersion of random states near stable interior equilibrium point. This method allows to construct a confidence domain and estimate the threshold value of the noise intensity for a transition from the coexistence to the extinction.

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

Tang, Yanmei; Li, Xinli; Bai, Yan

The measurement of multiphase flow parameters is of great importance in a wide range of industries. In the measurement of multiphase, the signals from the sensors are extremely weak and often buried in strong background noise. It is thus desirable to develop effective signal processing techniques that can detect the weak signal from the sensor outputs. In this paper, two methods, i.e., lock-in-amplifier (LIA) and improved Duffing chaotic oscillator are compared to detect and process the weak signal. For sinusoidal signal buried in noise, the correlation detection with sinusoidal reference signal is simulated by using LIA. The improved Duffing chaoticmore » oscillator method, which based on the Wigner transformation, can restore the signal waveform and detect the frequency. Two methods are combined to detect and extract the weak signal. Simulation results show the effectiveness and accuracy of the proposed improved method. The comparative analysis shows that the improved Duffing chaotic oscillator method can restrain noise strongly since it is sensitive to initial conditions.« less

Geostatistical estimation of signal-to-noise ratios for spectral vegetation indices

USGS Publications Warehouse

Ji, Lei; Zhang, Li; Rover, Jennifer R.; Wylie, Bruce K.; Chen, Xuexia

2014-01-01

In the past 40 years, many spectral vegetation indices have been developed to quantify vegetation biophysical parameters. An ideal vegetation index should contain the maximum level of signal related to specific biophysical characteristics and the minimum level of noise such as background soil influences and atmospheric effects. However, accurate quantification of signal and noise in a vegetation index remains a challenge, because it requires a large number of field measurements or laboratory experiments. In this study, we applied a geostatistical method to estimate signal-to-noise ratio (S/N) for spectral vegetation indices. Based on the sample semivariogram of vegetation index images, we used the standardized noise to quantify the noise component of vegetation indices. In a case study in the grasslands and shrublands of the western United States, we demonstrated the geostatistical method for evaluating S/N for a series of soil-adjusted vegetation indices derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. The soil-adjusted vegetation indices were found to have higher S/N values than the traditional normalized difference vegetation index (NDVI) and simple ratio (SR) in the sparsely vegetated areas. This study shows that the proposed geostatistical analysis can constitute an efficient technique for estimating signal and noise components in vegetation indices.

Prediction and Measurement of the Vibration and Acoustic Radiation of Panels Subjected to Acoustic Loading

NASA Technical Reports Server (NTRS)

Turner, Travis L.; Rizzi, Stephen A.

1995-01-01

Interior noise and sonic fatigue are important issues in the development and design of advanced subsonic and supersonic aircraft. Conventional aircraft typically employ passive treatments, such as constrained layer damping and acoustic absorption materials, to reduce the structural response and resulting acoustic levels in the aircraft interior. These techniques require significant addition of mass and only attenuate relatively high frequency noise transmitted through the fuselage. Although structural acoustic coupling is in general very important in the study of aircraft fuselage interior noise, analysis of noise transmission through a panel supported in an infinite rigid baffle (separating two semi-infinite acoustic domains) can be useful in evaluating the effects of active/adaptive materials, complex loading, etc. Recent work has been aimed at developing adaptive and/or active methods of controlling the structural acoustic response of panels to reduce the transmitted noise1. A finite element formulation was recently developed to study the dynamic response of shape memory alloy (SMA) hybrid composite panels (conventional composite panel with embedded SMA fibers) subject to combined acoustic and thermal loads2. Further analysis has been performed to predict the far-field acoustic radiation using the finite element dynamic panel response prediction3. The purpose of the present work is to validate the panel vibration and acoustic radiation prediction methods with baseline experimental results obtained from an isotropic panel, without the effect of SMA.

Substructuring of multibody systems for numerical transfer path analysis in internal combustion engines

NASA Astrophysics Data System (ADS)

Acri, Antonio; Offner, Guenter; Nijman, Eugene; Rejlek, Jan

2016-10-01

Noise legislations and the increasing customer demands determine the Noise Vibration and Harshness (NVH) development of modern commercial vehicles. In order to meet the stringent legislative requirements for the vehicle noise emission, exact knowledge of all vehicle noise sources and their acoustic behavior is required. Transfer path analysis (TPA) is a fairly well established technique for estimating and ranking individual low-frequency noise or vibration contributions via the different transmission paths. Transmission paths from different sources to target points of interest and their contributions can be analyzed by applying TPA. This technique is applied on test measurements, which can only be available on prototypes, at the end of the designing process. In order to overcome the limits of TPA, a numerical transfer path analysis methodology based on the substructuring of a multibody system is proposed in this paper. Being based on numerical simulation, this methodology can be performed starting from the first steps of the designing process. The main target of the proposed methodology is to get information of noise sources contributions of a dynamic system considering the possibility to have multiple forces contemporary acting on the system. The contributions of these forces are investigated with particular focus on distribute or moving forces. In this paper, the mathematical basics of the proposed methodology and its advantages in comparison with TPA will be discussed. Then, a dynamic system is investigated with a combination of two methods. Being based on the dynamic substructuring (DS) of the investigated model, the methodology proposed requires the evaluation of the contact forces at interfaces, which are computed with a flexible multi-body dynamic (FMBD) simulation. Then, the structure-borne noise paths are computed with the wave based method (WBM). As an example application a 4-cylinder engine is investigated and the proposed methodology is applied on the engine block. The aim is to get accurate and clear relationships between excitations and responses of the simulated dynamic system, analyzing the noise and vibrational sources inside a car engine, showing the main advantages of a numerical methodology.

Retrieval of reflections from ambient noise using illumination diagnosis

NASA Astrophysics Data System (ADS)

Vidal, C. Almagro; Draganov, D.; van der Neut, J.; Drijkoningen, G.; Wapenaar, K.

2014-09-01

Seismic interferometry (SI) enables the retrieval of virtual sources at the location of receivers. In the case of passive SI, no active sources are used for the retrieval of the reflection response of the subsurface, but ambient-noise recordings only. The resulting retrieved response is determined by the illumination characteristics of the recorded ambient noise. Characteristics like geometrical distribution and signature of the noise sources, together with the complexity of the medium and the length of the noise records, determine the quality of the retrieved virtual-shot events. To retrieve body wave reflections, one needs to correlate body-wave noise. A source of such noise might be regional seismicity. In regions with notable human presence, the dominant noise sources are generally located at or close to the surface. In the latter case, the noise will be dominated by surface waves and consequently also the retrieved virtual common-source panels will contain dominant retrieved surface waves, drowning out possible retrieved reflections. In order to retrieve reflection events, suppression of the surface waves becomes the most important pre-processing goal. Because of the reasons mentioned above, we propose a fast method to evaluate the illumination characteristics of ambient noise using the correlation results from ambient-noise records. The method is based on the analysis of the so-called source function of the retrieved virtual-shot panel, and evaluates the apparent slowness of arrivals in the correlation results that pass through the position of the virtual source and at zero time. The results of the diagnosis are used to suppress the retrieval of surface waves and therefore to improve the quality of the retrieved reflection response. We explain the approach using modelled data from transient and continuous noise sources and an example from a passive field data set recorded at Annerveen, Northern Netherlands.

Improving the surface metrology accuracy of optical profilers by using multiple measurements

NASA Astrophysics Data System (ADS)

Xu, Xudong; Huang, Qiushi; Shen, Zhengxiang; Wang, Zhanshan

2016-10-01

The performance of high-resolution optical systems is affected by small angle scattering at the mid-spatial-frequency irregularities of the optical surface. Characterizing these irregularities is, therefore, important. However, surface measurements obtained with optical profilers are influenced by additive white noise, as indicated by the heavy-tail effect observable on their power spectral density (PSD). A multiple-measurement method is used to reduce the effects of white noise by averaging individual measurements. The intensity of white noise is determined using a model based on the theoretical PSD of fractal surface measurements with additive white noise. The intensity of white noise decreases as the number of times of multiple measurements increases. Using multiple measurements also increases the highest observed spatial frequency; this increase is derived and calculated. Additionally, the accuracy obtained using multiple measurements is carefully studied, with the analysis of both the residual reference error after calibration, and the random errors appearing in the range of measured spatial frequencies. The resulting insights on the effects of white noise in optical profiler measurements and the methods to mitigate them may prove invaluable to improve the quality of surface metrology with optical profilers.

The Prediction and Analysis of Jet Flows and Scattered Turbulent Mixing Noise about Flight Vehicle Airframes

NASA Technical Reports Server (NTRS)

Miller, Steven A. E.

2014-01-01

Jet flows interacting with nearby surfaces exhibit a complex behavior in which acoustic and aerodynamic characteristics are altered. The physical understanding and prediction of these characteristics are essential to designing future low noise aircraft. A new approach is created for predicting scattered jet mixing noise that utilizes an acoustic analogy and steady Reynolds-averaged Navier-Stokes solutions. A tailored Green's function accounts for the propagation of mixing noise about the airframe and is calculated numerically using a newly developed ray tracing method. The steady aerodynamic statistics, associated unsteady sound source, and acoustic intensity are examined as jet conditions are varied about a large flat plate. A non-dimensional number is proposed to estimate the effect of the aerodynamic noise source relative to jet operating condition and airframe position.The steady Reynolds-averaged Navier-Stokes solutions, acoustic analogy, tailored Green's function, non-dimensional number, and predicted noise are validated with a wide variety of measurements. The combination of the developed theory, ray tracing method, and careful implementation in a stand-alone computer program result in an approach that is more first principles oriented than alternatives, computationally efficient, and captures the relevant physics of fluid-structure interaction.

The Prediction and Analysis of Jet Flows and Scattered Turbulent Mixing Noise About Flight Vehicle Airframes

NASA Technical Reports Server (NTRS)

Miller, Steven A.

2014-01-01

Jet flows interacting with nearby surfaces exhibit a complex behavior in which acoustic and aerodynamic characteristics are altered. The physical understanding and prediction of these characteristics are essential to designing future low noise aircraft. A new approach is created for predicting scattered jet mixing noise that utilizes an acoustic analogy and steady Reynolds-averaged Navier-Stokes solutions. A tailored Green's function accounts for the propagation of mixing noise about the air-frame and is calculated numerically using a newly developed ray tracing method. The steady aerodynamic statistics, associated unsteady sound source, and acoustic intensity are examined as jet conditions are varied about a large at plate. A non-dimensional number is proposed to estimate the effect of the aerodynamic noise source relative to jet operating condition and airframe position. The steady Reynolds-averaged Navier-Stokes solutions, acoustic analogy, tailored Green's function, non- dimensional number, and predicted noise are validated with a wide variety of measurements. The combination of the developed theory, ray tracing method, and careful implementation in a stand-alone computer program result in an approach that is more first principles oriented than alternatives, computationally efficient, and captures the relevant physics of fluid-structure interaction.

Highway traffic noise prediction based on GIS

NASA Astrophysics Data System (ADS)

Zhao, Jianghua; Qin, Qiming

2014-05-01

Before building a new road, we need to predict the traffic noise generated by vehicles. Traditional traffic noise prediction methods are based on certain locations and they are not only time-consuming, high cost, but also cannot be visualized. Geographical Information System (GIS) can not only solve the problem of manual data processing, but also can get noise values at any point. The paper selected a road segment from Wenxi to Heyang. According to the geographical overview of the study area and the comparison between several models, we combine the JTG B03-2006 model and the HJ2.4-2009 model to predict the traffic noise depending on the circumstances. Finally, we interpolate the noise values at each prediction point and then generate contours of noise. By overlaying the village data on the noise contour layer, we can get the thematic maps. The use of GIS for road traffic noise prediction greatly facilitates the decision-makers because of GIS spatial analysis function and visualization capabilities. We can clearly see the districts where noise are excessive, and thus it becomes convenient to optimize the road line and take noise reduction measures such as installing sound barriers and relocating villages and so on.

Using Empirical Mode Decomposition to process Marine Magnetotelluric Data

NASA Astrophysics Data System (ADS)

Chen, J.; Jegen, M. D.; Heincke, B. H.; Moorkamp, M.

2014-12-01

The magnetotelluric (MT) data always exhibits nonstationarities due to variations of source mechanisms causing MT variations on different time and spatial scales. An additional non-stationary component is introduced through noise, which is particularly pronounced in marine MT data through motion induced noise caused by time-varying wave motion and currents. We present a new heuristic method for dealing with the non-stationarity of MT time series based on Empirical Mode Decomposition (EMD). The EMD method is used in combination with the derived instantaneous spectra to determine impedance estimates. The procedure is tested on synthetic and field MT data. In synthetic tests the reliability of impedance estimates from EMD-based method is compared to the synthetic responses of a 1D layered model. To examine how estimates are affected by noise, stochastic stationary and non-stationary noise are added on the time series. Comparisons reveal that estimates by the EMD-based method are generally more stable than those by simple Fourier analysis. Furthermore, the results are compared to those derived by a commonly used Fourier-based MT data processing software (BIRRP), which incorporates additional sophisticated robust estimations to deal with noise issues. It is revealed that the results from both methods are already comparable, even though no robust estimate procedures are implemented in the EMD approach at present stage. The processing scheme is then applied to marine MT field data. Testing is performed on short, relatively quiet segments of several data sets, as well as on long segments of data with many non-stationary noise packages. Compared to BIRRP, the new method gives comparable or better impedance estimates, furthermore, the estimates are extended to lower frequencies and less noise biased estimates with smaller error bars are obtained at high frequencies. The new processing methodology represents an important step towards deriving a better resolved Earth model to greater depth underneath the seafloor.

The technology on noise reduction of the APD detection circuit

NASA Astrophysics Data System (ADS)

Wu, Xue-ying; Zheng, Yong-chao; Cui, Jian-yong

2013-09-01

The laser pulse detection is widely used in the field of laser range finders, laser communications, laser radar, laser Identification Friend or Foe, et al, for the laser pulse detection has the advantage of high accuracy, high sensitivity and strong anti-interference. The avalanche photodiodes (APD) has the advantage of high quantum efficiency, high response speed and huge gain. The APD is particularly suitable for weak signal detection. The technology that APD acts as the photodetector for weak signal reception and amplification is widely used in laser pulse detection. The APD will convert the laser signal to weak electrical signal. The weak signal is amplified, processed and exported by the circuit. In the circuit design, the optimal signal detection is one key point in photoelectric detection system. The issue discusses how to reduce the noise of the photoelectric signal detection circuit and how to improve the signal-to-noise ratio, related analysis and practice included. The essay analyzes the mathematical model of the signal-to-noise ratio for photoelectric conversion and the noise of the APD photoelectric detection system. By analysis the bandwidth of the detection system is determined, and the circuit devices are selected that match the APD. In the circuit design separated devices with low noise are combined with integrated operational amplifier for the purpose of noise reduction. The methods can effectively suppress the noise, and improve the detection sensitivity.

NONLINEAR AND FIBER OPTICS: Analysis of the mode noise in interference fiber channels used for the distribution of microwave signals

NASA Astrophysics Data System (ADS)

Bratchikov, A. N.; Glukhov, I. P.

1991-03-01

The results are given of a statistical theory of the speckle generalized to interference channels used for the distribution of microwave signals using multimode fiber waveguides with step and graded refractive-index profiles. A method is described for estimating the mode noise level in the open and closed regimes with one longitudinal speckle. The influence of the degree of mode filtering, losses at microbends, and spectral properties of a laser source on the statistical properties and the mode noise level is demonstrated. Numerical estimates are obtained of the ratio of the powers of the signal and mode noise for interference channels with typical parameters of fiber waveguides and a qualitative description is given of the effect of the mode noise.

Data preprocessing method for liquid chromatography-mass spectrometry based metabolomics.

PubMed

Wei, Xiaoli; Shi, Xue; Kim, Seongho; Zhang, Li; Patrick, Jeffrey S; Binkley, Joe; McClain, Craig; Zhang, Xiang

2012-09-18

A set of data preprocessing algorithms for peak detection and peak list alignment are reported for analysis of liquid chromatography-mass spectrometry (LC-MS)-based metabolomics data. For spectrum deconvolution, peak picking is achieved at the selected ion chromatogram (XIC) level. To estimate and remove the noise in XICs, each XIC is first segmented into several peak groups based on the continuity of scan number, and the noise level is estimated by all the XIC signals, except the regions potentially with presence of metabolite ion peaks. After removing noise, the peaks of molecular ions are detected using both the first and the second derivatives, followed by an efficient exponentially modified Gaussian-based peak deconvolution method for peak fitting. A two-stage alignment algorithm is also developed, where the retention times of all peaks are first transferred into the z-score domain and the peaks are aligned based on the measure of their mixture scores after retention time correction using a partial linear regression. Analysis of a set of spike-in LC-MS data from three groups of samples containing 16 metabolite standards mixed with metabolite extract from mouse livers demonstrates that the developed data preprocessing method performs better than two of the existing popular data analysis packages, MZmine2.6 and XCMS(2), for peak picking, peak list alignment, and quantification.

A Data Pre-processing Method for Liquid Chromatography Mass Spectrometry-based Metabolomics

PubMed Central

Wei, Xiaoli; Shi, Xue; Kim, Seongho; Zhang, Li; Patrick, Jeffrey S.; Binkley, Joe; McClain, Craig; Zhang, Xiang

2012-01-01

A set of data pre-processing algorithms for peak detection and peak list alignment are reported for analysis of LC-MS based metabolomics data. For spectrum deconvolution, peak picking is achieved at selected ion chromatogram (XIC) level. To estimate and remove the noise in XICs, each XIC is first segmented into several peak groups based on the continuity of scan number, and the noise level is estimated by all the XIC signals, except the regions potentially with presence of metabolite ion peaks. After removing noise, the peaks of molecular ions are detected using both the first and the second derivatives, followed by an efficient exponentially modified Gaussian-based peak deconvolution method for peak fitting. A two-stage alignment algorithm is also developed, where the retention times of all peaks are first transferred into z-score domain and the peaks are aligned based on the measure of their mixture scores after retention time correction using a partial linear regression. Analysis of a set of spike-in LC-MS data from three groups of samples containing 16 metabolite standards mixed with metabolite extract from mouse livers, demonstrates that the developed data pre-processing methods performs better than two of the existing popular data analysis packages, MZmine2.6 and XCMS2, for peak picking, peak list alignment and quantification. PMID:22931487

Hybrid Wavelet De-noising and Rank-Set Pair Analysis approach for forecasting hydro-meteorological time series

NASA Astrophysics Data System (ADS)

WANG, D.; Wang, Y.; Zeng, X.

2017-12-01

Accurate, fast forecasting of hydro-meteorological time series is presently a major challenge in drought and flood mitigation. This paper proposes a hybrid approach, Wavelet De-noising (WD) and Rank-Set Pair Analysis (RSPA), that takes full advantage of a combination of the two approaches to improve forecasts of hydro-meteorological time series. WD allows decomposition and reconstruction of a time series by the wavelet transform, and hence separation of the noise from the original series. RSPA, a more reliable and efficient version of Set Pair Analysis, is integrated with WD to form the hybrid WD-RSPA approach. Two types of hydro-meteorological data sets with different characteristics and different levels of human influences at some representative stations are used to illustrate the WD-RSPA approach. The approach is also compared to three other generic methods: the conventional Auto Regressive Integrated Moving Average (ARIMA) method, Artificial Neural Networks (ANNs) (BP-error Back Propagation, MLP-Multilayer Perceptron and RBF-Radial Basis Function), and RSPA alone. Nine error metrics are used to evaluate the model performance. The results show that WD-RSPA is accurate, feasible, and effective. In particular, WD-RSPA is found to be the best among the various generic methods compared in this paper, even when the extreme events are included within a time series.

Frequency domain analysis of noise in simple gene circuits

NASA Astrophysics Data System (ADS)

Cox, Chris D.; McCollum, James M.; Austin, Derek W.; Allen, Michael S.; Dar, Roy D.; Simpson, Michael L.

2006-06-01

Recent advances in single cell methods have spurred progress in quantifying and analyzing stochastic fluctuations, or noise, in genetic networks. Many of these studies have focused on identifying the sources of noise and quantifying its magnitude, and at the same time, paying less attention to the frequency content of the noise. We have developed a frequency domain approach to extract the information contained in the frequency content of the noise. In this article we review our work in this area and extend it to explicitly consider sources of extrinsic and intrinsic noise. First we review applications of the frequency domain approach to several simple circuits, including a constitutively expressed gene, a gene regulated by transitions in its operator state, and a negatively autoregulated gene. We then review our recent experimental study, in which time-lapse microscopy was used to measure noise in the expression of green fluorescent protein in individual cells. The results demonstrate how changes in rate constants within the gene circuit are reflected in the spectral content of the noise in a manner consistent with the predictions derived through frequency domain analysis. The experimental results confirm our earlier theoretical prediction that negative autoregulation not only reduces the magnitude of the noise but shifts its content out to higher frequency. Finally, we develop a frequency domain model of gene expression that explicitly accounts for extrinsic noise at the transcriptional and translational levels. We apply the model to interpret a shift in the autocorrelation function of green fluorescent protein induced by perturbations of the translational process as a shift in the frequency spectrum of extrinsic noise and a decrease in its weighting relative to intrinsic noise.

Separating intrinsic from extrinsic fluctuations in dynamic biological systems

PubMed Central

Paulsson, Johan

2011-01-01

From molecules in cells to organisms in ecosystems, biological populations fluctuate due to the intrinsic randomness of individual events and the extrinsic influence of changing environments. The combined effect is often too complex for effective analysis, and many studies therefore make simplifying assumptions, for example ignoring either intrinsic or extrinsic effects to reduce the number of model assumptions. Here we mathematically demonstrate how two identical and independent reporters embedded in a shared fluctuating environment can be used to identify intrinsic and extrinsic noise terms, but also how these contributions are qualitatively and quantitatively different from what has been previously reported. Furthermore, we show for which classes of biological systems the noise contributions identified by dual-reporter methods correspond to the noise contributions predicted by correct stochastic models of either intrinsic or extrinsic mechanisms. We find that for broad classes of systems, the extrinsic noise from the dual-reporter method can be rigorously analyzed using models that ignore intrinsic stochasticity. In contrast, the intrinsic noise can be rigorously analyzed using models that ignore extrinsic stochasticity only under very special conditions that rarely hold in biology. Testing whether the conditions are met is rarely possible and the dual-reporter method may thus produce flawed conclusions about the properties of the system, particularly about the intrinsic noise. Our results contribute toward establishing a rigorous framework to analyze dynamically fluctuating biological systems. PMID:21730172

Separating intrinsic from extrinsic fluctuations in dynamic biological systems.

PubMed

Hilfinger, Andreas; Paulsson, Johan

2011-07-19

From molecules in cells to organisms in ecosystems, biological populations fluctuate due to the intrinsic randomness of individual events and the extrinsic influence of changing environments. The combined effect is often too complex for effective analysis, and many studies therefore make simplifying assumptions, for example ignoring either intrinsic or extrinsic effects to reduce the number of model assumptions. Here we mathematically demonstrate how two identical and independent reporters embedded in a shared fluctuating environment can be used to identify intrinsic and extrinsic noise terms, but also how these contributions are qualitatively and quantitatively different from what has been previously reported. Furthermore, we show for which classes of biological systems the noise contributions identified by dual-reporter methods correspond to the noise contributions predicted by correct stochastic models of either intrinsic or extrinsic mechanisms. We find that for broad classes of systems, the extrinsic noise from the dual-reporter method can be rigorously analyzed using models that ignore intrinsic stochasticity. In contrast, the intrinsic noise can be rigorously analyzed using models that ignore extrinsic stochasticity only under very special conditions that rarely hold in biology. Testing whether the conditions are met is rarely possible and the dual-reporter method may thus produce flawed conclusions about the properties of the system, particularly about the intrinsic noise. Our results contribute toward establishing a rigorous framework to analyze dynamically fluctuating biological systems.

An Adaptive INS-Aided PLL Tracking Method for GNSS Receivers in Harsh Environments.

PubMed

Cong, Li; Li, Xin; Jin, Tian; Yue, Song; Xue, Rui

2016-01-23

As the weak link in global navigation satellite system (GNSS) signal processing, the phase-locked loop (PLL) is easily influenced with frequent cycle slips and loss of lock as a result of higher vehicle dynamics and lower signal-to-noise ratios. With inertial navigation system (INS) aid, PLLs' tracking performance can be improved. However, for harsh environments with high dynamics and signal attenuation, the traditional INS-aided PLL with fixed loop parameters has some limitations to improve the tracking adaptability. In this paper, an adaptive INS-aided PLL capable of adjusting its noise bandwidth and coherent integration time has been proposed. Through theoretical analysis, the relation between INS-aided PLL phase tracking error and carrier to noise density ratio (C/N₀), vehicle dynamics, aiding information update time, noise bandwidth, and coherent integration time has been built. The relation formulae are used to choose the optimal integration time and bandwidth for a given application under the minimum tracking error criterion. Software and hardware simulation results verify the correctness of the theoretical analysis, and demonstrate that the adaptive tracking method can effectively improve the PLL tracking ability and integrated GNSS/INS navigation performance. For harsh environments, the tracking sensitivity is increased by 3 to 5 dB, velocity errors are decreased by 36% to 50% and position errors are decreased by 6% to 24% when compared with other INS-aided PLL methods.

Analysis of nonreciprocal noise based on mode splitting in a high-Q optical microresonator

NASA Astrophysics Data System (ADS)

Yang, Zhaohua; Xiao, Yarong; Huo, Jiayan; Shao, Hui

2018-01-01

The whispering gallery mode optical microresonator offers a high quality factor, which enables it to act as the core component of a high sensitivity resonator optic gyro; however, nonreciprocal noise limits its precision. Considering the Sagnac effect, i.e. mode splitting in high-quality optical micro-resonators, we derive the explicit expression for the angular velocity versus the splitting amount, and verify the sensing mechanism by simulation using finite element method. Remarkably, the accuracy of the angular velocity measurement in the whispering gallery mode optical microresonator with a quality factor of 108 is 106 °/s. We obtain the optimal coupling position of the novel angular velocity sensing system by detecting the output transmittance spectra of different vertical coupling distances and axial coupling positions. In addition, the reason for the nonreciprocal phenomenon is determined by theoretical analysis of the evanescent distribution of a tapered fiber. These results will provide an effective method and a theoretical basis for suppression of the nonreciprocal noise.

Rotating coherent flow structures as a source for narrowband tip clearance noise from axial fans

NASA Astrophysics Data System (ADS)

Zhu, Tao; Lallier-Daniels, Dominic; Sanjosé, Marlène; Moreau, Stéphane; Carolus, Thomas

2018-03-01

Noise from axial fans typically increases significantly as the tip clearance is increased. In addition to the broadband tip clearance noise at the design flow rate, narrowband humps also associated with the tip flow are observed in the far-field acoustic spectra at lower flow rate. In this study, both experimental and numerical methods are used to shed more light on the noise generation mechanism of this narrowband tip clearance noise and provide a unified description of this source. Unsteady aeroacoustic predictions with the Lattice-Boltzmann Method (LBM) are successfully compared with experiment. Such a validation allows using LBM data to conduct a detailed modal analysis of the pressure field for detecting rotating coherent flow structures which might be considered as noise sources. As previously found in ring fans the narrowband humps in the far-field noise spectra are found to be related to the tip clearance noise that is generated by an interaction of coherent flow structures present in the tip region with the leading edge of the impeller blades. The visualization of the coherent structures shows that they are indeed part of the unsteady tip clearance vortex structures. They are hidden in a complex, spatially and temporally inhomogeneous flow field, but can be recovered by means of appropriate filtering techniques. Their pressure trace corresponds to the so-called rotational instability identified in previous turbomachinery studies, which brings a unified picture of this tip-noise phenomenon for the first time.

A robust detector for rolling element bearing condition monitoring based on the modulation signal bispectrum and its performance evaluation against the Kurtogram

NASA Astrophysics Data System (ADS)

Tian, Xiange; Xi Gu, James; Rehab, Ibrahim; Abdalla, Gaballa M.; Gu, Fengshou; Ball, A. D.

2018-02-01

Envelope analysis is a widely used method for rolling element bearing fault detection. To obtain high detection accuracy, it is critical to determine an optimal frequency narrowband for the envelope demodulation. However, many of the schemes which are used for the narrowband selection, such as the Kurtogram, can produce poor detection results because they are sensitive to random noise and aperiodic impulses which normally occur in practical applications. To achieve the purposes of denoising and frequency band optimisation, this paper proposes a novel modulation signal bispectrum (MSB) based robust detector for bearing fault detection. Because of its inherent noise suppression capability, the MSB allows effective suppression of both stationary random noise and discrete aperiodic noise. The high magnitude features that result from the use of the MSB also enhance the modulation effects of a bearing fault and can be used to provide optimal frequency bands for fault detection. The Kurtogram is generally accepted as a powerful means of selecting the most appropriate frequency band for envelope analysis, and as such it has been used as the benchmark comparator for performance evaluation in this paper. Both simulated and experimental data analysis results show that the proposed method produces more accurate and robust detection results than Kurtogram based approaches for common bearing faults under a range of representative scenarios.

Analysis of random signal combinations for spacecraft pointing stability

NASA Technical Reports Server (NTRS)

Howell, L.

1983-01-01

Methods for obtaining the probability density function of random signal combustions are discussed. These methods provide a realistic criteria for the design of control systems subjected to external noise with several important applications for aerospace problems.

Non-cavitating propeller noise modeling and inversion

NASA Astrophysics Data System (ADS)

Kim, Dongho; Lee, Keunhwa; Seong, Woojae

2014-12-01

Marine propeller is the dominant exciter of the hull surface above it causing high level of noise and vibration in the ship structure. Recent successful developments have led to non-cavitating propeller designs and thus present focus is the non-cavitating characteristics of propeller such as hydrodynamic noise and its induced hull excitation. In this paper, analytic source model of propeller non-cavitating noise, described by longitudinal quadrupoles and dipoles, is suggested based on the propeller hydrodynamics. To find the source unknown parameters, the multi-parameter inversion technique is adopted using the pressure data obtained from the model scale experiment and pressure field replicas calculated by boundary element method. The inversion results show that the proposed source model is appropriate in modeling non-cavitating propeller noise. The result of this study can be utilized in the prediction of propeller non-cavitating noise and hull excitation at various stages in design and analysis.

On the uncertainty in single molecule fluorescent lifetime and energy emission measurements

NASA Technical Reports Server (NTRS)

Brown, Emery N.; Zhang, Zhenhua; Mccollom, Alex D.

1995-01-01

Time-correlated single photon counting has recently been combined with mode-locked picosecond pulsed excitation to measure the fluorescent lifetimes and energy emissions of single molecules in a flow stream. Maximum likelihood (ML) and least square methods agree and are optimal when the number of detected photons is large however, in single molecule fluorescence experiments the number of detected photons can be less than 20, 67% of those can be noise and the detection time is restricted to 10 nanoseconds. Under the assumption that the photon signal and background noise are two independent inhomogeneous poisson processes, we derive the exact joint arrival time probably density of the photons collected in a single counting experiment performed in the presence of background noise. The model obviates the need to bin experimental data for analysis, and makes it possible to analyze formally the effect of background noise on the photon detection experiment using both ML or Bayesian methods. For both methods we derive the joint and marginal probability densities of the fluorescent lifetime and fluorescent emission. the ML and Bayesian methods are compared in an analysis of simulated single molecule fluorescence experiments of Rhodamine 110 using different combinations of expected background nose and expected fluorescence emission. While both the ML or Bayesian procedures perform well for analyzing fluorescence emissions, the Bayesian methods provide more realistic measures of uncertainty in the fluorescent lifetimes. The Bayesian methods would be especially useful for measuring uncertainty in fluorescent lifetime estimates in current single molecule flow stream experiments where the expected fluorescence emission is low. Both the ML and Bayesian algorithms can be automated for applications in molecular biology.

Error of the slanted edge method for measuring the modulation transfer function of imaging systems.

PubMed

Xie, Xufen; Fan, Hongda; Wang, Hongyuan; Wang, Zebin; Zou, Nianyu

2018-03-01

The slanted edge method is a basic approach for measuring the modulation transfer function (MTF) of imaging systems; however, its measurement accuracy is limited in practice. Theoretical analysis of the slanted edge MTF measurement method performed in this paper reveals that inappropriate edge angles and random noise reduce this accuracy. The error caused by edge angles is analyzed using sampling and reconstruction theory. Furthermore, an error model combining noise and edge angles is proposed. We verify the analyses and model with respect to (i) the edge angle, (ii) a statistical analysis of the measurement error, (iii) the full width at half-maximum of a point spread function, and (iv) the error model. The experimental results verify the theoretical findings. This research can be referential for applications of the slanted edge MTF measurement method.

Statistical analysis and digital processing of the Mössbauer spectra

NASA Astrophysics Data System (ADS)

Prochazka, Roman; Tucek, Pavel; Tucek, Jiri; Marek, Jaroslav; Mashlan, Miroslav; Pechousek, Jiri

2010-02-01

This work is focused on using the statistical methods and development of the filtration procedures for signal processing in Mössbauer spectroscopy. Statistical tools for noise filtering in the measured spectra are used in many scientific areas. The use of a pure statistical approach in accumulated Mössbauer spectra filtration is described. In Mössbauer spectroscopy, the noise can be considered as a Poisson statistical process with a Gaussian distribution for high numbers of observations. This noise is a superposition of the non-resonant photons counting with electronic noise (from γ-ray detection and discrimination units), and the velocity system quality that can be characterized by the velocity nonlinearities. The possibility of a noise-reducing process using a new design of statistical filter procedure is described. This mathematical procedure improves the signal-to-noise ratio and thus makes it easier to determine the hyperfine parameters of the given Mössbauer spectra. The filter procedure is based on a periodogram method that makes it possible to assign the statistically important components in the spectral domain. The significance level for these components is then feedback-controlled using the correlation coefficient test results. The estimation of the theoretical correlation coefficient level which corresponds to the spectrum resolution is performed. Correlation coefficient test is based on comparison of the theoretical and the experimental correlation coefficients given by the Spearman method. The correctness of this solution was analyzed by a series of statistical tests and confirmed by many spectra measured with increasing statistical quality for a given sample (absorber). The effect of this filter procedure depends on the signal-to-noise ratio and the applicability of this method has binding conditions.

Single Photon Counting Performance and Noise Analysis of CMOS SPAD-Based Image Sensors

PubMed Central

Dutton, Neale A. W.; Gyongy, Istvan; Parmesan, Luca; Henderson, Robert K.

2016-01-01

SPAD-based solid state CMOS image sensors utilising analogue integrators have attained deep sub-electron read noise (DSERN) permitting single photon counting (SPC) imaging. A new method is proposed to determine the read noise in DSERN image sensors by evaluating the peak separation and width (PSW) of single photon peaks in a photon counting histogram (PCH). The technique is used to identify and analyse cumulative noise in analogue integrating SPC SPAD-based pixels. The DSERN of our SPAD image sensor is exploited to confirm recent multi-photon threshold quanta image sensor (QIS) theory. Finally, various single and multiple photon spatio-temporal oversampling techniques are reviewed. PMID:27447643

Latency as a region contrast: Measuring ERP latency differences with Dynamic Time Warping.

PubMed

Zoumpoulaki, A; Alsufyani, A; Filetti, M; Brammer, M; Bowman, H

2015-12-01

Methods for measuring onset latency contrasts are evaluated against a new method utilizing the dynamic time warping (DTW) algorithm. This new method allows latency to be measured across a region instead of single point. We use computer simulations to compare the methods' power and Type I error rates under different scenarios. We perform per-participant analysis for different signal-to-noise ratios and two sizes of window (broad vs. narrow). In addition, the methods are tested in combination with single-participant and jackknife average waveforms for different effect sizes, at the group level. DTW performs better than the other methods, being less sensitive to noise as well as to placement and width of the window selected. © 2015 Society for Psychophysiological Research.

Evaluation of quantification methods for real-time PCR minor groove binding hybridization probe assays.

PubMed

Durtschi, Jacob D; Stevenson, Jeffery; Hymas, Weston; Voelkerding, Karl V

2007-02-01

Real-time PCR data analysis for quantification has been the subject of many studies aimed at the identification of new and improved quantification methods. Several analysis methods have been proposed as superior alternatives to the common variations of the threshold crossing method. Notably, sigmoidal and exponential curve fit methods have been proposed. However, these studies have primarily analyzed real-time PCR with intercalating dyes such as SYBR Green. Clinical real-time PCR assays, in contrast, often employ fluorescent probes whose real-time amplification fluorescence curves differ from those of intercalating dyes. In the current study, we compared four analysis methods related to recent literature: two versions of the threshold crossing method, a second derivative maximum method, and a sigmoidal curve fit method. These methods were applied to a clinically relevant real-time human herpes virus type 6 (HHV6) PCR assay that used a minor groove binding (MGB) Eclipse hybridization probe as well as an Epstein-Barr virus (EBV) PCR assay that used an MGB Pleiades hybridization probe. We found that the crossing threshold method yielded more precise results when analyzing the HHV6 assay, which was characterized by lower signal/noise and less developed amplification curve plateaus. In contrast, the EBV assay, characterized by greater signal/noise and amplification curves with plateau regions similar to those observed with intercalating dyes, gave results with statistically similar precision by all four analysis methods.

Analysis of Subthreshold Current Reset Noise in Image Sensors.

PubMed

Teranishi, Nobukazu

2016-05-10

To discuss the reset noise generated by slow subthreshold currents in image sensors, intuitive and simple analytical forms are derived, in spite of the subthreshold current nonlinearity. These solutions characterize the time evolution of the reset noise during the reset operation. With soft reset, the reset noise tends to m k T / 2 C P D when t → ∞ , in full agreement with previously published results. In this equation, C P D is the photodiode (PD) capacitance and m is a constant. The noise has an asymptotic time dependence of t - 1 , even though the asymptotic time dependence of the average (deterministic) PD voltage is as slow as log t . The flush reset method is effective because the hard reset part eliminates image lag, and the soft reset part reduces the noise to soft reset level. The feedback reset with reverse taper control method shows both a fast convergence and a good reset noise reduction. When the feedback amplifier gain, A, is larger, even small value of capacitance, C P , between the input and output of the feedback amplifier will drastically decrease the reset noise. If the feedback is sufficiently fast, the reset noise limit when t → ∞ , becomes m k T ( C P D + C P 1 ) 2 2 q 2 A ( C P D + ( 1 + A ) C P ) in terms of the number of electron in the PD. According to this simple model, if CPD = 10 fF, CP/CPD = 0.01, and A = 2700 are assumed, deep sub-electron rms reset noise is possible.

a Theoretical and Experimental Investigation of 1/F Noise in the Alpha Decay Rates of AMERICIUM-241.

NASA Astrophysics Data System (ADS)

Pepper, Gary T.

New experimental methods and data analysis techniques were used to investigate the hypothesis of the existence of 1/f noise in a alpha particle emission rates for ^{241}Am. Experimental estimates of the flicker floor were found to be almost two orders of magnitude less than Handel's theoretical prediction and previous measurements. The existence of a flicker floor for ^{57}Co decay, a process for which no charged particles are emitted, indicate that instrumental instability is likely responsible for the values of the flicker floor obtained. The experimental results and the theoretical arguments presented indicate that a re-examination of Handel's theory of 1/f noise is appropriate. Methods of numerical simulation of noise processes with a 1/f^{rm n} power spectral density were developed. These were used to investigate various statistical aspects of 1/f ^{rm n} noise. The probability density function for the Allan variance was investigated in order to establish confidence limits for the observations made. The effect of using grouped (correlated) data, for evaluating the Allan variance, was also investigated.

Optimal harvesting policy of a stochastic two-species competitive model with Lévy noise in a polluted environment

NASA Astrophysics Data System (ADS)

Zhao, Yu; Yuan, Sanling

2017-07-01

As well known that the sudden environmental shocks and toxicant can affect the population dynamics of fish species, a mechanistic understanding of how sudden environmental change and toxicant influence the optimal harvesting policy requires development. This paper presents the optimal harvesting of a stochastic two-species competitive model with Lévy noise in a polluted environment, where the Lévy noise is used to describe the sudden climate change. Due to the discontinuity of the Lévy noise, the classical optimal harvesting methods based on the explicit solution of the corresponding Fokker-Planck equation are invalid. The object of this paper is to fill up this gap and establish the optimal harvesting policy. By using of aggregation and ergodic methods, the approximation of the optimal harvesting effort and maximum expectation of sustainable yields are obtained. Numerical simulations are carried out to support these theoretical results. Our analysis shows that the Lévy noise and the mean stress measure of toxicant in organism may affect the optimal harvesting policy significantly.

The Okinawa study: an estimation of noise-induced hearing loss on the basis of the records of aircraft noise exposure around Kadena Air Base

NASA Astrophysics Data System (ADS)

Hiramatsu, K.; Matsui, T.; Ito, A.; Miyakita, T.; Osada, Y.; Yamamoto, T.

2004-10-01

Aircraft noise measurements were recorded at the residential areas in the vicinity of Kadena Air Base, Okinawa in 1968 and 1972 at the time of the Vietnam war. The estimated equivalent continuous A-weighted sound pressure level LAeq for 24 h was 85 dB.The time history of sound level during 24 h was estimated from the measurement conducted in 1968, and the sound level was converted into the spectrum level at the centre frequency of the critical band of temporary threshold shift (TTS) using the results of spectrum analysis of aircraft noise operated at the airfield. With the information of spectrum level and its time history, TTS was calculated as a function of time and level change. The permanent threshold shift was also calculated by means of Robinson's method and ISO's method. The results indicate the noise exposure around Kadena Air Base was hazardous to hearing and is likely to have caused hearing loss to people living in its vicinity.

Data-driven adaptive fractional order PI control for PMSM servo system with measurement noise and data dropouts.

PubMed

Xie, Yuanlong; Tang, Xiaoqi; Song, Bao; Zhou, Xiangdong; Guo, Yixuan

2018-04-01

In this paper, data-driven adaptive fractional order proportional integral (AFOPI) control is presented for permanent magnet synchronous motor (PMSM) servo system perturbed by measurement noise and data dropouts. The proposed method directly exploits the closed-loop process data for the AFOPI controller design under unknown noise distribution and data missing probability. Firstly, the proposed method constructs the AFOPI controller tuning problem as a parameter identification problem using the modified l p norm virtual reference feedback tuning (VRFT). Then, iteratively reweighted least squares is integrated into the l p norm VRFT to give a consistent compensation solution for the AFOPI controller. The measurement noise and data dropouts are estimated and eliminated by feedback compensation periodically, so that the AFOPI controller is updated online to accommodate the time-varying operating conditions. Moreover, the convergence and stability are guaranteed by mathematical analysis. Finally, the effectiveness of the proposed method is demonstrated both on simulations and experiments implemented on a practical PMSM servo system. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Estimation of neural energy in microelectrode signals

NASA Astrophysics Data System (ADS)

Gaumond, R. P.; Clement, R.; Silva, R.; Sander, D.

2004-09-01

We considered the problem of determining the neural contribution to the signal recorded by an intracortical electrode. We developed a linear least-squares approach to determine the energy fraction of a signal attributable to an arbitrary number of autocorrelation-defined signals buried in noise. Application of the method requires estimation of autocorrelation functions Rap(tgr) characterizing the action potential (AP) waveforms and Rn(tgr) characterizing background noise. This method was applied to the analysis of chronically implanted microelectrode signals from motor cortex of rat. We found that neural (AP) energy consisted of a large-signal component which grows linearly with the number of threshold-detected neural events and a small-signal component unrelated to the count of threshold-detected AP signals. The addition of pseudorandom noise to electrode signals demonstrated the algorithm's effectiveness for a wide range of noise-to-signal energy ratios (0.08 to 39). We suggest, therefore, that the method could be of use in providing a measure of neural response in situations where clearly identified spike waveforms cannot be isolated, or in providing an additional 'background' measure of microelectrode neural activity to supplement the traditional AP spike count.

Inference of Time-Evolving Coupled Dynamical Systems in the Presence of Noise

NASA Astrophysics Data System (ADS)

Stankovski, Tomislav; Duggento, Andrea; McClintock, Peter V. E.; Stefanovska, Aneta

2012-07-01

A new method is introduced for analysis of interactions between time-dependent coupled oscillators, based on the signals they generate. It distinguishes unsynchronized dynamics from noise-induced phase slips and enables the evolution of the coupling functions and other parameters to be followed. It is based on phase dynamics, with Bayesian inference of the time-evolving parameters achieved by shaping the prior densities to incorporate knowledge of previous samples. The method is tested numerically and applied to reveal and quantify the time-varying nature of cardiorespiratory interactions.

Noise Estimation and Quality Assessment of Gaussian Noise Corrupted Images

NASA Astrophysics Data System (ADS)

Kamble, V. M.; Bhurchandi, K.

2018-03-01

Evaluating the exact quantity of noise present in an image and quality of an image in the absence of reference image is a challenging task. We propose a near perfect noise estimation method and a no reference image quality assessment method for images corrupted by Gaussian noise. The proposed methods obtain initial estimate of noise standard deviation present in an image using the median of wavelet transform coefficients and then obtains a near to exact estimate using curve fitting. The proposed noise estimation method provides the estimate of noise within average error of +/-4%. For quality assessment, this noise estimate is mapped to fit the Differential Mean Opinion Score (DMOS) using a nonlinear function. The proposed methods require minimum training and yields the noise estimate and image quality score. Images from Laboratory for image and Video Processing (LIVE) database and Computational Perception and Image Quality (CSIQ) database are used for validation of the proposed quality assessment method. Experimental results show that the performance of proposed quality assessment method is at par with the existing no reference image quality assessment metric for Gaussian noise corrupted images.

Use of baited remote underwater video (BRUV) and motion analysis for studying the impacts of underwater noise upon free ranging fish and implications for marine energy management.

PubMed

Roberts, Louise; Pérez-Domínguez, Rafael; Elliott, Michael

2016-11-15

Free-ranging individual fish were observed using a baited remote underwater video (BRUV) system during sound playback experiments. This paper reports on test trials exploring BRUV design parameters, image analysis and practical experimental designs. Three marine species were exposed to playback noise, provided as examples of behavioural responses to impulsive sound at 163-171dB re 1μPa (peak-to-peak SPL) and continuous sound of 142.7dB re 1μPa (RMS, SPL), exhibiting directional changes and accelerations. The methods described here indicate the efficacy of BRUV to examine behaviour of free-ranging species to noise playback, rather than using confinement. Given the increasing concern about the effects of water-borne noise, for example its inclusion within the EU Marine Strategy Framework Directive, and the lack of empirical evidence in setting thresholds, this paper discusses the use of BRUV, and short term behavioural changes, in supporting population level marine noise management. Copyright © 2016 Elsevier Ltd. All rights reserved.

No-reference multiscale blur detection tool for content based image retrieval

NASA Astrophysics Data System (ADS)

Ezekiel, Soundararajan; Stocker, Russell; Harrity, Kyle; Alford, Mark; Ferris, David; Blasch, Erik; Gorniak, Mark

2014-06-01

In recent years, digital cameras have been widely used for image capturing. These devices are equipped in cell phones, laptops, tablets, webcams, etc. Image quality is an important component of digital image analysis. To assess image quality for these mobile products, a standard image is required as a reference image. In this case, Root Mean Square Error and Peak Signal to Noise Ratio can be used to measure the quality of the images. However, these methods are not possible if there is no reference image. In our approach, a discrete-wavelet transformation is applied to the blurred image, which decomposes into the approximate image and three detail sub-images, namely horizontal, vertical, and diagonal images. We then focus on noise-measuring the detail images and blur-measuring the approximate image to assess the image quality. We then compute noise mean and noise ratio from the detail images, and blur mean and blur ratio from the approximate image. The Multi-scale Blur Detection (MBD) metric provides both an assessment of the noise and blur content. These values are weighted based on a linear regression against full-reference y values. From these statistics, we can compare to normal useful image statistics for image quality without needing a reference image. We then test the validity of our obtained weights by R2 analysis as well as using them to estimate image quality of an image with a known quality measure. The result shows that our method provides acceptable results for images containing low to mid noise levels and blur content.

Automatic identification and removal of ocular artifacts in EEG--improved adaptive predictor filtering for portable applications.

PubMed

Zhao, Qinglin; Hu, Bin; Shi, Yujun; Li, Yang; Moore, Philip; Sun, Minghou; Peng, Hong

2014-06-01

Electroencephalogram (EEG) signals have a long history of use as a noninvasive approach to measure brain function. An essential component in EEG-based applications is the removal of Ocular Artifacts (OA) from the EEG signals. In this paper we propose a hybrid de-noising method combining Discrete Wavelet Transformation (DWT) and an Adaptive Predictor Filter (APF). A particularly novel feature of the proposed method is the use of the APF based on an adaptive autoregressive model for prediction of the waveform of signals in the ocular artifact zones. In our test, based on simulated data, the accuracy of noise removal in the proposed model was significantly increased when compared to existing methods including: Wavelet Packet Transform (WPT) and Independent Component Analysis (ICA), Discrete Wavelet Transform (DWT) and Adaptive Noise Cancellation (ANC). The results demonstrate that the proposed method achieved a lower mean square error and higher correlation between the original and corrected EEG. The proposed method has also been evaluated using data from calibration trials for the Online Predictive Tools for Intervention in Mental Illness (OPTIMI) project. The results of this evaluation indicate an improvement in performance in terms of the recovery of true EEG signals with EEG tracking and computational speed in the analysis. The proposed method is well suited to applications in portable environments where the constraints with respect to acceptable wearable sensor attachments usually dictate single channel devices.

Estimating Noise in the Hydrogen Epoch of Reionization Array

NASA Astrophysics Data System (ADS)

Englund Mathieu, Philip; HERA Team

2017-01-01

The Hydrogen Epoch of Reionization Array (HERA) is a radio telescope dedicated to observing large scale structure during and prior to the epoch of reionization. Once completed, HERA will have unprecedented sensitivity to the 21-cm signal from hydrogen reionization. This poster will present time- and frequency-subtraction methods and results from a preliminary analysis of the noise characteristics of the nineteen-element pathfinder array.

Data Unfolding with Wiener-SVD Method

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

Tang, W.; Li, X.; Qian, X.

Here, data unfolding is a common analysis technique used in HEP data analysis. Inspired by the deconvolution technique in the digital signal processing, a new unfolding technique based on the SVD technique and the well-known Wiener filter is introduced. The Wiener-SVD unfolding approach achieves the unfolding by maximizing the signal to noise ratios in the effective frequency domain given expectations of signal and noise and is free from regularization parameter. Through a couple examples, the pros and cons of the Wiener-SVD approach as well as the nature of the unfolded results are discussed.

Analysis of wind-driven ambient noise in a shallow water environment with a sandy seabed.

PubMed

Knobles, D P; Joshi, S M; Gaul, R D; Graber, H C; Williams, N J

2008-09-01

On the New Jersey continental shelf ambient sound levels were recorded during tropical storm Ernesto that produced wind speeds up to 40 knots in early September 2006. The seabed at the position of the acoustic measurements can be approximately described as coarse sand. Differences between the ambient noise levels for the New Jersey shelf measurements and deep water reference measurements are modeled using both normal mode and ray methods. The analysis is consistent with a nonlinear frequency dependent seabed attenuation for the New Jersey site.

Data Unfolding with Wiener-SVD Method

DOE PAGES

Tang, W.; Li, X.; Qian, X.; ...

2017-10-04

Here, data unfolding is a common analysis technique used in HEP data analysis. Inspired by the deconvolution technique in the digital signal processing, a new unfolding technique based on the SVD technique and the well-known Wiener filter is introduced. The Wiener-SVD unfolding approach achieves the unfolding by maximizing the signal to noise ratios in the effective frequency domain given expectations of signal and noise and is free from regularization parameter. Through a couple examples, the pros and cons of the Wiener-SVD approach as well as the nature of the unfolded results are discussed.

Structural analysis of vibroacoustical processes

NASA Technical Reports Server (NTRS)

Gromov, A. P.; Myasnikov, L. L.; Myasnikova, Y. N.; Finagin, B. A.

1973-01-01

The method of automatic identification of acoustical signals, by means of the segmentation was used to investigate noises and vibrations in machines and mechanisms, for cybernetic diagnostics. The structural analysis consists of presentation of a noise or vibroacoustical signal as a sequence of segments, determined by the time quantization, in which each segment is characterized by specific spectral characteristics. The structural spectrum is plotted as a histogram of the segments, also as a relation of the probability density of appearance of a segment to the segment type. It is assumed that the conditions of ergodic processes are maintained.

Nonlinear mode decomposition: A noise-robust, adaptive decomposition method

NASA Astrophysics Data System (ADS)

Iatsenko, Dmytro; McClintock, Peter V. E.; Stefanovska, Aneta

2015-09-01

The signals emanating from complex systems are usually composed of a mixture of different oscillations which, for a reliable analysis, should be separated from each other and from the inevitable background of noise. Here we introduce an adaptive decomposition tool—nonlinear mode decomposition (NMD)—which decomposes a given signal into a set of physically meaningful oscillations for any wave form, simultaneously removing the noise. NMD is based on the powerful combination of time-frequency analysis techniques—which, together with the adaptive choice of their parameters, make it extremely noise robust—and surrogate data tests used to identify interdependent oscillations and to distinguish deterministic from random activity. We illustrate the application of NMD to both simulated and real signals and demonstrate its qualitative and quantitative superiority over other approaches, such as (ensemble) empirical mode decomposition, Karhunen-Loève expansion, and independent component analysis. We point out that NMD is likely to be applicable and useful in many different areas of research, such as geophysics, finance, and the life sciences. The necessary matlab codes for running NMD are freely available for download.

Aircraft interior noise reduction by alternate resonance tuning

NASA Technical Reports Server (NTRS)

Gottwald, James A.; Bliss, Donald B.

1990-01-01

The focus is on a noise control method which considers aircraft fuselages lined with panels alternately tuned to frequencies above and below the frequency that must be attenuated. An interior noise reduction called alternate resonance tuning (ART) is described both theoretically and experimentally. Problems dealing with tuning single paneled wall structures for optimum noise reduction using the ART methodology are presented, and three theoretical problems are analyzed. The first analysis is a three dimensional, full acoustic solution for tuning a panel wall composed of repeating sections with four different panel tunings within that section, where the panels are modeled as idealized spring-mass-damper systems. The second analysis is a two dimensional, full acoustic solution for a panel geometry influenced by the effect of a propagating external pressure field such as that which might be associated with propeller passage by a fuselage. To reduce the analysis complexity, idealized spring-mass-damper panels are again employed. The final theoretical analysis presents the general four panel problem with real panel sections, where the effect of higher structural modes is discussed. Results from an experimental program highlight real applications of the ART concept and show the effectiveness of the tuning on real structures.

Development of a low cost method to estimate the seismic signature of a geothermal field from ambient seismic noise analysis, Authors: Tibuleac, I. M., J. Iovenitti, S. Pullammanapallil, D. von Seggern, F.H. Ibser, D. Shaw and H. McLahlan

NASA Astrophysics Data System (ADS)

Tibuleac, I. M.; Iovenitti, J. L.; Pullammanappallil, S. K.; von Seggern, D. H.; Ibser, H.; Shaw, D.; McLachlan, H.

2015-12-01

A new, cost effective and non-invasive exploration method using ambient seismic noise has been tested at Soda Lake, NV, with promising results. Seismic interferometry was used to extract Green's Functions (P and surface waves) from 21 days of continuous ambient seismic noise. With the advantage of S-velocity models estimated from surface waves, an ambient noise seismic reflection survey along a line (named Line 2), although with lower resolution, reproduced the results of the active survey, when the ambient seismic noise was not contaminated by strong cultural noise. Ambient noise resolution was less at depth (below 1000m) compared to the active survey. Useful information could be recovered from ambient seismic noise, including dipping features and fault locations. Processing method tests were developed, with potential to improve the virtual reflection survey results. Through innovative signal processing techniques, periods not typically analyzed with high frequency sensors were used in this study to obtain seismic velocity model information to a depth of 1.4km. New seismic parameters such as Green's Function reflection component lateral variations, waveform entropy, stochastic parameters (Correlation Length and Hurst number) and spectral frequency content extracted from active and passive surveys showed potential to indicate geothermal favorability through their correlation with high temperature anomalies, and showed potential as fault indicators, thus reducing the uncertainty in fault identification. Geothermal favorability maps along ambient seismic Line 2 were generated considering temperature, lithology and the seismic parameters investigated in this study and compared to the active Line 2 results. Pseudo-favorability maps were also generated using only the seismic parameters analyzed in this study.

Soundscape elaboration from anthrophonic adaptation of community noise

NASA Astrophysics Data System (ADS)

Teddy Badai Samodra, FX

2018-03-01

Under the situation of an urban environment, noise has been a critical issue in affecting the indoor environment. A reliable approach is required for evaluation of the community noise as one factor of anthrophonic in the urban environment. This research investigates the level of noise exposure from different community noise sources and elaborates the advantage of the noise disadvantages for soundscape innovation. Integrated building element design as a protector for noise control and speech intelligibility compliance using field experiment and MATLAB programming and modeling are also carried out. Meanwhile, for simulation analysis and building acoustic optimization, Sound Reduction-Speech Intelligibility and Reverberation Time are the main parameters for identifying tropical building model as case study object. The results show that the noise control should consider its integration with the other critical issue, thermal control, in an urban environment. The 1.1 second of reverberation time for speech activities and noise reduction more than 28.66 dBA for critical frequency (20 Hz), the speech intelligibility index could be reached more than fair assessment, 0.45. Furthermore, the environmental psychology adaptation result “Close The Opening” as the best method in high noise condition and personal adjustment as the easiest and the most adaptable way.

Characterizing local variability in long‐period horizontal tilt noise

USGS Publications Warehouse

Rohde, M.D.; Ringler, Adam; Hutt, Charles R.; Wilson, David; Holland, Austin; Sandoval, L.D; Storm, Tyler

2017-01-01

Horizontal seismic data are dominated by atmospherically induced tilt noise at long periods (i.e., 30 s and greater). Tilt noise limits our ability to use horizontal data for sensitive seismological studies such as observing free earth modes. To better understand the local spatial variability of long‐period horizontal noise, we observe horizontal noise during quiet time periods in the Albuquerque Seismological Laboratory (ASL) underground vault using four small‐aperture array configurations. Each array comprises eight Streckeisen STS‐2 broadband seismometers. We analyze the spectral content of the data using power spectral density and magnitude‐squared coherence (γ2‐coherence). Our results show a high degree of spatial variability and frequency dependence in the long‐period horizontal wavefield. The variable nature of long‐period horizontal noise in the ASL vault suggests that it might be highly local in nature and not easily characterized by simple physical models when overall noise levels are low, making it difficult to identify locations in the vault with lower horizontal noise. This variability could be limiting our ability to apply coherence analysis for estimating horizontal sensor self‐noise and could also complicate various indirect methods for removing long‐period horizontal noise (e.g., collocated rotational sensor or microbarograph).

An intervention for noise control of blast furnace in steel industry.

PubMed

Golmohammadi, Rostam; Giahi, Omid; Aliabadi, Mohsen; Darvishi, Ebrahim

2014-01-01

Noise pollution is currently a major health risk factor for workers in industries. The aim of this study was to investigate noise pollution and implement a control intervention plan for blast furnace in a steel industry. The measurement of sound pressure level (SPL) along with frequency analysis was done with the sound-level-meter Cell-450. Personal noise exposure was performed using dosimeter TES-1345 calibrated with CEL-282. Before planning noise controls, acoustic insulation properties of the furnace control unit and workers' rest room were assessed. Control room and workers' rest room were redesigned in order to improve acoustical condition. The SPL before intervention around the Blast Furnace was 90.3 dB (L) and its dominant frequency was 4000 Hz. Besides, noise transmission loss of the control and rest rooms were 10.3 dB and 4.2 dB, respectively. After intervention, noise reduction rates in the control and rest rooms were 27.4 dB and 27.7 dB, respectively. The workers' noise dose before and after the intervention was 240% and less than 100%, respectively. Improvement the workroom acoustic conditions through noise insulation can be considered effective method for preventing workers exposure to harmful noise.

Dealing with noise and physiological artifacts in human EEG recordings: empirical mode methods

NASA Astrophysics Data System (ADS)

Runnova, Anastasiya E.; Grubov, Vadim V.; Khramova, Marina V.; Hramov, Alexander E.

2017-04-01

In the paper we propose the new method for removing noise and physiological artifacts in human EEG recordings based on empirical mode decomposition (Hilbert-Huang transform). As physiological artifacts we consider specific oscillatory patterns that cause problems during EEG analysis and can be detected with additional signals recorded simultaneously with EEG (ECG, EMG, EOG, etc.) We introduce the algorithm of the proposed method with steps including empirical mode decomposition of EEG signal, choosing of empirical modes with artifacts, removing these empirical modes and reconstructing of initial EEG signal. We show the efficiency of the method on the example of filtration of human EEG signal from eye-moving artifacts.

Model Reduction via Principe Component Analysis and Markov Chain Monte Carlo (MCMC) Methods

NASA Astrophysics Data System (ADS)

Gong, R.; Chen, J.; Hoversten, M. G.; Luo, J.

2011-12-01

Geophysical and hydrogeological inverse problems often include a large number of unknown parameters, ranging from hundreds to millions, depending on parameterization and problems undertaking. This makes inverse estimation and uncertainty quantification very challenging, especially for those problems in two- or three-dimensional spatial domains. Model reduction technique has the potential of mitigating the curse of dimensionality by reducing total numbers of unknowns while describing the complex subsurface systems adequately. In this study, we explore the use of principal component analysis (PCA) and Markov chain Monte Carlo (MCMC) sampling methods for model reduction through the use of synthetic datasets. We compare the performances of three different but closely related model reduction approaches: (1) PCA methods with geometric sampling (referred to as 'Method 1'), (2) PCA methods with MCMC sampling (referred to as 'Method 2'), and (3) PCA methods with MCMC sampling and inclusion of random effects (referred to as 'Method 3'). We consider a simple convolution model with five unknown parameters as our goal is to understand and visualize the advantages and disadvantages of each method by comparing their inversion results with the corresponding analytical solutions. We generated synthetic data with noise added and invert them under two different situations: (1) the noised data and the covariance matrix for PCA analysis are consistent (referred to as the unbiased case), and (2) the noise data and the covariance matrix are inconsistent (referred to as biased case). In the unbiased case, comparison between the analytical solutions and the inversion results show that all three methods provide good estimates of the true values and Method 1 is computationally more efficient. In terms of uncertainty quantification, Method 1 performs poorly because of relatively small number of samples obtained, Method 2 performs best, and Method 3 overestimates uncertainty due to inclusion of random effects. However, in the biased case, only Method 3 correctly estimates all the unknown parameters, and both Methods 1 and 2 provide wrong values for the biased parameters. The synthetic case study demonstrates that if the covariance matrix for PCA analysis is inconsistent with true models, the PCA methods with geometric or MCMC sampling will provide incorrect estimates.

Brightness checkerboard lattice method for the calibration of the coaxial reverse Hartmann test

NASA Astrophysics Data System (ADS)

Li, Xinji; Hui, Mei; Li, Ning; Hu, Shinan; Liu, Ming; Kong, Lingqin; Dong, Liquan; Zhao, Yuejin

2018-01-01

The coaxial reverse Hartmann test (RHT) is widely used in the measurement of large aspheric surfaces as an auxiliary method for interference measurement, because of its large dynamic range, highly flexible test with low frequency of surface errors, and low cost. And the accuracy of the coaxial RHT depends on the calibration. However, the calibration process remains inefficient, and the signal-to-noise ratio limits the accuracy of the calibration. In this paper, brightness checkerboard lattices were used to replace the traditional dot matrix. The brightness checkerboard method can reduce the number of dot matrix projections in the calibration process, thus improving efficiency. An LCD screen displayed a brightness checkerboard lattice, in which the brighter checkerboard and the darker checkerboard alternately arranged. Based on the image on the detector, the relationship between the rays at certain angles and the photosensitive positions of the detector coordinates can be obtained. And a differential de-noising method can effectively reduce the impact of noise on the measurement results. Simulation and experimentation proved the feasibility of the method. Theoretical analysis and experimental results show that the efficiency of the brightness checkerboard lattices is about four times that of the traditional dot matrix, and the signal-to-noise ratio of the calibration is significantly improved.

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.

On the effect of experimental noise on the classification of biological samples using Raman micro-spectroscopy

NASA Astrophysics Data System (ADS)

Barton, Sinead J.; Kerr, Laura T.; Domijan, Katarina; Hennelly, Bryan M.

2016-04-01

Raman micro-spectroscopy is an optoelectronic technique that can be used to evaluate the chemical composition of biological samples and has been shown to be a powerful diagnostic tool for the investigation of various cancer related diseases including bladder, breast, and cervical cancer. Raman scattering is an inherently weak process with approximately 1 in 107 photons undergoing scattering and for this reason, noise from the recording system can have a significant impact on the quality of the signal, and its suitability for diagnostic classification. The main sources of noise in the recorded signal are shot noise, CCD dark current, and CCD readout noise. Shot noise results from the low signal photon count while dark current results from thermally generated electrons in the semiconductor pixels. Both of these noise sources are time dependent; readout noise is time independent but is inherent in each individual recording and results in the fundamental limit of measurement, arising from the internal electronics of the camera. In this paper, each of the aforementioned noise sources are analysed in isolation, and used to experimentally validate a mathematical model. This model is then used to simulate spectra that might be acquired under various experimental conditions including the use of different cameras, different source wavelength, and power etc. Simulated noisy datasets of T24 and RT112 cell line spectra are generated based on true cell Raman spectrum irradiance values (recorded using very long exposure times) and the addition of simulated noise. These datasets are then input to multivariate classification using Principal Components Analysis and Linear Discriminant Analysis. This method enables an investigation into the effect of noise on the sensitivity and specificity of Raman based classification under various experimental conditions and using different equipment.

Analysis of possible factors of vocal interference during the teaching activity

PubMed Central

Silva, Bárbara Gabriela; Chammas, Tiago Visacre; Zenari, Marcia Simões; Moreira, Renata Rodrigues; Samelli, Alessandra Giannella; Nemr, Kátia

2017-01-01

ABSTRACT OBJECTIVE To measure the risk of dysphonia in teachers, as well as investigate whether the perceptual-auditory and acoustic aspects of the voice of teachers in situations of silence and noise, the signal-to-noise ratio, and the noise levels in the classroom are associated with the presence of dysphonia. METHODS This is an observational cross-sectional research with 23 primary and secondary school teachers from a private school in the municipality of São Paulo, Brazil, divided into the groups without dysphonia and with dysphonia. We performed the following procedures: general Dysphonia Risk Screening Protocol (General-DRSP) and complementary to speaking voice - teacher (Specific-DRSP), voice recording during class and in an individual situation in a silent room, and measurement of the signal-to-noise ratio and noise levels of classrooms. RESULTS We have found differences between groups regarding physical activity (General-DRSP) and particularities of the profession (Specific-DRSP), as well as in all aspects of the perceptual-auditory vocal analysis. We have found signs of voice wear in the group without dysphonia. Regarding the vocal resources in the situations of noise and silence, we have identified a difference for the production of abrupt vocal attack and the tendency of a more precise speech in the situation of noise. Both the signal-to-noise ratio and the room noise levels during class were high in both groups. CONCLUSIONS Teachers in both groups are at high risk for developing dysphonia and have negative vocal signals to a greater or lesser extent. Signal-to-noise ratio was inadequate in most classrooms, considering the standards for both children with normal hearing and with hearing loss, as well as equivalent noise levels. PMID:29236878

An optimized ensemble local mean decomposition method for fault detection of mechanical components

NASA Astrophysics Data System (ADS)

Zhang, Chao; Li, Zhixiong; Hu, Chao; Chen, Shuai; Wang, Jianguo; Zhang, Xiaogang

2017-03-01

Mechanical transmission systems have been widely adopted in most of industrial applications, and issues related to the maintenance of these systems have attracted considerable attention in the past few decades. The recently developed ensemble local mean decomposition (ELMD) method shows satisfactory performance in fault detection of mechanical components for preventing catastrophic failures and reducing maintenance costs. However, the performance of ELMD often heavily depends on proper selection of its model parameters. To this end, this paper proposes an optimized ensemble local mean decomposition (OELMD) method to determinate an optimum set of ELMD parameters for vibration signal analysis. In OELMD, an error index termed the relative root-mean-square error (Relative RMSE) is used to evaluate the decomposition performance of ELMD with a certain amplitude of the added white noise. Once a maximum Relative RMSE, corresponding to an optimal noise amplitude, is determined, OELMD then identifies optimal noise bandwidth and ensemble number based on the Relative RMSE and signal-to-noise ratio (SNR), respectively. Thus, all three critical parameters of ELMD (i.e. noise amplitude and bandwidth, and ensemble number) are optimized by OELMD. The effectiveness of OELMD was evaluated using experimental vibration signals measured from three different mechanical components (i.e. the rolling bearing, gear and diesel engine) under faulty operation conditions.

MO-F-CAMPUS-J-04: One-Year Analysis of Elekta CBCT Image Quality Using NPS and MTF

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

Nakahara, S; Tachibana, M; Watanabe, Y

2015-06-15

Purpose: To compare quantitative image quality (IQ) evaluation methods using Noise Power Spectrum (NPS) and Modulation Transfer Function (MTF) with standard IQ analyses for minimizing the observer subjectivity of the standard methods and maximizing the information content. Methods: For our routine IQ tests of Elekta XVI Cone-Beam CT, image noise was quantified by the standard deviation of CT number (CT#) (Sigma) over a small area in an IQ test phantom (CatPhan), and the high spatial resolution (HSR) was evaluated by the number of line-pairs (LP#) visually recognizable on the image. We also measured the image uniformity, the low contrast resolutionmore » ratio, and the distances of two points for geometrical accuracy. For this study, we did additional evaluation of the XVI data for 12 monthly IQ tests by using NPS for noise, MTF for HSR, and the CT#-to-density relationship. NPS was obtained by applying Fourier analysis in a small area on the uniformity test section of CatPhan. The MTF analysis was performed by applying the Droege-Morin (D-M) method to the line pairs on the phantom. The CT#-to-density was obtained for inserts in the low-contrast test section of the phantom. Results: All the quantities showed a noticeable change over the one-year period. Especially the noise level changed significantly after a repair of the imager. NPS was more sensitive to the IQ change than Sigma. MTF could provide more quantitative and objective evaluation of the HSR. The CT# was very different from the expected CT#; but, the CT#-to-density curves were constant within 5% except two months. Conclusion: Since the D-M method is easy to implement, we recommend using MTF instead of the LP# even for routine periodic QA. The month-to-month variation of IQ was not negligible; hence a routine IQ test must be performed, particularly after any modification of hardware including detector calibration.« less

Adaptive signal processing and higher order time- frequency analysis for acoustic and vibration signatures in condition monitoring

NASA Astrophysics Data System (ADS)

Lee, Sang-Kwon

This thesis is concerned with the development of a useful engineering technique to detect and analyse faults in rotating machinery. The methods developed are based on the advanced signal processing such as the adaptive signal processing and higher-order time frequency methods. The two-stage Adaptive Line Enhancer (ALE), using adaptive signal processing, has been developed for increasing the Signal to Noise Ratio of impulsive signals. The enhanced signal can then be analysed using time frequency methods to identify fault characteristics. However, if after pre-processing by the two stage ALE, the SNR of the signals is low, the residual noise often hinders clear identification of the fault characteristics in the time-frequency domain. In such cases, higher order time-frequency methods have been proposed and studied. As examples of rotating machinery, the internal combustion engine and an industrial gear box are considered in this thesis. The noise signal from an internal combustion engine and vibration signal measured on a gear box are studied in detail. Typically an impulsive signal manifests itself when the fault occurs in the machinery and is embedded in background noise, such as the fundamental frequency and its harmonic orders of the rotation speed and broadband noise. The two-stage ALE is developed for reducing this background noise. Conditions for the choice of adaptive filter parameters are studied and suitable adaptive algorithms given. The enhanced impulsive signal is analysed in the time- frequency domain using the Wigner higher order moment spectra (WHOMS) and the multi-time WHOMS (which is a dual form of the WHOMS). The WHOMS suffers from unwanted cross-terms, which increase dramatically as the order increases. Novel expressions for the cross-terms in WHOMS have been presented. The number of cross-terms can be reduced by taking the principal slice of the WHOMS. The residual cross-terms are smoothed by using a general class of kernel functions and the γ-method kernel function which is a novel development in this thesis. The WVD and the sliced WHOMS for synthesised signals and measured data from rotating machinery are analysed. The estimated ROC (Receive Operating Characteristic) curves for these methods are computed. These results lead to the conclusion that the detection performance when using the sliced WHOMS, for impulsive signals in embedded in broadband noise, is better than that of the Wigner-Ville distribution. Real data from a faulty car engine and faulty industrial gears are analysed. The car engine radiates an impulsive noise signal due to the loosening of a spark plug. The faulty industrial gear produces an impulsive vibration signal due to a spall on the tooth face in gear. The two- stage ALE and WHOMS are successfully applied to detection and analysis of these impulsive signals.

Intertime jump statistics of state-dependent Poisson processes.

PubMed

Daly, Edoardo; Porporato, Amilcare

2007-01-01

A method to obtain the probability distribution of the interarrival times of jump occurrences in systems driven by state-dependent Poisson noise is proposed. Such a method uses the survivor function obtained by a modified version of the master equation associated to the stochastic process under analysis. A model for the timing of human activities shows the capability of state-dependent Poisson noise to generate power-law distributions. The application of the method to a model for neuron dynamics and to a hydrological model accounting for land-atmosphere interaction elucidates the origin of characteristic recurrence intervals and possible persistence in state-dependent Poisson models.

Noise-free recovery of optodigital encrypted and multiplexed images.

PubMed

Henao, Rodrigo; Rueda, Edgar; Barrera, John F; Torroba, Roberto

2010-02-01

We present a method that allows storing multiple encrypted data using digital holography and a joint transform correlator architecture with a controllable angle reference wave. In this method, the information is multiplexed by using a key and a different reference wave angle for each object. In the recovering process, the use of different reference wave angles prevents noise produced by the nonrecovered objects from being superimposed on the recovered object; moreover, the position of the recovered object in the exit plane can be fully controlled. We present the theoretical analysis and the experimental results that show the potential and applicability of the method.

Long-term Self-noise Estimates of Seismic Sensors From a High-noise Vault

NASA Astrophysics Data System (ADS)

Hicks, S. P.; Goessen, S.; Hill, P.; Rietbrock, A.

2017-12-01

To understand the detection capabilities of seismic stations and for reducing biases in ambient noise imaging, it is vital to assess the contribution of instrument self-noise to overall site noise. Self-noise estimates typically come from vault installations in continental interiors with very low ambient noise levels. However, this approach restricts the independent assessment of self-noise by individual end-users to assess any variations in their own instrument pools from nominal specifications given by manufacturers and from estimations given in comparative test papers. However, the calculation method should be adapted to variable installation conditions. One problem is that microseism noise can contaminate self-noise results caused by instrument misalignment errors or manufacturing limits; this effect becomes stronger where ambient noise is higher. Moreover, due to expected stochastic and time-varying sensor noise, estimates based on hand-picking small numbers of data segments may not accurately reflect true self-noise. We report on results from a self-noise test experiment of Güralp seismic instruments (3T, 3ESPC broadband seismometers, Fortis strong motion accelerometer) that were installed in the sub-surface vault of the Eskdalemuir Seismic Observatory in Scotland, UK over the period October 2016-August 2017. Due to vault's proximity to the ocean, secondary microseism noise is strong, so we efficiently compute the angle of misalignment that maximises waveform coherence with a reference sensor. Self-noise was calculated using the 3-sensor correlation technique and we compute probability density functions of self-noise to assess its spread over time. We find that not correcting for misalignments as low as 0.1° can cause self-noise to be artificially higher by up to 15 dB at frequencies of 0.1-1 Hz. Our method thus efficiently removes the effect of microseism contamination on self-noise; for example, it restores the minimum noise floor for a 360s - 50 Hz 3T to -195 dB at 0.2 Hz. Furthermore, based on the analysis of our calculated probability density functions, we find at long-periods (> 30 s) the average self-noise can be up to 5 dB higher than the minimum noise floor. We discuss the validity of these results in terms of making direct comparisons with self-noise results from much quieter installations.

Design and analysis of the Gemini chain system in dual clutch transmission of automobile

NASA Astrophysics Data System (ADS)

Cheng, Yabing; Guo, Haitao; Fu, Zhenming; Wan, Nen; Li, Lei; Wang, Yang

2015-01-01

Chain drive system is widely used in the conditions of high-speed, overload, variable speed and load. Many studies are focused on the meshing theory and wear characteristics of chain drive system, but system design, analysis, and noise characteristics of the chain drive system are weak. System design and noise characteristic are studied for a new type Gemini chain of dual-clutch automatic transmission. Based on the meshing theory of silent chain, the design parameters of the Gemini chain system are calculated and the mathematical models and dynamic analysis models of the Gemini chain system are established. Dynamic characteristics of the Gemini chain system is simulated and the contact force of plate and pin, plate and sprockets, the chain tension forces, the transmission error and the stress of plates and pins are analyzed. According to the simulation results of the Gemini chain system, the noise experiment about system is carried out. The noise values are tested at different speed and load and spectral characteristics are analyzed. The results of simulation and experimental show that the contact forces of plate and pin, plate and sprockets are smaller than the allowable stress values, the chain tension force is less than ultimate tension and transmission error is limited in 1.2%. The noise values can meet the requirements of industrial design, and it is proved that the design and analysis method of the Gemini chain system is scientific and feasible. The design and test system is built from analysis to test of Gemini chain system. This research presented will provide a corresponding theoretical guidance for the design and dynamic characteristics and noise characteristics of chain drive system.

Prospective ECG-Triggered Coronary CT Angiography: Clinical Value of Noise-Based Tube Current Reduction Method with Iterative Reconstruction

PubMed Central

Shen, Junlin; Du, Xiangying; Guo, Daode; Cao, Lizhen; Gao, Yan; Yang, Qi; Li, Pengyu; Liu, Jiabin; Li, Kuncheng

2013-01-01

Objectives To evaluate the clinical value of noise-based tube current reduction method with iterative reconstruction for obtaining consistent image quality with dose optimization in prospective electrocardiogram (ECG)-triggered coronary CT angiography (CCTA). Materials and Methods We performed a prospective randomized study evaluating 338 patients undergoing CCTA with prospective ECG-triggering. Patients were randomly assigned to fixed tube current with filtered back projection (Group 1, n = 113), noise-based tube current with filtered back projection (Group 2, n = 109) or with iterative reconstruction (Group 3, n = 116). Tube voltage was fixed at 120 kV. Qualitative image quality was rated on a 5-point scale (1 = impaired, to 5 = excellent, with 3–5 defined as diagnostic). Image noise and signal intensity were measured; signal-to-noise ratio was calculated; radiation dose parameters were recorded. Statistical analyses included one-way analysis of variance, chi-square test, Kruskal-Wallis test and multivariable linear regression. Results Image noise was maintained at the target value of 35HU with small interquartile range for Group 2 (35.00–35.03HU) and Group 3 (34.99–35.02HU), while from 28.73 to 37.87HU for Group 1. All images in the three groups were acceptable for diagnosis. A relative 20% and 51% reduction in effective dose for Group 2 (2.9 mSv) and Group 3 (1.8 mSv) were achieved compared with Group 1 (3.7 mSv). After adjustment for scan characteristics, iterative reconstruction was associated with 26% reduction in effective dose. Conclusion Noise-based tube current reduction method with iterative reconstruction maintains image noise precisely at the desired level and achieves consistent image quality. Meanwhile, effective dose can be reduced by more than 50%. PMID:23741444

Distortion analysis of subband adaptive filtering methods for FMRI active noise control systems.

PubMed

Milani, Ali A; Panahi, Issa M; Briggs, Richard

2007-01-01

Delayless subband filtering structure, as a high performance frequency domain filtering technique, is used for canceling broadband fMRI noise (8 kHz bandwidth). In this method, adaptive filtering is done in subbands and the coefficients of the main canceling filter are computed by stacking the subband weights together. There are two types of stacking methods called FFT and FFT-2. In this paper, we analyze the distortion introduced by these two stacking methods. The effect of the stacking distortion on the performance of different adaptive filters in FXLMS algorithm with non-minimum phase secondary path is explored. The investigation is done for different adaptive algorithms (nLMS, APA and RLS), different weight stacking methods, and different number of subbands.

How does C-VIEW image quality compare with conventional 2D FFDM?

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

Nelson, Jeffrey S., E-mail: nelson.jeffrey@duke.edu; Wells, Jered R.; Baker, Jay A.

Purpose: The FDA approved the use of digital breast tomosynthesis (DBT) in 2011 as an adjunct to 2D full field digital mammography (FFDM) with the constraint that all DBT acquisitions must be paired with a 2D image to assure adequate interpretative information is provided. Recently manufacturers have developed methods to provide a synthesized 2D image generated from the DBT data with the hope of sparing patients the radiation exposure from the FFDM acquisition. While this much needed alternative effectively reduces the total radiation burden, differences in image quality must also be considered. The goal of this study was to comparemore » the intrinsic image quality of synthesized 2D C-VIEW and 2D FFDM images in terms of resolution, contrast, and noise. Methods: Two phantoms were utilized in this study: the American College of Radiology mammography accreditation phantom (ACR phantom) and a novel 3D printed anthropomorphic breast phantom. Both phantoms were imaged using a Hologic Selenia Dimensions 3D system. Analysis of the ACR phantom includes both visual inspection and objective automated analysis using in-house software. Analysis of the 3D anthropomorphic phantom includes visual assessment of resolution and Fourier analysis of the noise. Results: Using ACR-defined scoring criteria for the ACR phantom, the FFDM images scored statistically higher than C-VIEW according to both the average observer and automated scores. In addition, between 50% and 70% of C-VIEW images failed to meet the nominal minimum ACR accreditation requirements—primarily due to fiber breaks. Software analysis demonstrated that C-VIEW provided enhanced visualization of medium and large microcalcification objects; however, the benefits diminished for smaller high contrast objects and all low contrast objects. Visual analysis of the anthropomorphic phantom showed a measureable loss of resolution in the C-VIEW image (11 lp/mm FFDM, 5 lp/mm C-VIEW) and loss in detection of small microcalcification objects. Spectral analysis of the anthropomorphic phantom showed higher total noise magnitude in the FFDM image compared with C-VIEW. Whereas the FFDM image contained approximately white noise texture, the C-VIEW image exhibited marked noise reduction at midfrequency and high frequency with far less noise suppression at low frequencies resulting in a mottled noise appearance. Conclusions: Their analysis demonstrates many instances where the C-VIEW image quality differs from FFDM. Compared to FFDM, C-VIEW offers a better depiction of objects of certain size and contrast, but provides poorer overall resolution and noise properties. Based on these findings, the utilization of C-VIEW images in the clinical setting requires careful consideration, especially if considering the discontinuation of FFDM imaging. Not explicitly explored in this study is how the combination of DBT + C-VIEW performs relative to DBT + FFDM or FFDM alone.« less

Detection of Road Surface States from Tire Noise Using Neural Network Analysis

NASA Astrophysics Data System (ADS)

Kongrattanaprasert, Wuttiwat; Nomura, Hideyuki; Kamakura, Tomoo; Ueda, Koji

This report proposes a new processing method for automatically detecting the states of road surfaces from tire noises of passing vehicles. In addition to multiple indicators of the signal features in the frequency domain, we propose a few feature indicators in the time domain to successfully classify the road states into four categories: snowy, slushy, wet, and dry states. The method is based on artificial neural networks. The proposed classification is carried out in multiple neural networks using learning vector quantization. The outcomes of the networks are then integrated by the voting decision-making scheme. Experimental results obtained from recorded signals for ten days in the snowy season demonstrated that an accuracy of approximately 90% can be attained for predicting road surface states using only tire noise data.

23 CFR 772.11 - Analysis of traffic noise impacts.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 23 Highways 1 2012-04-01 2012-04-01 false Analysis of traffic noise impacts. 772.11 Section 772.11... PROCEDURES FOR ABATEMENT OF HIGHWAY TRAFFIC NOISE AND CONSTRUCTION NOISE § 772.11 Analysis of traffic noise impacts. (a) The highway agency shall determine and analyze expected traffic noise impacts. (1) For...

23 CFR 772.11 - Analysis of traffic noise impacts.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 23 Highways 1 2013-04-01 2013-04-01 false Analysis of traffic noise impacts. 772.11 Section 772.11... PROCEDURES FOR ABATEMENT OF HIGHWAY TRAFFIC NOISE AND CONSTRUCTION NOISE § 772.11 Analysis of traffic noise impacts. (a) The highway agency shall determine and analyze expected traffic noise impacts. (1) For...

23 CFR 772.11 - Analysis of traffic noise impacts.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 23 Highways 1 2014-04-01 2014-04-01 false Analysis of traffic noise impacts. 772.11 Section 772.11... PROCEDURES FOR ABATEMENT OF HIGHWAY TRAFFIC NOISE AND CONSTRUCTION NOISE § 772.11 Analysis of traffic noise impacts. (a) The highway agency shall determine and analyze expected traffic noise impacts. (1) For...

Noise Certification Predictions for FJX-2-Powered Aircraft Using Analytic Methods

NASA Technical Reports Server (NTRS)

Berton, Jeffrey J.

1999-01-01

Williams International Co. is currently developing the 700-pound thrust class FJX-2 turbofan engine for the general Aviation Propulsion Program's Turbine Engine Element. As part of the 1996 NASA-Williams cooperative working agreement, NASA agreed to analytically calculate the noise certification levels of the FJX-2-powered V-Jet II test bed aircraft. Although the V-Jet II is a demonstration aircraft that is unlikely to be produced and certified, the noise results presented here may be considered to be representative of the noise levels of small, general aviation jet aircraft that the FJX-2 would power. A single engine variant of the V-Jet II, the V-Jet I concept airplane, is also considered. Reported in this paper are the analytically predicted FJX-2/V-Jet noise levels appropriate for Federal Aviation Regulation certification. Also reported are FJX-2/V-Jet noise levels using noise metrics appropriate for the propeller-driven aircraft that will be its major market competition, as well as a sensitivity analysis of the certification noise levels to major system uncertainties.

Space vehicle acoustics prediction improvement for payloads. [space shuttle

NASA Technical Reports Server (NTRS)

Dandridge, R. E.

1979-01-01

The modal analysis method was extensively modified for the prediction of space vehicle noise reduction in the shuttle payload enclosure, and this program was adapted to the IBM 360 computer. The predicted noise reduction levels for two test cases were compared with experimental results to determine the validity of the analytical model for predicting space vehicle payload noise environments in the 10 Hz one-third octave band regime. The prediction approach for the two test cases generally gave reasonable magnitudes and trends when compared with the measured noise reduction spectra. The discrepancies in the predictions could be corrected primarily by improved modeling of the vehicle structural walls and of the enclosed acoustic space to obtain a more accurate assessment of normal modes. Techniques for improving and expandng the noise prediction for a payload environment are also suggested.

Diagnostics and Active Control of Aircraft Interior Noise

NASA Technical Reports Server (NTRS)

Fuller, C. R.

1998-01-01

This project deals with developing advanced methods for investigating and controlling interior noise in aircraft. The work concentrates on developing and applying the techniques of Near Field Acoustic Holography (NAH) and Principal Component Analysis (PCA) to the aircraft interior noise dynamic problem. This involves investigating the current state of the art, developing new techniques and then applying them to the particular problem being studied. The knowledge gained under the first part of the project was then used to develop and apply new, advanced noise control techniques for reducing interior noise. A new fully active control approach based on the PCA was developed and implemented on a test cylinder. Finally an active-passive approach based on tunable vibration absorbers was to be developed and analytically applied to a range of test structures from simple plates to aircraft fuselages.

Frequency-domain method for discrete frequency noise prediction of rotors in arbitrary steady motion

NASA Astrophysics Data System (ADS)

Gennaretti, M.; Testa, C.; Bernardini, G.

2012-12-01

A novel frequency-domain formulation for the prediction of the tonal noise emitted by rotors in arbitrary steady motion is presented. It is derived from Farassat's 'Formulation 1A', that is a time-domain boundary integral representation for the solution of the Ffowcs-Williams and Hawkings equation, and represents noise as harmonic response to body kinematics and aerodynamic loads via frequency-response-function matrices. The proposed frequency-domain solver is applicable to rotor configurations for which sound pressure levels of discrete tones are much higher than those of broadband noise. The numerical investigation concerns the analysis of noise produced by an advancing helicopter rotor in blade-vortex interaction conditions, as well as the examination of pressure disturbances radiated by the interaction of a marine propeller with a non-uniform inflow.

Noise-band factor analysis of cancer Fourier transform infrared evanescent-wave fiber optical (FTIR-FEW) spectra

NASA Astrophysics Data System (ADS)

Sukuta, Sydney; Bruch, Reinhard F.

2002-05-01

The goal of this study is to test the feasibility of using noise factor/eigenvector bands as general clinical analytical tools for diagnoses. We developed a new technique, Noise Band Factor Cluster Analysis (NBFCA), to diagnose benign tumors via their Fourier transform IR fiber optic evanescent wave spectral data for the first time. The middle IR region of human normal skin tissue and benign and melanoma tumors, were analyzed using this new diagnostic technique. Our results are not in full-agreement with pathological classifications hence there is a possibility that our approaches could complement or improve these traditional classification schemes. Moreover, the use of NBFCA make it much easier to delineate class boundaries hence this method provides results with much higher certainty.

Security Analysis of Measurement-Device-Independent Quantum Key Distribution in Collective-Rotation Noisy Environment

NASA Astrophysics Data System (ADS)

Li, Na; Zhang, Yu; Wen, Shuang; Li, Lei-lei; Li, Jian

2018-01-01

Noise is a problem that communication channels cannot avoid. It is, thus, beneficial to analyze the security of MDI-QKD in noisy environment. An analysis model for collective-rotation noise is introduced, and the information theory methods are used to analyze the security of the protocol. The maximum amount of information that Eve can eavesdrop is 50%, and the eavesdropping can always be detected if the noise level ɛ ≤ 0.68. Therefore, MDI-QKD protocol is secure as quantum key distribution protocol. The maximum probability that the relay outputs successful results is 16% when existing eavesdropping. Moreover, the probability that the relay outputs successful results when existing eavesdropping is higher than the situation without eavesdropping. The paper validates that MDI-QKD protocol has better robustness.

Haralick texture features from apparent diffusion coefficient (ADC) MRI images depend on imaging and pre-processing parameters.

PubMed

Brynolfsson, Patrik; Nilsson, David; Torheim, Turid; Asklund, Thomas; Karlsson, Camilla Thellenberg; Trygg, Johan; Nyholm, Tufve; Garpebring, Anders

2017-06-22

In recent years, texture analysis of medical images has become increasingly popular in studies investigating diagnosis, classification and treatment response assessment of cancerous disease. Despite numerous applications in oncology and medical imaging in general, there is no consensus regarding texture analysis workflow, or reporting of parameter settings crucial for replication of results. The aim of this study was to assess how sensitive Haralick texture features of apparent diffusion coefficient (ADC) MR images are to changes in five parameters related to image acquisition and pre-processing: noise, resolution, how the ADC map is constructed, the choice of quantization method, and the number of gray levels in the quantized image. We found that noise, resolution, choice of quantization method and the number of gray levels in the quantized images had a significant influence on most texture features, and that the effect size varied between different features. Different methods for constructing the ADC maps did not have an impact on any texture feature. Based on our results, we recommend using images with similar resolutions and noise levels, using one quantization method, and the same number of gray levels in all quantized images, to make meaningful comparisons of texture feature results between different subjects.

Preparation of Ultracold Atom Clouds at the Shot Noise Level.

PubMed

Gajdacz, M; Hilliard, A J; Kristensen, M A; Pedersen, P L; Klempt, C; Arlt, J J; Sherson, J F

2016-08-12

We prepare number stabilized ultracold atom clouds through the real-time analysis of nondestructive images and the application of feedback. In our experiments, the atom number N∼10^{6} is determined by high precision Faraday imaging with uncertainty ΔN below the shot noise level, i.e., ΔN

Online Estimation of Allan Variance Coefficients Based on a Neural-Extended Kalman Filter

PubMed Central

Miao, Zhiyong; Shen, Feng; Xu, Dingjie; He, Kunpeng; Tian, Chunmiao

2015-01-01

As a noise analysis method for inertial sensors, the traditional Allan variance method requires the storage of a large amount of data and manual analysis for an Allan variance graph. Although the existing online estimation methods avoid the storage of data and the painful procedure of drawing slope lines for estimation, they require complex transformations and even cause errors during the modeling of dynamic Allan variance. To solve these problems, first, a new state-space model that directly models the stochastic errors to obtain a nonlinear state-space model was established for inertial sensors. Then, a neural-extended Kalman filter algorithm was used to estimate the Allan variance coefficients. The real noises of an ADIS16405 IMU and fiber optic gyro-sensors were analyzed by the proposed method and traditional methods. The experimental results show that the proposed method is more suitable to estimate the Allan variance coefficients than the traditional methods. Moreover, the proposed method effectively avoids the storage of data and can be easily implemented using an online processor. PMID:25625903

Passive detection and localization of fatigue cracking in aluminum plates using Green's function reconstruction from ambient noise.

PubMed

Yang, Yang; Xiao, Li; Qu, Wenzhong; Lu, Ye

2017-11-01

Recent theoretical and experimental studies have demonstrated that a local Green's function can be retrieved from the cross-correlation of ambient noise field. This technique can be used to detect fatigue cracking in metallic structures, owing to the fact that the presence of crack can lead to a change in Green's function. This paper presents a method of structural fatigue cracking characterization method by measuring Green's function reconstruction from noise excitation and verifies the feasibility of crack detection in poor noise source distribution. Fatigue cracks usually generate nonlinear effects, in which different wave amplitudes and frequency compositions can cause different nonlinear responses. This study also undertakes analysis of the capacity of the proposed approach to identify fatigue cracking under different noise amplitudes and frequency ranges. Experimental investigations of an aluminum plate are conducted to assess the cross-correlations of received noise between sensor pairs and finally to detect the introduced fatigue crack. A damage index is proposed according to the variation between cross-correlations obtained from the pristine crack closed state and the crack opening-closure state when sufficient noise amplitude is used to generate nonlinearity. A probability distribution map of damage is calculated based on damage indices. The fatigue crack introduced in the aluminum plate is successfully identified and oriented, verifying that a fatigue crack can be detected by reconstructing Green's functions from an imperfect diffuse field in which ambient noise sources exist locally. Copyright © 2017 Elsevier B.V. All rights reserved.

Comparison of automatic denoising methods for phonocardiograms with extraction of signal parameters via the Hilbert Transform

NASA Astrophysics Data System (ADS)

Messer, Sheila R.; Agzarian, John; Abbott, Derek

2001-05-01

Phonocardiograms (PCGs) have many advantages over traditional auscultation (listening to the heart) because they may be replayed, may be analyzed for spectral and frequency content, and frequencies inaudible to the human ear may be recorded. However, various sources of noise may pollute a PCG including lung sounds, environmental noise and noise generated from contact between the recording device and the skin. Because PCG signals are known to be nonlinear and it is often not possible to determine their noise content, traditional de-noising methods may not be effectively applied. However, other methods including wavelet de-noising, wavelet packet de-noising and averaging can be employed to de-noise the PCG. This study examines and compares these de-noising methods. This study answers such questions as to which de-noising method gives a better SNR, the magnitude of signal information that is lost as a result of the de-noising process, the appropriate uses of the different methods down to such specifics as to which wavelets and decomposition levels give best results in wavelet and wavelet packet de-noising. In general, the wavelet and wavelet packet de-noising performed roughly equally with optimal de-noising occurring at 3-5 levels of decomposition. Averaging also proved a highly useful de- noising technique; however, in some cases averaging is not appropriate. The Hilbert Transform is used to illustrate the results of the de-noising process and to extract instantaneous features including instantaneous amplitude, frequency, and phase.

A New Feature-Enhanced Speckle Reduction Method Based on Multiscale Analysis for Ultrasound B-Mode Imaging.

PubMed

Kang, Jinbum; Lee, Jae Young; Yoo, Yangmo

2016-06-01

Effective speckle reduction in ultrasound B-mode imaging is important for enhancing the image quality and improving the accuracy in image analysis and interpretation. In this paper, a new feature-enhanced speckle reduction (FESR) method based on multiscale analysis and feature enhancement filtering is proposed for ultrasound B-mode imaging. In FESR, clinical features (e.g., boundaries and borders of lesions) are selectively emphasized by edge, coherence, and contrast enhancement filtering from fine to coarse scales while simultaneously suppressing speckle development via robust diffusion filtering. In the simulation study, the proposed FESR method showed statistically significant improvements in edge preservation, mean structure similarity, speckle signal-to-noise ratio, and contrast-to-noise ratio (CNR) compared with other speckle reduction methods, e.g., oriented speckle reducing anisotropic diffusion (OSRAD), nonlinear multiscale wavelet diffusion (NMWD), the Laplacian pyramid-based nonlinear diffusion and shock filter (LPNDSF), and the Bayesian nonlocal means filter (OBNLM). Similarly, the FESR method outperformed the OSRAD, NMWD, LPNDSF, and OBNLM methods in terms of CNR, i.e., 10.70 ± 0.06 versus 9.00 ± 0.06, 9.78 ± 0.06, 8.67 ± 0.04, and 9.22 ± 0.06 in the phantom study, respectively. Reconstructed B-mode images that were developed using the five speckle reduction methods were reviewed by three radiologists for evaluation based on each radiologist's diagnostic preferences. All three radiologists showed a significant preference for the abdominal liver images obtained using the FESR methods in terms of conspicuity, margin sharpness, artificiality, and contrast, p<0.0001. For the kidney and thyroid images, the FESR method showed similar improvement over other methods. However, the FESR method did not show statistically significant improvement compared with the OBNLM method in margin sharpness for the kidney and thyroid images. These results demonstrate that the proposed FESR method can improve the image quality of ultrasound B-mode imaging by enhancing the visualization of lesion features while effectively suppressing speckle noise.

Pilot study of methods and equipment for in-home noise level measurements.

PubMed

Neitzel, Richard L; Heikkinen, Maire S A; Williams, Christopher C; Viet, Susan Marie; Dellarco, Michael

2015-01-15

Knowledge of the auditory and non-auditory effects of noise has increased dramatically over the past decade, but indoor noise exposure measurement methods have not advanced appreciably, despite the introduction of applicable new technologies. This study evaluated various conventional and smart devices for exposure assessment in the National Children's Study. Three devices were tested: a sound level meter (SLM), a dosimeter, and a smart device with a noise measurement application installed. Instrument performance was evaluated in a series of semi-controlled tests in office environments over 96-hour periods, followed by measurements made continuously in two rooms (a child's bedroom and a most used room) in nine participating homes over a 7-day period with subsequent computation of a range of noise metrics. The SLMs and dosimeters yielded similar A-weighted average noise levels. Levels measured by the smart devices often differed substantially (showing both positive and negative bias, depending on the metric) from those measured via SLM and dosimeter, and demonstrated attenuation in some frequency bands in spectral analysis compared to SLM results. Virtually all measurements exceeded the Environmental Protection Agency's 45 dBA day-night limit for indoor residential exposures. The measurement protocol developed here can be employed in homes, demonstrates the possibility of measuring long-term noise exposures in homes with technologies beyond traditional SLMs, and highlights potential pitfalls associated with measurements made by smart devices.

[Analysis and experimental verification of sensitivity and SNR of laser warning receiver].

PubMed

Zhang, Ji-Long; Wang, Ming; Tian, Er-Ming; Li, Xiao; Wang, Zhi-Bin; Zhang, Yue

2009-01-01

In order to countermeasure increasingly serious threat from hostile laser in modern war, it is urgent to do research on laser warning technology and system, and the sensitivity and signal to noise ratio (SNR) are two important performance parameters in laser warning system. In the present paper, based on the signal statistical detection theory, a method for calculation of the sensitivity and SNR in coherent detection laser warning receiver (LWR) has been proposed. Firstly, the probabilities of the laser signal and receiver noise were analyzed. Secondly, based on the threshold detection theory and Neyman-Pearson criteria, the signal current equation was established by introducing detection probability factor and false alarm rate factor, then, the mathematical expressions of sensitivity and SNR were deduced. Finally, by using method, the sensitivity and SNR of the sinusoidal grating laser warning receiver developed by our group were analyzed, and the theoretic calculation and experimental results indicate that the SNR analysis method is feasible, and can be used in performance analysis of LWR.

Enhancing the management of the noise level using six sigma method: a case study on the machining industry

NASA Astrophysics Data System (ADS)

Rimantho, D.; Hanantya, M. W.

2017-12-01

The hearing disorder is caused by noises in the workplace, it has been a concern for numerous researchers. This study aims to improve the performance of the management of the noise level by applying the six sigma method. Data collection is done directly by using a sound level meter. In addition, several key informants also used in order to gather information related to the problem. The results showed the values of Cp and Cpk on the entire department are still below the recommended value. Moreover, the results also showed the potential failure (DPMO) approximately 115,260.6 and equivalent to the Sigma value is approximately 2.70. Furthermore, the highest value of the RPN in FMEA analysis is the workers not wear factor of earplug which is about 56. Thus, it is necessary to make enhancements to the process of managing the noise level in the framework of continuous improvement.

Removal of power line interference of space bearing vibration signal based on the morphological filter and blind source separation

NASA Astrophysics Data System (ADS)

Dong, Shaojiang; Sun, Dihua; Xu, Xiangyang; Tang, Baoping

2017-06-01

Aiming at the problem that it is difficult to extract the feature information from the space bearing vibration signal because of different noise, for example the running trend information, high-frequency noise and especially the existence of lot of power line interference (50Hz) and its octave ingredients of the running space simulated equipment in the ground. This article proposed a combination method to eliminate them. Firstly, the EMD is used to remove the running trend item information of the signal, the running trend that affect the signal processing accuracy is eliminated. Then the morphological filter is used to eliminate high-frequency noise. Finally, the components and characteristics of the power line interference are researched, based on the characteristics of the interference, the revised blind source separation model is used to remove the power line interferences. Through analysis of simulation and practical application, results suggest that the proposed method can effectively eliminate those noise.

An unsteady aerodynamic formulation for efficient rotor tonal noise prediction

NASA Astrophysics Data System (ADS)

Gennaretti, M.; Testa, C.; Bernardini, G.

2013-12-01

An aerodynamic/aeroacoustic solution methodology for predction of tonal noise emitted by helicopter rotors and propellers is presented. It is particularly suited for configurations dominated by localized, high-frequency inflow velocity fields as those generated by blade-vortex interactions. The unsteady pressure distributions are determined by the sectional, frequency-domain Küssner-Schwarz formulation, with downwash including the wake inflow velocity predicted by a three-dimensional, unsteady, panel-method formulation suited for the analysis of rotors operating in complex aerodynamic environments. The radiated noise is predicted through solution of the Ffowcs Williams-Hawkings equation. The proposed approach yields a computationally efficient solution procedure that may be particularly useful in preliminary design/multidisciplinary optimization applications. It is validated through comparisons with solutions that apply the airloads directly evaluated by the time-marching, panel-method formulation. The results are provided in terms of blade loads, noise signatures and sound pressure level contours. An estimation of the computational efficiency of the proposed solution process is also presented.

Rolling Bearing Fault Diagnosis Based on an Improved HTT Transform

PubMed Central

Tang, Guiji; Tian, Tian; Zhou, Chong

2018-01-01

When rolling bearing failure occurs, vibration signals generally contain different signal components, such as impulsive fault feature signals, background noise and harmonic interference signals. One of the most challenging aspects of rolling bearing fault diagnosis is how to inhibit noise and harmonic interference signals, while enhancing impulsive fault feature signals. This paper presents a novel bearing fault diagnosis method, namely an improved Hilbert time–time (IHTT) transform, by combining a Hilbert time–time (HTT) transform with principal component analysis (PCA). Firstly, the HTT transform was performed on vibration signals to derive a HTT transform matrix. Then, PCA was employed to de-noise the HTT transform matrix in order to improve the robustness of the HTT transform. Finally, the diagonal time series of the de-noised HTT transform matrix was extracted as the enhanced impulsive fault feature signal and the contained fault characteristic information was identified through further analyses of amplitude and envelope spectrums. Both simulated and experimental analyses validated the superiority of the presented method for detecting bearing failures. PMID:29662013

Noise Radiation from a Continuous Mold-Line Link Flap Configuration

NASA Technical Reports Server (NTRS)

Hutcheson, Florence V.; Brooks, Thomas F.; Humphreys, William M., Jr.

2011-01-01

The results of an experimental study of the noise from a Continuous Mold-Line Link (CML) flap are presented. Acoustic and unsteady surface pressure measurements were performed on a main element wing section with a half-span CML flap in NASA Langley s Quiet Flow Facility. The acoustic data were acquired with a medium aperture directional array (MADA) of microphones. The Deconvolution Approach for the Mapping of Acoustic Sources (DAMAS) method is applied to determine the spatial distribution and strength of the noise sources over the surface of the test model. A Coherent Output Power (COP) method which relates the output from unsteady surface pressure sensors to the output of the MADA is also used to obtain more detailed characteristics of the noise source distribution in the trailing edge region of the CML. These results are compared to those obtained for a blunt flap to quantify the level of noise benefit that is achieved with the CML flap. The results indicate that the noise from the CML region of the flap is 5 to 17 dB lower (depending on flap deflection and Mach number) than the noise from the side edge region of the blunt flap. Lower noise levels are obtained for all frequencies. Spectral analysis of the noise from the cove region of the CML and blunt flap models also reveal a spectral peak in the high frequency range that is related to noise scattering at the trailing edge of the main element. The peaks in the CML and blunt flap cove noise spectra are close in level and often exceed blunt side edge noise. Applying a strip of serrated tape to the trailing edge of the CML flap model main airfoil reduced the peak but increased other noise somewhat. Directivity measurements show that the CML flap can be more directional than the blunt flap.

Noise Radiation from a Continuous Mold-Line Link Flap Configuration

NASA Technical Reports Server (NTRS)

Hutcheson, Florence V.; Brooks, Thomas F.; Humphreys, William M.

2008-01-01

The results of an experimental study of the noise from a Continuous Mold-Line Link (CML) flap are presented. Acoustic and unsteady surface pressure measurements were performed on a main element wing section with a half-span CML flap in NASA Langley s Quiet Flow Facility. The acoustic data were acquired with a medium aperture directional array (MADA) of microphones. The Deconvolution Approach for the Mapping of Acoustic Sources (DAMAS) method is applied to determine the spatial distribution and strength of the noise sources over the surface of the test model. A Coherent Output Power (COP) method which relates the output from unsteady surface pressure sensors to the output of the MADA is also used to obtain more detailed characteristics of the noise source distribution in the trailing edge region of the CML. These results are compared to those obtained for a blunt flap to quantify the level of noise benefit that is achieved with the CML flap. The results indicate that the noise from the CML region of the flap is 5 to 17 dB lower (depending on flap deflection and Mach number) than the noise from the side edge region of the blunt flap. Lower noise levels are obtained for all frequencies. Spectral analysis of the noise from the cove region of the CML and blunt flap models also reveal a spectral peak in the high frequency range that is related to noise scattering at the trailing edge of the main element. The peaks in the CML and blunt flap cove noise spectra are close in level and often exceed blunt side edge noise. Applying a strip of serrated tape to the trailing edge of the CML flap model main airfoil, reduced the peak but increased other noise somewhat. Directivity measurements show that the CML flap can be more directional than the blunt flap.

Design of the Next Generation Aircraft Noise Prediction Program: ANOPP2

NASA Technical Reports Server (NTRS)

Lopes, Leonard V., Dr.; Burley, Casey L.

2011-01-01

The requirements, constraints, and design of NASA's next generation Aircraft NOise Prediction Program (ANOPP2) are introduced. Similar to its predecessor (ANOPP), ANOPP2 provides the U.S. Government with an independent aircraft system noise prediction capability that can be used as a stand-alone program or within larger trade studies that include performance, emissions, and fuel burn. The ANOPP2 framework is designed to facilitate the combination of acoustic approaches of varying fidelity for the analysis of noise from conventional and unconventional aircraft. ANOPP2 integrates noise prediction and propagation methods, including those found in ANOPP, into a unified system that is compatible for use within general aircraft analysis software. The design of the system is described in terms of its functionality and capability to perform predictions accounting for distributed sources, installation effects, and propagation through a non-uniform atmosphere including refraction and the influence of terrain. The philosophy of mixed fidelity noise prediction through the use of nested Ffowcs Williams and Hawkings surfaces is presented and specific issues associated with its implementation are identified. Demonstrations for a conventional twin-aisle and an unconventional hybrid wing body aircraft configuration are presented to show the feasibility and capabilities of the system. Isolated model-scale jet noise predictions are also presented using high-fidelity and reduced order models, further demonstrating ANOPP2's ability to provide predictions for model-scale test configurations.

Stripe nonuniformity correction for infrared imaging system based on single image optimization

NASA Astrophysics Data System (ADS)

Hua, Weiping; Zhao, Jufeng; Cui, Guangmang; Gong, Xiaoli; Ge, Peng; Zhang, Jiang; Xu, Zhihai

2018-06-01

Infrared imaging is often disturbed by stripe nonuniformity noise. Scene-based correction method can effectively reduce the impact of stripe noise. In this paper, a stripe nonuniformity correction method based on differential constraint is proposed. Firstly, the gray distribution of stripe nonuniformity is analyzed and the penalty function is constructed by the difference of horizontal gradient and vertical gradient. With the weight function, the penalty function is optimized to obtain the corrected image. Comparing with other single-frame approaches, experiments show that the proposed method performs better in both subjective and objective analysis, and does less damage to edge and detail. Meanwhile, the proposed method runs faster. We have also discussed the differences between the proposed idea and multi-frame methods. Our method is finally well applied in hardware system.

Efficient bias correction for magnetic resonance image denoising.

PubMed

Mukherjee, Partha Sarathi; Qiu, Peihua

2013-05-30

Magnetic resonance imaging (MRI) is a popular radiology technique that is used for visualizing detailed internal structure of the body. Observed MRI images are generated by the inverse Fourier transformation from received frequency signals of a magnetic resonance scanner system. Previous research has demonstrated that random noise involved in the observed MRI images can be described adequately by the so-called Rician noise model. Under that model, the observed image intensity at a given pixel is a nonlinear function of the true image intensity and of two independent zero-mean random variables with the same normal distribution. Because of such a complicated noise structure in the observed MRI images, denoised images by conventional denoising methods are usually biased, and the bias could reduce image contrast and negatively affect subsequent image analysis. Therefore, it is important to address the bias issue properly. To this end, several bias-correction procedures have been proposed in the literature. In this paper, we study the Rician noise model and the corresponding bias-correction problem systematically and propose a new and more effective bias-correction formula based on the regression analysis and Monte Carlo simulation. Numerical studies show that our proposed method works well in various applications. Copyright © 2012 John Wiley & Sons, Ltd.

A method of noise reduction in heterodyne interferometric vibration metrology by combining auto-correlation analysis and spectral filtering

NASA Astrophysics Data System (ADS)

Hao, Hongliang; Xiao, Wen; Chen, Zonghui; Ma, Lan; Pan, Feng

2018-01-01

Heterodyne interferometric vibration metrology is a useful technique for dynamic displacement and velocity measurement as it can provide a synchronous full-field output signal. With the advent of cost effective, high-speed real-time signal processing systems and software, processing of the complex signals encountered in interferometry has become more feasible. However, due to the coherent nature of the laser sources, the sequence of heterodyne interferogram are corrupted by a mixture of coherent speckle and incoherent additive noise, which can severely degrade the accuracy of the demodulated signal and the optical display. In this paper, a new heterodyne interferometric demodulation method by combining auto-correlation analysis and spectral filtering is described leading to an expression for the dynamic displacement and velocity of the object under test that is significantly more accurate in both the amplitude and frequency of the vibrating waveform. We present a mathematical model of the signals obtained from interferograms that contain both vibration information of the measured objects and the noise. A simulation of the signal demodulation process is presented and used to investigate the noise from the system and external factors. The experimental results show excellent agreement with measurements from a commercial Laser Doppler Velocimetry (LDV).

A new full-field interferometry approach for counting and differentiating aquatic biotic nanoparticles (Conference Presentation)

NASA Astrophysics Data System (ADS)

Boccara, A. Claude; Fedala, Yasmina; Voronkoff, Justine; Paffoni, Nina; Boccara, Martine

2017-03-01

Due to the huge abundance and the major role that viruses and membrane vesicles play in the seas or rivers ecosystems it is necessary to develop simple, sensitive, compact and reliable methods for their detection and characterization. Our approach is based on the measurement of the weak light level scattered by the biotic nanoparticles. We describe a new full-field, incoherently illuminated, shot-noise limited, common-path interferometric detection method coupled with the analysis of Brownian motion to detect, quantify, and differentiate biotic nanoparticles. The last developments take advantage of a new fast (700 Hz) camera with 2 Me- full well capacity that improves the signal to noise ratio and increases the precision of the Brownian motion characterization. We validated the method with calibrated nanoparticles and homogeneous DNA or RNA.viruses. The smallest virus size that we characterized with a suitable signal-to-noise ratio was around 30 nm in diameter with a target towards the numerous 20 nm diameter viruses. We show for the first time anisotropic trajectories for myoviruses meaning that there is a memory of the initial direction of their Brownian motions. Significant improvements have been made in the handling of the sample as well as in the statistical analysis for differentiating the various families of vesicles and virus. We further applied the method for vesicles detection and for analysis of coastal and oligotrophic samples from Tara Oceans circumnavigation as well of various rivers.

Design and performance evaluation of the imaging payload for a remote sensing satellite

NASA Astrophysics Data System (ADS)

Abolghasemi, Mojtaba; Abbasi-Moghadam, Dariush

2012-11-01

In this paper an analysis method and corresponding analytical tools for design of the experimental imaging payload (IMPL) of a remote sensing satellite (SINA-1) are presented. We begin with top-level customer system performance requirements and constraints and derive the critical system and component parameters, then analyze imaging payload performance until a preliminary design that meets customer requirements. We consider system parameters and components composing the image chain for imaging payload system which includes aperture, focal length, field of view, image plane dimensions, pixel dimensions, detection quantum efficiency, and optical filter requirements. The performance analysis is accomplished by calculating the imaging payload's SNR (signal-to-noise ratio), and imaging resolution. The noise components include photon noise due to signal scene and atmospheric background, cold shield, out-of-band optical filter leakage and electronic noise. System resolution is simulated through cascaded modulation transfer functions (MTFs) and includes effects due to optics, image sampling, and system motion. Calculations results for the SINA-1 satellite are also presented.

The deterministic chaos and random noise in turbulent jet

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

Yao, Tian-Liang; Shanghai Institute of Space Propulsion, Shanghai 201112; Shanghai Engineering Research Center of Space Engine, Shanghai Institute of Space Propulsion, Shanghai 201112

2014-06-01

A turbulent flow is usually treated as a superposition of coherent structure and incoherent turbulence. In this paper, the largest Lyapunov exponent and the random noise in the near field of round jet and plane jet are estimated with our previously proposed method of chaotic time series analysis [T. L. Yao, et al., Chaos 22, 033102 (2012)]. The results show that the largest Lyapunov exponents of the round jet and plane jet are in direct proportion to the reciprocal of the integral time scale of turbulence, which is in accordance with the results of the dimensional analysis, and the proportionalitymore » coefficients are equal. In addition, the random noise of the round jet and plane jet has the same linear relation with the Kolmogorov velocity scale of turbulence. As a result, the random noise may well be from the incoherent disturbance in turbulence, and the coherent structure in turbulence may well follow the rule of chaotic motion.« less

Improved moving window cross-spectral analysis for resolving large temporal seismic velocity changes in permafrost

DOE PAGES

James, S. R.; Knox, H. A.; Abbott, R. E.; ...

2017-04-13

Cross correlations of seismic noise can potentially record large changes in subsurface velocity due to permafrost dynamics and be valuable for long-term Arctic monitoring. We applied seismic interferometry, using moving window cross-spectral analysis (MWCS), to 2 years of ambient noise data recorded in central Alaska to investigate whether seismic noise could be used to quantify relative velocity changes due to seasonal active-layer dynamics. The large velocity changes (>75%) between frozen and thawed soil caused prevalent cycle-skipping which made the method unusable in this setting. We developed an improved MWCS procedure which uses a moving reference to measure daily velocity variationsmore » that are then accumulated to recover the full seasonal change. This approach reduced cycle-skipping and recovered a seasonal trend that corresponded well with the timing of active-layer freeze and thaw. Lastly, this improvement opens the possibility of measuring large velocity changes by using MWCS and permafrost monitoring by using ambient noise.« less

Fractal dimension analysis for robust ultrasonic non-destructive evaluation (NDE) of coarse grained materials

NASA Astrophysics Data System (ADS)

Li, Minghui; Hayward, Gordon

2018-04-01

Over the recent decades, there has been a growing demand on reliable and robust non-destructive evaluation (NDE) of structures and components made from coarse grained materials such as alloys, stainless steels, carbon-reinforced composites and concrete; however, when inspected using ultrasound, the flaw echoes are usually contaminated by high-level, time-invariant, and correlated grain noise originating from the microstructure and grain boundaries, leading to pretty low signal-to-noise ratio (SNR) and the flaw information being obscured or completely hidden by the grain noise. In this paper, the fractal dimension analysis of the A-scan echoes is investigated as a measure of complexity of the time series to distinguish the echoes originating from the real defects and the grain noise, and then the normalized fractal dimension coefficients are applied to the amplitudes as the weighting factor to enhance the SNR and defect detection. Experiments on industrial samples of the mild steel and the stainless steel are conducted and the results confirm the great benefits of the method.

A method for discrimination of noise and EMG signal regions recorded during rhythmic behaviors.

PubMed

Ying, Rex; Wall, Christine E

2016-12-08

Analyses of muscular activity during rhythmic behaviors provide critical data for biomechanical studies. Electrical potentials measured from muscles using electromyography (EMG) require discrimination of noise regions as the first step in analysis. An experienced analyst can accurately identify the onset and offset of EMG but this process takes hours to analyze a short (10-15s) record of rhythmic EMG bursts. Existing computational techniques reduce this time but have limitations. These include a universal threshold for delimiting noise regions (i.e., a single signal value for identifying the EMG signal onset and offset), pre-processing using wide time intervals that dampen sensitivity for EMG signal characteristics, poor performance when a low frequency component (e.g., DC offset) is present, and high computational complexity leading to lack of time efficiency. We present a new statistical method and MATLAB script (EMG-Extractor) that includes an adaptive algorithm to discriminate noise regions from EMG that avoids these limitations and allows for multi-channel datasets to be processed. We evaluate the EMG-Extractor with EMG data on mammalian jaw-adductor muscles during mastication, a rhythmic behavior typified by low amplitude onsets/offsets and complex signal pattern. The EMG-Extractor consistently and accurately distinguishes noise from EMG in a manner similar to that of an experienced analyst. It outputs the raw EMG signal region in a form ready for further analysis. Copyright © 2016 Elsevier Ltd. All rights reserved.

OBS Data Denoising Based on Compressed Sensing Using Fast Discrete Curvelet Transform

NASA Astrophysics Data System (ADS)

Nan, F.; Xu, Y.

2017-12-01

OBS (Ocean Bottom Seismometer) data denoising is an important step of OBS data processing and inversion. It is necessary to get clearer seismic phases for further velocity structure analysis. Traditional methods for OBS data denoising include band-pass filter, Wiener filter and deconvolution etc. (Liu, 2015). Most of these filtering methods are based on Fourier Transform (FT). Recently, the multi-scale transform methods such as wavelet transform (WT) and Curvelet transform (CvT) are widely used for data denoising in various applications. The FT, WT and CvT could represent signal sparsely and separate noise in transform domain. They could be used in different cases. Compared with Curvelet transform, the FT has Gibbs phenomenon and it cannot handle points discontinuities well. WT is well localized and multi scale, but it has poor orientation selectivity and could not handle curves discontinuities well. CvT is a multiscale directional transform that could represent curves with only a small number of coefficients. It provide an optimal sparse representation of objects with singularities along smooth curves, which is suitable for seismic data processing. As we know, different seismic phases in OBS data are showed as discontinuous curves in time domain. Hence, we promote to analysis the OBS data via CvT and separate the noise in CvT domain. In this paper, our sparsity-promoting inversion approach is restrained by L1 condition and we solve this L1 problem by using modified iteration thresholding. Results show that the proposed method could suppress the noise well and give sparse results in Curvelet domain. Figure 1 compares the Curvelet denoising method with Wavelet method on the same iterations and threshold through synthetic example. a)Original data. b) Add-noise data. c) Denoised data using CvT. d) Denoised data using WT. The CvT can well eliminate the noise and has better result than WT. Further we applied the CvT denoise method for the OBS data processing. Figure 2a is a common receiver gather collected in the Bohai Sea, China. The whole profile is 120km long with 987 shots. The horizontal axis is shot number. The vertical axis is travel time reduced by 6km/s. We use our method to process the data and get a denoised profile figure 2b. After denoising, most of the high frequency noise was suppressed and the seismic phases were clearer.

Evaluation of internal noise methods for Hotelling observers

NASA Astrophysics Data System (ADS)

Zhang, Yani; Pham, Binh T.; Eckstein, Miguel P.

2005-04-01

Including internal noise in computer model observers to degrade model observer performance to human levels is a common method to allow for quantitatively comparisons of human and model performance. In this paper, we studied two different types of methods for injecting internal noise to Hotelling model observers. The first method adds internal noise to the output of the individual channels: a) Independent non-uniform channel noise, b) Independent uniform channel noise. The second method adds internal noise to the decision variable arising from the combination of channel responses: a) internal noise standard deviation proportional to decision variable's standard deviation due to the external noise, b) internal noise standard deviation proportional to decision variable's variance caused by the external noise. We tested the square window Hotelling observer (HO), channelized Hotelling observer (CHO), and Laguerre-Gauss Hotelling observer (LGHO). The studied task was detection of a filling defect of varying size/shape in one of four simulated arterial segment locations with real x-ray angiography backgrounds. Results show that the internal noise method that leads to the best prediction of human performance differs across the studied models observers. The CHO model best predicts human observer performance with the channel internal noise. The HO and LGHO best predict human observer performance with the decision variable internal noise. These results might help explain why previous studies have found different results on the ability of each Hotelling model to predict human performance. Finally, the present results might guide researchers with the choice of method to include internal noise into their Hotelling models.

Noise exposure-response relationships established from repeated binary observations: Modeling approaches and applications.

PubMed

Schäffer, Beat; Pieren, Reto; Mendolia, Franco; Basner, Mathias; Brink, Mark

2017-05-01

Noise exposure-response relationships are used to estimate the effects of noise on individuals or a population. Such relationships may be derived from independent or repeated binary observations, and modeled by different statistical methods. Depending on the method by which they were established, their application in population risk assessment or estimation of individual responses may yield different results, i.e., predict "weaker" or "stronger" effects. As far as the present body of literature on noise effect studies is concerned, however, the underlying statistical methodology to establish exposure-response relationships has not always been paid sufficient attention. This paper gives an overview on two statistical approaches (subject-specific and population-averaged logistic regression analysis) to establish noise exposure-response relationships from repeated binary observations, and their appropriate applications. The considerations are illustrated with data from three noise effect studies, estimating also the magnitude of differences in results when applying exposure-response relationships derived from the two statistical approaches. Depending on the underlying data set and the probability range of the binary variable it covers, the two approaches yield similar to very different results. The adequate choice of a specific statistical approach and its application in subsequent studies, both depending on the research question, are therefore crucial.

Effects of Vehicle Weight and True Versus Indicated Airspeed on BVI Noise During Steady Descending Flight

NASA Technical Reports Server (NTRS)

Stephenson, James H.; Greenwood, Eric

2015-01-01

Blade-vortex interaction noise measurements are analyzed for an AS350B helicopter operated at 7000 ft elevation above sea level. Blade-vortex interaction (BVI) noise from four, 6 degree descent conditions are investigated with descents flown at 80 knot true and indicated airspeed, as well as 4400 and 3915 pound take-off weights. BVI noise is extracted from the acquired acoustic signals by way of a previously developed time-frequency analysis technique. The BVI extraction technique is shown to provide a better localization of BVI noise, compared to the standard Fourier transform integration method. Using this technique, it was discovered that large changes in BVI noise amplitude occurred due to changes in vehicle gross weight. Changes in BVI noise amplitude were too large to be due solely to changes in the vortex strength caused by varying vehicle weight. Instead, it is suggested that vehicle weight modifies the tip-path-plane angle of attack, as well as induced inflow, resulting in large variations of BVI noise. It was also shown that defining flight conditions by true airspeed, rather than indicated airspeed, provides more consistent BVI noise signals.

A complete passive blind image copy-move forensics scheme based on compound statistics features.

PubMed

Peng, Fei; Nie, Yun-ying; Long, Min

2011-10-10

Since most sensor pattern noise based image copy-move forensics methods require a known reference sensor pattern noise, it generally results in non-blinded passive forensics, which significantly confines the application circumstances. In view of this, a novel passive-blind image copy-move forensics scheme is proposed in this paper. Firstly, a color image is transformed into a grayscale one, and wavelet transform based de-noising filter is used to extract the sensor pattern noise, then the variance of the pattern noise, the signal noise ratio between the de-noised image and the pattern noise, the information entropy and the average energy gradient of the original grayscale image are chosen as features, non-overlapping sliding window operations are done to the images to divide them into different sub-blocks. Finally, the tampered areas are detected by analyzing the correlation of the features between the sub-blocks and the whole image. Experimental results and analysis show that the proposed scheme is completely passive-blind, has a good detection rate, and is robust against JPEG compression, noise, rotation, scaling and blurring. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Ultra–Short-Term Reproducibility of Speckle-Noise Freed Fluid and Tissue Compartmentalization of the Choroid Analyzed by Standard OCT

PubMed Central

Maloca, Peter; Gyger, Cyrill; Schoetzau, Andreas; Hasler, Pascal W.

2015-01-01

Purpose We measured reproducibility of speckle-noise freed fluid and tissue compartmentalization of the choroid (choroidal angiography and tissue characterization). Methods This study included 26 eyes of 13 healthy females: 13 were used for repeated measurements and 13 were used for side comparison. A semiautomated algorithm removed speckle-noise with structure preservation. Results Intraclass correlation (ICC), with respect to reproducibility of the method, showed an ICC for choroidal fluid inner space analysis (FISA) of 95.15% (90.01–98.24). The ICC of tissue inner space analysis (TISA) was 99.75% (99.47–99.91). The total choroid ratio (TCR), calculated from volumes of tissue to vessels, showed an ICC of 88.84% (78.28–95.82). Comparison of eyes (left to right) showed a difference for FISA of 0.033 (95% confidence interval [CI] −0.0018–0.0680, P = 0.063), TISA −0.118 (CI −0.2373–0.0023, P = 0.055), and TCR −0.590 (CI −0.9047 to −0.2754, P = 0.004). The ICC for FISA and TISA showed a trend in the difference comparing left and right eyes; however, TCR showed a significant difference between the eyes in the measured area (P < 0.001). Mean overall FISA was 0.58 mm3 (range, 0.25–0.98 mm3, SD = 0.14). Mean TISA was 3.45 mm3 (range, 2.38–5.0 mm3, SD 0.072). Mean TCR was 6.13 (overall range, 3.93–10.2, SD = 1.34). Conclusions Differences in choroidal layers between subjects were found mainly due to alterations in choroidal tissue. Reproducibility of speckle-noise freed choroidal angiography appeared excellent. Translational Relevance Speckle noise is a granular “noise” that appears in a wide range of medical imaging methods as ultrasonography, magnetic resonance, computer tomography, or optical coherence tomography (OCT). Findings from basic science about speckle noise were translated into a novel, medical image postprocessing application that can separate signal from speckle noise with structure preservation with high reproducibility and enhance medical imaging. PMID:26629399

Implementation of New Reactivity Measurement System and New Reactor Noise Analysis Equipment in a VVER-440 Nuclear Power Plant

NASA Astrophysics Data System (ADS)

Vegh, János; Kiss, Sándor; Lipcsei, Sándor; Horvath, Csaba; Pos, István; Kiss, Gábor

2010-10-01

The paper deals with two recently developed, high-precision nuclear measurement systems installed at the VVER-440 units of the Hungarian Paks NPP. Both developments were motivated by the reactor power increase to 108%, and by the planned plant service time extension. The first part describes the RMR start-up reactivity measurement system with advanced services. High-precision picoampere meters were installed at each reactor unit and measured ionization chamber current signals are handled by a portable computer providing data acquisition and online reactivity calculation service. Detailed offline evaluation and analysis of reactor start-up measurements can be performed on the portable unit, too. The second part of the paper describes a new reactor noise diagnostics system using state-of-the-art data acquisition hardware and signal processing methods. Details of the new reactor noise measurement evaluation software are also outlined. Noise diagnostics at Paks NPP is a standard tool for core anomaly detection and for long-term noise trend monitoring. Regular application of these systems is illustrated by real plant data, e.g., results of standard reactivity measurements during a reactor startup session are given. Noise applications are also illustrated by real plant measurements; results of core anomaly detection are presented.

A comparative intelligibility study of single-microphone noise reduction algorithms.

PubMed

Hu, Yi; Loizou, Philipos C

2007-09-01

The evaluation of intelligibility of noise reduction algorithms is reported. IEEE sentences and consonants were corrupted by four types of noise including babble, car, street and train at two signal-to-noise ratio levels (0 and 5 dB), and then processed by eight speech enhancement methods encompassing four classes of algorithms: spectral subtractive, sub-space, statistical model based and Wiener-type algorithms. The enhanced speech was presented to normal-hearing listeners for identification. With the exception of a single noise condition, no algorithm produced significant improvements in speech intelligibility. Information transmission analysis of the consonant confusion matrices indicated that no algorithm improved significantly the place feature score, significantly, which is critically important for speech recognition. The algorithms which were found in previous studies to perform the best in terms of overall quality, were not the same algorithms that performed the best in terms of speech intelligibility. The subspace algorithm, for instance, was previously found to perform the worst in terms of overall quality, but performed well in the present study in terms of preserving speech intelligibility. Overall, the analysis of consonant confusion matrices suggests that in order for noise reduction algorithms to improve speech intelligibility, they need to improve the place and manner feature scores.

Innovative Approach for Developing Spacecraft Interior Acoustic Requirement Allocation

NASA Technical Reports Server (NTRS)

Chu, S. Reynold; Dandaroy, Indranil; Allen, Christopher S.

2016-01-01

The Orion Multi-Purpose Crew Vehicle (MPCV) is an American spacecraft for carrying four astronauts during deep space missions. This paper describes an innovative application of Power Injection Method (PIM) for allocating Orion cabin continuous noise Sound Pressure Level (SPL) limits to the sound power level (PWL) limits of major noise sources in the Environmental Control and Life Support System (ECLSS) during all mission phases. PIM is simulated using both Statistical Energy Analysis (SEA) and Hybrid Statistical Energy Analysis-Finite Element (SEA-FE) models of the Orion MPCV to obtain the transfer matrix from the PWL of the noise sources to the acoustic energies of the receivers, i.e., the cavities associated with the cabin habitable volume. The goal of the allocation strategy is to control the total energy of cabin habitable volume for maintaining the required SPL limits. Simulations are used to demonstrate that applying the allocated PWLs to the noise sources in the models indeed reproduces the SPL limits in the habitable volume. The effects of Noise Control Treatment (NCT) on allocated noise source PWLs are investigated. The measurement of source PWLs of involved fan and pump development units are also discussed as it is related to some case-specific details of the allocation strategy discussed here.

The effects of railway noise on sleep medication intake: results from the ALPNAP-study.

PubMed

Lercher, P; Brink, M; Rudisser, J; Van Renterghem, T; Botteldooren, D; Baulac, M; Defrance, J

2010-01-01

In the 1980s/90s, a number of socio-acoustic surveys and laboratory studies on railway noise effects have observed less reported disturbance/interference with sleep at the same exposure level compared with other modes of transportation. This lower grade of disturbance has received the label "railway bonus", was implemented in noise legislation in a number of European countries and was applied in planning and environmental impact assessments. However, majority of the studies investigating physiological outcomes did not find the bespoke difference. In a telephone survey (N=1643) we investigated the relationship between railway noise and sleep medication intake and the impact of railway noise events on motility parameters during night was assessed with contact-free high resolution actimetry devices. Multiple logistic regression analysis with cubic splines was applied to assess the probability of sleep medication use based on railway sound level and nine covariates. The non-linear exposure-response curve showed a statistically significant leveling off around 60 dB (A), Lden. Age, health status and trauma history were the most important covariates. The results were supported also by a similar analysis based on the indicator "night time noise annoyance". No railway bonus could be observed above 55 dB(A), Lden. In the actimetry study, the slope of rise of train noise events proved to be almost as important a predictor for motility reactions as was the maximum sound pressure level - an observation which confirms similar findings from laboratory experiments and field studies on aircraft noise and sleep disturbance. Legislation using a railway bonus will underestimate the noise impact by about 10 dB (A), Lden under the conditions comparable with those in the survey study. The choice of the noise calculation method may influence the threshold for guideline setting.

Flap Edge Aeroacoustic Measurements and Predictions

NASA Technical Reports Server (NTRS)

Brooks, Thomas F.; Humphreys, William M., Jr.

2000-01-01

An aeroacoustic model test has been conducted to investigate the mechanisms of sound generation on high-lift wing configurations. This paper presents an analysis of flap side-edge noise, which is often the most dominant source. A model of a main element wing section with a half-span flap was tested at low speeds of up to a Mach number of 0.17, corresponding to a wing chord Reynolds number of approximately 1.7 million. Results are presented for flat (or blunt), flanged, and round flap-edge geometries, with and without boundary-layer tripping, deployed at both moderate and high flap angles. The acoustic database is obtained from a Small Aperture Directional Array (SADA) of microphones, which was constructed to electronically steer to different regions of the model and to obtain farfield noise spectra and directivity from these regions. The basic flap-edge aerodynamics is established by static surface pressure data, as well as by Computational Fluid Dynamics (CFD) calculations and simplified edge flow analyses. Distributions of unsteady pressure sensors over the flap allow the noise source regions to be defined and quantified via cross-spectral diagnostics using the SADA output. It is found that shear layer instability and related pressure scatter is the primary noise mechanism. For the flat edge flap, two noise prediction methods based on unsteady surface pressure measurements are evaluated and compared to measured noise. One is a new causality spectral approach developed here. The other is a new application of an edge-noise scatter prediction method. The good comparisons for both approaches suggest that much of the physics is captured by the prediction models. Areas of disagreement appear to reveal when the assumed edge noise mechanism does not fully define the noise production. For the different edge conditions, extensive spectra and directivity are presented. Significantly, for each edge configuration, the spectra for different flow speeds, flap angles, and surface roughness were successfully scaled by utilizing aerodynamic performance and boundary layer scaling methods developed herein.

Flap Edge Aeroacoustic Measurements and Predictions

NASA Technical Reports Server (NTRS)

Brooks, Thomas F.; Humphreys, William M., Jr.

2000-01-01

An aeroacoustic model test has been conducted to investigate the mechanisms of sound generation on high-lift wing configurations. This paper presents an analysis of flap side-edge noise, which is often the most dominant source. A model of a main element wing section with a half-span flap was tested at low speeds of up to a Mach number of 0.17, corresponding to a wing chord Reynolds number of approximately 1.7 million. Results are presented for flat (or blunt), flanged, and round flap-edge geometries, with and without boundary-layer tripping, deployed at both moderate and high flap angles. The acoustic database is obtained from a Small Aperture Directional Array (SADA) of microphones, which was constructed to electronically steer to different regions of the model and to obtain farfield noise spectra and directivity from these regions. The basic flap-edge aerodynamics is established by static surface pressure data, as well as by Computational Fluid Dynamics (CFD) calculations and simplified edge flow analyses. Distributions of unsteady pressure sensors over the flap allow the noise source regions to be defined and quantified via cross-spectral diagnostics using the SADA output. It is found that shear layer instability and related pressure scatter is the primary noise mechanism. For the flat edge flap, two noise prediction methods based on unsteady-surface-pressure measurements are evaluated and compared to measured noise. One is a new causality spectral approach developed here. The other is a new application of an edge-noise scatter prediction method. The good comparisons for both approaches suggest that much of the physics is captured by the prediction models. Areas of disagreement appear to reveal when the assumed edge noise mechanism does not fully define, the noise production. For the different edge conditions, extensive spectra and directivity are presented. Significantly, for each edge configuration, the spectra for different flow speeds, flap angles, and surface roughness were successfully scaled by utilizing aerodynamic performance and boundary layer scaling method developed herein.

Road Traffic and Railway Noise Exposures and Adiposity in Adults: A Cross-Sectional Analysis of the Danish Diet, Cancer, and Health Cohort

PubMed Central

Christensen, Jeppe Schultz; Raaschou-Nielsen, Ole; Tjønneland, Anne; Overvad, Kim; Nordsborg, Rikke B.; Ketzel, Matthias; Sørensen, Thorkild IA; Sørensen, Mette

2015-01-01

Background Traffic noise has been associated with cardiovascular and metabolic disorders. Potential modes of action are through stress and sleep disturbance, which may lead to endocrine dysregulation and overweight. Objectives We aimed to investigate the relationship between residential traffic and railway noise and adiposity. Methods In this cross-sectional study of 57,053 middle-aged people, height, weight, waist circumference, and bioelectrical impedance were measured at enrollment (1993–1997). Body mass index (BMI), body fat mass index (BFMI), and lean body mass index (LBMI) were calculated. Residential exposure to road and railway traffic noise exposure was calculated using the Nordic prediction method. Associations between traffic noise and anthropometric measures at enrollment were analyzed using general linear models and logistic regression adjusted for demographic and lifestyle factors. Results Linear regression models adjusted for age, sex, and socioeconomic factors showed that 5-year mean road traffic noise exposure preceding enrollment was associated with a 0.35-cm wider waist circumference (95% CI: 0.21, 0.50) and a 0.18-point higher BMI (95% CI: 0.12, 0.23) per 10 dB. Small, significant increases were also found for BFMI and LBMI. All associations followed linear exposure–response relationships. Exposure to railway noise was not linearly associated with adiposity measures. However, exposure > 60 dB was associated with a 0.71-cm wider waist circumference (95% CI: 0.23, 1.19) and a 0.19-point higher BMI (95% CI: 0.0072, 0.37) compared with unexposed participants (0–20 dB). Conclusions The present study finds positive associations between residential exposure to road traffic and railway noise and adiposity. Citation Christensen JS, Raaschou-Nielsen O, Tjønneland A, Overvad K, Nordsborg RB, Ketzel M, Sørensen TI, Sørensen M. 2016. Road traffic and railway noise exposures and adiposity in adults: a cross-sectional analysis of the Danish Diet, Cancer, and Health cohort. Environ Health Perspect 124:329–335; http://dx.doi.org/10.1289/ehp.1409052 PMID:26241990

Bearing faults identification and resonant band demodulation based on wavelet de-noising methods and envelope analysis

NASA Astrophysics Data System (ADS)

Abdelrhman, Ahmed M.; Sei Kien, Yong; Salman Leong, M.; Meng Hee, Lim; Al-Obaidi, Salah M. Ali

2017-07-01

The vibration signals produced by rotating machinery contain useful information for condition monitoring and fault diagnosis. Fault severities assessment is a challenging task. Wavelet Transform (WT) as a multivariate analysis tool is able to compromise between the time and frequency information in the signals and served as a de-noising method. The CWT scaling function gives different resolutions to the discretely signals such as very fine resolution at lower scale but coarser resolution at a higher scale. However, the computational cost increased as it needs to produce different signal resolutions. DWT has better low computation cost as the dilation function allowed the signals to be decomposed through a tree of low and high pass filters and no further analysing the high-frequency components. In this paper, a method for bearing faults identification is presented by combing Continuous Wavelet Transform (CWT) and Discrete Wavelet Transform (DWT) with envelope analysis for bearing fault diagnosis. The experimental data was sampled by Case Western Reserve University. The analysis result showed that the proposed method is effective in bearing faults detection, identify the exact fault’s location and severity assessment especially for the inner race and outer race faults.

Time-frequency domain SNR estimation and its application in seismic data processing

NASA Astrophysics Data System (ADS)

Zhao, Yan; Liu, Yang; Li, Xuxuan; Jiang, Nansen

2014-08-01

Based on an approach estimating frequency domain signal-to-noise ratio (FSNR), we propose a method to evaluate time-frequency domain signal-to-noise ratio (TFSNR). This method adopts short-time Fourier transform (STFT) to estimate instantaneous power spectrum of signal and noise, and thus uses their ratio to compute TFSNR. Unlike FSNR describing the variation of SNR with frequency only, TFSNR depicts the variation of SNR with time and frequency, and thus better handles non-stationary seismic data. By considering TFSNR, we develop methods to improve the effects of inverse Q filtering and high frequency noise attenuation in seismic data processing. Inverse Q filtering considering TFSNR can better solve the problem of amplitude amplification of noise. The high frequency noise attenuation method considering TFSNR, different from other de-noising methods, distinguishes and suppresses noise using an explicit criterion. Examples of synthetic and real seismic data illustrate the correctness and effectiveness of the proposed methods.

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

A Noise-Assisted Data Analysis Method for Automatic EOG-Based Sleep Stage Classification Using Ensemble Learning.

PubMed

Olesen, Alexander Neergaard; Christensen, Julie A E; Sorensen, Helge B D; Jennum, Poul J

2016-08-01

Reducing the number of recording modalities for sleep staging research can benefit both researchers and patients, under the condition that they provide as accurate results as conventional systems. This paper investigates the possibility of exploiting the multisource nature of the electrooculography (EOG) signals by presenting a method for automatic sleep staging using the complete ensemble empirical mode decomposition with adaptive noise algorithm, and a random forest classifier. It achieves a high overall accuracy of 82% and a Cohen's kappa of 0.74 indicating substantial agreement between automatic and manual scoring.

Methods in Astronomical Image Processing

NASA Astrophysics Data System (ADS)

Jörsäter, S.

A Brief Introductory Note History of Astronomical Imaging Astronomical Image Data Images in Various Formats Digitized Image Data Digital Image Data Philosophy of Astronomical Image Processing Properties of Digital Astronomical Images Human Image Processing Astronomical vs. Computer Science Image Processing Basic Tools of Astronomical Image Processing Display Applications Calibration of Intensity Scales Calibration of Length Scales Image Re-shaping Feature Enhancement Noise Suppression Noise and Error Analysis Image Processing Packages: Design of AIPS and MIDAS AIPS MIDAS Reduction of CCD Data Bias Subtraction Clipping Preflash Subtraction Dark Subtraction Flat Fielding Sky Subtraction Extinction Correction Deconvolution Methods Rebinning/Combining Summary and Prospects for the Future

Adaptive fault feature extraction from wayside acoustic signals from train bearings

NASA Astrophysics Data System (ADS)

Zhang, Dingcheng; Entezami, Mani; Stewart, Edward; Roberts, Clive; Yu, Dejie

2018-07-01

Wayside acoustic detection of train bearing faults plays a significant role in maintaining safety in the railway transport system. However, the bearing fault information is normally masked by strong background noises and harmonic interferences generated by other components (e.g. axles and gears). In order to extract the bearing fault feature information effectively, a novel method called improved singular value decomposition (ISVD) with resonance-based signal sparse decomposition (RSSD), namely the ISVD-RSSD method, is proposed in this paper. A Savitzky-Golay (S-G) smoothing filter is used to filter singular vectors (SVs) in the ISVD method as an extension of the singular value decomposition (SVD) theorem. Hilbert spectrum entropy and a stepwise optimisation strategy are used to optimize the S-G filter's parameters. The RSSD method is able to nonlinearly decompose the wayside acoustic signal of a faulty train bearing into high and low resonance components, the latter of which contains bearing fault information. However, the high level of noise usually results in poor decomposition results from the RSSD method. Hence, the collected wayside acoustic signal must first be de-noised using the ISVD component of the ISVD-RSSD method. Next, the de-noised signal is decomposed by using the RSSD method. The obtained low resonance component is then demodulated with a Hilbert transform such that the bearing fault can be detected by observing Hilbert envelope spectra. The effectiveness of the ISVD-RSSD method is verified through both laboratory field-based experiments as described in the paper. The results indicate that the proposed method is superior to conventional spectrum analysis and ensemble empirical mode decomposition methods.

Comparative study of performance of neutral axis tracking based damage detection

NASA Astrophysics Data System (ADS)

Soman, R.; Malinowski, P.; Ostachowicz, W.

2015-07-01

This paper presents a comparative study of a novel SHM technique for damage isolation. The performance of the Neutral Axis (NA) tracking based damage detection strategy is compared to other popularly used vibration based damage detection methods viz. ECOMAC, Mode Shape Curvature Method and Strain Flexibility Index Method. The sensitivity of the novel method is compared under changing ambient temperature conditions and in the presence of measurement noise. Finite Element Analysis (FEA) of the DTU 10 MW Wind Turbine was conducted to compare the local damage identification capability of each method and the results are presented. Under the conditions examined, the proposed method was found to be robust to ambient condition changes and measurement noise. The damage identification in some is either at par with the methods mentioned in the literature or better under the investigated damage scenarios.

[A new peak detection algorithm of Raman spectra].

PubMed

Jiang, Cheng-Zhi; Sun, Qiang; Liu, Ying; Liang, Jing-Qiu; An, Yan; Liu, Bing

2014-01-01

The authors proposed a new Raman peak recognition method named bi-scale correlation algorithm. The algorithm uses the combination of the correlation coefficient and the local signal-to-noise ratio under two scales to achieve Raman peak identification. We compared the performance of the proposed algorithm with that of the traditional continuous wavelet transform method through MATLAB, and then tested the algorithm with real Raman spectra. The results show that the average time for identifying a Raman spectrum is 0.51 s with the algorithm, while it is 0.71 s with the continuous wavelet transform. When the signal-to-noise ratio of Raman peak is greater than or equal to 6 (modern Raman spectrometers feature an excellent signal-to-noise ratio), the recognition accuracy with the algorithm is higher than 99%, while it is less than 84% with the continuous wavelet transform method. The mean and the standard deviations of the peak position identification error of the algorithm are both less than that of the continuous wavelet transform method. Simulation analysis and experimental verification prove that the new algorithm possesses the following advantages: no needs of human intervention, no needs of de-noising and background removal operation, higher recognition speed and higher recognition accuracy. The proposed algorithm is operable in Raman peak identification.

Speech perception at positive signal-to-noise ratios using adaptive adjustment of time compression.

PubMed

Schlueter, Anne; Brand, Thomas; Lemke, Ulrike; Nitzschner, Stefan; Kollmeier, Birger; Holube, Inga

2015-11-01

Positive signal-to-noise ratios (SNRs) characterize listening situations most relevant for hearing-impaired listeners in daily life and should therefore be considered when evaluating hearing aid algorithms. For this, a speech-in-noise test was developed and evaluated, in which the background noise is presented at fixed positive SNRs and the speech rate (i.e., the time compression of the speech material) is adaptively adjusted. In total, 29 younger and 12 older normal-hearing, as well as 24 older hearing-impaired listeners took part in repeated measurements. Younger normal-hearing and older hearing-impaired listeners conducted one of two adaptive methods which differed in adaptive procedure and step size. Analysis of the measurements with regard to list length and estimation strategy for thresholds resulted in a practical method measuring the time compression for 50% recognition. This method uses time-compression adjustment and step sizes according to Versfeld and Dreschler [(2002). J. Acoust. Soc. Am. 111, 401-408], with sentence scoring, lists of 30 sentences, and a maximum likelihood method for threshold estimation. Evaluation of the procedure showed that older participants obtained higher test-retest reliability compared to younger participants. Depending on the group of listeners, one or two lists are required for training prior to data collection.

Analytical prediction of the interior noise for cylindrical models of aircraft fuselages for prescribed exterior noise fields. Phase 2: Models for sidewall trim, stiffened structures and cabin acoustics with floor partition

NASA Technical Reports Server (NTRS)

Pope, L. D.; Wilby, E. G.

1982-01-01

An airplane interior noise prediction model is developed to determine the important parameters associated with sound transmission into the interiors of airplanes, and to identify apropriate noise control methods. Models for stiffened structures, and cabin acoustics with floor partition are developed. Validation studies are undertaken using three test articles: a ring stringer stiffened cylinder, an unstiffened cylinder with floor partition, and ring stringer stiffened cylinder with floor partition and sidewall trim. The noise reductions of the three test articles are computed using the heoretical models and compared to measured values. A statistical analysis of the comparison data indicates that there is no bias in the predictions although a substantial random error exists so that a discrepancy of more than five or six dB can be expected for about one out of three predictions.

Radar target classification method with high accuracy and decision speed performance using MUSIC spectrum vectors and PCA projection

NASA Astrophysics Data System (ADS)

Secmen, Mustafa

2011-10-01

This paper introduces the performance of an electromagnetic target recognition method in resonance scattering region, which includes pseudo spectrum Multiple Signal Classification (MUSIC) algorithm and principal component analysis (PCA) technique. The aim of this method is to classify an "unknown" target as one of the "known" targets in an aspect-independent manner. The suggested method initially collects the late-time portion of noise-free time-scattered signals obtained from different reference aspect angles of known targets. Afterward, these signals are used to obtain MUSIC spectrums in real frequency domain having super-resolution ability and noise resistant feature. In the final step, PCA technique is applied to these spectrums in order to reduce dimensionality and obtain only one feature vector per known target. In the decision stage, noise-free or noisy scattered signal of an unknown (test) target from an unknown aspect angle is initially obtained. Subsequently, MUSIC algorithm is processed for this test signal and resulting test vector is compared with feature vectors of known targets one by one. Finally, the highest correlation gives the type of test target. The method is applied to wire models of airplane targets, and it is shown that it can tolerate considerable noise levels although it has a few different reference aspect angles. Besides, the runtime of the method for a test target is sufficiently low, which makes the method suitable for real-time applications.