Relationships between digital signal processing and control and estimation theory

NASA Technical Reports Server (NTRS)

Willsky, A. S.

1978-01-01

Research areas associated with digital signal processing and control and estimation theory are identified. Particular attention is given to image processing, system identification problems (parameter identification, linear prediction, least squares, Kalman filtering), stability analyses (the use of the Liapunov theory, frequency domain criteria, passivity), and multiparameter systems, distributed processes, and random fields.

Separation and reconstruction of high pressure water-jet reflective sound signal based on ICA

NASA Astrophysics Data System (ADS)

Yang, Hongtao; Sun, Yuling; Li, Meng; Zhang, Dongsu; Wu, Tianfeng

2011-12-01

The impact of high pressure water-jet on the different materials target will produce different reflective mixed sound. In order to reconstruct the reflective sound signals distribution on the linear detecting line accurately and to separate the environment noise effectively, the mixed sound signals acquired by linear mike array were processed by ICA. The basic principle of ICA and algorithm of FASTICA were described in detail. The emulation experiment was designed. The environment noise signal was simulated by using band-limited white noise and the reflective sound signal was simulated by using pulse signal. The reflective sound signal attenuation produced by the different distance transmission was simulated by weighting the sound signal with different contingencies. The mixed sound signals acquired by linear mike array were synthesized by using the above simulated signals and were whitened and separated by ICA. The final results verified that the environment noise separation and the reconstruction of the detecting-line sound distribution can be realized effectively.

EEG feature selection method based on decision tree.

PubMed

Duan, Lijuan; Ge, Hui; Ma, Wei; Miao, Jun

2015-01-01

This paper aims to solve automated feature selection problem in brain computer interface (BCI). In order to automate feature selection process, we proposed a novel EEG feature selection method based on decision tree (DT). During the electroencephalogram (EEG) signal processing, a feature extraction method based on principle component analysis (PCA) was used, and the selection process based on decision tree was performed by searching the feature space and automatically selecting optimal features. Considering that EEG signals are a series of non-linear signals, a generalized linear classifier named support vector machine (SVM) was chosen. In order to test the validity of the proposed method, we applied the EEG feature selection method based on decision tree to BCI Competition II datasets Ia, and the experiment showed encouraging results.

Time Delay Estimation

DTIC Science & Technology

1976-04-09

of the signal and noise remain HH ***^-^*--~ 53 h, to r(Mc) h2(r» r(we) Figure 3-2 Sy&toetric Impulse Response for Two FIR Linear Phase...Inputs x,y and Outputs x.j. , 15 2-2 Linear System with Impulse Response h("r) 23 2-3 Model of Error Resulting from Linearly Filtering x(t) to...Corrupted with Additive Noise 42 2-6 Model of Directional Signal Corrupted with Additive Noise and Processed .... 45 2-7 Source Driving Two

Input-output characterization of an ultrasonic testing system by digital signal analysis

NASA Technical Reports Server (NTRS)

Karaguelle, H.; Lee, S. S.; Williams, J., Jr.

1984-01-01

The input/output characteristics of an ultrasonic testing system used for stress wave factor measurements were studied. The fundamentals of digital signal processing are summarized. The inputs and outputs are digitized and processed in a microcomputer using digital signal processing techniques. The entire ultrasonic test system, including transducers and all electronic components, is modeled as a discrete-time linear shift-invariant system. Then the impulse response and frequency response of the continuous time ultrasonic test system are estimated by interpolating the defining points in the unit sample response and frequency response of the discrete time system. It is found that the ultrasonic test system behaves as a linear phase bandpass filter. Good results were obtained for rectangular pulse inputs of various amplitudes and durations and for tone burst inputs whose center frequencies are within the passband of the test system and for single cycle inputs of various amplitudes. The input/output limits on the linearity of the system are determined.

Noise removal in extended depth of field microscope images through nonlinear signal processing.

PubMed

Zahreddine, Ramzi N; Cormack, Robert H; Cogswell, Carol J

2013-04-01

Extended depth of field (EDF) microscopy, achieved through computational optics, allows for real-time 3D imaging of live cell dynamics. EDF is achieved through a combination of point spread function engineering and digital image processing. A linear Wiener filter has been conventionally used to deconvolve the image, but it suffers from high frequency noise amplification and processing artifacts. A nonlinear processing scheme is proposed which extends the depth of field while minimizing background noise. The nonlinear filter is generated via a training algorithm and an iterative optimizer. Biological microscope images processed with the nonlinear filter show a significant improvement in image quality and signal-to-noise ratio over the conventional linear filter.

Linear friction weld process monitoring of fixture cassette deformations using empirical mode decomposition

NASA Astrophysics Data System (ADS)

Bakker, O. J.; Gibson, C.; Wilson, P.; Lohse, N.; Popov, A. A.

2015-10-01

Due to its inherent advantages, linear friction welding is a solid-state joining process of increasing importance to the aerospace, automotive, medical and power generation equipment industries. Tangential oscillations and forge stroke during the burn-off phase of the joining process introduce essential dynamic forces, which can also be detrimental to the welding process. Since burn-off is a critical phase in the manufacturing stage, process monitoring is fundamental for quality and stability control purposes. This study aims to improve workholding stability through the analysis of fixture cassette deformations. Methods and procedures for process monitoring are developed and implemented in a fail-or-pass assessment system for fixture cassette deformations during the burn-off phase. Additionally, the de-noised signals are compared to results from previous production runs. The observed deformations as a consequence of the forces acting on the fixture cassette are measured directly during the welding process. Data on the linear friction-welding machine are acquired and de-noised using empirical mode decomposition, before the burn-off phase is extracted. This approach enables a direct, objective comparison of the signal features with trends from previous successful welds. The capacity of the whole process monitoring system is validated and demonstrated through the analysis of a large number of signals obtained from welding experiments.

Distributed Estimation using Bayesian Consensus Filtering

DTIC Science & Technology

2014-06-06

Convergence rate analysis of distributed gossip (linear parameter) estimation: Fundamental limits and tradeoffs,” IEEE J. Sel. Topics Signal Process...Dimakis, S. Kar, J. Moura, M. Rabbat, and A. Scaglione, “ Gossip algorithms for distributed signal processing,” Proc. of the IEEE, vol. 98, no. 11, pp

Signal processing methodologies for an acoustic fetal heart rate monitor

NASA Technical Reports Server (NTRS)

Pretlow, Robert A., III; Stoughton, John W.

1992-01-01

Research and development is presented of real time signal processing methodologies for the detection of fetal heart tones within a noise-contaminated signal from a passive acoustic sensor. A linear predictor algorithm is utilized for detection of the heart tone event and additional processing derives heart rate. The linear predictor is adaptively 'trained' in a least mean square error sense on generic fetal heart tones recorded from patients. A real time monitor system is described which outputs to a strip chart recorder for plotting the time history of the fetal heart rate. The system is validated in the context of the fetal nonstress test. Comparisons are made with ultrasonic nonstress tests on a series of patients. Comparative data provides favorable indications of the feasibility of the acoustic monitor for clinical use.

Mapping the Information Trace in Local Field Potentials by a Computational Method of Two-Dimensional Time-Shifting Synchronization Likelihood Based on Graphic Processing Unit Acceleration.

PubMed

Zhao, Zi-Fang; Li, Xue-Zhu; Wan, You

2017-12-01

The local field potential (LFP) is a signal reflecting the electrical activity of neurons surrounding the electrode tip. Synchronization between LFP signals provides important details about how neural networks are organized. Synchronization between two distant brain regions is hard to detect using linear synchronization algorithms like correlation and coherence. Synchronization likelihood (SL) is a non-linear synchronization-detecting algorithm widely used in studies of neural signals from two distant brain areas. One drawback of non-linear algorithms is the heavy computational burden. In the present study, we proposed a graphic processing unit (GPU)-accelerated implementation of an SL algorithm with optional 2-dimensional time-shifting. We tested the algorithm with both artificial data and raw LFP data. The results showed that this method revealed detailed information from original data with the synchronization values of two temporal axes, delay time and onset time, and thus can be used to reconstruct the temporal structure of a neural network. Our results suggest that this GPU-accelerated method can be extended to other algorithms for processing time-series signals (like EEG and fMRI) using similar recording techniques.

DOA Finding with Support Vector Regression Based Forward-Backward Linear Prediction.

PubMed

Pan, Jingjing; Wang, Yide; Le Bastard, Cédric; Wang, Tianzhen

2017-05-27

Direction-of-arrival (DOA) estimation has drawn considerable attention in array signal processing, particularly with coherent signals and a limited number of snapshots. Forward-backward linear prediction (FBLP) is able to directly deal with coherent signals. Support vector regression (SVR) is robust with small samples. This paper proposes the combination of the advantages of FBLP and SVR in the estimation of DOAs of coherent incoming signals with low snapshots. The performance of the proposed method is validated with numerical simulations in coherent scenarios, in terms of different angle separations, numbers of snapshots, and signal-to-noise ratios (SNRs). Simulation results show the effectiveness of the proposed method.

A robust approach to measuring the detective quantum efficiency of radiographic detectors in a clinical setting

NASA Astrophysics Data System (ADS)

McDonald, Michael C.; Kim, H. K.; Henry, J. R.; Cunningham, I. A.

2012-03-01

The detective quantum efficiency (DQE) is widely accepted as a primary measure of x-ray detector performance in the scientific community. A standard method for measuring the DQE, based on IEC 62220-1, requires the system to have a linear response meaning that the detector output signals are proportional to the incident x-ray exposure. However, many systems have a non-linear response due to characteristics of the detector, or post processing of the detector signals, that cannot be disabled and may involve unknown algorithms considered proprietary by the manufacturer. For these reasons, the DQE has not been considered as a practical candidate for routine quality assurance testing in a clinical setting. In this article we described a method that can be used to measure the DQE of both linear and non-linear systems that employ only linear image processing algorithms. The method was validated on a Cesium Iodide based flat panel system that simultaneously stores a raw (linear) and processed (non-linear) image for each exposure. It was found that the resulting DQE was equivalent to a conventional standards-compliant DQE with measurement precision, and the gray-scale inversion and linear edge enhancement did not affect the DQE result. While not IEC 62220-1 compliant, it may be adequate for QA programs.

Signal Processing in Periodically Forced Gradient Frequency Neural Networks

PubMed Central

Kim, Ji Chul; Large, Edward W.

2015-01-01

Oscillatory instability at the Hopf bifurcation is a dynamical phenomenon that has been suggested to characterize active non-linear processes observed in the auditory system. Networks of oscillators poised near Hopf bifurcation points and tuned to tonotopically distributed frequencies have been used as models of auditory processing at various levels, but systematic investigation of the dynamical properties of such oscillatory networks is still lacking. Here we provide a dynamical systems analysis of a canonical model for gradient frequency neural networks driven by a periodic signal. We use linear stability analysis to identify various driven behaviors of canonical oscillators for all possible ranges of model and forcing parameters. The analysis shows that canonical oscillators exhibit qualitatively different sets of driven states and transitions for different regimes of model parameters. We classify the parameter regimes into four main categories based on their distinct signal processing capabilities. This analysis will lead to deeper understanding of the diverse behaviors of neural systems under periodic forcing and can inform the design of oscillatory network models of auditory signal processing. PMID:26733858

The analysis of decimation and interpolation in the linear canonical transform domain.

PubMed

Xu, Shuiqing; Chai, Yi; Hu, Youqiang; Huang, Lei; Feng, Li

2016-01-01

Decimation and interpolation are the two basic building blocks in the multirate digital signal processing systems. As the linear canonical transform (LCT) has been shown to be a powerful tool for optics and signal processing, it is worthwhile and interesting to analyze the decimation and interpolation in the LCT domain. In this paper, the definition of equivalent filter in the LCT domain have been given at first. Then, by applying the definition, the direct implementation structure and polyphase networks for decimator and interpolator in the LCT domain have been proposed. Finally, the perfect reconstruction expressions for differential filters in the LCT domain have been presented as an application. The proposed theorems in this study are the bases for generalizations of the multirate signal processing in the LCT domain, which can advance the filter banks theorems in the LCT domain.

Cognitive Processing Speed, Working Memory, and the Intelligibility of Hearing Aid-Processed Speech in Persons with Hearing Impairment

PubMed Central

Yumba, Wycliffe Kabaywe

2017-01-01

Previous studies have demonstrated that successful listening with advanced signal processing in digital hearing aids is associated with individual cognitive capacity, particularly working memory capacity (WMC). This study aimed to examine the relationship between cognitive abilities (cognitive processing speed and WMC) and individual listeners’ responses to digital signal processing settings in adverse listening conditions. A total of 194 native Swedish speakers (83 women and 111 men), aged 33–80 years (mean = 60.75 years, SD = 8.89), with bilateral, symmetrical mild to moderate sensorineural hearing loss who had completed a lexical decision speed test (measuring cognitive processing speed) and semantic word-pair span test (SWPST, capturing WMC) participated in this study. The Hagerman test (capturing speech recognition in noise) was conducted using an experimental hearing aid with three digital signal processing settings: (1) linear amplification without noise reduction (NoP), (2) linear amplification with noise reduction (NR), and (3) non-linear amplification without NR (“fast-acting compression”). The results showed that cognitive processing speed was a better predictor of speech intelligibility in noise, regardless of the types of signal processing algorithms used. That is, there was a stronger association between cognitive processing speed and NR outcomes and fast-acting compression outcomes (in steady state noise). We observed a weaker relationship between working memory and NR, but WMC did not relate to fast-acting compression. WMC was a relatively weaker predictor of speech intelligibility in noise. These findings might have been different if the participants had been provided with training and or allowed to acclimatize to binary masking noise reduction or fast-acting compression. PMID:28861009

Relationships between digital signal processing and control and estimation theory

NASA Technical Reports Server (NTRS)

Willsky, A. S.

1978-01-01

Research directions in the fields of digital signal processing and modern control and estimation theory are discussed. Stability theory, linear prediction and parameter identification, system synthesis and implementation, two-dimensional filtering, decentralized control and estimation, and image processing are considered in order to uncover some of the basic similarities and differences in the goals, techniques, and philosophy of the disciplines.

Disequilibrium After Traumatic Brain Injury: Vestibular Mechanisms

DTIC Science & Technology

2011-09-01

of otolith signal processing, including the integration of head acceleration26 and the disambiguation of linear ac- celeration signals related to tilt ...Foveal versus full-field visual stabilization strategies for translational and rotational head movements. J. Neurosci. 23: 1104–1108. 14. Walker, M.F., M...in the vestibular reflexes that compensate for linear movements of the head and body during standing and walking. The experimental protocol has two

A Differential Monolithically Integrated Inductive Linear Displacement Measurement Microsystem

PubMed Central

Podhraški, Matija; Trontelj, Janez

2016-01-01

An inductive linear displacement measurement microsystem realized as a monolithic Application-Specific Integrated Circuit (ASIC) is presented. The system comprises integrated microtransformers as sensing elements, and analog front-end electronics for signal processing and demodulation, both jointly fabricated in a conventional commercially available four-metal 350-nm CMOS process. The key novelty of the presented system is its full integration, straightforward fabrication, and ease of application, requiring no external light or magnetic field source. Such systems therefore have the possibility of substituting certain conventional position encoder types. The microtransformers are excited by an AC signal in MHz range. The displacement information is modulated into the AC signal by a metal grating scale placed over the microsystem, employing a differential measurement principle. Homodyne mixing is used for the demodulation of the scale displacement information, returned by the ASIC as a DC signal in two quadrature channels allowing the determination of linear position of the target scale. The microsystem design, simulations, and characterization are presented. Various system operating conditions such as frequency, phase, target scale material and distance have been experimentally evaluated. The best results have been achieved at 4 MHz, demonstrating a linear resolution of 20 µm with steel and copper scale, having respective sensitivities of 0.71 V/mm and 0.99 V/mm. PMID:26999146

A Differential Monolithically Integrated Inductive Linear Displacement Measurement Microsystem.

PubMed

Podhraški, Matija; Trontelj, Janez

2016-03-17

An inductive linear displacement measurement microsystem realized as a monolithic Application-Specific Integrated Circuit (ASIC) is presented. The system comprises integrated microtransformers as sensing elements, and analog front-end electronics for signal processing and demodulation, both jointly fabricated in a conventional commercially available four-metal 350-nm CMOS process. The key novelty of the presented system is its full integration, straightforward fabrication, and ease of application, requiring no external light or magnetic field source. Such systems therefore have the possibility of substituting certain conventional position encoder types. The microtransformers are excited by an AC signal in MHz range. The displacement information is modulated into the AC signal by a metal grating scale placed over the microsystem, employing a differential measurement principle. Homodyne mixing is used for the demodulation of the scale displacement information, returned by the ASIC as a DC signal in two quadrature channels allowing the determination of linear position of the target scale. The microsystem design, simulations, and characterization are presented. Various system operating conditions such as frequency, phase, target scale material and distance have been experimentally evaluated. The best results have been achieved at 4 MHz, demonstrating a linear resolution of 20 µm with steel and copper scale, having respective sensitivities of 0.71 V/mm and 0.99 V/mm.

EMG prediction from Motor Cortical Recordings via a Non-Negative Point Process Filter

PubMed Central

Nazarpour, Kianoush; Ethier, Christian; Paninski, Liam; Rebesco, James M.; Miall, R. Chris; Miller, Lee E.

2012-01-01

A constrained point process filtering mechanism for prediction of electromyogram (EMG) signals from multi-channel neural spike recordings is proposed here. Filters from the Kalman family are inherently sub-optimal in dealing with non-Gaussian observations, or a state evolution that deviates from the Gaussianity assumption. To address these limitations, we modeled the non-Gaussian neural spike train observations by using a generalized linear model (GLM) that encapsulates covariates of neural activity, including the neurons’ own spiking history, concurrent ensemble activity, and extrinsic covariates (EMG signals). In order to predict the envelopes of EMGs, we reformulated the Kalman filter (KF) in an optimization framework and utilized a non-negativity constraint. This structure characterizes the non-linear correspondence between neural activity and EMG signals reasonably. The EMGs were recorded from twelve forearm and hand muscles of a behaving monkey during a grip-force task. For the case of limited training data, the constrained point process filter improved the prediction accuracy when compared to a conventional Wiener cascade filter (a linear causal filter followed by a static non-linearity) for different bin sizes and delays between input spikes and EMG output. For longer training data sets, results of the proposed filter and that of the Wiener cascade filter were comparable. PMID:21659018

Brain signal variability as a window into the bidirectionality between music and language processing: moving from a linear to a nonlinear model

PubMed Central

Hutka, Stefanie; Bidelman, Gavin M.; Moreno, Sylvain

2013-01-01

There is convincing empirical evidence for bidirectional transfer between music and language, such that experience in either domain can improve mental processes required by the other. This music-language relationship has been studied using linear models (e.g., comparing mean neural activity) that conceptualize brain activity as a static entity. The linear approach limits how we can understand the brain’s processing of music and language because the brain is a nonlinear system. Furthermore, there is evidence that the networks supporting music and language processing interact in a nonlinear manner. We therefore posit that the neural processing and transfer between the domains of language and music are best viewed through the lens of a nonlinear framework. Nonlinear analysis of neurophysiological activity may yield new insight into the commonalities, differences, and bidirectionality between these two cognitive domains not measurable in the local output of a cortical patch. We thus propose a novel application of brain signal variability (BSV) analysis, based on mutual information and signal entropy, to better understand the bidirectionality of music-to-language transfer in the context of a nonlinear framework. This approach will extend current methods by offering a nuanced, network-level understanding of the brain complexity involved in music-language transfer. PMID:24454295

Brain signal variability as a window into the bidirectionality between music and language processing: moving from a linear to a nonlinear model.

PubMed

Hutka, Stefanie; Bidelman, Gavin M; Moreno, Sylvain

2013-12-30

There is convincing empirical evidence for bidirectional transfer between music and language, such that experience in either domain can improve mental processes required by the other. This music-language relationship has been studied using linear models (e.g., comparing mean neural activity) that conceptualize brain activity as a static entity. The linear approach limits how we can understand the brain's processing of music and language because the brain is a nonlinear system. Furthermore, there is evidence that the networks supporting music and language processing interact in a nonlinear manner. We therefore posit that the neural processing and transfer between the domains of language and music are best viewed through the lens of a nonlinear framework. Nonlinear analysis of neurophysiological activity may yield new insight into the commonalities, differences, and bidirectionality between these two cognitive domains not measurable in the local output of a cortical patch. We thus propose a novel application of brain signal variability (BSV) analysis, based on mutual information and signal entropy, to better understand the bidirectionality of music-to-language transfer in the context of a nonlinear framework. This approach will extend current methods by offering a nuanced, network-level understanding of the brain complexity involved in music-language transfer.

Integrated circuits for accurate linear analogue electric signal processing

NASA Astrophysics Data System (ADS)

Huijsing, J. H.

1981-11-01

The main lines in the design of integrated circuits for accurate analog linear electric signal processing in a frequency range including DC are investigated. A categorization of universal active electronic devices is presented on the basis of the connections of one of the terminals of the input and output ports to the common ground potential. The means for quantifying the attributes of four types of universal active electronic devices are included. The design of integrated operational voltage amplifiers (OVA) is discussed. Several important applications in the field of general instrumentation are numerically evaluated, and the design of operatinal floating amplifiers is presented.

PID-based error signal modeling

NASA Astrophysics Data System (ADS)

Yohannes, Tesfay

1997-10-01

This paper introduces a PID based signal error modeling. The error modeling is based on the betterment process. The resulting iterative learning algorithm is introduced and a detailed proof is provided for both linear and nonlinear systems.

Non-linear Post Processing Image Enhancement

NASA Technical Reports Server (NTRS)

Hunt, Shawn; Lopez, Alex; Torres, Angel

1997-01-01

A non-linear filter for image post processing based on the feedforward Neural Network topology is presented. This study was undertaken to investigate the usefulness of "smart" filters in image post processing. The filter has shown to be useful in recovering high frequencies, such as those lost during the JPEG compression-decompression process. The filtered images have a higher signal to noise ratio, and a higher perceived image quality. Simulation studies comparing the proposed filter with the optimum mean square non-linear filter, showing examples of the high frequency recovery, and the statistical properties of the filter are given,

The Seismic Tool-Kit (STK): An Open Source Software For Learning the Basis of Signal Processing and Seismology.

NASA Astrophysics Data System (ADS)

Reymond, D.

2016-12-01

We present an open source software project (GNU public license), named STK: Seismic Tool-Kit, that is dedicated mainly for learning signal processing and seismology. The STK project that started in 2007, is hosted by SourceForge.net, and count more than 20000 downloads at the date of writing.The STK project is composed of two main branches:First, a graphical interface dedicated to signal processing (in the SAC format (SAC_ASCII and SAC_BIN): where the signal can be plotted, zoomed, filtered, integrated, derivated, ... etc. (a large variety of IFR and FIR filter is proposed). The passage in the frequency domain via the Fourier transform is used to introduce the estimation of spectral density of the signal , with visualization of the Power Spectral Density (PSD) in linear or log scale, and also the evolutive time-frequency representation (or sonagram). The 3-components signals can be also processed for estimating their polarization properties, either for a given window, or either for evolutive windows along the time. This polarization analysis is useful for extracting the polarized noises, differentiating P waves, Rayleigh waves, Love waves, ... etc. Secondly, a panel of Utilities-Program are proposed for working in a terminal mode, with basic programs for computing azimuth and distance in spherical geometry, inter/auto-correlation, spectral density, time-frequency for an entire directory of signals, focal planes, and main components axis, radiation pattern of P waves, Polarization analysis of different waves (including noise), under/over-sampling the signals, cubic-spline smoothing, and linear/non linear regression analysis of data set. STK is developed in C/C++, mainly under Linux OS, and it has been also partially implemented under MS-Windows. STK has been used in some schools for viewing and plotting seismic records provided by IRIS, and it has been used as a practical support for teaching the basis of signal processing. Useful links:http://sourceforge.net/projects/seismic-toolkit/http://sourceforge.net/p/seismic-toolkit/wiki/browse_pages/

Balancing Vibrations at Harmonic Frequencies by Injecting Harmonic Balancing Signals into the Armature of a Linear Motor/Alternator Coupled to a Stirling Machine

NASA Technical Reports Server (NTRS)

Holliday, Ezekiel S. (Inventor)

2014-01-01

Vibrations at harmonic frequencies are reduced by injecting harmonic balancing signals into the armature of a linear motor/alternator coupled to a Stirling machine. The vibrations are sensed to provide a signal representing the mechanical vibrations. A harmonic balancing signal is generated for selected harmonics of the operating frequency by processing the sensed vibration signal with adaptive filter algorithms of adaptive filters for each harmonic. Reference inputs for each harmonic are applied to the adaptive filter algorithms at the frequency of the selected harmonic. The harmonic balancing signals for all of the harmonics are summed with a principal control signal. The harmonic balancing signals modify the principal electrical drive voltage and drive the motor/alternator with a drive voltage component in opposition to the vibration at each harmonic.

Signal Construction-Based Dispersion Compensation of Lamb Waves Considering Signal Waveform and Amplitude Spectrum Preservation

PubMed Central

Cai, Jian; Yuan, Shenfang; Wang, Tongguang

2016-01-01

The results of Lamb wave identification for the aerospace structures could be easily affected by the nonlinear-dispersion characteristics. In this paper, dispersion compensation of Lamb waves is of particular concern. Compared with the similar research works on the traditional signal domain transform methods, this study is based on signal construction from the viewpoint of nonlinear wavenumber linearization. Two compensation methods of linearly-dispersive signal construction (LDSC) and non-dispersive signal construction (NDSC) are proposed. Furthermore, to improve the compensation effect, the influence of the signal construction process on the other crucial signal properties, including the signal waveform and amplitude spectrum, is considered during the investigation. The linear-dispersion and non-dispersion effects are firstly analyzed. Then, after the basic signal construction principle is explored, the numerical realization of LDSC and NDSC is discussed, in which the signal waveform and amplitude spectrum preservation is especially regarded. Subsequently, associated with the delay-and-sum algorithm, LDSC or NDSC is employed for high spatial resolution damage imaging, so that the adjacent multi-damage or quantitative imaging capacity of Lamb waves can be strengthened. To verify the proposed signal construction and damage imaging methods, the experimental and numerical validation is finally arranged on the aluminum plates. PMID:28772366

Signal Construction-Based Dispersion Compensation of Lamb Waves Considering Signal Waveform and Amplitude Spectrum Preservation.

PubMed

Cai, Jian; Yuan, Shenfang; Wang, Tongguang

2016-12-23

The results of Lamb wave identification for the aerospace structures could be easily affected by the nonlinear-dispersion characteristics. In this paper, dispersion compensation of Lamb waves is of particular concern. Compared with the similar research works on the traditional signal domain transform methods, this study is based on signal construction from the viewpoint of nonlinear wavenumber linearization. Two compensation methods of linearly-dispersive signal construction (LDSC) and non-dispersive signal construction (NDSC) are proposed. Furthermore, to improve the compensation effect, the influence of the signal construction process on the other crucial signal properties, including the signal waveform and amplitude spectrum, is considered during the investigation. The linear-dispersion and non-dispersion effects are firstly analyzed. Then, after the basic signal construction principle is explored, the numerical realization of LDSC and NDSC is discussed, in which the signal waveform and amplitude spectrum preservation is especially regarded. Subsequently, associated with the delay-and-sum algorithm, LDSC or NDSC is employed for high spatial resolution damage imaging, so that the adjacent multi-damage or quantitative imaging capacity of Lamb waves can be strengthened. To verify the proposed signal construction and damage imaging methods, the experimental and numerical validation is finally arranged on the aluminum plates.

Characterization of a signal recording system for accurate velocity estimation using a VISAR

NASA Astrophysics Data System (ADS)

Rav, Amit; Joshi, K. D.; Singh, Kulbhushan; Kaushik, T. C.

2018-02-01

The linearity of a signal recording system (SRS) in time as well as in amplitude are important for the accurate estimation of the free surface velocity history of a moving target during shock loading and unloading when measured using optical interferometers such as a velocity interferometer system for any reflector (VISAR). Signal recording being the first step in a long sequence of signal processes, the incorporation of errors due to nonlinearity, and low signal-to-noise ratio (SNR) affects the overall accuracy and precision of the estimation of velocity history. In shock experiments the small duration (a few µs) of loading/unloading, the reflectivity of moving target surface, and the properties of optical components, control the amount of input of light to the SRS of a VISAR and this in turn affects the linearity and SNR of the overall measurement. These factors make it essential to develop in situ procedures for (i) minimizing the effect of signal induced noise and (ii) determine the linear region of operation for the SRS. Here we report on a procedure for the optimization of SRS parameters such as photodetector gain, optical power, aperture etc, so as to achieve a linear region of operation with a high SNR. The linear region of operation so determined has been utilized successfully to estimate the temporal history of the free surface velocity of the moving target in shock experiments.

Linear Mathematical Model for Seam Tracking with an Arc Sensor in P-GMAW Processes

PubMed Central

Liu, Wenji; Li, Liangyu; Hong, Ying; Yue, Jianfeng

2017-01-01

Arc sensors have been used in seam tracking and widely studied since the 80s and commercial arc sensing products for T and V shaped grooves have been developed. However, it is difficult to use these arc sensors in narrow gap welding because the arc stability and sensing accuracy are not satisfactory. Pulse gas melting arc welding (P-GMAW) has been successfully applied in narrow gap welding and all position welding processes, so it is worthwhile to research P-GMAW arc sensing technology. In this paper, we derived a linear mathematical P-GMAW model for arc sensing, and the assumptions for the model are verified through experiments and finite element methods. Finally, the linear characteristics of the mathematical model were investigated. In torch height changing experiments, uphill experiments, and groove angle changing experiments the P-GMAW arc signals all satisfied the linear rules. In addition, the faster the welding speed, the higher the arc signal sensitivities; the smaller the groove angle, the greater the arc sensitivities. The arc signal variation rate needs to be modified according to the welding power, groove angles, and weaving or rotate speed. PMID:28335425

Linear Mathematical Model for Seam Tracking with an Arc Sensor in P-GMAW Processes.

PubMed

Liu, Wenji; Li, Liangyu; Hong, Ying; Yue, Jianfeng

2017-03-14

Arc sensors have been used in seam tracking and widely studied since the 80s and commercial arc sensing products for T and V shaped grooves have been developed. However, it is difficult to use these arc sensors in narrow gap welding because the arc stability and sensing accuracy are not satisfactory. Pulse gas melting arc welding (P-GMAW) has been successfully applied in narrow gap welding and all position welding processes, so it is worthwhile to research P-GMAW arc sensing technology. In this paper, we derived a linear mathematical P-GMAW model for arc sensing, and the assumptions for the model are verified through experiments and finite element methods. Finally, the linear characteristics of the mathematical model were investigated. In torch height changing experiments, uphill experiments, and groove angle changing experiments the P-GMAW arc signals all satisfied the linear rules. In addition, the faster the welding speed, the higher the arc signal sensitivities; the smaller the groove angle, the greater the arc sensitivities. The arc signal variation rate needs to be modified according to the welding power, groove angles, and weaving or rotate speed.

Linearly Additive Shape and Color Signals in Monkey Inferotemporal Cortex

PubMed Central

McMahon, David B. T.; Olson, Carl R.

2009-01-01

How does the brain represent a red circle? One possibility is that there is a specialized and possibly time-consuming process whereby the attributes of shape and color, carried by separate populations of neurons in low-order visual cortex, are bound together into a unitary neural representation. Another possibility is that neurons in high-order visual cortex are selective, by virtue of their bottom-up input from low-order visual areas, for particular conjunctions of shape and color. A third possibility is that they simply sum shape and color signals linearly. We tested these ideas by measuring the responses of inferotemporal cortex neurons to sets of stimuli in which two attributes—shape and color—varied independently. We find that a few neurons exhibit conjunction selectivity but that in most neurons the influences of shape and color sum linearly. Contrary to the idea of conjunction coding, few neurons respond selectively to a particular combination of shape and color. Contrary to the idea that binding requires time, conjunction signals, when present, occur as early as feature signals. We argue that neither conjunction selectivity nor a specialized feature binding process is necessary for the effective representation of shape–color combinations. PMID:19144745

Linearly additive shape and color signals in monkey inferotemporal cortex.

PubMed

McMahon, David B T; Olson, Carl R

2009-04-01

How does the brain represent a red circle? One possibility is that there is a specialized and possibly time-consuming process whereby the attributes of shape and color, carried by separate populations of neurons in low-order visual cortex, are bound together into a unitary neural representation. Another possibility is that neurons in high-order visual cortex are selective, by virtue of their bottom-up input from low-order visual areas, for particular conjunctions of shape and color. A third possibility is that they simply sum shape and color signals linearly. We tested these ideas by measuring the responses of inferotemporal cortex neurons to sets of stimuli in which two attributes-shape and color-varied independently. We find that a few neurons exhibit conjunction selectivity but that in most neurons the influences of shape and color sum linearly. Contrary to the idea of conjunction coding, few neurons respond selectively to a particular combination of shape and color. Contrary to the idea that binding requires time, conjunction signals, when present, occur as early as feature signals. We argue that neither conjunction selectivity nor a specialized feature binding process is necessary for the effective representation of shape-color combinations.

Investigation of Cepstrum Analysis for Seismic/Acoustic Signal Sensor Range Determination.

DTIC Science & Technology

1981-01-01

distorted by transmission through a linear system . For example, the effect of multipath and reverberation may be modeled in terms of a signal that is...called the short time averaged cepstrum. To derive some analytical expressions for short time average cepstrums we choose some functions of interest...linear process applied to the time series or any equivalent time function Repiod Period The amount of time required for one cycle of a time series Saphe

RADC Multi-Dimensional Signal-Processing Research Program.

DTIC Science & Technology

1980-09-30

Formulation 7 3.2.2 Methods of Accelerating Convergence 8 3.2.3 Application to Image Deblurring 8 3.2.4 Extensions 11 3.3 Convergence of Iterative Signal... noise -driven linear filters, permit development of the joint probability density function oz " kelihood function for the image. With an expression...spatial linear filter driven by white noise (see Fig. i). If the probability density function for the white noise is known, Fig. t. Model for image

Input-output characterization of an ultrasonic testing system by digital signal analysis

NASA Technical Reports Server (NTRS)

Williams, J. H., Jr.; Lee, S. S.; Karagulle, H.

1986-01-01

Ultrasonic test system input-output characteristics were investigated by directly coupling the transmitting and receiving transducers face to face without a test specimen. Some of the fundamentals of digital signal processing were summarized. Input and output signals were digitized by using a digital oscilloscope, and the digitized data were processed in a microcomputer by using digital signal-processing techniques. The continuous-time test system was modeled as a discrete-time, linear, shift-invariant system. In estimating the unit-sample response and frequency response of the discrete-time system, it was necessary to use digital filtering to remove low-amplitude noise, which interfered with deconvolution calculations. A digital bandpass filter constructed with the assistance of a Blackman window and a rectangular time window were used. Approximations of the impulse response and the frequency response of the continuous-time test system were obtained by linearly interpolating the defining points of the unit-sample response and the frequency response of the discrete-time system. The test system behaved as a linear-phase bandpass filter in the frequency range 0.6 to 2.3 MHz. These frequencies were selected in accordance with the criterion that they were 6 dB below the maximum peak of the amplitude of the frequency response. The output of the system to various inputs was predicted and the results were compared with the corresponding measurements on the system.

Application of Mathematical Signal Processing Techniques to Mission Systems. (l’Application des techniques mathematiques du traitement du signal aux systemes de conduite des missions)

DTIC Science & Technology

1999-11-01

represents the linear time invariant (LTI) response of the combined analysis /synthesis system while the second repre- sents the aliasing introduced into...effectively to implement voice scrambling systems based on time - frequency permutation . The most general form of such a system is shown in Fig. 22 where...92201 NEUILLY-SUR-SEINE CEDEX, FRANCE RTO LECTURE SERIES 216 Application of Mathematical Signal Processing Techniques to Mission Systems (1

Decoding Signal Processing at the Single-Cell Level

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

Wiley, H. Steven

The ability of cells to detect and decode information about their extracellular environment is critical to generating an appropriate response. In multicellular organisms, cells must decode dozens of signals from their neighbors and extracellular matrix to maintain tissue homeostasis while still responding to environmental stressors. How cells detect and process information from their surroundings through a surprisingly limited number of signal transduction pathways is one of the most important question in biology. Despite many decades of research, many of the fundamental principles that underlie cell signal processing remain obscure. However, in this issue of Cell Systems, Gillies et al presentmore » compelling evidence that the early response gene circuit can act as a linear signal integrator, thus providing significant insight into how cells handle fluctuating signals and noise in their environment.« less

Restoring Low Sidelobe Antenna Patterns with Failed Elements in a Phased Array Antenna

DTIC Science & Technology

2016-02-01

optimum low sidelobes are demonstrated in several examples. Index Terms — Array signal processing, beams, linear algebra , phased arrays, shaped...represented by a linear combination of low sidelobe beamformers with no failed elements, ’s, in a neighborhood around under the constraint that the linear ...would expect that linear combinations of them in a neighborhood around would also have low sidelobes. The algorithms in this paper exploit this

SPECIAL ISSUE ON OPTICAL PROCESSING OF INFORMATION: Optical signal-processing systems based on anisotropic media

NASA Astrophysics Data System (ADS)

Kiyashko, B. V.

1995-10-01

Partially coherent optical systems for signal processing are considered. The transfer functions are formed in these systems by interference of polarised light transmitted by an anisotropic medium. It is shown that such systems can perform various integral transformations of both optical and electric signals, in particular, two-dimensional Fourier and Fresnel transformations, as well as spectral analysis of weak light sources. It is demonstrated that such systems have the highest luminosity and vibration immunity among the systems with interference formation of transfer functions. An experimental investigation is reported of the application of these systems in the processing of signals from a linear hydroacoustic antenna array, and in measurements of the optical spectrum and of the intrinsic noise.

Interferometric architectures based All-Optical logic design methods and their implementations

NASA Astrophysics Data System (ADS)

Singh, Karamdeep; Kaur, Gurmeet

2015-06-01

All-Optical Signal Processing is an emerging technology which can avoid costly Optical-electronic-optical (O-E-O) conversions which are usually compulsory in traditional Electronic Signal Processing systems, thus greatly enhancing operating bit rate with some added advantages such as electro-magnetic interference immunity and low power consumption etc. In order to implement complex signal processing tasks All-Optical logic gates are required as backbone elements. This review describes the advances in the field of All-Optical logic design methods based on interferometric architectures such as Mach-Zehnder Interferometer (MZI), Sagnac Interferometers and Ultrafast Non-Linear Interferometer (UNI). All-Optical logic implementations for realization of arithmetic and signal processing applications based on each interferometric arrangement are also presented in a categorized manner.

Guided wave imaging of oblique reflecting interfaces in pipes using common-source synthetic focusing

NASA Astrophysics Data System (ADS)

Sun, Zeqing; Sun, Anyu; Ju, Bing-Feng

2018-04-01

Cross-mode-family mode conversion and secondary reflection of guided waves in pipes complicate the processing of guided waves signals, and can cause false detection. In this paper, filters operating in the spectral domain of wavenumber, circumferential order and frequency are designed to suppress the signal components of unwanted mode-family and unwanted traveling direction. Common-source synthetic focusing is used to reconstruct defect images from the guided wave signals. Simulations of the reflections from linear oblique defects and a semicircle defect are separately implemented. Defect images, which are reconstructed from the simulation results under different excitation conditions, are comparatively studied in terms of axial resolution, reflection amplitude, detectable oblique angle and so on. Further, the proposed method is experimentally validated by detecting linear cracks with various oblique angles (10-40°). The proposed method relies on the guided wave signals that are captured during 2-D scanning of a cylindrical area on the pipe. The redundancy of the signals is analyzed to reduce the time-consumption of the scanning process and to enhance the practicability of the proposed method.

System for generating a beam of acoustic energy from a borehole, and applications thereof

DOEpatents

Vu, Cung Khac; Sinha, Dipen N.; Pantea, Cristian; Nihei, Kurt T.; Schmitt, Denis P.; Skelt, Christopher

2012-09-04

In some aspects of the invention, a device, positioned within a well bore, configured to generate and direct an acoustic beam into a rock formation around a borehole is disclosed. The device comprises a source configured to generate a first signal at a first frequency and a second signal at a second frequency; a transducer configured to receive the generated first and the second signals and produce acoustic waves at the first frequency and the second frequency; and a non-linear material, coupled to the transducer, configured to generate a collimated beam with a frequency equal to the difference between the first frequency and the second frequency by a non-linear mixing process, wherein the non-linear material includes one or more of a mixture of liquids, a solid, a granular material, embedded microspheres, or an emulsion.

System for generating a beam of acoustic energy from a borehole, and applications thereof

DOEpatents

Vu, Cung Khac [Houston, TX; Sinha, Dipen N [Los Alamos, NM; Pantea, Cristian [Los Alamos, NM; Nihei, Kurt T [Oakland, CA; Schmitt, Denis P [Katy, TX; Skelt, Christopher [Houston, TX

2012-07-31

In some aspects of the invention, a device, positioned within a well bore, configured to generate and direct an acoustic beam into a rock formation around a borehole is disclosed. The device comprises a source configured to generate a first signal at a first frequency and a second signal at a second frequency; a transducer configured to receive the generated first and the second signals and produce acoustic waves at the first frequency and the second frequency; and a non-linear material, coupled to the transducer, configured to generate a collimated beam with a frequency equal to the difference between the first frequency and the second frequency by a non-linear mixing process, wherein the non-linear material includes one or more of a mixture of liquids, a solid, a granular material, embedded microspheres, or an emulsion.

Nonuniform sampling theorems for random signals in the linear canonical transform domain

NASA Astrophysics Data System (ADS)

Shuiqing, Xu; Congmei, Jiang; Yi, Chai; Youqiang, Hu; Lei, Huang

2018-06-01

Nonuniform sampling can be encountered in various practical processes because of random events or poor timebase. The analysis and applications of the nonuniform sampling for deterministic signals related to the linear canonical transform (LCT) have been well considered and researched, but up to now no papers have been published regarding the various nonuniform sampling theorems for random signals related to the LCT. The aim of this article is to explore the nonuniform sampling and reconstruction of random signals associated with the LCT. First, some special nonuniform sampling models are briefly introduced. Second, based on these models, some reconstruction theorems for random signals from various nonuniform samples associated with the LCT have been derived. Finally, the simulation results are made to prove the accuracy of the sampling theorems. In addition, the latent real practices of the nonuniform sampling for random signals have been also discussed.

Detector signal correction method and system

DOEpatents

Carangelo, Robert M.; Duran, Andrew J.; Kudman, Irwin

1995-07-11

Corrective factors are applied so as to remove anomalous features from the signal generated by a photoconductive detector, and to thereby render the output signal highly linear with respect to the energy of incident, time-varying radiation. The corrective factors may be applied through the use of either digital electronic data processing means or analog circuitry, or through a combination of those effects.

Detector signal correction method and system

DOEpatents

Carangelo, R.M.; Duran, A.J.; Kudman, I.

1995-07-11

Corrective factors are applied so as to remove anomalous features from the signal generated by a photoconductive detector, and to thereby render the output signal highly linear with respect to the energy of incident, time-varying radiation. The corrective factors may be applied through the use of either digital electronic data processing means or analog circuitry, or through a combination of those effects. 5 figs.

A robust color signal processing with wide dynamic range WRGB CMOS image sensor

NASA Astrophysics Data System (ADS)

Kawada, Shun; Kuroda, Rihito; Sugawa, Shigetoshi

2011-01-01

We have developed a robust color reproduction methodology by a simple calculation with a new color matrix using the formerly developed wide dynamic range WRGB lateral overflow integration capacitor (LOFIC) CMOS image sensor. The image sensor was fabricated through a 0.18 μm CMOS technology and has a 45 degrees oblique pixel array, the 4.2 μm effective pixel pitch and the W pixels. A W pixel was formed by replacing one of the two G pixels in the Bayer RGB color filter. The W pixel has a high sensitivity through the visible light waveband. An emerald green and yellow (EGY) signal is generated from the difference between the W signal and the sum of RGB signals. This EGY signal mainly includes emerald green and yellow lights. These colors are difficult to be reproduced accurately by the conventional simple linear matrix because their wave lengths are in the valleys of the spectral sensitivity characteristics of the RGB pixels. A new linear matrix based on the EGY-RGB signal was developed. Using this simple matrix, a highly accurate color processing with a large margin to the sensitivity fluctuation and noise has been achieved.

Monitoring fetal heart rate during pregnancy: contributions from advanced signal processing and wearable technology.

PubMed

Signorini, Maria G; Fanelli, Andrea; Magenes, Giovanni

2014-01-01

Monitoring procedures are the basis to evaluate the clinical state of patients and to assess changes in their conditions, thus providing necessary interventions in time. Both these two objectives can be achieved by integrating technological development with methodological tools, thus allowing accurate classification and extraction of useful diagnostic information. The paper is focused on monitoring procedures applied to fetal heart rate variability (FHRV) signals, collected during pregnancy, in order to assess fetal well-being. The use of linear time and frequency techniques as well as the computation of non linear indices can contribute to enhancing the diagnostic power and reliability of fetal monitoring. The paper shows how advanced signal processing approaches can contribute to developing new diagnostic and classification indices. Their usefulness is evaluated by comparing two selected populations: normal fetuses and intra uterine growth restricted (IUGR) fetuses. Results show that the computation of different indices on FHRV signals, either linear and nonlinear, gives helpful indications to describe pathophysiological mechanisms involved in the cardiovascular and neural system controlling the fetal heart. As a further contribution, the paper briefly describes how the introduction of wearable systems for fetal ECG recording could provide new technological solutions improving the quality and usability of prenatal monitoring.

A UWB Radar Signal Processing Platform for Real-Time Human Respiratory Feature Extraction Based on Four-Segment Linear Waveform Model.

PubMed

Hsieh, Chi-Hsuan; Chiu, Yu-Fang; Shen, Yi-Hsiang; Chu, Ta-Shun; Huang, Yuan-Hao

2016-02-01

This paper presents an ultra-wideband (UWB) impulse-radio radar signal processing platform used to analyze human respiratory features. Conventional radar systems used in human detection only analyze human respiration rates or the response of a target. However, additional respiratory signal information is available that has not been explored using radar detection. The authors previously proposed a modified raised cosine waveform (MRCW) respiration model and an iterative correlation search algorithm that could acquire additional respiratory features such as the inspiration and expiration speeds, respiration intensity, and respiration holding ratio. To realize real-time respiratory feature extraction by using the proposed UWB signal processing platform, this paper proposes a new four-segment linear waveform (FSLW) respiration model. This model offers a superior fit to the measured respiration signal compared with the MRCW model and decreases the computational complexity of feature extraction. In addition, an early-terminated iterative correlation search algorithm is presented, substantially decreasing the computational complexity and yielding negligible performance degradation. These extracted features can be considered the compressed signals used to decrease the amount of data storage required for use in long-term medical monitoring systems and can also be used in clinical diagnosis. The proposed respiratory feature extraction algorithm was designed and implemented using the proposed UWB radar signal processing platform including a radar front-end chip and an FPGA chip. The proposed radar system can detect human respiration rates at 0.1 to 1 Hz and facilitates the real-time analysis of the respiratory features of each respiration period.

Signal Prediction With Input Identification

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan; Chen, Ya-Chin

1999-01-01

A novel coding technique is presented for signal prediction with applications including speech coding, system identification, and estimation of input excitation. The approach is based on the blind equalization method for speech signal processing in conjunction with the geometric subspace projection theory to formulate the basic prediction equation. The speech-coding problem is often divided into two parts, a linear prediction model and excitation input. The parameter coefficients of the linear predictor and the input excitation are solved simultaneously and recursively by a conventional recursive least-squares algorithm. The excitation input is computed by coding all possible outcomes into a binary codebook. The coefficients of the linear predictor and excitation, and the index of the codebook can then be used to represent the signal. In addition, a variable-frame concept is proposed to block the same excitation signal in sequence in order to reduce the storage size and increase the transmission rate. The results of this work can be easily extended to the problem of disturbance identification. The basic principles are outlined in this report and differences from other existing methods are discussed. Simulations are included to demonstrate the proposed method.

Advanced linear and nonlinear compensations for 16QAM SC-400G unrepeatered transmission system

NASA Astrophysics Data System (ADS)

Zhang, Junwen; Yu, Jianjun; Chien, Hung-Chang

2018-02-01

Digital signal processing (DSP) with both linear equalization and nonlinear compensations are studied in this paper for the single-carrier 400G system based on 65-GBaud 16-quadrature amplitude modulation (QAM) signals. The 16-QAM signals are generated and pre-processed with pre-equalization (Pre-EQ) and Look-up-Table (LUT) based pre-distortion (Pre-DT) at the transmitter (Tx)-side. The implementation principle of training-based equalization and pre-distortion are presented here in this paper with experimental studies. At the receiver (Rx)-side, fiber-nonlinearity compensation based on digital backward propagation (DBP) are also utilized to further improve the transmission performances. With joint LUT-based Pre-DT and DBP-based post-compensation to mitigate the opto-electronic components and fiber nonlinearity impairments, we demonstrate the unrepeatered transmission of 1.6Tb/s based on 4-lane 400G single-carrier PDM-16QAM over 205-km SSMF without distributed amplifier.

Off-Grid Direction of Arrival Estimation Based on Joint Spatial Sparsity for Distributed Sparse Linear Arrays

PubMed Central

Liang, Yujie; Ying, Rendong; Lu, Zhenqi; Liu, Peilin

2014-01-01

In the design phase of sensor arrays during array signal processing, the estimation performance and system cost are largely determined by array aperture size. In this article, we address the problem of joint direction-of-arrival (DOA) estimation with distributed sparse linear arrays (SLAs) and propose an off-grid synchronous approach based on distributed compressed sensing to obtain larger array aperture. We focus on the complex source distribution in the practical applications and classify the sources into common and innovation parts according to whether a signal of source can impinge on all the SLAs or a specific one. For each SLA, we construct a corresponding virtual uniform linear array (ULA) to create the relationship of random linear map between the signals respectively observed by these two arrays. The signal ensembles including the common/innovation sources for different SLAs are abstracted as a joint spatial sparsity model. And we use the minimization of concatenated atomic norm via semidefinite programming to solve the problem of joint DOA estimation. Joint calculation of the signals observed by all the SLAs exploits their redundancy caused by the common sources and decreases the requirement of array size. The numerical results illustrate the advantages of the proposed approach. PMID:25420150

A high resolution model of linear trend in mass variations from DMT-2: Added value of accounting for coloured noise in GRACE data

NASA Astrophysics Data System (ADS)

Farahani, Hassan H.; Ditmar, Pavel; Inácio, Pedro; Didova, Olga; Gunter, Brian; Klees, Roland; Guo, Xiang; Guo, Jing; Sun, Yu; Liu, Xianglin; Zhao, Qile; Riva, Riccardo

2017-01-01

We present a high resolution model of the linear trend in the Earth's mass variations based on DMT-2 (Delft Mass Transport model, release 2). DMT-2 was produced primarily from K-Band Ranging (KBR) data of the Gravity Recovery And Climate Experiment (GRACE). It comprises a time series of monthly solutions complete to spherical harmonic degree 120. A novel feature in its production was the accurate computation and incorporation of stochastic properties of coloured noise when processing KBR data. The unconstrained DMT-2 monthly solutions are used to estimate the linear trend together with a bias, as well as annual and semi-annual sinusoidal terms. The linear term is further processed with an anisotropic Wiener filter, which uses full noise and signal covariance matrices. Given the fact that noise in an unconstrained model of the trend is reduced substantially as compared to monthly solutions, the Wiener filter associated with the trend is much less aggressive compared to a Wiener filter applied to monthly solutions. Consequently, the trend estimate shows an enhanced spatial resolution. It allows signals in relatively small water bodies, such as Aral sea and Ladoga lake, to be detected. Over the ice sheets, it allows for a clear identification of signals associated with some outlet glaciers or their groups. We compare the obtained trend estimate with the ones from the CSR-RL05 model using (i) the same approach based on monthly noise covariance matrices and (ii) a commonly-used approach based on the DDK-filtered monthly solutions. We use satellite altimetry data as independent control data. The comparison demonstrates a high spatial resolution of the DMT-2 linear trend. We link this to the usage of high-accuracy monthly noise covariance matrices, which is due to an accurate computation and incorporation of coloured noise when processing KBR data. A preliminary comparison of the linear trend based on DMT-2 with that computed from GSFC_global_mascons_v01 reveals, among other, a high concentration of the signal along the coast for both models in areas like the ice sheets, Gulf of Alaska, and Iceland.

Data acquisition and processing system and method for investigating sub-surface features of a rock formation

DOEpatents

Vu, Cung Khac; Nihei, Kurt; Johnson, Paul A; Guyer, Robert; Ten Cate, James A; Le Bas, Pierre-Yves; Larmat, Carene S

2015-01-27

A system and a method includes generating a first signal at a first frequency; and a second signal at a second frequency. Respective sources are positioned within the borehole and controllable such that the signals intersect in an intersection volume outside the borehole. A receiver detects a difference signal returning to the borehole generated by a non-linear mixing process within the intersection volume, and records the detected signal and stores the detected signal in a storage device and records measurement parameters including a position of the first acoustic source, a position of the second acoustic source, a position of the receiver, elevation angle and azimuth angle of the first acoustic signal and elevation angle and azimuth angle of the second acoustic signal.

Effects of masker frequency and duration in forward masking: further evidence for the influence of peripheral nonlinearity.

PubMed

Oxenham, A J; Plack, C J

2000-12-01

Forward masking has often been thought of in terms of neural adaptation, with nonlinearities in the growth and decay of forward masking being accounted for by the nonlinearities inherent in adaptation. In contrast, this study presents further evidence for the hypothesis that forward masking can be described as a linear process, once peripheral, mechanical nonlinearities are taken into account. The first experiment compares the growth of masking for on- and off-frequency maskers. Signal thresholds were measured as a function of masker level for three masker-signal intervals of 0, 10, and 30 ms. The brief 4-kHz sinusoidal signal was masked by a 200-ms sinusoidal forward masker which had a frequency of either 2.4 kHz (off-frequency) or 4 kHz (on-frequency). As in previous studies, for the on-frequency condition, the slope of the function relating signal threshold to masker level became shallower as the delay between the masker and signal was increased. In contrast, the slopes for the off-frequency condition were independent of masker-signal delay and had a value of around unity, indicating linear growth of masking for all masker-signal delays. In the second experiment, a broadband Gaussian noise forward masker was used to mask a brief 6-kHz sinusoidal signal. The spectrum level of the masker was either 0 or 40 dB (re: 20 microPa). The gap between the masker and signal was either 0 or 20 ms. Signal thresholds were measured for masker durations from 5 to 200 ms. The effect of masker duration was found to depend more on signal level than on gap duration or masker level. Overall, the results support the idea that forward masking can be modeled as a linear process, preceded by a static nonlinearity resembling that found on the basilar membrane.

Spiked Models of Large Dimensional Random Matrices Applied to Wireless Communications and Array Signal Processing

DTIC Science & Technology

2013-12-14

population covariance matrix with application to array signal processing; and 5) a sample covariance matrix for which a CLT is studied on linear...Applications , (01 2012): 1150004. doi: Walid Hachem, Malika Kharouf, Jamal Najim, Jack W. Silverstein. A CLT FOR INFORMATION- THEORETIC STATISTICS...for Multi-source Power Estimation, (04 2010) Malika Kharouf, Jamal Najim, Jack W. Silverstein, Walid Hachem. A CLT FOR INFORMATION- THEORETIC

Chirp Scaling Algorithms for SAR Processing

NASA Technical Reports Server (NTRS)

Jin, M.; Cheng, T.; Chen, M.

1993-01-01

The chirp scaling SAR processing algorithm is both accurate and efficient. Successful implementation requires proper selection of the interval of output samples, which is a function of the chirp interval, signal sampling rate, and signal bandwidth. Analysis indicates that for both airborne and spaceborne SAR applications in the slant range domain a linear chirp scaling is sufficient. To perform nonlinear interpolation process such as to output ground range SAR images, one can use a nonlinear chirp scaling interpolator presented in this paper.

Digital signal processing and control and estimation theory -- Points of tangency, area of intersection, and parallel directions

NASA Technical Reports Server (NTRS)

Willsky, A. S.

1976-01-01

A number of current research directions in the fields of digital signal processing and modern control and estimation theory were studied. Topics such as stability theory, linear prediction and parameter identification, system analysis and implementation, two-dimensional filtering, decentralized control and estimation, image processing, and nonlinear system theory were examined in order to uncover some of the basic similarities and differences in the goals, techniques, and philosophy of the two disciplines. An extensive bibliography is included.

Six different roles for crossover inhibition in the retina: correcting the nonlinearities of synaptic transmission.

PubMed

Werblin, Frank S

2010-03-01

Early retinal studies categorized ganglion cell behavior as either linear or nonlinear and rectifying as represented by the familiar X- and Y-type ganglion cells in cat. Nonlinear behavior is in large part a consequence of the rectifying nonlinearities inherent in synaptic transmission. These nonlinear signals underlie many special functions in retinal processing, including motion detection, motion in motion, and local edge detection. But linear behavior is also required for some visual processing tasks. For these tasks, the inherently nonlinear signals are "linearized" by "crossover inhibition." Linearization utilizes a circuitry whereby nonlinear ON inhibition adds with nonlinear OFF excitation or ON excitation adds with OFF inhibition to generate a more linear postsynaptic voltage response. Crossover inhibition has now been measured in most bipolar, amacrine, and ganglion cells. Functionally crossover inhibition enhances edge detection, allows ganglion cells to recognize luminance-neutral patterns with their receptive fields, permits ganglion cells to distinguish contrast from luminance, and maintains a more constant conductance during the light response. In some cases, crossover extends the operating range of cone-driven OFF ganglion cells into the scotopic levels. Crossover inhibition is also found in neurons of the lateral geniculate nucleus and V1.

Comparison of laser Doppler and laser speckle contrast imaging using a concurrent processing system

NASA Astrophysics Data System (ADS)

Sun, Shen; Hayes-Gill, Barrie R.; He, Diwei; Zhu, Yiqun; Huynh, Nam T.; Morgan, Stephen P.

2016-08-01

Full field laser Doppler imaging (LDI) and single exposure laser speckle contrast imaging (LSCI) are directly compared using a novel instrument which can concurrently image blood flow using both LDI and LSCI signal processing. Incorporating a commercial CMOS camera chip and a field programmable gate array (FPGA) the flow images of LDI and the contrast maps of LSCI are simultaneously processed by utilizing the same detected optical signals. The comparison was carried out by imaging a rotating diffuser. LDI has a linear response to the velocity. In contrast, LSCI is exposure time dependent and does not provide a linear response in the presence of static speckle. It is also demonstrated that the relationship between LDI and LSCI can be related through a power law which depends on the exposure time of LSCI.

Optimal and adaptive methods of processing hydroacoustic signals (review)

NASA Astrophysics Data System (ADS)

Malyshkin, G. S.; Sidel'nikov, G. B.

2014-09-01

Different methods of optimal and adaptive processing of hydroacoustic signals for multipath propagation and scattering are considered. Advantages and drawbacks of the classical adaptive (Capon, MUSIC, and Johnson) algorithms and "fast" projection algorithms are analyzed for the case of multipath propagation and scattering of strong signals. The classical optimal approaches to detecting multipath signals are presented. A mechanism of controlled normalization of strong signals is proposed to automatically detect weak signals. The results of simulating the operation of different detection algorithms for a linear equidistant array under multipath propagation and scattering are presented. An automatic detector is analyzed, which is based on classical or fast projection algorithms, which estimates the background proceeding from median filtering or the method of bilateral spatial contrast.

Device and method for generating a beam of acoustic energy from a borehole, and applications thereof

DOEpatents

Vu, Cung Khac; Sinha, Dipen N.; Pantea, Cristian; Nihei, Kurt; Schmitt, Denis P.; Skelt, Christopher

2010-11-23

In some aspects of the invention, a device, positioned within a well bore, configured to generate and direct an acoustic beam into a rock formation around a borehole is disclosed. The device comprises a source configured to generate a first signal at a first frequency and a second signal at a second frequency; a transducer configured to receive the generated first and the second signals and produce acoustic waves at the first frequency and the second frequency; and a non-linear material, coupled to the transducer, configured to generate a collimated beam with a frequency equal to the difference between the first frequency and the second frequency by a non-linear mixing process, wherein the non-linear material includes one or more of a mixture of liquids, a solid, a granular material, embedded microspheres, or an emulsion.

Method and system for photoconductive detector signal correction

DOEpatents

Carangelo, Robert M.; Hamblen, David G.; Brouillette, Carl R.

1992-08-04

A corrective factor is applied so as to remove anomalous features from the signal generated by a photoconductive detector, and to thereby render the output signal highly linear with respect to the energy of incident, time-varying radiation. The corrective factor may be applied through the use of either digital electronic data processing means or analog circuitry, or through a combination of those effects.

Method and system for photoconductive detector signal correction

DOEpatents

Carangelo, R.M.; Hamblen, D.G.; Brouillette, C.R.

1992-08-04

A corrective factor is applied so as to remove anomalous features from the signal generated by a photoconductive detector, and to thereby render the output signal highly linear with respect to the energy of incident, time-varying radiation. The corrective factor may be applied through the use of either digital electronic data processing means or analog circuitry, or through a combination of those effects. 5 figs.

Linear prediction data extrapolation superresolution radar imaging

NASA Astrophysics Data System (ADS)

Zhu, Zhaoda; Ye, Zhenru; Wu, Xiaoqing

1993-05-01

Range resolution and cross-range resolution of range-doppler imaging radars are related to the effective bandwidth of transmitted signal and the angle through which the object rotates relatively to the radar line of sight (RLOS) during the coherent processing time, respectively. In this paper, linear prediction data extrapolation discrete Fourier transform (LPDEDFT) superresolution imaging method is investigated for the purpose of surpassing the limitation imposed by the conventional FFT range-doppler processing and improving the resolution capability of range-doppler imaging radar. The LPDEDFT superresolution imaging method, which is conceptually simple, consists of extrapolating observed data beyond the observation windows by means of linear prediction, and then performing the conventional IDFT of the extrapolated data. The live data of a metalized scale model B-52 aircraft mounted on a rotating platform in a microwave anechoic chamber and a flying Boeing-727 aircraft were processed. It is concluded that, compared to the conventional Fourier method, either higher resolution for the same effective bandwidth of transmitted signals and total rotation angle of the object or equal-quality images from smaller bandwidth and total angle may be obtained by LPDEDFT.

Establishing a conceptual framework for handoffs using communication theory.

PubMed

Mohorek, Matthew; Webb, Travis P

2015-01-01

A significant consequence of the 2003 Accreditation Council for Graduate Medical Education duty hour restrictions has been the dramatic increase in patient care handoffs. Ineffective handoffs have been identified as the third most common cause of medical error. However, research into health care handoffs lacks a unifying foundational structure. We sought to identify a conceptual framework that could be used to critically analyze handoffs. A scholarly review focusing on communication theory as a possible conceptual framework for handoffs was conducted. A PubMed search of published handoff research was also performed, and the literature was analyzed and matched to the most relevant theory for health care handoff models. The Shannon-Weaver Linear Model of Communication was identified as the most appropriate conceptual framework for health care handoffs. The Linear Model describes communication as a linear process. A source encodes a message into a signal, the signal is sent through a channel, and the signal is decoded back into a message at the destination, all in the presence of internal and external noise. The Linear Model identifies 3 separate instances in handoff communication where error occurs: the transmitter (message encoding), channel, and receiver (signal decoding). The Linear Model of Communication is a suitable conceptual framework for handoff research and provides a structured approach for describing handoff variables. We propose the Linear Model should be used as a foundation for further research into interventions to improve health care handoffs. Copyright © 2015 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Optical modulation techniques for analog signal processing and CMOS compatible electro-optic modulation

NASA Astrophysics Data System (ADS)

Gill, Douglas M.; Rasras, Mahmoud; Tu, Kun-Yii; Chen, Young-Kai; White, Alice E.; Patel, Sanjay S.; Carothers, Daniel; Pomerene, Andrew; Kamocsai, Robert; Beattie, James; Kopa, Anthony; Apsel, Alyssa; Beals, Mark; Mitchel, Jurgen; Liu, Jifeng; Kimerling, Lionel C.

2008-02-01

Integrating electronic and photonic functions onto a single silicon-based chip using techniques compatible with mass-production CMOS electronics will enable new design paradigms for existing system architectures and open new opportunities for electro-optic applications with the potential to dramatically change the management, cost, footprint, weight, and power consumption of today's communication systems. While broadband analog system applications represent a smaller volume market than that for digital data transmission, there are significant deployments of analog electro-optic systems for commercial and military applications. Broadband linear modulation is a critical building block in optical analog signal processing and also could have significant applications in digital communication systems. Recently, broadband electro-optic modulators on a silicon platform have been demonstrated based on the plasma dispersion effect. The use of the plasma dispersion effect within a CMOS compatible waveguide creates new challenges and opportunities for analog signal processing since the index and propagation loss change within the waveguide during modulation. We will review the current status of silicon-based electrooptic modulators and also linearization techniques for optical modulation.

Multidimensional biochemical information processing of dynamical patterns

NASA Astrophysics Data System (ADS)

Hasegawa, Yoshihiko

2018-02-01

Cells receive signaling molecules by receptors and relay information via sensory networks so that they can respond properly depending on the type of signal. Recent studies have shown that cells can extract multidimensional information from dynamical concentration patterns of signaling molecules. We herein study how biochemical systems can process multidimensional information embedded in dynamical patterns. We model the decoding networks by linear response functions, and optimize the functions with the calculus of variations to maximize the mutual information between patterns and output. We find that, when the noise intensity is lower, decoders with different linear response functions, i.e., distinct decoders, can extract much information. However, when the noise intensity is higher, distinct decoders do not provide the maximum amount of information. This indicates that, when transmitting information by dynamical patterns, embedding information in multiple patterns is not optimal when the noise intensity is very large. Furthermore, we explore the biochemical implementations of these decoders using control theory and demonstrate that these decoders can be implemented biochemically through the modification of cascade-type networks, which are prevalent in actual signaling pathways.

Multidimensional biochemical information processing of dynamical patterns.

PubMed

Hasegawa, Yoshihiko

2018-02-01

Cells receive signaling molecules by receptors and relay information via sensory networks so that they can respond properly depending on the type of signal. Recent studies have shown that cells can extract multidimensional information from dynamical concentration patterns of signaling molecules. We herein study how biochemical systems can process multidimensional information embedded in dynamical patterns. We model the decoding networks by linear response functions, and optimize the functions with the calculus of variations to maximize the mutual information between patterns and output. We find that, when the noise intensity is lower, decoders with different linear response functions, i.e., distinct decoders, can extract much information. However, when the noise intensity is higher, distinct decoders do not provide the maximum amount of information. This indicates that, when transmitting information by dynamical patterns, embedding information in multiple patterns is not optimal when the noise intensity is very large. Furthermore, we explore the biochemical implementations of these decoders using control theory and demonstrate that these decoders can be implemented biochemically through the modification of cascade-type networks, which are prevalent in actual signaling pathways.

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.

Comparison of digital signal-signal beat interference compensation techniques in direct-detection subcarrier modulation systems.

PubMed

Li, Zhe; Erkilinc, M Sezer; Galdino, Lidia; Shi, Kai; Thomsen, Benn C; Bayvel, Polina; Killey, Robert I

2016-12-12

Single-polarization direct-detection transceivers may offer advantages compared to digital coherent technology for some metro, back-haul, access and inter-data center applications since they offer low-cost and complexity solutions. However, a direct-detection receiver introduces nonlinearity upon photo detection, since it is a square-law device, which results in signal distortion due to signal-signal beat interference (SSBI). Consequently, it is desirable to develop effective and low-cost SSBI compensation techniques to improve the performance of such transceivers. In this paper, we compare the performance of a number of recently proposed digital signal processing-based SSBI compensation schemes, including the use of single- and two-stage linearization filters, an iterative linearization filter and a SSBI estimation and cancellation technique. Their performance is assessed experimentally using a 7 × 25 Gb/s wavelength division multiplexed (WDM) single-sideband 16-QAM Nyquist-subcarrier modulation system operating at a net information spectral density of 2.3 (b/s)/Hz.

Interpolation algorithm for asynchronous ADC-data

NASA Astrophysics Data System (ADS)

Bramburger, Stefan; Zinke, Benny; Killat, Dirk

2017-09-01

This paper presents a modified interpolation algorithm for signals with variable data rate from asynchronous ADCs. The Adaptive weights Conjugate gradient Toeplitz matrix (ACT) algorithm is extended to operate with a continuous data stream. An additional preprocessing of data with constant and linear sections and a weighted overlap of step-by-step into spectral domain transformed signals improve the reconstruction of the asycnhronous ADC signal. The interpolation method can be used if asynchronous ADC data is fed into synchronous digital signal processing.

Bypassing the Limits of Ll Regularization: Convex Sparse Signal Processing Using Non-Convex Regularization

NASA Astrophysics Data System (ADS)

Parekh, Ankit

Sparsity has become the basis of some important signal processing methods over the last ten years. Many signal processing problems (e.g., denoising, deconvolution, non-linear component analysis) can be expressed as inverse problems. Sparsity is invoked through the formulation of an inverse problem with suitably designed regularization terms. The regularization terms alone encode sparsity into the problem formulation. Often, the ℓ1 norm is used to induce sparsity, so much so that ℓ1 regularization is considered to be `modern least-squares'. The use of ℓ1 norm, as a sparsity-inducing regularizer, leads to a convex optimization problem, which has several benefits: the absence of extraneous local minima, well developed theory of globally convergent algorithms, even for large-scale problems. Convex regularization via the ℓ1 norm, however, tends to under-estimate the non-zero values of sparse signals. In order to estimate the non-zero values more accurately, non-convex regularization is often favored over convex regularization. However, non-convex regularization generally leads to non-convex optimization, which suffers from numerous issues: convergence may be guaranteed to only a stationary point, problem specific parameters may be difficult to set, and the solution is sensitive to the initialization of the algorithm. The first part of this thesis is aimed toward combining the benefits of non-convex regularization and convex optimization to estimate sparse signals more effectively. To this end, we propose to use parameterized non-convex regularizers with designated non-convexity and provide a range for the non-convex parameter so as to ensure that the objective function is strictly convex. By ensuring convexity of the objective function (sum of data-fidelity and non-convex regularizer), we can make use of a wide variety of convex optimization algorithms to obtain the unique global minimum reliably. The second part of this thesis proposes a non-linear signal decomposition technique for an important biomedical signal processing problem: the detection of sleep spindles and K-complexes in human sleep electroencephalography (EEG). We propose a non-linear model for the EEG consisting of three components: (1) a transient (sparse piecewise constant) component, (2) a low-frequency component, and (3) an oscillatory component. The oscillatory component admits a sparse time-frequency representation. Using a convex objective function, we propose a fast non-linear optimization algorithm to estimate the three components in the proposed signal model. The low-frequency and oscillatory components are then used to estimate the K-complexes and sleep spindles respectively. The proposed detection method is shown to outperform several state-of-the-art automated sleep spindles detection methods.

Optical measurement of the weak non-linearity in the eardrum vibration response to auditory stimuli

NASA Astrophysics Data System (ADS)

Aerts, Johan

The mammalian hearing organ consists of the external ear (auricle and ear canal) followed by the middle ear (eardrum and ossicles) and the inner ear (cochlea). Its function is to convert the incoming sound waves and convert them into nerve pulses which are processed in the final stage by the brain. The main task of the external and middle ear is to concentrate the incoming sound waves on a smaller surface to reduce the loss that would normally occur in transmission from air to inner ear fluid. In the past it has been shown that this is a linear process, thus without serious distortions, for sound waves going up to pressures of 130 dB SPL (˜90 Pa). However, at large pressure changes up to several kPa, the middle ear movement clearly shows non-linear behaviour. Thus, it is possible that some small non-linear distortions are also present in the middle ear vibration at lower sound pressures. In this thesis a sensitive measurement set-up is presented to detect this weak non-linear behaviour. Essentially, this set-up consists of a loud-speaker which excites the middle ear, and the resulting vibration is measured with an heterodyne vibrometer. The use of specially designed acoustic excitation signals (odd random phase multisines) enables the separation of the linear and non-linear response. The application of this technique on the middle ear demonstrates that there are already non-linear distortions present in the vibration of the middle ear at a sound pressure of 93 dB SPL. This non-linear component also grows strongly with increasing sound pressure. Knowledge of this non-linear component can contribute to the improvement of modern hearing aids, which operate at higher sound pressures where the non-linearities could distort the signal considerably. It is also important to know the contribution of middle ear non-linearity to otoacoustic emissions. This are non-linearities caused by the active feedback amplifier in the inner ear, and can be detected in the external and middle ear. These signals are used for diagnostic purposes, and therefore it is important to have an estimate the non-linear middle ear contribution to these emissions.

Optimal space communications techniques. [using digital and phase locked systems for signal processing

NASA Technical Reports Server (NTRS)

Schilling, D. L.

1974-01-01

Digital multiplication of two waveforms using delta modulation (DM) is discussed. It is shown that while conventional multiplication of two N bit words requires N2 complexity, multiplication using DM requires complexity which increases linearly with N. Bounds on the signal-to-quantization noise ratio (SNR) resulting from this multiplication are determined and compared with the SNR obtained using standard multiplication techniques. The phase locked loop (PLL) system, consisting of a phase detector, voltage controlled oscillator, and a linear loop filter, is discussed in terms of its design and system advantages. Areas requiring further research are identified.

Theoretical analysis of degradation mechanisms in the formation of morphogen gradients

NASA Astrophysics Data System (ADS)

Bozorgui, Behnaz; Teimouri, Hamid; Kolomeisky, Anatoly B.

2015-07-01

Fundamental biological processes of development of tissues and organs in multicellular organisms are governed by various signaling molecules, which are called morphogens. It is known that spatial and temporal variations in the concentration profiles of signaling molecules, which are frequently referred as morphogen gradients, lead to a cell differentiation via activating specific genes in a concentration-dependent manner. It is widely accepted that the establishment of the morphogen gradients involves multiple biochemical reactions and diffusion processes. One of the critical elements in the formation of morphogen gradients is a degradation of signaling molecules. We develop a new theoretical approach that provides a comprehensive description of the degradation mechanisms. It is based on the idea that the degradation works as an effective potential that drives the signaling molecules away from the source region. Utilizing the method of first-passage processes, the dynamics of the formation of morphogen gradients for various degradation mechanisms is explicitly evaluated. It is found that linear degradation processes lead to a dynamic behavior specified by times to form the morphogen gradients that depend linearly on the distance from the source. This is because the effective potential due to the degradation is quite strong. At the same time, nonlinear degradation mechanisms yield a quadratic scaling in the morphogen gradients formation times since the effective potentials are much weaker. Physical-chemical explanations of these phenomena are presented.

Sequence information signal processor for local and global string comparisons

DOEpatents

Peterson, John C.; Chow, Edward T.; Waterman, Michael S.; Hunkapillar, Timothy J.

1997-01-01

A sequence information signal processing integrated circuit chip designed to perform high speed calculation of a dynamic programming algorithm based upon the algorithm defined by Waterman and Smith. The signal processing chip of the present invention is designed to be a building block of a linear systolic array, the performance of which can be increased by connecting additional sequence information signal processing chips to the array. The chip provides a high speed, low cost linear array processor that can locate highly similar global sequences or segments thereof such as contiguous subsequences from two different DNA or protein sequences. The chip is implemented in a preferred embodiment using CMOS VLSI technology to provide the equivalent of about 400,000 transistors or 100,000 gates. Each chip provides 16 processing elements, and is designed to provide 16 bit, two's compliment operation for maximum score precision of between -32,768 and +32,767. It is designed to provide a comparison between sequences as long as 4,194,304 elements without external software and between sequences of unlimited numbers of elements with the aid of external software. Each sequence can be assigned different deletion and insertion weight functions. Each processor is provided with a similarity measure device which is independently variable. Thus, each processor can contribute to maximum value score calculation using a different similarity measure.

FPGA based hardware optimized implementation of signal processing system for LFM pulsed radar

NASA Astrophysics Data System (ADS)

Azim, Noor ul; Jun, Wang

2016-11-01

Signal processing is one of the main parts of any radar system. Different signal processing algorithms are used to extract information about different parameters like range, speed, direction etc, of a target in the field of radar communication. This paper presents LFM (Linear Frequency Modulation) pulsed radar signal processing algorithms which are used to improve target detection, range resolution and to estimate the speed of a target. Firstly, these algorithms are simulated in MATLAB to verify the concept and theory. After the conceptual verification in MATLAB, the simulation is converted into implementation on hardware using Xilinx FPGA. Chosen FPGA is Xilinx Virtex-6 (XC6LVX75T). For hardware implementation pipeline optimization is adopted and also other factors are considered for resources optimization in the process of implementation. Focusing algorithms in this work for improving target detection, range resolution and speed estimation are hardware optimized fast convolution processing based pulse compression and pulse Doppler processing.

Certification of windshear performance with RTCA class D radomes

NASA Technical Reports Server (NTRS)

Mathews, Bruce D.; Miller, Fran; Rittenhouse, Kirk; Barnett, Lee; Rowe, William

1994-01-01

Superposition testing of detection range performance forms a digital signal for input into a simulation of signal and data processing equipment and algorithms to be employed in a sensor system for advanced warning of hazardous windshear. For suitable pulse-Doppler radar, recording of the digital data at the input to the digital signal processor furnishes a realistic operational scenario and environmentally responsive clutter signal including all sidelobe clutter, ground moving target indications (GMTI), and large signal spurious due to mainbeam clutter and/or RFI respective of the urban airport clutter and aircraft scenarios (approach and landing antenna pointing). For linear radar system processes, a signal at the same point in the process from a hazard phenomena may be calculated from models of the scattering phenomena, for example, as represented in fine 3 dimensional reflectivity and velocity grid structures. Superposition testing furnishes a competing signal environment for detection and warning time performance confirmation of phenomena uncontrollable in a natural environment.

Effect of linear energy on the properties of an AL alloy in DPMIG welding

NASA Astrophysics Data System (ADS)

Liao, Tianfa; Jin, Li; Xue, Jiaxiang

2018-01-01

The effect of different linear energy parameters on the DPMIG welding performance of AA1060 aluminium alloy is studied in this paper. The stability of the welding process is verified with a Labview electrical signal acquisition system, and the microstructure and tensile properties of the welded joint are studied via optical microscopy, scanning electron microscopy and electrical tensile tests. The test results show that the welding process for the DPMIG methods stable and that the weld beads appear as scales. Tensile strength results indicate that, with increasing linear energy, the tensile strength first increases and then decreases. The tensile strength of the joint is maximized when the linear energy is 120.5 J / mm-1.

Direction of Radio Finding via MUSIC (Multiple Signal Classification) Algorithm for Hardware Design System

NASA Astrophysics Data System (ADS)

Zhang, Zheng

2017-10-01

Concept of radio direction finding systems, which use radio direction finding is based on digital signal processing algorithms. Thus, the radio direction finding system becomes capable to locate and track signals by the both. Performance of radio direction finding significantly depends on effectiveness of digital signal processing algorithms. The algorithm uses the Direction of Arrival (DOA) algorithms to estimate the number of incidents plane waves on the antenna array and their angle of incidence. This manuscript investigates implementation of the DOA algorithms (MUSIC) on the uniform linear array in the presence of white noise. The experiment results exhibit that MUSIC algorithm changed well with the radio direction.

Digital processing of array seismic recordings

USGS Publications Warehouse

Ryall, Alan; Birtill, John

1962-01-01

This technical letter contains a brief review of the operations which are involved in digital processing of array seismic recordings by the methods of velocity filtering, summation, cross-multiplication and integration, and by combinations of these operations (the "UK Method" and multiple correlation). Examples are presented of analyses by the several techniques on array recordings which were obtained by the U.S. Geological Survey during chemical and nuclear explosions in the western United States. Seismograms are synthesized using actual noise and Pn-signal recordings, such that the signal-to-noise ratio, onset time and velocity of the signal are predetermined for the synthetic record. These records are then analyzed by summation, cross-multiplication, multiple correlation and the UK technique, and the results are compared. For all of the examples presented, analysis by the non-linear techniques of multiple correlation and cross-multiplication of the traces on an array recording are preferred to analyses by the linear operations involved in summation and the UK Method.

Numerical investigation of multi-beam laser heterodyne measurement with ultra-precision for linear expansion coefficient of metal based on oscillating mirror modulation

NASA Astrophysics Data System (ADS)

Li, Yan-Chao; Wang, Chun-Hui; Qu, Yang; Gao, Long; Cong, Hai-Fang; Yang, Yan-Ling; Gao, Jie; Wang, Ao-You

2011-01-01

This paper proposes a novel method of multi-beam laser heterodyne measurement for metal linear expansion coefficient. Based on the Doppler effect and heterodyne technology, the information is loaded of length variation to the frequency difference of the multi-beam laser heterodyne signal by the frequency modulation of the oscillating mirror, this method can obtain many values of length variation caused by temperature variation after the multi-beam laser heterodyne signal demodulation simultaneously. Processing these values by weighted-average, it can obtain length variation accurately, and eventually obtain the value of linear expansion coefficient of metal by the calculation. This novel method is used to simulate measurement for linear expansion coefficient of metal rod under different temperatures by MATLAB, the obtained result shows that the relative measurement error of this method is just 0.4%.

Using bivariate signal analysis to characterize the epileptic focus: the benefit of surrogates.

PubMed

Andrzejak, R G; Chicharro, D; Lehnertz, K; Mormann, F

2011-04-01

The disease epilepsy is related to hypersynchronous activity of networks of neurons. While acute epileptic seizures are the most extreme manifestation of this hypersynchronous activity, an elevated level of interdependence of neuronal dynamics is thought to persist also during the seizure-free interval. In multichannel recordings from brain areas involved in the epileptic process, this interdependence can be reflected in an increased linear cross correlation but also in signal properties of higher order. Bivariate time series analysis comprises a variety of approaches, each with different degrees of sensitivity and specificity for interdependencies reflected in lower- or higher-order properties of pairs of simultaneously recorded signals. Here we investigate which approach is best suited to detect putatively elevated interdependence levels in signals recorded from brain areas involved in the epileptic process. For this purpose, we use the linear cross correlation that is sensitive to lower-order signatures of interdependence, a nonlinear interdependence measure that integrates both lower- and higher-order properties, and a surrogate-corrected nonlinear interdependence measure that aims to specifically characterize higher-order properties. We analyze intracranial electroencephalographic recordings of the seizure-free interval from 29 patients with an epileptic focus located in the medial temporal lobe. Our results show that all three approaches detect higher levels of interdependence for signals recorded from the brain hemisphere containing the epileptic focus as compared to signals recorded from the opposite hemisphere. For the linear cross correlation, however, these differences are not significant. For the nonlinear interdependence measure, results are significant but only of moderate accuracy with regard to the discriminative power for the focal and nonfocal hemispheres. The highest significance and accuracy is obtained for the surrogate-corrected nonlinear interdependence measure.

Using bivariate signal analysis to characterize the epileptic focus: The benefit of surrogates

NASA Astrophysics Data System (ADS)

Andrzejak, R. G.; Chicharro, D.; Lehnertz, K.; Mormann, F.

2011-04-01

The disease epilepsy is related to hypersynchronous activity of networks of neurons. While acute epileptic seizures are the most extreme manifestation of this hypersynchronous activity, an elevated level of interdependence of neuronal dynamics is thought to persist also during the seizure-free interval. In multichannel recordings from brain areas involved in the epileptic process, this interdependence can be reflected in an increased linear cross correlation but also in signal properties of higher order. Bivariate time series analysis comprises a variety of approaches, each with different degrees of sensitivity and specificity for interdependencies reflected in lower- or higher-order properties of pairs of simultaneously recorded signals. Here we investigate which approach is best suited to detect putatively elevated interdependence levels in signals recorded from brain areas involved in the epileptic process. For this purpose, we use the linear cross correlation that is sensitive to lower-order signatures of interdependence, a nonlinear interdependence measure that integrates both lower- and higher-order properties, and a surrogate-corrected nonlinear interdependence measure that aims to specifically characterize higher-order properties. We analyze intracranial electroencephalographic recordings of the seizure-free interval from 29 patients with an epileptic focus located in the medial temporal lobe. Our results show that all three approaches detect higher levels of interdependence for signals recorded from the brain hemisphere containing the epileptic focus as compared to signals recorded from the opposite hemisphere. For the linear cross correlation, however, these differences are not significant. For the nonlinear interdependence measure, results are significant but only of moderate accuracy with regard to the discriminative power for the focal and nonfocal hemispheres. The highest significance and accuracy is obtained for the surrogate-corrected nonlinear interdependence measure.

Modeling Signal-Noise Processes Supports Student Construction of a Hierarchical Image of Sample

ERIC Educational Resources Information Center

Lehrer, Richard

2017-01-01

Grade 6 (modal age 11) students invented and revised models of the variability generated as each measured the perimeter of a table in their classroom. To construct models, students represented variability as a linear composite of true measure (signal) and multiple sources of random error. Students revised models by developing sampling…

Intracortical multiplication of thalamocortical signals in mouse auditory cortex.

PubMed

Li, Ling-yun; Li, Ya-tang; Zhou, Mu; Tao, Huizhong W; Zhang, Li I

2013-09-01

Cortical processing of sensory information begins with the transformation of thalamically relayed signals. We optogenetically silenced intracortical circuits to isolate thalamic inputs to layer 4 neurons and found that intracortical excitation linearly amplified thalamocortical responses underlying frequency and direction selectivity, with spectral range and tuning preserved, and prolonged the response duration. This signal pre-amplification and prolongation enhanced the salience of thalamocortically relayed information and ensured its robust, faithful and more persistent representation.

Optically isolated signal coupler with linear response

DOEpatents

Kronberg, James W.

1994-01-01

An optocoupler for isolating electrical signals that translates an electrical input signal linearly to an electrical output signal. The optocoupler comprises a light emitter, a light receiver, and a light transmitting medium. The light emitter, preferably a blue, silicon carbide LED, is of the type that provides linear, electro-optical conversion of electrical signals within a narrow wavelength range. Correspondingly, the light receiver, which converts light signals to electrical signals and is preferably a cadmium sulfide photoconductor, is linearly responsive to light signals within substantially the same wavelength range as the blue LED.

A digital strategy for manometer dynamic enhancement. [for wind tunnel monitoring

NASA Technical Reports Server (NTRS)

Stoughton, J. W.

1978-01-01

Application of digital signal processing techniques to improve the non-linear dynamic characteristics of a sonar-type mercury manometer is described. The dynamic enhancement strategy quasi-linearizes the manometer characteristics and improves the effective bandwidth in the context of a wind-tunnel pressure regulation system. Model identification data and real-time hybrid simulation data demonstrate feasibility of approach.

Coherent detection and digital signal processing for fiber optic communications

NASA Astrophysics Data System (ADS)

Ip, Ezra

The drive towards higher spectral efficiency in optical fiber systems has generated renewed interest in coherent detection. We review different detection methods, including noncoherent, differentially coherent, and coherent detection, as well as hybrid detection methods. We compare the modulation methods that are enabled and their respective performances in a linear regime. An important system parameter is the number of degrees of freedom (DOF) utilized in transmission. Polarization-multiplexed quadrature-amplitude modulation maximizes spectral efficiency and power efficiency as it uses all four available DOF contained in the two field quadratures in the two polarizations. Dual-polarization homodyne or heterodyne downconversion are linear processes that can fully recover the received signal field in these four DOF. When downconverted signals are sampled at the Nyquist rate, compensation of transmission impairments can be performed using digital signal processing (DSP). Software based receivers benefit from the robustness of DSP, flexibility in design, and ease of adaptation to time-varying channels. Linear impairments, including chromatic dispersion (CD) and polarization-mode dispersion (PMD), can be compensated quasi-exactly using finite impulse response filters. In practical systems, sampling the received signal at 3/2 times the symbol rate is sufficient to enable an arbitrary amount of CD and PMD to be compensated for a sufficiently long equalizer whose tap length scales linearly with transmission distance. Depending on the transmitted constellation and the target bit error rate, the analog-to-digital converter (ADC) should have around 5 to 6 bits of resolution. Digital coherent receivers are naturally suited for the implementation of feedforward carrier recovery, which has superior linewidth tolerance than phase-locked loops, and does not suffer from feedback delay constraints. Differential bit encoding can be used to prevent catastrophic receiver failure due to cycle slips. In systems where nonlinear effects are concentrated mostly at fiber locations with small accumulated dispersion, nonlinear phase de-rotation is a low-complexity algorithm that can partially mitigate nonlinear effects. For systems with arbitrary dispersion maps, however, backpropagation is the only universal technique that can jointly compensate dispersion and fiber nonlinearity. Backpropagation requires solving the nonlinear Schrodinger equation at the receiver, and has high computational cost. Backpropagation is most effective when dispersion compensation fibers are removed, and when signal processing is performed at three times oversampling. Backpropagation can improve system performance and increase transmission distance. With anticipated advances in analog-to-digital converters and integrated circuit technology, DSP-based coherent receivers at bit rates up to 100 Gb/s should become practical in the near future.

Dynamic single sideband modulation for realizing parametric loudspeaker

NASA Astrophysics Data System (ADS)

Sakai, Shinichi; Kamakura, Tomoo

2008-06-01

A parametric loudspeaker, that presents remarkably narrow directivity compared with a conventional loudspeaker, is newly produced and examined. To work the loudspeaker optimally, we prototyped digitally a single sideband modulator based on the Weaver method and appropriate signal processing. The processing techniques are to change the carrier amplitude dynamically depending on the envelope of audio signals, and then to operate the square root or fourth root to the carrier amplitude for improving input-output acoustic linearity. The usefulness of the present modulation scheme has been verified experimentally.

Neural Networks Applied to Signal Processing

DTIC Science & Technology

1989-09-01

Distributed Processing, The MIT Press, Cambridge, MA, 1988. 3. Marvin Minsky and Seymour Papert, Perceptrons, The MIT Press, Cambridge, MA, 1969. 4...signum function, the linear function, and the sigmoid function. Initial research conducted in the 1950’s and 1960’s by Rosenblat, Minsky and others used

The iso-response method: measuring neuronal stimulus integration with closed-loop experiments

PubMed Central

Gollisch, Tim; Herz, Andreas V. M.

2012-01-01

Throughout the nervous system, neurons integrate high-dimensional input streams and transform them into an output of their own. This integration of incoming signals involves filtering processes and complex non-linear operations. The shapes of these filters and non-linearities determine the computational features of single neurons and their functional roles within larger networks. A detailed characterization of signal integration is thus a central ingredient to understanding information processing in neural circuits. Conventional methods for measuring single-neuron response properties, such as reverse correlation, however, are often limited by the implicit assumption that stimulus integration occurs in a linear fashion. Here, we review a conceptual and experimental alternative that is based on exploring the space of those sensory stimuli that result in the same neural output. As demonstrated by recent results in the auditory and visual system, such iso-response stimuli can be used to identify the non-linearities relevant for stimulus integration, disentangle consecutive neural processing steps, and determine their characteristics with unprecedented precision. Automated closed-loop experiments are crucial for this advance, allowing rapid search strategies for identifying iso-response stimuli during experiments. Prime targets for the method are feed-forward neural signaling chains in sensory systems, but the method has also been successfully applied to feedback systems. Depending on the specific question, “iso-response” may refer to a predefined firing rate, single-spike probability, first-spike latency, or other output measures. Examples from different studies show that substantial progress in understanding neural dynamics and coding can be achieved once rapid online data analysis and stimulus generation, adaptive sampling, and computational modeling are tightly integrated into experiments. PMID:23267315

A theoretical signal processing framework for linear diffusion MRI: Implications for parameter estimation and experiment design.

PubMed

Varadarajan, Divya; Haldar, Justin P

2017-11-01

The data measured in diffusion MRI can be modeled as the Fourier transform of the Ensemble Average Propagator (EAP), a probability distribution that summarizes the molecular diffusion behavior of the spins within each voxel. This Fourier relationship is potentially advantageous because of the extensive theory that has been developed to characterize the sampling requirements, accuracy, and stability of linear Fourier reconstruction methods. However, existing diffusion MRI data sampling and signal estimation methods have largely been developed and tuned without the benefit of such theory, instead relying on approximations, intuition, and extensive empirical evaluation. This paper aims to address this discrepancy by introducing a novel theoretical signal processing framework for diffusion MRI. The new framework can be used to characterize arbitrary linear diffusion estimation methods with arbitrary q-space sampling, and can be used to theoretically evaluate and compare the accuracy, resolution, and noise-resilience of different data acquisition and parameter estimation techniques. The framework is based on the EAP, and makes very limited modeling assumptions. As a result, the approach can even provide new insight into the behavior of model-based linear diffusion estimation methods in contexts where the modeling assumptions are inaccurate. The practical usefulness of the proposed framework is illustrated using both simulated and real diffusion MRI data in applications such as choosing between different parameter estimation methods and choosing between different q-space sampling schemes. Copyright © 2017 Elsevier Inc. All rights reserved.

Perception of the dynamic visual vertical during sinusoidal linear motion.

PubMed

Pomante, A; Selen, L P J; Medendorp, W P

2017-10-01

The vestibular system provides information for spatial orientation. However, this information is ambiguous: because the otoliths sense the gravitoinertial force, they cannot distinguish gravitational and inertial components. As a consequence, prolonged linear acceleration of the head can be interpreted as tilt, referred to as the somatogravic effect. Previous modeling work suggests that the brain disambiguates the otolith signal according to the rules of Bayesian inference, combining noisy canal cues with the a priori assumption that prolonged linear accelerations are unlikely. Within this modeling framework the noise of the vestibular signals affects the dynamic characteristics of the tilt percept during linear whole-body motion. To test this prediction, we devised a novel paradigm to psychometrically characterize the dynamic visual vertical-as a proxy for the tilt percept-during passive sinusoidal linear motion along the interaural axis (0.33 Hz motion frequency, 1.75 m/s 2 peak acceleration, 80 cm displacement). While subjects ( n =10) kept fixation on a central body-fixed light, a line was briefly flashed (5 ms) at different phases of the motion, the orientation of which had to be judged relative to gravity. Consistent with the model's prediction, subjects showed a phase-dependent modulation of the dynamic visual vertical, with a subject-specific phase shift with respect to the imposed acceleration signal. The magnitude of this modulation was smaller than predicted, suggesting a contribution of nonvestibular signals to the dynamic visual vertical. Despite their dampening effect, our findings may point to a link between the noise components in the vestibular system and the characteristics of dynamic visual vertical. NEW & NOTEWORTHY A fundamental question in neuroscience is how the brain processes vestibular signals to infer the orientation of the body and objects in space. We show that, under sinusoidal linear motion, systematic error patterns appear in the disambiguation of linear acceleration and spatial orientation. We discuss the dynamics of these illusory percepts in terms of a dynamic Bayesian model that combines uncertainty in the vestibular signals with priors based on the natural statistics of head motion. Copyright © 2017 the American Physiological Society.

How quantitative measures unravel design principles in multi-stage phosphorylation cascades.

PubMed

Frey, Simone; Millat, Thomas; Hohmann, Stefan; Wolkenhauer, Olaf

2008-09-07

We investigate design principles of linear multi-stage phosphorylation cascades by using quantitative measures for signaling time, signal duration and signal amplitude. We compare alternative pathway structures by varying the number of phosphorylations and the length of the cascade. We show that a model for a weakly activated pathway does not reflect the biological context well, unless it is restricted to certain parameter combinations. Focusing therefore on a more general model, we compare alternative structures with respect to a multivariate optimization criterion. We test the hypothesis that the structure of a linear multi-stage phosphorylation cascade is the result of an optimization process aiming for a fast response, defined by the minimum of the product of signaling time and signal duration. It is then shown that certain pathway structures minimize this criterion. Several popular models of MAPK cascades form the basis of our study. These models represent different levels of approximation, which we compare and discuss with respect to the quantitative measures.

Towards brain-activity-controlled information retrieval: Decoding image relevance from MEG signals.

PubMed

Kauppi, Jukka-Pekka; Kandemir, Melih; Saarinen, Veli-Matti; Hirvenkari, Lotta; Parkkonen, Lauri; Klami, Arto; Hari, Riitta; Kaski, Samuel

2015-05-15

We hypothesize that brain activity can be used to control future information retrieval systems. To this end, we conducted a feasibility study on predicting the relevance of visual objects from brain activity. We analyze both magnetoencephalographic (MEG) and gaze signals from nine subjects who were viewing image collages, a subset of which was relevant to a predetermined task. We report three findings: i) the relevance of an image a subject looks at can be decoded from MEG signals with performance significantly better than chance, ii) fusion of gaze-based and MEG-based classifiers significantly improves the prediction performance compared to using either signal alone, and iii) non-linear classification of the MEG signals using Gaussian process classifiers outperforms linear classification. These findings break new ground for building brain-activity-based interactive image retrieval systems, as well as for systems utilizing feedback both from brain activity and eye movements. Copyright © 2015 Elsevier Inc. All rights reserved.

FPGA-based real-time swept-source OCT systems for B-scan live-streaming or volumetric imaging

NASA Astrophysics Data System (ADS)

Bandi, Vinzenz; Goette, Josef; Jacomet, Marcel; von Niederhäusern, Tim; Bachmann, Adrian H.; Duelk, Marcus

2013-03-01

We have developed a Swept-Source Optical Coherence Tomography (Ss-OCT) system with high-speed, real-time signal processing on a commercially available Data-Acquisition (DAQ) board with a Field-Programmable Gate Array (FPGA). The Ss-OCT system simultaneously acquires OCT and k-clock reference signals at 500MS/s. From the k-clock signal of each A-scan we extract a remap vector for the k-space linearization of the OCT signal. The linear but oversampled interpolation is followed by a 2048-point FFT, additional auxiliary computations, and a data transfer to a host computer for real-time, live-streaming of B-scan or volumetric C-scan OCT visualization. We achieve a 100 kHz A-scan rate by parallelization of our hardware algorithms, which run on standard and affordable, commercially available DAQ boards. Our main development tool for signal analysis as well as for hardware synthesis is MATLAB® with add-on toolboxes and 3rd-party tools.

A unified formulation of dichroic signals using the Borrmann effect and twisted photon beams.

PubMed

Collins, Stephen P; Lovesey, Stephen W

2018-05-21

Dichroic X-ray signals derived from the Borrmann effect and a twisted photon beam with topological charge l = 1 are formulated with an effective wavevector. The unification applies for non-magnetic and magnetic materials. Electronic degrees of freedom associated with an ion are encapsulated in multipoles previously used to interpret conventional dichroism and Bragg diffraction enhanced by an atomic resonance. A dichroic signal exploiting the Borrmann effect with a linearly polarized beam presents charge-like multipoles that include a hexadecapole. A difference between dichroic signals obtained with a twisted beam carrying spin polarization (circular polarization) and opposite winding numbers presents charge-like atomic multipoles, whereas a twisted beam carrying linear polarization alone presents magnetic (time-odd) multipoles. Charge-like multipoles include a quadrupole, and magnetic multipoles include a dipole and an octupole. We discuss the practicalities and relative merits of spectroscopy exploiting the two remarkably closely-related processes. Signals using beams with topological charges l ≥ 2 present additional atomic multipoles.

Robust Nonlinear Causality Analysis of Nonstationary Multivariate Physiological Time Series.

PubMed

Schack, Tim; Muma, Michael; Feng, Mengling; Guan, Cuntai; Zoubir, Abdelhak M

2018-06-01

An important research area in biomedical signal processing is that of quantifying the relationship between simultaneously observed time series and to reveal interactions between the signals. Since biomedical signals are potentially nonstationary and the measurements may contain outliers and artifacts, we introduce a robust time-varying generalized partial directed coherence (rTV-gPDC) function. The proposed method, which is based on a robust estimator of the time-varying autoregressive (TVAR) parameters, is capable of revealing directed interactions between signals. By definition, the rTV-gPDC only displays the linear relationships between the signals. We therefore suggest to approximate the residuals of the TVAR process, which potentially carry information about the nonlinear causality by a piece-wise linear time-varying moving-average model. The performance of the proposed method is assessed via extensive simulations. To illustrate the method's applicability to real-world problems, it is applied to a neurophysiological study that involves intracranial pressure, arterial blood pressure, and brain tissue oxygenation level (PtiO2) measurements. The rTV-gPDC reveals causal patterns that are in accordance with expected cardiosudoral meachanisms and potentially provides new insights regarding traumatic brain injuries. The rTV-gPDC is not restricted to the above problem but can be useful in revealing interactions in a broad range of applications.

Maximally reliable Markov chains under energy constraints.

PubMed

Escola, Sean; Eisele, Michael; Miller, Kenneth; Paninski, Liam

2009-07-01

Signal-to-noise ratios in physical systems can be significantly degraded if the outputs of the systems are highly variable. Biological processes for which highly stereotyped signal generations are necessary features appear to have reduced their signal variabilities by employing multiple processing steps. To better understand why this multistep cascade structure might be desirable, we prove that the reliability of a signal generated by a multistate system with no memory (i.e., a Markov chain) is maximal if and only if the system topology is such that the process steps irreversibly through each state, with transition rates chosen such that an equal fraction of the total signal is generated in each state. Furthermore, our result indicates that by increasing the number of states, it is possible to arbitrarily increase the reliability of the system. In a physical system, however, an energy cost is associated with maintaining irreversible transitions, and this cost increases with the number of such transitions (i.e., the number of states). Thus, an infinite-length chain, which would be perfectly reliable, is infeasible. To model the effects of energy demands on the maximally reliable solution, we numerically optimize the topology under two distinct energy functions that penalize either irreversible transitions or incommunicability between states, respectively. In both cases, the solutions are essentially irreversible linear chains, but with upper bounds on the number of states set by the amount of available energy. We therefore conclude that a physical system for which signal reliability is important should employ a linear architecture, with the number of states (and thus the reliability) determined by the intrinsic energy constraints of the system.

Distinguishing graded and ultrasensitive signalling cascade kinetics by the shape of morphogen gradients in Drosophila.

PubMed

MacNamara, Shev; Baker, Ruth E; Maini, Philip K

2011-09-21

Recently, signalling gradients in cascades of two-state reaction-diffusion systems were described as a model for understanding key biochemical mechanisms that underlie development and differentiation processes in the Drosophila embryo. Diffusion-trapping at the exterior of the cell membrane triggers the mitogen-activated protein kinase (MAPK) cascade to relay an appropriate signal from the membrane to the inner part of the cytosol, whereupon another diffusion-trapping mechanism involving the nucleus reads out this signal to trigger appropriate changes in gene expression. Proposed mathematical models exhibit equilibrium distributions consistent with experimental measurements of key spatial gradients in these processes. A significant property of the formulation is that the signal is assumed to be relayed from one system to the next in a linear fashion. However, the MAPK cascade often exhibits nonlinear dose-response properties and the final remark of Berezhkovskii et al. (2009) is that this assumption remains an important property to be tested experimentally, perhaps via a new quantitative assay across multiple genetic backgrounds. In anticipation of the need to be able to sensibly interpret data from such experiments, here we provide a complementary analysis that recovers existing formulae as a special case but is also capable of handling nonlinear functional forms. Predictions of linear and nonlinear signal relays and, in particular, graded and ultrasensitive MAPK kinetics, are compared. Copyright © 2011 Elsevier Ltd. All rights reserved.

Dysphagia Screening: Contributions of Cervical Auscultation Signals and Modern Signal-Processing Techniques

PubMed Central

Dudik, Joshua M.; Coyle, James L.

2015-01-01

Cervical auscultation is the recording of sounds and vibrations caused by the human body from the throat during swallowing. While traditionally done by a trained clinician with a stethoscope, much work has been put towards developing more sensitive and clinically useful methods to characterize the data obtained with this technique. The eventual goal of the field is to improve the effectiveness of screening algorithms designed to predict the risk that swallowing disorders pose to individual patients’ health and safety. This paper provides an overview of these signal processing techniques and summarizes recent advances made with digital transducers in hopes of organizing the highly varied research on cervical auscultation. It investigates where on the body these transducers are placed in order to record a signal as well as the collection of analog and digital filtering techniques used to further improve the signal quality. It also presents the wide array of methods and features used to characterize these signals, ranging from simply counting the number of swallows that occur over a period of time to calculating various descriptive features in the time, frequency, and phase space domains. Finally, this paper presents the algorithms that have been used to classify this data into ‘normal’ and ‘abnormal’ categories. Both linear as well as non-linear techniques are presented in this regard. PMID:26213659

Integrated Sensing and Processing (ISP) Phase II: Demonstration and Evaluation for Distributed Sensor Netowrks and Missile Seeker Systems

DTIC Science & Technology

2007-02-28

Shah, D. Waagen, H. Schmitt, S. Bellofiore, A. Spanias, and D. Cochran, 32nd International Conference on Acoustics, Speech , and Signal Processing...Information Exploitation Office kNN k-Nearest Neighbor LEAN Laplacian Eigenmap Adaptive Neighbor LIP Linear Integer Programming ISP

Introduction to the Discrete Fourier Series Considering Both Mathematical and Engineering Aspects--A Linear Algebra Approach

ERIC Educational Resources Information Center

Kohaupt, Ludwig

2015-01-01

The discrete Fourier series is a valuable tool developed and used by mathematicians and engineers alike. One of the most prominent applications is signal processing. Usually, it is important that the signals be transmitted fast, for example, when transmitting images over large distances such as between the moon and the earth or when generating…

The Shock and Vibration Bulletin: Proceedings on the Symposium on ShocK and Vibration (52nd) Held in New Orleans, Louisiana on 26-28 October 1981. Part 3. Environmental Testing and Simulation, Flight Environments.

DTIC Science & Technology

1982-05-01

signal generation history can then be generated. These opera- processes generally consisted of recording tions work quite well electromagnetic ex...fninduerointe gualinicharactestics I PLOTTER MULTI CHANNEL TAPE RECORDER TEST ITEM 71T RESPONSE MOTIO ANALOG SIGNAL SHOCK CONDITIONING SPECTRUM ANALYZER...of TM to the EM. The exciter displacement producing a drive signal with excessive actua- drive signal is generated fron the linear sm tor stroke

Bayesian or Laplacien inference, entropy and information theory and information geometry in data and signal processing

NASA Astrophysics Data System (ADS)

Mohammad-Djafari, Ali

2015-01-01

The main object of this tutorial article is first to review the main inference tools using Bayesian approach, Entropy, Information theory and their corresponding geometries. This review is focused mainly on the ways these tools have been used in data, signal and image processing. After a short introduction of the different quantities related to the Bayes rule, the entropy and the Maximum Entropy Principle (MEP), relative entropy and the Kullback-Leibler divergence, Fisher information, we will study their use in different fields of data and signal processing such as: entropy in source separation, Fisher information in model order selection, different Maximum Entropy based methods in time series spectral estimation and finally, general linear inverse problems.

HCPCF-based in-line fiber Fabry-Perot refractometer and high sensitivity signal processing method

NASA Astrophysics Data System (ADS)

Liu, Xiaohui; Jiang, Mingshun; Sui, Qingmei; Geng, Xiangyi; Song, Furong

2017-12-01

An in-line fiber Fabry-Perot interferometer (FPI) based on the hollow-core photonic crystal fiber (HCPCF) for refractive index (RI) measurement is proposed in this paper. The FPI is formed by splicing both ends of a short section of the HCPCF to single mode fibers (SMFs) and cleaving the SMF pigtail to a proper length. The RI response of the sensor is analyzed theoretically and demonstrated experimentally. The results show that the FPI sensor has linear response to external RI and good repeatability. The sensitivity calculated from the maximum fringe contrast is -136 dB/RIU. A new spectrum differential integration (SDI) method for signal processing is also presented in this study. In this method, the RI is obtained from the integrated intensity of the absolute difference between the interference spectrum and its smoothed spectrum. The results show that the sensitivity obtained from the integrated intensity is about -1.34×105 dB/RIU. Compared with the maximum fringe contrast method, the new SDI method can provide the higher sensitivity, better linearity, improved reliability, and accuracy, and it's also convenient for automatic and fast signal processing in real-time monitoring of RI.

Discrete linear canonical transforms based on dilated Hermite functions.

PubMed

Pei, Soo-Chang; Lai, Yun-Chiu

2011-08-01

Linear canonical transform (LCT) is very useful and powerful in signal processing and optics. In this paper, discrete LCT (DLCT) is proposed to approximate LCT by utilizing the discrete dilated Hermite functions. The Wigner distribution function is also used to investigate DLCT performances in the time-frequency domain. Compared with the existing digital computation of LCT, our proposed DLCT possess additivity and reversibility properties with no oversampling involved. In addition, the length of input/output signals will not be changed before and after the DLCT transformations, which is consistent with the time-frequency area-preserving nature of LCT; meanwhile, the proposed DLCT has very good approximation of continuous LCT.

Characteristic W-ino signals in a linear collider from anomaly mediated supersymmetry breaking

NASA Astrophysics Data System (ADS)

Ghosh, Dilip Kumar; Kundu, Anirban; Roy, Probir; Roy, Sourov

2001-12-01

Though the minimal model of anomaly-mediated supersymmetry breaking has been significantly constrained by recent experimental and theoretical work, there are still allowed regions of the parameter space for moderate to large values of tan β. We show that these regions will be comprehensively probed in a s=1 TeV e+e- linear collider. Diagnostic signals to this end are studied by zeroing in on a unique and distinct feature of a large class of models in this genre: a neutral W-ino-like lightest supersymmetric particle closely degenerate in mass with a W-ino-like chargino. The pair production processes e+e--->e+/-Le-/+L, e+/-Re-/+R, e+/-Le-/+R, ν~νbar, χ~01χ~02, χ~02χ~02 are all considered at s=1 TeV corresponding to the proposed DESY TEV Energy Superconducting Linear Accelerator linear collider in two natural categories of mass ordering in the sparticle spectra. The signals analyzed comprise multiple combinations of fast charged leptons (any of which can act as the trigger) plus displaced vertices XD (any of which can be identified by a heavy ionizing track terminating in the detector) and/or associated soft pions with characteristic momentum distributions.

Statistical Signal Models and Algorithms for Image Analysis

DTIC Science & Technology

1984-10-25

In this report, two-dimensional stochastic linear models are used in developing algorithms for image analysis such as classification, segmentation, and object detection in images characterized by textured backgrounds. These models generate two-dimensional random processes as outputs to which statistical inference procedures can naturally be applied. A common thread throughout our algorithms is the interpretation of the inference procedures in terms of linear prediction

Intelligent measurement and compensation of linear motor force ripple: a projection-based learning approach in the presence of noise

NASA Astrophysics Data System (ADS)

Liu, Yang; Song, Fazhi; Yang, Xiaofeng; Dong, Yue; Tan, Jiubin

2018-06-01

Due to their structural simplicity, linear motors are increasingly receiving attention for use in high velocity and high precision applications. The force ripple, as a space-periodic disturbance, however, would deteriorate the achievable dynamic performance. Conventional force ripple measurement approaches are time-consuming and have high requirements on the experimental conditions. In this paper, a novel learning identification algorithm is proposed for force ripple intelligent measurement and compensation. Existing identification schemes always use all the error signals to update the parameters in the force ripple. However, the error induced by noise is non-effective for force ripple identification, and even deteriorates the identification process. In this paper only the most pertinent information in the error signal is utilized for force ripple identification. Firstly, the effective error signals caused by the reference trajectory and the force ripple are extracted by projecting the overall error signals onto a subspace spanned by the physical model of the linear motor as well as the sinusoidal model of the force ripple. The time delay in the linear motor is compensated in the basis functions. Then, a data-driven approach is proposed to design the learning gain. It balances the trade-off between convergence speed and robustness against noise. Simulation and experimental results validate the proposed method and confirm its effectiveness and superiority.

Least squares reconstruction of non-linear RF phase encoded MR data.

PubMed

Salajeghe, Somaie; Babyn, Paul; Sharp, Jonathan C; Sarty, Gordon E

2016-09-01

The numerical feasibility of reconstructing MRI signals generated by RF coils that produce B1 fields with a non-linearly varying spatial phase is explored. A global linear spatial phase variation of B1 is difficult to produce from current confined to RF coils. Here we use regularized least squares inversion, in place of the usual Fourier transform, to reconstruct signals generated in B1 fields with non-linear phase variation. RF encoded signals were simulated for three RF coil configurations: ideal linear, parallel conductors and, circular coil pairs. The simulated signals were reconstructed by Fourier transform and by regularized least squares. The Fourier reconstruction of simulated RF encoded signals from the parallel conductor coil set showed minor distortions over the reconstruction of signals from the ideal linear coil set but the Fourier reconstruction of signals from the circular coil set produced severe geometric distortion. Least squares inversion in all cases produced reconstruction errors comparable to the Fourier reconstruction of the simulated signal from the ideal linear coil set. MRI signals encoded in B1 fields with non-linearly varying spatial phase may be accurately reconstructed using regularized least squares thus pointing the way to the use of simple RF coil designs for RF encoded MRI. Crown Copyright © 2016. Published by Elsevier Inc. All rights reserved.

Achieving a Linear Dose Rate Response in Pulse-Mode Silicon Photodiode Scintillation Detectors Over a Wide Range of Excitations

NASA Astrophysics Data System (ADS)

Carroll, Lewis

2014-02-01

We are developing a new dose calibrator for nuclear pharmacies that can measure radioactivity in a vial or syringe without handling it directly or removing it from its transport shield “pig”. The calibrator's detector comprises twin opposing scintillating crystals coupled to Si photodiodes and current-amplifying trans-resistance amplifiers. Such a scheme is inherently linear with respect to dose rate over a wide range of radiation intensities, but accuracy at low activity levels may be impaired, beyond the effects of meager photon statistics, by baseline fluctuation and drift inevitably present in high-gain, current-mode photodiode amplifiers. The work described here is motivated by our desire to enhance accuracy at low excitations while maintaining linearity at high excitations. Thus, we are also evaluating a novel “pulse-mode” analog signal processing scheme that employs a linear threshold discriminator to virtually eliminate baseline fluctuation and drift. We will show the results of a side-by-side comparison of current-mode versus pulse-mode signal processing schemes, including perturbing factors affecting linearity and accuracy at very low and very high excitations. Bench testing over a wide range of excitations is done using a Poisson random pulse generator plus an LED light source to simulate excitations up to ˜106 detected counts per second without the need to handle and store large amounts of radioactive material.

CORDIC-based digital signal processing (DSP) element for adaptive signal processing

NASA Astrophysics Data System (ADS)

Bolstad, Gregory D.; Neeld, Kenneth B.

1995-04-01

The High Performance Adaptive Weight Computation (HAWC) processing element is a CORDIC based application specific DSP element that, when connected in a linear array, can perform extremely high throughput (100s of GFLOPS) matrix arithmetic operations on linear systems of equations in real time. In particular, it very efficiently performs the numerically intense computation of optimal least squares solutions for large, over-determined linear systems. Most techniques for computing solutions to these types of problems have used either a hard-wired, non-programmable systolic array approach, or more commonly, programmable DSP or microprocessor approaches. The custom logic methods can be efficient, but are generally inflexible. Approaches using multiple programmable generic DSP devices are very flexible, but suffer from poor efficiency and high computation latencies, primarily due to the large number of DSP devices that must be utilized to achieve the necessary arithmetic throughput. The HAWC processor is implemented as a highly optimized systolic array, yet retains some of the flexibility of a programmable data-flow system, allowing efficient implementation of algorithm variations. This provides flexible matrix processing capabilities that are one to three orders of magnitude less expensive and more dense than the current state of the art, and more importantly, allows a realizable solution to matrix processing problems that were previously considered impractical to physically implement. HAWC has direct applications in RADAR, SONAR, communications, and image processing, as well as in many other types of systems.

Dynamic decomposition of spatiotemporal neural signals

PubMed Central

2017-01-01

Neural signals are characterized by rich temporal and spatiotemporal dynamics that reflect the organization of cortical networks. Theoretical research has shown how neural networks can operate at different dynamic ranges that correspond to specific types of information processing. Here we present a data analysis framework that uses a linearized model of these dynamic states in order to decompose the measured neural signal into a series of components that capture both rhythmic and non-rhythmic neural activity. The method is based on stochastic differential equations and Gaussian process regression. Through computer simulations and analysis of magnetoencephalographic data, we demonstrate the efficacy of the method in identifying meaningful modulations of oscillatory signals corrupted by structured temporal and spatiotemporal noise. These results suggest that the method is particularly suitable for the analysis and interpretation of complex temporal and spatiotemporal neural signals. PMID:28558039

Generation and coherent detection of QPSK signal using a novel method of digital signal processing

NASA Astrophysics Data System (ADS)

Zhao, Yuan; Hu, Bingliang; He, Zhen-An; Xie, Wenjia; Gao, Xiaohui

2018-02-01

We demonstrate an optical quadrature phase-shift keying (QPSK) signal transmitter and an optical receiver for demodulating optical QPSK signal with homodyne detection and digital signal processing (DSP). DSP on the homodyne detection scheme is employed without locking the phase of the local oscillator (LO). In this paper, we present an extracting one-dimensional array of down-sampling method for reducing unwanted samples of constellation diagram measurement. Such a novel scheme embodies the following major advantages over the other conventional optical QPSK signal detection methods. First, this homodyne detection scheme does not need strict requirement on LO in comparison with linear optical sampling, such as having a flat spectral density and phase over the spectral support of the source under test. Second, the LabVIEW software is directly used for recovering the QPSK signal constellation without employing complex DSP circuit. Third, this scheme is applicable to multilevel modulation formats such as M-ary PSK and quadrature amplitude modulation (QAM) or higher speed signals by making minor changes.

Information Processing Capacity of Dynamical Systems

NASA Astrophysics Data System (ADS)

Dambre, Joni; Verstraeten, David; Schrauwen, Benjamin; Massar, Serge

2012-07-01

Many dynamical systems, both natural and artificial, are stimulated by time dependent external signals, somehow processing the information contained therein. We demonstrate how to quantify the different modes in which information can be processed by such systems and combine them to define the computational capacity of a dynamical system. This is bounded by the number of linearly independent state variables of the dynamical system, equaling it if the system obeys the fading memory condition. It can be interpreted as the total number of linearly independent functions of its stimuli the system can compute. Our theory combines concepts from machine learning (reservoir computing), system modeling, stochastic processes, and functional analysis. We illustrate our theory by numerical simulations for the logistic map, a recurrent neural network, and a two-dimensional reaction diffusion system, uncovering universal trade-offs between the non-linearity of the computation and the system's short-term memory.

Information Processing Capacity of Dynamical Systems

PubMed Central

Dambre, Joni; Verstraeten, David; Schrauwen, Benjamin; Massar, Serge

2012-01-01

Many dynamical systems, both natural and artificial, are stimulated by time dependent external signals, somehow processing the information contained therein. We demonstrate how to quantify the different modes in which information can be processed by such systems and combine them to define the computational capacity of a dynamical system. This is bounded by the number of linearly independent state variables of the dynamical system, equaling it if the system obeys the fading memory condition. It can be interpreted as the total number of linearly independent functions of its stimuli the system can compute. Our theory combines concepts from machine learning (reservoir computing), system modeling, stochastic processes, and functional analysis. We illustrate our theory by numerical simulations for the logistic map, a recurrent neural network, and a two-dimensional reaction diffusion system, uncovering universal trade-offs between the non-linearity of the computation and the system's short-term memory. PMID:22816038

A case of "order insensitivity"? Natural and artificial language processing in a man with primary progressive aphasia.

PubMed

Zimmerer, Vitor C; Varley, Rosemary A

2015-08-01

Processing of linear word order (linear configuration) is important for virtually all languages and essential to languages such as English which have little functional morphology. Damage to systems underpinning configurational processing may specifically affect word-order reliant sentence structures. We explore order processing in WR, a man with primary progressive aphasia (PPA). In a previous report, we showed how WR showed impaired processing of actives, which rely strongly on word order, but not passives where functional morphology signals thematic roles. Using the artificial grammar learning (AGL) paradigm, we examined WR's ability to process order in non-verbal, visual sequences and compared his profile to that of healthy controls, and aphasic participants with and without severe syntactic disorder. Results suggested that WR, like some other patients with severe syntactic impairment, was unable to detect linear configurational structure. The data are consistent with the notion that disruption of possibly domain-general linearization systems differentially affects processing of active and passive sentence structures. Further research is needed to test this account, and we suggest hypotheses for future studies. Copyright © 2015 Elsevier Ltd. All rights reserved.

Enhanced Multistatic Active Sonar via Innovative Signal Processing

DTIC Science & Technology

2015-09-30

3. DATES COVERED (From - To) Oct. 01, 2014-Sept. 30, 2015 4. TITLE AND SUBTITLE Enhanced Multistatic Active Sonar via Innovative Signal...active sonar (CAS) in the presence of strong direct blast is studied for the Doppler-tolerant linear frequency modulation waveform. A receiver design...beamformer variants is examined. 15. SUBJECT TERMS Pulsed active sonar (PAS), continuous active sonar (CAS), strong delay and Doppler-spread direct blast

Correction of Non-Linear Propagation Artifact in Contrast-Enhanced Ultrasound Imaging of Carotid Arteries: Methods and in Vitro Evaluation.

PubMed

Yildiz, Yesna O; Eckersley, Robert J; Senior, Roxy; Lim, Adrian K P; Cosgrove, David; Tang, Meng-Xing

2015-07-01

Non-linear propagation of ultrasound creates artifacts in contrast-enhanced ultrasound images that significantly affect both qualitative and quantitative assessments of tissue perfusion. This article describes the development and evaluation of a new algorithm to correct for this artifact. The correction is a post-processing method that estimates and removes non-linear artifact in the contrast-specific image using the simultaneously acquired B-mode image data. The method is evaluated on carotid artery flow phantoms with large and small vessels containing microbubbles of various concentrations at different acoustic pressures. The algorithm significantly reduces non-linear artifacts while maintaining the contrast signal from bubbles to increase the contrast-to-tissue ratio by up to 11 dB. Contrast signal from a small vessel 600 μm in diameter buried in tissue artifacts before correction was recovered after the correction. Copyright © 2015 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Use of Mueller and non-Mueller matrices to describe polarization properties of telescope-based polarimeters

NASA Astrophysics Data System (ADS)

Seagraves, P. H.; Elmore, David F.

1994-09-01

Systems using optical elements such as linear polarizers, retarders, and mirrors can be represented by Mueller matrices. Some polarimeters include elements with time-varying polarization properties, multiple light beams, light detectors, and signal processing equipment. Standard Mueller matrix forms describing time-varying retarders, and beam splitters are presented, as well as non-Mueller matrices which describe detection and signal processing. These matrices provide a compact and intuitive mathematical description of polarimeter response which can aid in the refining of instrument designs.

Video-signal improvement using comb filtering techniques.

NASA Technical Reports Server (NTRS)

Arndt, G. D.; Stuber, F. M.; Panneton, R. J.

1973-01-01

Significant improvement in the signal-to-noise performance of television signals has been obtained through the application of comb filtering techniques. This improvement is achieved by removing the inherent redundancy in the television signal through linear prediction and by utilizing the unique noise-rejection characteristics of the receiver comb filter. Theoretical and experimental results describe the signal-to-noise ratio and picture-quality improvement obtained through the use of baseband comb filters and the implementation of a comb network as the loop filter in a phase-lock-loop demodulator. Attention is given to the fact that noise becomes correlated when processed by the receiver comb filter.

Voltage mode electronically tunable full-wave rectifier

NASA Astrophysics Data System (ADS)

Petrović, Predrag B.; Vesković, Milan; Đukić, Slobodan

2017-01-01

The paper presents a new realization of bipolar full-wave rectifier of input sinusoidal signals, employing one MO-CCCII (multiple output current controlled current conveyor), a zero-crossing detector (ZCD), and one resistor connected to fixed potential. The circuit provides the operating frequency up to 10 MHz with increased linearity and precision in processing of input voltage signal, with a very low harmonic distortion. The errors related to the signal processing and errors bound were investigated and provided in the paper. The PSpice simulations are depicted and agree well with the theoretical anticipation. The maximum power consumption of the converter is approximately 2.83 mW, at ±1.2 V supply voltages.

Signal Restoration of Non-stationary Acoustic Signals in the Time Domain

NASA Technical Reports Server (NTRS)

Babkin, Alexander S.

1988-01-01

Signal restoration is a method of transforming a nonstationary signal acquired by a ground based microphone to an equivalent stationary signal. The benefit of the signal restoration is a simplification of the flight test requirements because it could dispense with the need to acquire acoustic data with another aircraft flying in concert with the rotorcraft. The data quality is also generally improved because the contamination of the signal by the propeller and wind noise is not present. The restoration methodology can also be combined with other data acquisition methods, such as a multiple linear microphone array for further improvement of the test results. The methodology and software are presented for performing the signal restoration in the time domain. The method has no restrictions on flight path geometry or flight regimes. Only requirement is that the aircraft spatial position be known relative to the microphone location and synchronized with the acoustic data. The restoration process assumes that the moving source radiates a stationary signal, which is then transformed into a nonstationary signal by various modulation processes. The restoration contains only the modulation due to the source motion.

A quasi-likelihood approach to non-negative matrix factorization

PubMed Central

Devarajan, Karthik; Cheung, Vincent C.K.

2017-01-01

A unified approach to non-negative matrix factorization based on the theory of generalized linear models is proposed. This approach embeds a variety of statistical models, including the exponential family, within a single theoretical framework and provides a unified view of such factorizations from the perspective of quasi-likelihood. Using this framework, a family of algorithms for handling signal-dependent noise is developed and its convergence proven using the Expectation-Maximization algorithm. In addition, a measure to evaluate the goodness-of-fit of the resulting factorization is described. The proposed methods allow modeling of non-linear effects via appropriate link functions and are illustrated using an application in biomedical signal processing. PMID:27348511

Optical amplifiers for coherent lidar

NASA Technical Reports Server (NTRS)

Fork, Richard

1996-01-01

We examine application of optical amplification to coherent lidar for the case of a weak return signal (a number of quanta of the return optical field close to unity). We consider the option that has been explored to date, namely, incorporation of an optical amplifier operated in a linear manner located after reception of the signal and immediately prior to heterodyning and photodetection. We also consider alternative strategies where the coherent interaction, the nonlinear processes, and the amplification are not necessarily constrained to occur in the manner investigated to date. We include the complications that occur because of mechanisms that occur at the level of a few, or one, quantum excitation. Two factors combine in the work to date that limit the value of the approach. These are: (1) the weak signal tends to require operation of the amplifier in the linear regime where the important advantages of nonlinear optical processing are not accessed, (2) the linear optical amplifier has a -3dB noise figure (SN(out)/SN(in)) that necessarily degrades the signal. Some improvement is gained because the gain provided by the optical amplifier can be used to overcome losses in the heterodyned process and photodetection. The result, however, is that introduction of an optical amplifier in a well optimized coherent lidar system results in, at best, a modest improvement in signal to noise. Some improvement may also be realized on incorporating more optical components in a coherent lidar system for purely practical reasons. For example, more compact, lighter weight, components, more robust alignment, or more rapid processing may be gained. We further find that there remain a number of potentially valuable, but unexplored options offered both by the rapidly expanding base of optical technology and the recent investigation of novel nonlinear coherent interference phenomena occurring at the single quantum excitation level. Key findings are: (1) insertion of linear optical amplifiers in well optimized conventional lidar systems offers modest improvements, at best, (2) the practical advantages of optical amplifiers, especially fiber amplifiers, such as ease of alignment, compactness, efficiency, lightweight, etc., warrant further investigation for coherent lidar, (3) the possibility of more fully optical lidar systems should be explored, (4) advantages gained by use of coherent interference of optical fields at the level of one, or a few, signal quanta should be explored, (5) amplification without inversion, population trapping, and use of electromagnetic induced transparency warrant investigation in connection with coherent lidar, (6) these new findings are probably more applicable to earth related NASA work, although applications to deep space should not be excluded, and (7) our own work in the Ultrafast Laboratory at UAH along some of the above lines of investigation, may be useful.

Acousto-optic RF signal acquisition system

NASA Astrophysics Data System (ADS)

Bloxham, Laurence H.

1990-09-01

This paper describes the architecture and performance of a prototype Acousto-Optic RF Signal Acquisition System designed to intercept, automatically identify, and track communication signals in the VHF band. The system covers 28.0 to 92.0 MHz with five manually selectable, dual conversion; 12.8 MHZ bandwidth front ends. An acousto-optic spectrum analyzer (AOSA) implemented using a tellurium dioxide (Te02) Bragg cell is used to channelize the 12.8 MHz pass band into 512 25 KHz channels. Polarization switching is used to suppress optical noise. Excellent isolation and dynamic range are achieved by using a linear array of 512 custom 40/50 micron fiber optic cables to collect the light at the focal plane of the AOSA and route the light to individual photodetectors. The photodetectors are operated in the photovoltaic mode to compress the greater than 60 dB input optical dynamic range into an easily processed electrical signal. The 512 signals are multiplexed and processed as a line in a video image by a customized digital image processing system. The image processor simultaneously analyzes the channelized signal data and produces a classical waterfall display.

DOA estimation of noncircular signals for coprime linear array via locally reduced-dimensional Capon

NASA Astrophysics Data System (ADS)

Zhai, Hui; Zhang, Xiaofei; Zheng, Wang

2018-05-01

We investigate the issue of direction of arrival (DOA) estimation of noncircular signals for coprime linear array (CLA). The noncircular property enhances the degree of freedom and improves angle estimation performance, but it leads to a more complex angle ambiguity problem. To eliminate ambiguity, we theoretically prove that the actual DOAs of noncircular signals can be uniquely estimated by finding the coincide results from the two decomposed subarrays based on the coprimeness. We propose a locally reduced-dimensional (RD) Capon algorithm for DOA estimation of noncircular signals for CLA. The RD processing is used in the proposed algorithm to avoid two dimensional (2D) spectral peak search, and coprimeness is employed to avoid the global spectral peak search. The proposed algorithm requires one-dimensional locally spectral peak search, and it has very low computational complexity. Furthermore, the proposed algorithm needs no prior knowledge of the number of sources. We also derive the Crámer-Rao bound of DOA estimation of noncircular signals in CLA. Numerical simulation results demonstrate the effectiveness and superiority of the algorithm.

Master-slave interferometry for parallel spectral domain interferometry sensing and versatile 3D optical coherence tomography.

PubMed

Podoleanu, Adrian Gh; Bradu, Adrian

2013-08-12

Conventional spectral domain interferometry (SDI) methods suffer from the need of data linearization. When applied to optical coherence tomography (OCT), conventional SDI methods are limited in their 3D capability, as they cannot deliver direct en-face cuts. Here we introduce a novel SDI method, which eliminates these disadvantages. We denote this method as Master - Slave Interferometry (MSI), because a signal is acquired by a slave interferometer for an optical path difference (OPD) value determined by a master interferometer. The MSI method radically changes the main building block of an SDI sensor and of a spectral domain OCT set-up. The serially provided signal in conventional technology is replaced by multiple signals, a signal for each OPD point in the object investigated. This opens novel avenues in parallel sensing and in parallelization of signal processing in 3D-OCT, with applications in high- resolution medical imaging and microscopy investigation of biosamples. Eliminating the need of linearization leads to lower cost OCT systems and opens potential avenues in increasing the speed of production of en-face OCT images in comparison with conventional SDI.

Seismoelectric data processing for surface surveys of shallow targets

USGS Publications Warehouse

Haines, S.S.; Guitton, A.; Biondi, B.

2007-01-01

The utility of the seismoelectric method relies on the development of methods to extract the signal of interest from background and source-generated coherent noise that may be several orders-of-magnitude stronger. We compare data processing approaches to develop a sequence of preprocessing and signal/noise separation and to quantify the noise level from which we can extract signal events. Our preferred sequence begins with the removal of power line harmonic noise and the use of frequency filters to minimize random and source-generated noise. Mapping to the linear Radon domain with an inverse process incorporating a sparseness constraint provides good separation of signal from noise, though it is ineffective on noise that shows the same dip as the signal. Similarly, the seismoelectric signal and noise do not separate cleanly in the Fourier domain, so f-k filtering can not remove all of the source-generated noise and it also disrupts signal amplitude patterns. We find that prediction-error filters provide the most effective method to separate signal and noise, while also preserving amplitude information, assuming that adequate pattern models can be determined for the signal and noise. These Radon-domain and prediction-error-filter methods successfully separate signal from <33 dB stronger noise in our test data. ?? 2007 Society of Exploration Geophysicists.

Design and evaluation of a parametric model for cardiac sounds.

PubMed

Ibarra-Hernández, Roilhi F; Alonso-Arévalo, Miguel A; Cruz-Gutiérrez, Alejandro; Licona-Chávez, Ana L; Villarreal-Reyes, Salvador

2017-10-01

Heart sound analysis plays an important role in the auscultative diagnosis process to detect the presence of cardiovascular diseases. In this paper we propose a novel parametric heart sound model that accurately represents normal and pathological cardiac audio signals, also known as phonocardiograms (PCG). The proposed model considers that the PCG signal is formed by the sum of two parts: one of them is deterministic and the other one is stochastic. The first part contains most of the acoustic energy. This part is modeled by the Matching Pursuit (MP) algorithm, which performs an analysis-synthesis procedure to represent the PCG signal as a linear combination of elementary waveforms. The second part, also called residual, is obtained after subtracting the deterministic signal from the original heart sound recording and can be accurately represented as an autoregressive process using the Linear Predictive Coding (LPC) technique. We evaluate the proposed heart sound model by performing subjective and objective tests using signals corresponding to different pathological cardiac sounds. The results of the objective evaluation show an average Percentage of Root-Mean-Square Difference of approximately 5% between the original heart sound and the reconstructed signal. For the subjective test we conducted a formal methodology for perceptual evaluation of audio quality with the assistance of medical experts. Statistical results of the subjective evaluation show that our model provides a highly accurate approximation of real heart sound signals. We are not aware of any previous heart sound model rigorously evaluated as our proposal. Copyright © 2017 Elsevier Ltd. All rights reserved.

Nonlinear processing of a multicomponent communication signal by combination-sensitive neurons in the anuran inferior colliculus.

PubMed

Lee, Norman; Schrode, Katrina M; Bee, Mark A

2017-09-01

Diverse animals communicate using multicomponent signals. How a receiver's central nervous system integrates multiple signal components remains largely unknown. We investigated how female green treefrogs (Hyla cinerea) integrate the multiple spectral components present in male advertisement calls. Typical calls have a bimodal spectrum consisting of formant-like low-frequency (~0.9 kHz) and high-frequency (~2.7 kHz) components that are transduced by different sensory organs in the inner ear. In behavioral experiments, only bimodal calls reliably elicited phonotaxis in no-choice tests, and they were selectively chosen over unimodal calls in two-alternative choice tests. Single neurons in the inferior colliculus of awake, passively listening subjects were classified as combination-insensitive units (27.9%) or combination-sensitive units (72.1%) based on patterns of relative responses to the same bimodal and unimodal calls. Combination-insensitive units responded similarly to the bimodal call and one or both unimodal calls. In contrast, combination-sensitive units exhibited both linear responses (i.e., linear summation) and, more commonly, nonlinear responses (e.g., facilitation, compressive summation, or suppression) to the spectral combination in the bimodal call. These results are consistent with the hypothesis that nonlinearities play potentially critical roles in spectral integration and in the neural processing of multicomponent communication signals.

Instrumentation and signal processing for the detection of heavy water using off axis-integrated cavity output spectroscopy technique

NASA Astrophysics Data System (ADS)

Gupta, A.; Singh, P. J.; Gaikwad, D. Y.; Udupa, D. V.; Topkar, A.; Sahoo, N. K.

2018-02-01

An experimental setup is developed for the trace level detection of heavy water (HDO) using the off axis-integrated cavity output spectroscopy technique. The absorption spectrum of water samples is recorded in the spectral range of 7190.7 cm-1-7191.5 cm-1 with the diode laser as the light source. From the recorded water vapor absorption spectrum, the heavy water concentration is determined from the HDO and water line. The effect of cavity gain nonlinearity with per pass absorption is studied. The signal processing and data fitting procedure is devised to obtain linear calibration curves by including nonlinear cavity gain effects into the calculation. Initial calibration of mirror reflectivity is performed by measurements on the natural water sample. The signal processing and data fitting method has been validated by the measurement of the HDO concentration in water samples over a wide range from 20 ppm to 2280 ppm showing a linear calibration curve. The average measurement time is about 30 s. The experimental technique presented in this paper could be applied for the development of a portable instrument for the fast measurement of water isotopic composition in heavy water plants and for the detection of heavy water leak in pressurized heavy water reactors.

Combining linear polarization spectroscopy and the Representative Layer Theory to measure the Beer-Lambert law absorbance of highly scattering materials.

PubMed

Gobrecht, Alexia; Bendoula, Ryad; Roger, Jean-Michel; Bellon-Maurel, Véronique

2015-01-01

Visible and Near Infrared (Vis-NIR) Spectroscopy is a powerful non destructive analytical method used to analyze major compounds in bulk materials and products and requiring no sample preparation. It is widely used in routine analysis and also in-line in industries, in-vivo with biomedical applications or in-field for agricultural and environmental applications. However, highly scattering samples subvert Beer-Lambert law's linear relationship between spectral absorbance and the concentrations. Instead of spectral pre-processing, which is commonly used by Vis-NIR spectroscopists to mitigate the scattering effect, we put forward an optical method, based on Polarized Light Spectroscopy to improve the absorbance signal measurement on highly scattering samples. This method selects part of the signal which is less impacted by scattering. The resulted signal is combined in the Absorption/Remission function defined in Dahm's Representative Layer Theory to compute an absorbance signal fulfilling Beer-Lambert's law, i.e. being linearly related to concentration of the chemicals composing the sample. The underpinning theories have been experimentally evaluated on scattering samples in liquid form and in powdered form. The method produced more accurate spectra and the Pearson's coefficient assessing the linearity between the absorbance spectra and the concentration of the added dye improved from 0.94 to 0.99 for liquid samples and 0.84-0.97 for powdered samples. Copyright © 2014 Elsevier B.V. All rights reserved.

Linear Space-Variant Image Restoration of Photon-Limited Images

DTIC Science & Technology

1978-03-01

levels of performance of the wavefront seisor. The parameter ^ represents the residual rms wavefront error ^measurement noise plus ♦ttting error...known to be optimum only when the signal and noise are uncorrelated stationary random processes «nd when the noise statistics are gaussian. In the...regime of photon-Iimited imaging, the noise is non-gaussian and signaI-dependent, and it is therefore reasonable to assume that tome form of linear

Machinery Bearing Fault Diagnosis Using Variational Mode Decomposition and Support Vector Machine as a Classifier

NASA Astrophysics Data System (ADS)

Rama Krishna, K.; Ramachandran, K. I.

2018-02-01

Crack propagation is a major cause of failure in rotating machines. It adversely affects the productivity, safety, and the machining quality. Hence, detecting the crack’s severity accurately is imperative for the predictive maintenance of such machines. Fault diagnosis is an established concept in identifying the faults, for observing the non-linear behaviour of the vibration signals at various operating conditions. In this work, we find the classification efficiencies for both original and the reconstructed vibrational signals. The reconstructed signals are obtained using Variational Mode Decomposition (VMD), by splitting the original signal into three intrinsic mode functional components and framing them accordingly. Feature extraction, feature selection and feature classification are the three phases in obtaining the classification efficiencies. All the statistical features from the original signals and reconstructed signals are found out in feature extraction process individually. A few statistical parameters are selected in feature selection process and are classified using the SVM classifier. The obtained results show the best parameters and appropriate kernel in SVM classifier for detecting the faults in bearings. Hence, we conclude that better results were obtained by VMD and SVM process over normal process using SVM. This is owing to denoising and filtering the raw vibrational signals.

An approach to predict Sudden Cardiac Death (SCD) using time domain and bispectrum features from HRV signal.

PubMed

Houshyarifar, Vahid; Chehel Amirani, Mehdi

2016-08-12

In this paper we present a method to predict Sudden Cardiac Arrest (SCA) with higher order spectral (HOS) and linear (Time) features extracted from heart rate variability (HRV) signal. Predicting the occurrence of SCA is important in order to avoid the probability of Sudden Cardiac Death (SCD). This work is a challenge to predict five minutes before SCA onset. The method consists of four steps: pre-processing, feature extraction, feature reduction, and classification. In the first step, the QRS complexes are detected from the electrocardiogram (ECG) signal and then the HRV signal is extracted. In second step, bispectrum features of HRV signal and time-domain features are obtained. Six features are extracted from bispectrum and two features from time-domain. In the next step, these features are reduced to one feature by the linear discriminant analysis (LDA) technique. Finally, KNN and support vector machine-based classifiers are used to classify the HRV signals. We used two database named, MIT/BIH Sudden Cardiac Death (SCD) Database and Physiobank Normal Sinus Rhythm (NSR). In this work we achieved prediction of SCD occurrence for six minutes before the SCA with the accuracy over 91%.

A new signal restoration method based on deconvolution of the Point Spread Function (PSF) for the Flat-Field Holographic Concave Grating UV spectrometer system

NASA Astrophysics Data System (ADS)

Dai, Honglin; Luo, Yongdao

2013-12-01

In recent years, with the development of the Flat-Field Holographic Concave Grating, they are adopted by all kinds of UV spectrometers. By means of single optical surface, the Flat-Field Holographic Concave Grating can implement dispersion and imaging that make the UV spectrometer system design quite compact. However, the calibration of the Flat-Field Holographic Concave Grating is very difficult. Various factors make its imaging quality difficult to be guaranteed. So we have to process the spectrum signal with signal restoration before using it. Guiding by the theory of signals and systems, and after a series of experiments, we found that our UV spectrometer system is a Linear Space- Variant System. It means that we have to measure PSF of every pixel of the system which contains thousands of pixels. Obviously, that's a large amount of calculation .For dealing with this problem, we proposes a novel signal restoration method. This method divides the system into several Linear Space-Invariant subsystems and then makes signal restoration with PSFs. Our experiments turn out that this method is effective and inexpensive.

System and method for linearly amplifying optical analog signals by backward Raman scattering

DOEpatents

Lin, Cheng-Heui

1988-01-01

A system for linearly amplifying an optical analog signal by backward stimulated Raman scattering comprises a laser source for generating a pump pulse; and an optic fiber having two opposed apertures, a first aperture for receiving the pump pulse and a second aperture for receiving the optical analog signal, wherein the optical analog signal is linearly amplified to an amplified optical analog signal.

System and method for linearly amplifying optical analog signals by backward Raman scattering

DOEpatents

Lin, Cheng-Heui

1988-07-05

A system for linearly amplifying an optical analog signal by backward stimulated Raman scattering comprises a laser source for generating a pump pulse; and an optic fiber having two opposed apertures, a first aperture for receiving the pump pulse and a second aperture for receiving the optical analog signal, wherein the optical analog signal is linearly amplified to an amplified optical analog signal.

Integrating a Linear Signal Model with Groundwater and Rainfall time-series on the Characteristic Identification of Groundwater Systems

NASA Astrophysics Data System (ADS)

Chen, Yu-Wen; Wang, Yetmen; Chang, Liang-Cheng

2017-04-01

Groundwater resources play a vital role on regional supply. To avoid irreversible environmental impact such as land subsidence, the characteristic identification of groundwater system is crucial before sustainable management of groundwater resource. This study proposes a signal process approach to identify the character of groundwater systems based on long-time hydrologic observations include groundwater level and rainfall. The study process contains two steps. First, a linear signal model (LSM) is constructed and calibrated to simulate the variation of underground hydrology based on the time series of groundwater levels and rainfall. The mass balance equation of the proposed LSM contains three major terms contain net rate of horizontal exchange, rate of rainfall recharge and rate of pumpage and four parameters are required to calibrate. Because reliable records of pumpage is rare, the time-variant groundwater amplitudes of daily frequency (P ) calculated by STFT are assumed as linear indicators of puamage instead of pumpage records. Time series obtained from 39 observation wells and 50 rainfall stations in and around the study area, Pintung Plain, are paired for model construction. Second, the well-calibrated parameters of the linear signal model can be used to interpret the characteristic of groundwater system. For example, the rainfall recharge coefficient (γ) means the transform ratio between rainfall intention and groundwater level raise. The area around the observation well with higher γ means that the saturated zone here is easily affected by rainfall events and the material of unsaturated zone might be gravel or coarse sand with high infiltration ratio. Considering the spatial distribution of γ, the values of γ decrease from the upstream to the downstream of major rivers and also are correlated to the spatial distribution of grain size of surface soil. Via the time-series of groundwater levels and rainfall, the well-calibrated parameters of LSM have ability to identify the characteristic of aquifer.

Coherent control of optical polarization effects in metamaterials

PubMed Central

Mousavi, Seyedmohammad A.; Plum, Eric; Shi, Jinhui; Zheludev, Nikolay I.

2015-01-01

Processing of photonic information usually relies on electronics. Aiming to avoid the conversion between photonic and electronic signals, modulation of light with light based on optical nonlinearity has become a major research field and coherent optical effects on the nanoscale are emerging as new means of handling and distributing signals. Here we demonstrate that in slabs of linear material of sub-wavelength thickness optical manifestations of birefringence and optical activity (linear and circular birefringence and dichroism) can be controlled by a wave coherent with the wave probing the polarization effect. We demonstrate this in proof-of-principle experiments for chiral and anisotropic microwave metamaterials, where we show that the large parameter space of polarization characteristics may be accessed at will by coherent control. Such control can be exerted at arbitrarily low intensities, thus arguably allowing for fast handling of electromagnetic signals without facing thermal management and energy challenges. PMID:25755071

Identification of significant intrinsic mode functions for the diagnosis of induction motor fault.

PubMed

Cho, Sangjin; Shahriar, Md Rifat; Chong, Uipil

2014-08-01

For the analysis of non-stationary signals generated by a non-linear process like fault of an induction motor, empirical mode decomposition (EMD) is the best choice as it decomposes the signal into its natural oscillatory modes known as intrinsic mode functions (IMFs). However, some of these oscillatory modes obtained from a fault signal are not significant as they do not bear any fault signature and can cause misclassification of the fault instance. To solve this issue, a novel IMF selection algorithm is proposed in this work.

The neural basis of attaining conscious awareness of sad mood.

PubMed

Smith, Ryan; Braden, B Blair; Chen, Kewei; Ponce, Francisco A; Lane, Richard D; Baxter, Leslie C

2015-09-01

The neural processes associated with becoming aware of sad mood are not fully understood. We examined the dynamic process of becoming aware of sad mood and recovery from sad mood. Sixteen healthy subjects underwent fMRI while participating in a sadness induction task designed to allow for variable mood induction times. Individualized regressors linearly modeled the time periods during the attainment of self-reported sad and baseline "neutral" mood states, and the validity of the linearity assumption was further tested using independent component analysis. During sadness induction the dorsomedial and ventrolateral prefrontal cortices, and anterior insula exhibited a linear increase in the blood oxygen level-dependent (BOLD) signal until subjects became aware of a sad mood and then a subsequent linear decrease as subjects transitioned from sadness back to the non-sadness baseline condition. These findings extend understanding of the neural basis of conscious emotional experience.

Linear signal noise summer accurately determines and controls S/N ratio

NASA Technical Reports Server (NTRS)

Sundry, J. L.

1966-01-01

Linear signal noise summer precisely controls the relative power levels of signal and noise, and mixes them linearly in accurately known ratios. The S/N ratio accuracy and stability are greatly improved by this technique and are attained simultaneously.

Signal processing for molecular and cellular biological physics: an emerging field.

PubMed

Little, Max A; Jones, Nick S

2013-02-13

Recent advances in our ability to watch the molecular and cellular processes of life in action--such as atomic force microscopy, optical tweezers and Forster fluorescence resonance energy transfer--raise challenges for digital signal processing (DSP) of the resulting experimental data. This article explores the unique properties of such biophysical time series that set them apart from other signals, such as the prevalence of abrupt jumps and steps, multi-modal distributions and autocorrelated noise. It exposes the problems with classical linear DSP algorithms applied to this kind of data, and describes new nonlinear and non-Gaussian algorithms that are able to extract information that is of direct relevance to biological physicists. It is argued that these new methods applied in this context typify the nascent field of biophysical DSP. Practical experimental examples are supplied.

Signal processing methods for in-situ creep specimen monitoring

NASA Astrophysics Data System (ADS)

Guers, Manton J.; Tittmann, Bernhard R.

2018-04-01

Previous work investigated using guided waves for monitoring creep deformation during accelerated life testing. The basic objective was to relate observed changes in the time-of-flight to changes in the environmental temperature and specimen gage length. The work presented in this paper investigated several signal processing strategies for possible application in the in-situ monitoring system. Signal processing methods for both group velocity (wave-packet envelope) and phase velocity (peak tracking) time-of-flight were considered. Although the Analytic Envelope found via the Hilbert transform is commonly applied for group velocity measurements, erratic behavior in the indicated time-of-flight was observed when this technique was applied to the in-situ data. The peak tracking strategies tested had generally linear trends, and tracking local minima in the raw waveform ultimately showed the most consistent results.

Signal processing for molecular and cellular biological physics: an emerging field

PubMed Central

Little, Max A.; Jones, Nick S.

2013-01-01

Recent advances in our ability to watch the molecular and cellular processes of life in action—such as atomic force microscopy, optical tweezers and Forster fluorescence resonance energy transfer—raise challenges for digital signal processing (DSP) of the resulting experimental data. This article explores the unique properties of such biophysical time series that set them apart from other signals, such as the prevalence of abrupt jumps and steps, multi-modal distributions and autocorrelated noise. It exposes the problems with classical linear DSP algorithms applied to this kind of data, and describes new nonlinear and non-Gaussian algorithms that are able to extract information that is of direct relevance to biological physicists. It is argued that these new methods applied in this context typify the nascent field of biophysical DSP. Practical experimental examples are supplied. PMID:23277603

Automated speech understanding: the next generation

NASA Astrophysics Data System (ADS)

Picone, J.; Ebel, W. J.; Deshmukh, N.

1995-04-01

Modern speech understanding systems merge interdisciplinary technologies from Signal Processing, Pattern Recognition, Natural Language, and Linguistics into a unified statistical framework. These systems, which have applications in a wide range of signal processing problems, represent a revolution in Digital Signal Processing (DSP). Once a field dominated by vector-oriented processors and linear algebra-based mathematics, the current generation of DSP-based systems rely on sophisticated statistical models implemented using a complex software paradigm. Such systems are now capable of understanding continuous speech input for vocabularies of several thousand words in operational environments. The current generation of deployed systems, based on small vocabularies of isolated words, will soon be replaced by a new technology offering natural language access to vast information resources such as the Internet, and provide completely automated voice interfaces for mundane tasks such as travel planning and directory assistance.

Canal–Otolith Interactions and Detection Thresholds of Linear and Angular Components During Curved-Path Self-Motion

PubMed Central

MacNeilage, Paul R.; Turner, Amanda H.

2010-01-01

Gravitational signals arising from the otolith organs and vertical plane rotational signals arising from the semicircular canals interact extensively for accurate estimation of tilt and inertial acceleration. Here we used a classical signal detection paradigm to examine perceptual interactions between otolith and horizontal semicircular canal signals during simultaneous rotation and translation on a curved path. In a rotation detection experiment, blindfolded subjects were asked to detect the presence of angular motion in blocks where half of the trials were pure nasooccipital translation and half were simultaneous translation and yaw rotation (curved-path motion). In separate, translation detection experiments, subjects were also asked to detect either the presence or the absence of nasooccipital linear motion in blocks, in which half of the trials were pure yaw rotation and half were curved path. Rotation thresholds increased slightly, but not significantly, with concurrent linear velocity magnitude. Yaw rotation detection threshold, averaged across all conditions, was 1.45 ± 0.81°/s (3.49 ± 1.95°/s2). Translation thresholds, on the other hand, increased significantly with increasing magnitude of concurrent angular velocity. Absolute nasooccipital translation detection threshold, averaged across all conditions, was 2.93 ± 2.10 cm/s (7.07 ± 5.05 cm/s2). These findings suggest that conscious perception might not have independent access to separate estimates of linear and angular movement parameters during curved-path motion. Estimates of linear (and perhaps angular) components might instead rely on integrated information from canals and otoliths. Such interaction may underlie previously reported perceptual errors during curved-path motion and may originate from mechanisms that are specialized for tilt-translation processing during vertical plane rotation. PMID:20554843

Linear excitation and detection in Fourier transform ion cyclotron resonance mass spectrometry

NASA Astrophysics Data System (ADS)

Grosshans, Peter B.; Chen, Ruidan; Limbach, Patrick A.; Marshall, Alan G.

1994-11-01

We present the first Fourier transform ion cyclotron resonance (FT-ICR) ion trap designed to produce both a linear spatial variation of the excitation electric potential field and a linear response of the detection circuit to the motion of the confined ions. With this trap, the magnitude of the detected signal at a given ion cyclotron frequency varies linearly with both the number of ions of given mass-to-charge ratio and also with the magnitude-mode excitation signal at the ion cyclotron orbital frequency; the proportionality constant is mass independent. Interestingly, this linearization may be achieved with any ion trap geometry. The excitation/detection design consists of an array of capacitively coupled electrodes which provide a voltage-divider network that produces a nearly spatially homogeneous excitation electric field throughout the linearized trap; resistive coupling to the electrodes isolates the a.c. excitation (or detection) circuit from the d.c. (trapping) potential. The design is based on analytical expressions for the potential associated with each electrode, from which we are able to compute the deviation from linearity for a trap with a finite number of elements. Based on direct experimental comparisons to an unmodified cubic trap, the linearized trap demonstrates the following performance advantages at the cost of some additional mechanical complexity: (a) signal response linearly proportional to excitation electric field amplitude; (b) vastly reduced axial excitation/ejection for significantly improved ion relative abundance accuracy; (c) elimination of harmonics and sidebands of the fundamental frequencies of ion motion. As a result, FT-ICR mass spectra are now more reproducible. Moreover, the linearized trap should facilitate the characterization of other fundamental aspects of ion behavior in an ICR ion trap, e.g. effects of space charge, non-quadrupolar electrostatic trapping field, etc. Furthermore, this novel design should improve significantly the precision of ion relative abundance and mass accuracy measurements, while removing spectral artifacts of the detection process. We discuss future modifications that linearize the spatial variation of the electrostatic trapping electric field as well, thereby completing the linearization of the entire FT-ICR mass spectrometric techniques. Suggested FT-ICR mass spectrometric applications for the linearized trap are discussed.

Photonics-based real-time ultra-high-range-resolution radar with broadband signal generation and processing.

PubMed

Zhang, Fangzheng; Guo, Qingshui; Pan, Shilong

2017-10-23

Real-time and high-resolution target detection is highly desirable in modern radar applications. Electronic techniques have encountered grave difficulties in the development of such radars, which strictly rely on a large instantaneous bandwidth. In this article, a photonics-based real-time high-range-resolution radar is proposed with optical generation and processing of broadband linear frequency modulation (LFM) signals. A broadband LFM signal is generated in the transmitter by photonic frequency quadrupling, and the received echo is de-chirped to a low frequency signal by photonic frequency mixing. The system can operate at a high frequency and a large bandwidth while enabling real-time processing by low-speed analog-to-digital conversion and digital signal processing. A conceptual radar is established. Real-time processing of an 8-GHz LFM signal is achieved with a sampling rate of 500 MSa/s. Accurate distance measurement is implemented with a maximum error of 4 mm within a range of ~3.5 meters. Detection of two targets is demonstrated with a range-resolution as high as 1.875 cm. We believe the proposed radar architecture is a reliable solution to overcome the limitations of current radar on operation bandwidth and processing speed, and it is hopefully to be used in future radars for real-time and high-resolution target detection and imaging.

Transient high frequency signal estimation: A model-based processing approach

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

Barnes, F.L.

1985-03-22

By utilizing the superposition property of linear systems a method of estimating the incident signal from reflective nondispersive data is developed. One of the basic merits of this approach is that, the reflections were removed by direct application of a Weiner type estimation algorithm, after the appropriate input was synthesized. The structure of the nondispersive signal model is well documented, and thus its' credence is established. The model is stated and more effort is devoted to practical methods of estimating the model parameters. Though a general approach was developed for obtaining the reflection weights, a simpler approach was employed here,more » since a fairly good reflection model is available. The technique essentially consists of calculating ratios of the autocorrelation function at lag zero and that lag where the incident and first reflection coincide. We initially performed our processing procedure on a measurement of a single signal. Multiple application of the processing procedure was required when we applied the reflection removal technique on a measurement containing information from the interaction of two physical phenomena. All processing was performed using SIG, an interactive signal processing package. One of the many consequences of using SIG was that repetitive operations were, for the most part, automated. A custom menu was designed to perform the deconvolution process.« less

Digital signal processing algorithms for automatic voice recognition

NASA Technical Reports Server (NTRS)

Botros, Nazeih M.

1987-01-01

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

A silicon avalanche photodiode detector circuit for Nd:YAG laser scattering

NASA Astrophysics Data System (ADS)

Hsieh, C.-L.; Haskovec, J.; Carlstrom, T. N.; Deboo, J. C.; Greenfield, C. M.; Snider, R. T.; Trost, P.

1990-06-01

A silicon avalanche photodiode with an internal gain of about 50 to 100 is used in a temperature controlled environment to measure the Nd:YAG laser Thomson scattered spectrum in the wavelength range from 700 to 1150 nm. A charge sensitive preamplifier was developed for minimizing the noise contribution from the detector electronics. Signal levels as low as 20 photoelectrons (S/N = 1) can be detected. Measurements show that both the signal and the variance of the signal vary linearly with the input light level over the range of interest, indicating Poisson statistics. The signal is processed using a 100 ns delay line and a differential amplifier which subtracts the low frequency background light component. The background signal is amplified with a computer controlled variable gain amplifier and is used for an estimate of the measurement error, calibration, and Z sub eff measurements of the plasma. The signal processing was analyzed using a theoretical model to aid the system design and establish the procedure for data error analysis.

Silicon avalanche photodiode detector circuit for Nd:YAG laser scattering

NASA Astrophysics Data System (ADS)

Hsieh, C. L.; Haskovec, J.; Carlstrom, T. N.; DeBoo, J. C.; Greenfield, C. M.; Snider, R. T.; Trost, P.

1990-10-01

A silicon avalanche photodiode with an internal gain of about 50 to 100 is used in a temperature-controlled environment to measure the Nd:YAG laser Thomson scattered spectrum in the wavelength range from 700 to 1150 nm. A charge-sensitive preamplifier has been developed for minimizing the noise contribution from the detector electronics. Signal levels as low as 20 photoelectrons (S/N=1) can be detected. Measurements show that both the signal and the variance of the signal vary linearly with the input light level over the range of interest, indicating Poisson statistics. The signal is processed using a 100 ns delay line and a differential amplifier which subtracts the low-frequency background light component. The background signal is amplified with a computer-controlled variable gain amplifier and is used for an estimate of the measurement error, calibration, and Zeff measurements of the plasma. The signal processing has been analyzed using a theoretical model to aid the system design and establish the procedure for data error analysis.

High-Speed Edge-Detecting Line Scan Smart Camera

NASA Technical Reports Server (NTRS)

Prokop, Norman F.

2012-01-01

A high-speed edge-detecting line scan smart camera was developed. The camera is designed to operate as a component in a NASA Glenn Research Center developed inlet shock detection system. The inlet shock is detected by projecting a laser sheet through the airflow. The shock within the airflow is the densest part and refracts the laser sheet the most in its vicinity, leaving a dark spot or shadowgraph. These spots show up as a dip or negative peak within the pixel intensity profile of an image of the projected laser sheet. The smart camera acquires and processes in real-time the linear image containing the shock shadowgraph and outputting the shock location. Previously a high-speed camera and personal computer would perform the image capture and processing to determine the shock location. This innovation consists of a linear image sensor, analog signal processing circuit, and a digital circuit that provides a numerical digital output of the shock or negative edge location. The smart camera is capable of capturing and processing linear images at over 1,000 frames per second. The edges are identified as numeric pixel values within the linear array of pixels, and the edge location information can be sent out from the circuit in a variety of ways, such as by using a microcontroller and onboard or external digital interface to include serial data such as RS-232/485, USB, Ethernet, or CAN BUS; parallel digital data; or an analog signal. The smart camera system can be integrated into a small package with a relatively small number of parts, reducing size and increasing reliability over the previous imaging system..

Dual-range linearized transimpedance amplifier system

DOEpatents

Wessendorf, Kurt O.

2010-11-02

A transimpedance amplifier system is disclosed which simultaneously generates a low-gain output signal and a high-gain output signal from an input current signal using a single transimpedance amplifier having two different feedback loops with different amplification factors to generate two different output voltage signals. One of the feedback loops includes a resistor, and the other feedback loop includes another resistor in series with one or more diodes. The transimpedance amplifier system includes a signal linearizer to linearize one or both of the low- and high-gain output signals by scaling and adding the two output voltage signals from the transimpedance amplifier. The signal linearizer can be formed either as an analog device using one or two summing amplifiers, or alternately can be formed as a digital device using two analog-to-digital converters and a digital signal processor (e.g. a microprocessor or a computer).

Design and Parametric Study of the Magnetic Sensor for Position Detection in Linear Motor Based on Nonlinear Parametric Model Order Reduction

PubMed Central

Paul, Sarbajit; Chang, Junghwan

2017-01-01

This paper presents a design approach for a magnetic sensor module to detect mover position using the proper orthogonal decomposition-dynamic mode decomposition (POD-DMD)-based nonlinear parametric model order reduction (PMOR). The parameterization of the sensor module is achieved by using the multipolar moment matching method. Several geometric variables of the sensor module are considered while developing the parametric study. The operation of the sensor module is based on the principle of the airgap flux density distribution detection by the Hall Effect IC. Therefore, the design objective is to achieve a peak flux density (PFD) greater than 0.1 T and total harmonic distortion (THD) less than 3%. To fulfill the constraint conditions, the specifications for the sensor module is achieved by using POD-DMD based reduced model. The POD-DMD based reduced model provides a platform to analyze the high number of design models very fast, with less computational burden. Finally, with the final specifications, the experimental prototype is designed and tested. Two different modes, 90° and 120° modes respectively are used to obtain the position information of the linear motor mover. The position information thus obtained are compared with that of the linear scale data, used as a reference signal. The position information obtained using the 120° mode has a standard deviation of 0.10 mm from the reference linear scale signal, whereas the 90° mode position signal shows a deviation of 0.23 mm from the reference. The deviation in the output arises due to the mechanical tolerances introduced into the specification during the manufacturing process. This provides a scope for coupling the reliability based design optimization in the design process as a future extension. PMID:28671580

Design and Parametric Study of the Magnetic Sensor for Position Detection in Linear Motor Based on Nonlinear Parametric model order reduction.

PubMed

Paul, Sarbajit; Chang, Junghwan

2017-07-01

This paper presents a design approach for a magnetic sensor module to detect mover position using the proper orthogonal decomposition-dynamic mode decomposition (POD-DMD)-based nonlinear parametric model order reduction (PMOR). The parameterization of the sensor module is achieved by using the multipolar moment matching method. Several geometric variables of the sensor module are considered while developing the parametric study. The operation of the sensor module is based on the principle of the airgap flux density distribution detection by the Hall Effect IC. Therefore, the design objective is to achieve a peak flux density (PFD) greater than 0.1 T and total harmonic distortion (THD) less than 3%. To fulfill the constraint conditions, the specifications for the sensor module is achieved by using POD-DMD based reduced model. The POD-DMD based reduced model provides a platform to analyze the high number of design models very fast, with less computational burden. Finally, with the final specifications, the experimental prototype is designed and tested. Two different modes, 90° and 120° modes respectively are used to obtain the position information of the linear motor mover. The position information thus obtained are compared with that of the linear scale data, used as a reference signal. The position information obtained using the 120° mode has a standard deviation of 0.10 mm from the reference linear scale signal, whereas the 90° mode position signal shows a deviation of 0.23 mm from the reference. The deviation in the output arises due to the mechanical tolerances introduced into the specification during the manufacturing process. This provides a scope for coupling the reliability based design optimization in the design process as a future extension.

Non-linear Analysis of Scalp EEG by Using Bispectra: The Effect of the Reference Choice

PubMed Central

Chella, Federico; D'Andrea, Antea; Basti, Alessio; Pizzella, Vittorio; Marzetti, Laura

2017-01-01

Bispectral analysis is a signal processing technique that makes it possible to capture the non-linear and non-Gaussian properties of the EEG signals. It has found various applications in EEG research and clinical practice, including the assessment of anesthetic depth, the identification of epileptic seizures, and more recently, the evaluation of non-linear cross-frequency brain functional connectivity. However, the validity and reliability of the indices drawn from bispectral analysis of EEG signals are potentially biased by the use of a non-neutral EEG reference. The present study aims at investigating the effects of the reference choice on the analysis of the non-linear features of EEG signals through bicoherence, as well as on the estimation of cross-frequency EEG connectivity through two different non-linear measures, i.e., the cross-bicoherence and the antisymmetric cross-bicoherence. To this end, four commonly used reference schemes were considered: the vertex electrode (Cz), the digitally linked mastoids, the average reference, and the Reference Electrode Standardization Technique (REST). The reference effects were assessed both in simulations and in a real EEG experiment. The simulations allowed to investigated: (i) the effects of the electrode density on the performance of the above references in the estimation of bispectral measures; and (ii) the effects of the head model accuracy in the performance of the REST. For real data, the EEG signals recorded from 10 subjects during eyes open resting state were examined, and the distortions induced by the reference choice in the patterns of alpha-beta bicoherence, cross-bicoherence, and antisymmetric cross-bicoherence were assessed. The results showed significant differences in the findings depending on the chosen reference, with the REST providing superior performance than all the other references in approximating the ideal neutral reference. In conclusion, this study highlights the importance of considering the effects of the reference choice in the interpretation and comparison of the results of bispectral analysis of scalp EEG. PMID:28559790

Subspace Signal Processing in Structured Noise

DTIC Science & Technology

1990-12-01

1.7 Motivation for the Model ....... ........................... 8 1.8 E x am p les...S). We do not require that H be orthogonal to S. * 1.7 Motivation for the Model The linear model is quite versatile in terms of the types of signals...cross terms zero, we choose . = (SHs)- mS~u’ (3.69) This implies that = Ps4 , (3.70) and S t s (3.71) : = Ps . RPs -. The last step is to maximize

Adaptive learning in complex reproducing kernel Hilbert spaces employing Wirtinger's subgradients.

PubMed

Bouboulis, Pantelis; Slavakis, Konstantinos; Theodoridis, Sergios

2012-03-01

This paper presents a wide framework for non-linear online supervised learning tasks in the context of complex valued signal processing. The (complex) input data are mapped into a complex reproducing kernel Hilbert space (RKHS), where the learning phase is taking place. Both pure complex kernels and real kernels (via the complexification trick) can be employed. Moreover, any convex, continuous and not necessarily differentiable function can be used to measure the loss between the output of the specific system and the desired response. The only requirement is the subgradient of the adopted loss function to be available in an analytic form. In order to derive analytically the subgradients, the principles of the (recently developed) Wirtinger's calculus in complex RKHS are exploited. Furthermore, both linear and widely linear (in RKHS) estimation filters are considered. To cope with the problem of increasing memory requirements, which is present in almost all online schemes in RKHS, the sparsification scheme, based on projection onto closed balls, has been adopted. We demonstrate the effectiveness of the proposed framework in a non-linear channel identification task, a non-linear channel equalization problem and a quadrature phase shift keying equalization scheme, using both circular and non circular synthetic signal sources.

Linear-phase delay filters for ultra-low-power signal processing in neural recording implants.

PubMed

Gosselin, Benoit; Sawan, Mohamad; Kerherve, Eric

2010-06-01

We present the design and implementation of linear-phase delay filters for ultra-low-power signal processing in neural recording implants. We use these filters as low-distortion delay elements along with an automatic biopotential detector to perform integral waveform extraction and efficient power management. The presented delay elements are realized employing continuous-time OTA-C filters featuring 9th-order equiripple transfer functions with constant group delay. Such analog delay enables processing neural waveforms with reduced overhead compared to a digital delay since it does not requires sampling and digitization. It uses an allpass transfer function for achieving wider constant-delay bandwidth than all-pole does. Two filters realizations are compared for implementing the delay element: the Cascaded structure and the Inverse follow-the-leader feedback filter. Their respective strengths and drawbacks are assessed by modeling parasitics and non-idealities of OTAs, and by transistor-level simulations. A budget of 200 nA is used in both filters. Experimental measurements with the chosen filter topology are presented and discussed.

Acoustic methods to monitor sliver linear density and yarn strength

DOEpatents

Sheen, Shuh-Haw; Chien, Hual-Te; Raptis, Apostolos C.

1997-01-01

Methods and apparatus are provided for monitoring sliver and yarn characteristics. Transverse waves are generated relative to the sliver or yarn. At least one acoustic sensor is in contact with the sliver or yarn for detecting waves coupled to the sliver or yarn and for generating a signal. The generated signal is processed to identify the predefined characteristics including sliver or yarn linear density. The transverse waves can be generated with a high-powered acoustic transmitter spaced relative to the sliver or yarn with large amplitude pulses having a central frequency in a range between 20 KHz and 40 KHz applied to the transmitter. The transverse waves can be generated by mechanically agitating the sliver or yarn with a tapping member.

Solution for the nonuniformity correction of infrared focal plane arrays.

PubMed

Zhou, Huixin; Liu, Shangqian; Lai, Rui; Wang, Dabao; Cheng, Yubao

2005-05-20

Based on the S-curve model of the detector response of infrared focal plan arrays (IRFPAs), an improved two-point correction algorithm is presented. The algorithm first transforms the nonlinear image data into linear data and then uses the normal two-point algorithm to correct the linear data. The algorithm can effectively overcome the influence of nonlinearity of the detector's response, and it enlarges the correction precision and the dynamic range of the response. A real-time imaging-signal-processing system for IRFPAs that is based on a digital signal processor and field-programmable gate arrays is also presented. The nonuniformity correction capability of the presented solution is validated by experimental imaging procedures of a 128 x 128 pixel IRFPA camera prototype.

Music preferences with hearing aids: effects of signal properties, compression settings, and listener characteristics.

PubMed

Croghan, Naomi B H; Arehart, Kathryn H; Kates, James M

2014-01-01

Current knowledge of how to design and fit hearing aids to optimize music listening is limited. Many hearing-aid users listen to recorded music, which often undergoes compression limiting (CL) in the music industry. Therefore, hearing-aid users may experience twofold effects of compression when listening to recorded music: music-industry CL and hearing-aid wide dynamic-range compression (WDRC). The goal of this study was to examine the roles of input-signal properties, hearing-aid processing, and individual variability in the perception of recorded music, with a focus on the effects of dynamic-range compression. A group of 18 experienced hearing-aid users made paired-comparison preference judgments for classical and rock music samples using simulated hearing aids. Music samples were either unprocessed before hearing-aid input or had different levels of music-industry CL. Hearing-aid conditions included linear gain and individually fitted WDRC. Combinations of four WDRC parameters were included: fast release time (50 msec), slow release time (1,000 msec), three channels, and 18 channels. Listeners also completed several psychophysical tasks. Acoustic analyses showed that CL and WDRC reduced temporal envelope contrasts, changed amplitude distributions across the acoustic spectrum, and smoothed the peaks of the modulation spectrum. Listener judgments revealed that fast WDRC was least preferred for both genres of music. For classical music, linear processing and slow WDRC were equally preferred, and the main effect of number of channels was not significant. For rock music, linear processing was preferred over slow WDRC, and three channels were preferred to 18 channels. Heavy CL was least preferred for classical music, but the amount of CL did not change the patterns of WDRC preferences for either genre. Auditory filter bandwidth as estimated from psychophysical tuning curves was associated with variability in listeners' preferences for classical music. Fast, multichannel WDRC often leads to poor music quality, whereas linear processing or slow WDRC are generally preferred. Furthermore, the effect of WDRC is more important for music preferences than music-industry CL applied to signals before the hearing-aid input stage. Variability in hearing-aid users' perceptions of music quality may be partially explained by frequency resolution abilities.

Extended observability of linear time-invariant systems under recurrent loss of output data

NASA Technical Reports Server (NTRS)

Luck, Rogelio; Ray, Asok; Halevi, Yoram

1989-01-01

Recurrent loss of sensor data in integrated control systems of an advanced aircraft may occur under different operating conditions that include detected frame errors and queue saturation in computer networks, and bad data suppression in signal processing. This paper presents an extension of the concept of observability based on a set of randomly selected nonconsecutive outputs in finite-dimensional, linear, time-invariant systems. Conditions for testing extended observability have been established.

Noncoherent parallel optical processor for discrete two-dimensional linear transformations.

PubMed

Glaser, I

1980-10-01

We describe a parallel optical processor, based on a lenslet array, that provides general linear two-dimensional transformations using noncoherent light. Such a processor could become useful in image- and signal-processing applications in which the throughput requirements cannot be adequately satisfied by state-of-the-art digital processors. Experimental results that illustrate the feasibility of the processor by demonstrating its use in parallel optical computation of the two-dimensional Walsh-Hadamard transformation are presented.

Space-Time Adaptive Processing for Airborne Radar

DTIC Science & Technology

1994-12-13

horizontal plane Uniform linear antenna array (possibly columns of a planar array) Identical element patterns 13 14 15 9 7 7,33 7 7 Target Model ...Parameters for Example Scenario 31 3 Assumptions Made for Radar System and Signal Model 52 4 Platform and Interference Scenario for Baseline Scenario. 61 5...pulses, is addressed first. Fully adaptive STAP requires the solution to a system of linear equations of size MN, where N is the number of array

Otolith-Canal Convergence In Vestibular Nuclei Neurons

NASA Technical Reports Server (NTRS)

Dickman, J. David; Si, Xiao-Hong

2002-01-01

The current final report covers the period from June 1, 1999 to May 31, 2002. The primary objective of the investigation was to determine how information regarding head movements and head position relative to gravity is received and processed by central vestibular nuclei neurons in the brainstem. Specialized receptors in the vestibular labyrinths of the inner ear function to detect angular and linear accelerations of the head, with receptors located in the semicircular canals transducing rotational head movements and receptors located in the otolith organs transducing changes in head position relative to gravity or linear accelerations of the head. The information from these different receptors is then transmitted to central vestibular nuclei neurons which process the input signals, then project the appropriate output information to the eye, head, and body musculature motor neurons to control compensatory reflexes. Although a number of studies have reported on the responsiveness of vestibular nuclei neurons, it has not yet been possible to determine precisely how these cells combine the information from the different angular and linear acceleration receptors into a correct neural output signal. In the present project, rotational and linear motion stimuli were separately delivered while recording responses from vestibular nuclei neurons that were characterized according to direct input from the labyrinth and eye movement sensitivity. Responses from neurons receiving convergent input from the semicircular canals and otolith organs were quantified and compared to non-convergent neurons.

Model-based damage evaluation of layered CFRP structures

NASA Astrophysics Data System (ADS)

Munoz, Rafael; Bochud, Nicolas; Rus, Guillermo; Peralta, Laura; Melchor, Juan; Chiachío, Juan; Chiachío, Manuel; Bond, Leonard J.

2015-03-01

An ultrasonic evaluation technique for damage identification of layered CFRP structures is presented. This approach relies on a model-based estimation procedure that combines experimental data and simulation of ultrasonic damage-propagation interactions. The CFPR structure, a [0/90]4s lay-up, has been tested in an immersion through transmission experiment, where a scan has been performed on a damaged specimen. Most ultrasonic techniques in industrial practice consider only a few features of the received signals, namely, time of flight, amplitude, attenuation, frequency contents, and so forth. In this case, once signals are captured, an algorithm is used to reconstruct the complete signal waveform and extract the unknown damage parameters by means of modeling procedures. A linear version of the data processing has been performed, where only Young modulus has been monitored and, in a second nonlinear version, the first order nonlinear coefficient β was incorporated to test the possibility of detection of early damage. The aforementioned physical simulation models are solved by the Transfer Matrix formalism, which has been extended from linear to nonlinear harmonic generation technique. The damage parameter search strategy is based on minimizing the mismatch between the captured and simulated signals in the time domain in an automated way using Genetic Algorithms. Processing all scanned locations, a C-scan of the parameter of each layer can be reconstructed, obtaining the information describing the state of each layer and each interface. Damage can be located and quantified in terms of changes in the selected parameter with a measurable extension. In the case of the nonlinear coefficient of first order, evidence of higher sensitivity to damage than imaging the linearly estimated Young Modulus is provided.

White-Light Optical Information Processing and Holography.

DTIC Science & Technology

1984-06-22

Processing, Image Deblurring , Source Encoding, Signal Sampling, Coherence Measurement, Noise Performance, / Pseudocolor Encoding. , ’ ’ * .~ 10.ASS!RACT...o 2.1 Broad Spectral Band Color Image Deblurring .. . 4 2.2 Noise Performance ...... ...... .. . 4 2.3 Pseudocolor Encoding with Three Primary...spectra. This technique is particularly suitable for linear smeared color image deblurring . 2.2 Noise Performance In this period, we have also

A Phonocardiographic-Based Fiber-Optic Sensor and Adaptive Filtering System for Noninvasive Continuous Fetal Heart Rate Monitoring.

PubMed

Martinek, Radek; Nedoma, Jan; Fajkus, Marcel; Kahankova, Radana; Konecny, Jaromir; Janku, Petr; Kepak, Stanislav; Bilik, Petr; Nazeran, Homer

2017-04-18

This paper focuses on the design, realization, and verification of a novel phonocardiographic- based fiber-optic sensor and adaptive signal processing system for noninvasive continuous fetal heart rate (fHR) monitoring. Our proposed system utilizes two Mach-Zehnder interferometeric sensors. Based on the analysis of real measurement data, we developed a simplified dynamic model for the generation and distribution of heart sounds throughout the human body. Building on this signal model, we then designed, implemented, and verified our adaptive signal processing system by implementing two stochastic gradient-based algorithms: the Least Mean Square Algorithm (LMS), and the Normalized Least Mean Square (NLMS) Algorithm. With this system we were able to extract the fHR information from high quality fetal phonocardiograms (fPCGs), filtered from abdominal maternal phonocardiograms (mPCGs) by performing fPCG signal peak detection. Common signal processing methods such as linear filtering, signal subtraction, and others could not be used for this purpose as fPCG and mPCG signals share overlapping frequency spectra. The performance of the adaptive system was evaluated by using both qualitative (gynecological studies) and quantitative measures such as: Signal-to-Noise Ratio-SNR, Root Mean Square Error-RMSE, Sensitivity-S+, and Positive Predictive Value-PPV.

A Phonocardiographic-Based Fiber-Optic Sensor and Adaptive Filtering System for Noninvasive Continuous Fetal Heart Rate Monitoring

PubMed Central

Martinek, Radek; Nedoma, Jan; Fajkus, Marcel; Kahankova, Radana; Konecny, Jaromir; Janku, Petr; Kepak, Stanislav; Bilik, Petr; Nazeran, Homer

2017-01-01

This paper focuses on the design, realization, and verification of a novel phonocardiographic- based fiber-optic sensor and adaptive signal processing system for noninvasive continuous fetal heart rate (fHR) monitoring. Our proposed system utilizes two Mach-Zehnder interferometeric sensors. Based on the analysis of real measurement data, we developed a simplified dynamic model for the generation and distribution of heart sounds throughout the human body. Building on this signal model, we then designed, implemented, and verified our adaptive signal processing system by implementing two stochastic gradient-based algorithms: the Least Mean Square Algorithm (LMS), and the Normalized Least Mean Square (NLMS) Algorithm. With this system we were able to extract the fHR information from high quality fetal phonocardiograms (fPCGs), filtered from abdominal maternal phonocardiograms (mPCGs) by performing fPCG signal peak detection. Common signal processing methods such as linear filtering, signal subtraction, and others could not be used for this purpose as fPCG and mPCG signals share overlapping frequency spectra. The performance of the adaptive system was evaluated by using both qualitative (gynecological studies) and quantitative measures such as: Signal-to-Noise Ratio—SNR, Root Mean Square Error—RMSE, Sensitivity—S+, and Positive Predictive Value—PPV. PMID:28420215

Near DC force measurement using PVDF sensors

NASA Astrophysics Data System (ADS)

Ramanathan, Arun Kumar; Headings, Leon M.; Dapino, Marcelo J.

2018-03-01

There is a need for high-performance force sensors capable of operating at frequencies near DC while producing a minimal mass penalty. Example application areas include steering wheel sensors, powertrain torque sensors, robotic arms, and minimally invasive surgery. The beta crystallographic phase polyvinylidene fluoride (PVDF) films are suitable for this purpose owing to their large piezoelectric constant. Unlike conventional capacitive sensors, beta crystallographic phase PVDF films exhibit a broad linear range and can potentially be designed to operate without complex electronics or signal processing. A fundamental challenge that prevents the implementation of PVDF in certain high-performance applications is their inability to measure static signals, which results from their first-order electrical impedance. Charge readout algorithms have been implemented which address this issue only partially, as they often require integration of the output signal to obtain the applied force profile, resulting in signal drift and signal processing complexities. In this paper, we propose a straightforward real time drift compensation strategy that is applicable to high output impedance PVDF films. This strategy makes it possible to utilize long sample times with a minimal loss of accuracy; our measurements show that the static output remains within 5% of the original value during half-hour measurements. The sensitivity and full-scale range are shown to be determined by the feedback capacitance of the charge amplifier. A linear model of the PVDF sensor system is developed and validated against experimental measurements, along with benchmark tests against a commercial load cell.

The Elementary Operations of Human Vision Are Not Reducible to Template-Matching

PubMed Central

Neri, Peter

2015-01-01

It is generally acknowledged that biological vision presents nonlinear characteristics, yet linear filtering accounts of visual processing are ubiquitous. The template-matching operation implemented by the linear-nonlinear cascade (linear filter followed by static nonlinearity) is the most widely adopted computational tool in systems neuroscience. This simple model achieves remarkable explanatory power while retaining analytical tractability, potentially extending its reach to a wide range of systems and levels in sensory processing. The extent of its applicability to human behaviour, however, remains unclear. Because sensory stimuli possess multiple attributes (e.g. position, orientation, size), the issue of applicability may be asked by considering each attribute one at a time in relation to a family of linear-nonlinear models, or by considering all attributes collectively in relation to a specified implementation of the linear-nonlinear cascade. We demonstrate that human visual processing can operate under conditions that are indistinguishable from linear-nonlinear transduction with respect to substantially different stimulus attributes of a uniquely specified target signal with associated behavioural task. However, no specific implementation of a linear-nonlinear cascade is able to account for the entire collection of results across attributes; a satisfactory account at this level requires the introduction of a small gain-control circuit, resulting in a model that no longer belongs to the linear-nonlinear family. Our results inform and constrain efforts at obtaining and interpreting comprehensive characterizations of the human sensory process by demonstrating its inescapably nonlinear nature, even under conditions that have been painstakingly fine-tuned to facilitate template-matching behaviour and to produce results that, at some level of inspection, do conform to linear filtering predictions. They also suggest that compliance with linear transduction may be the targeted outcome of carefully crafted nonlinear circuits, rather than default behaviour exhibited by basic components. PMID:26556758

Real-time windowing in imaging radar using FPGA technique

NASA Astrophysics Data System (ADS)

Ponomaryov, Volodymyr I.; Escamilla-Hernandez, Enrique

2005-02-01

The imaging radar uses the high frequency electromagnetic waves reflected from different objects for estimating of its parameters. Pulse compression is a standard signal processing technique used to minimize the peak transmission power and to maximize SNR, and to get a better resolution. Usually the pulse compression can be achieved using a matched filter. The level of the side-lobes in the imaging radar can be reduced using the special weighting function processing. There are very known different weighting functions: Hamming, Hanning, Blackman, Chebyshev, Blackman-Harris, Kaiser-Bessel, etc., widely used in the signal processing applications. Field Programmable Gate Arrays (FPGAs) offers great benefits like instantaneous implementation, dynamic reconfiguration, design, and field programmability. This reconfiguration makes FPGAs a better solution over custom-made integrated circuits. This work aims at demonstrating a reasonably flexible implementation of FM-linear signal and pulse compression using Matlab, Simulink, and System Generator. Employing FPGA and mentioned software we have proposed the pulse compression design on FPGA using classical and novel windows technique to reduce the side-lobes level. This permits increasing the detection ability of the small or nearly placed targets in imaging radar. The advantage of FPGA that can do parallelism in real time processing permits to realize the proposed algorithms. The paper also presents the experimental results of proposed windowing procedure in the marine radar with such the parameters: signal is linear FM (Chirp); frequency deviation DF is 9.375MHz; the pulse width T is 3.2μs taps number in the matched filter is 800 taps; sampling frequency 253.125*106 MHz. It has been realized the reducing of side-lobes levels in real time permitting better resolution of the small targets.

Linear feature projection-based real-time decoding of limb state from dorsal root ganglion recordings.

PubMed

Han, Sungmin; Chu, Jun-Uk; Park, Jong Woong; Youn, Inchan

2018-05-15

Proprioceptive afferent activities recorded by a multichannel microelectrode have been used to decode limb movements to provide sensory feedback signals for closed-loop control in a functional electrical stimulation (FES) system. However, analyzing the high dimensionality of neural activity is one of the major challenges in real-time applications. This paper proposes a linear feature projection method for the real-time decoding of ankle and knee joint angles. Single-unit activity was extracted as a feature vector from proprioceptive afferent signals that were recorded from the L7 dorsal root ganglion during passive movements of ankle and knee joints. The dimensionality of this feature vector was then reduced using a linear feature projection composed of projection pursuit and negentropy maximization (PP/NEM). Finally, a time-delayed Kalman filter was used to estimate the ankle and knee joint angles. The PP/NEM approach had a better decoding performance than did other feature projection methods, and all processes were completed within the real-time constraints. These results suggested that the proposed method could be a useful decoding method to provide real-time feedback signals in closed-loop FES systems.

Assessment of the non-Gaussianity and non-linearity levels of simulated sEMG signals on stationary segments.

PubMed

Messaoudi, Noureddine; Bekka, Raïs El'hadi; Ravier, Philippe; Harba, Rachid

2017-02-01

The purpose of this paper was to evaluate the effects of the longitudinal single differential (LSD), the longitudinal double differential (LDD) and the normal double differential (NDD) spatial filters, the electrode shape, the inter-electrode distance (IED) on non-Gaussianity and non-linearity levels of simulated surface EMG (sEMG) signals when the maximum voluntary contraction (MVC) varied from 10% to 100% by a step of 10%. The effects of recruitment range thresholds (RR), the firing rate (FR) strategy and the peak firing rate (PFR) of motor units were also considered. A cylindrical multilayer model of the volume conductor and a model of motor unit (MU) recruitment and firing rate were used to simulate sEMG signals in a pool of 120 MUs for 5s. Firstly, the stationarity of sEMG signals was tested by the runs, the reverse arrangements (RA) and the modified reverse arrangements (MRA) tests. Then the non-Gaussianity was characterised with bicoherence and kurtosis, and non-linearity levels was evaluated with linearity test. The kurtosis analysis showed that the sEMG signals detected by the LSD filter were the most Gaussian and those detected by the NDD filter were the least Gaussian. In addition, the sEMG signals detected by the LSD filter were the most linear. For a given filter, the sEMG signals detected by using rectangular electrodes were more Gaussian and more linear than that detected with circular electrodes. Moreover, the sEMG signals are less non-Gaussian and more linear with reverse onion-skin firing rate strategy than those with onion-skin strategy. The levels of sEMG signal Gaussianity and linearity increased with the increase of the IED, RR and PFR. Copyright © 2016 Elsevier Ltd. All rights reserved.

Spatial modeling of the membrane-cytosolic interface in protein kinase signal transduction

PubMed Central

Schröder, Andreas

2018-01-01

The spatial architecture of signaling pathways and the interaction with cell size and morphology are complex, but little understood. With the advances of single cell imaging and single cell biology, it becomes crucial to understand intracellular processes in time and space. Activation of cell surface receptors often triggers a signaling cascade including the activation of membrane-attached and cytosolic signaling components, which eventually transmit the signal to the cell nucleus. Signaling proteins can form steep gradients in the cytosol, which cause strong cell size dependence. We show that the kinetics at the membrane-cytosolic interface and the ratio of cell membrane area to the enclosed cytosolic volume change the behavior of signaling cascades significantly. We suggest an estimate of average concentration for arbitrary cell shapes depending on the cell volume and cell surface area. The normalized variance, known from image analysis, is suggested as an alternative measure to quantify the deviation from the average concentration. A mathematical analysis of signal transduction in time and space is presented, providing analytical solutions for different spatial arrangements of linear signaling cascades. Quantification of signaling time scales reveals that signal propagation is faster at the membrane than at the nucleus, while this time difference decreases with the number of signaling components in the cytosol. Our investigations are complemented by numerical simulations of non-linear cascades with feedback and asymmetric cell shapes. We conclude that intracellular signal propagation is highly dependent on cell geometry and, thereby, conveys information on cell size and shape to the nucleus. PMID:29630597

Improvement in airborne position measurements based on an ultrasonic linear-period-modulated wave by 1-bit signal processing

NASA Astrophysics Data System (ADS)

Thong-un, Natee; Hirata, Shinnosuke; Kurosawa, Minoru K.

2015-07-01

In this paper, we describe an expansion of the airborne ultrasonic systems for object localization in the three-dimensional spaces of navigation. A system, which revises the microphone arrangement and algorithm, can expand the object-position measurement from +90° in a previous method up to +180° for both the elevation and azimuth angles. The proposed system consists of a sound source and four acoustical receivers. Moreover, the system is designed to utilize low-cost devices, and low-cost computation relying on 1-bit signal processing is used to support the real-time application on a field-programmable gate array (FPGA). An object location is identified using spherical coordinates. A spherical object, which has a curved surface, is considered a target for this system. The transmit pulse to the target is a linear-period-modulated ultrasonic wave with a chirp rate of 50-20 kHz. Statistical evaluation of this work is the experimental investigation under repeatability.

Assessment of weaning indexes based on diaphragm activity in mechanically ventilated subjects after cardiovascular surgery. A pilot study

PubMed Central

Ortega, Isabel Cristina Muñoz; Valdivieso, Alher Mauricio Hernández; Lopez, Joan Francesc Alonso; Villanueva, Miguel Ángel Mañanas; Lopez, Luis Horacio Atehortúa

2017-01-01

Objective The aim of this pilot study was to evaluate the feasibility of surface electromyographic signal derived indexes for the prediction of weaning outcomes among mechanically ventilated subjects after cardiac surgery. Methods A sample of 10 postsurgical adult subjects who received cardiovascular surgery that did not meet the criteria for early extubation were included. Surface electromyographic signals from diaphragm and ventilatory variables were recorded during the weaning process, with the moment determined by the medical staff according to their expertise. Several indexes of respiratory muscle expenditure from surface electromyography using linear and non-linear processing techniques were evaluated. Two groups were compared: successfully and unsuccessfully weaned patients. Results The obtained indexes allow estimation of the diaphragm activity of each subject, showing a correlation between high expenditure and weaning test failure. Conclusion Surface electromyography is becoming a promising procedure for assessing the state of mechanically ventilated patients, even in complex situations such as those that involve a patient after cardiovascular surgery. PMID:28977261

A Highly Linear and Wide Input Range Four-Quadrant CMOS Analog Multiplier Using Active Feedback

NASA Astrophysics Data System (ADS)

Huang, Zhangcai; Jiang, Minglu; Inoue, Yasuaki

Analog multipliers are one of the most important building blocks in analog signal processing circuits. The performance with high linearity and wide input range is usually required for analog four-quadrant multipliers in most applications. Therefore, a highly linear and wide input range four-quadrant CMOS analog multiplier using active feedback is proposed in this paper. Firstly, a novel configuration of four-quadrant multiplier cell is presented. Its input dynamic range and linearity are improved significantly by adding two resistors compared with the conventional structure. Then based on the proposed multiplier cell configuration, a four-quadrant CMOS analog multiplier with active feedback technique is implemented by two operational amplifiers. Because of both the proposed multiplier cell and active feedback technique, the proposed multiplier achieves a much wider input range with higher linearity than conventional structures. The proposed multiplier was fabricated by a 0.6µm CMOS process. Experimental results show that the input range of the proposed multiplier can be up to 5.6Vpp with 0.159% linearity error on VX and 4.8Vpp with 0.51% linearity error on VY for ±2.5V power supply voltages, respectively.

Phase analysis of coherent radial-breathing-mode phonons in carbon nanotubes: Implications for generation and detection processes

NASA Astrophysics Data System (ADS)

Shimura, Akihiko; Yanagi, Kazuhiro; Yoshizawa, Masayuki

2018-01-01

In time-resolved pump-probe spectroscopy of carbon nanotubes, the fundamental understanding of the optical generation and detection processes of radial-breathing-mode (RBM) phonons has been inconsistent among the previous reports. In this study, the tunable-pumping/broadband-probing scheme was used to fully reveal the amplitude and phase of the phonon-modulated signals. We observed that signals detected off resonantly to excitonic transitions are delayed by π /2 radians with respect to resonantly detected signals, which demonstrates that RBM phonons are detected through dynamically modulating the linear response, not through adiabatically modulating the light absorption. Furthermore, we found that the initial phases are independent of the pump detuning across the first (E11) and the second (E22) excitonic resonances, evidencing that the RBM phonons are generated by the displacive excitation rather than stimulated Raman process.

Méthode de traitement des intérferogrammes à deux ondes pour accroître leur sensibilité.

PubMed

Roblin, G; Prévost, M

1980-08-01

Two-beam interference fringes are not always able to give sufficient information to determine the topography of very weakly deformed wave surfaces. The process described allows us to intercalate several intermediate levels, which vary linearly in terms of the phase, between the brightness extrema of a fringe. The interference pattern is submitted to an optoelectronics treatment where the photoelectric signal is compared with an adjustable electric reference signal.

On-field measurement trial of 4×128 Gbps PDM-QPSK signals by linear optical sampling

NASA Astrophysics Data System (ADS)

Bin Liu; Wu, Zhichao; Fu, Songnian; Feng, Yonghua; Liu, Deming

2017-02-01

Linear optical sampling is a promising characterization technique for advanced modulation formats, together with digital signal processing (DSP) and software-synchronized algorithm. We theoretically investigate the acquisition of optical sampling, when the high-speed signal under test is either periodic or random. Especially, when the profile of optical sampling pulse is asymmetrical, the repetition frequency of sampling pulse needs careful adjustment in order to obtain correct waveform. Then, we demonstrate on-field measurement trial of commercial four-channel 128 Gbps polarization division multiplexing quadrature phase shift keying (PDM-QPSK) signals with truly random characteristics by self-developed equipment. A passively mode-locked fiber laser (PMFL) with a repetition frequency of 95.984 MHz is used as optical sampling source, meanwhile four balanced photo detectors (BPDs) with 400 MHz bandwidth and four-channel analog-to-digital convertor (ADC) with 1.25 GS/s sampling rate are used for data acquisition. The performance comparison with conventional optical modulation analyzer (OMA) verifies that the self-developed equipment has the advantages of low cost, easy implementation, and fast response.

Application of temporal moments and other signal processing algorithms to analysis of ultrasonic signals through melting wax

DOE PAGES

Lau, Sarah J.; Moore, David G.; Stair, Sarah L.; ...

2016-01-01

Ultrasonic analysis is being explored as a way to capture events during melting of highly dispersive wax. Typical events include temperature changes in the material, phase transition of the material, surface flows and reformations, and void filling as the material melts. Melt tests are performed with wax to evaluate the usefulness of different signal processing algorithms in capturing event data. Several algorithm paths are being pursued. The first looks at changes in the velocity of the signal through the material. This is only appropriate when the changes from one ultrasonic signal to the next can be represented by a linearmore » relationship, which is not always the case. The second tracks changes in the frequency content of the signal. The third algorithm tracks changes in the temporal moments of a signal over a full test. This method does not require that the changes in the signal be represented by a linear relationship, but attaching changes in the temporal moments to physical events can be difficult. This study describes the algorithm paths applied to experimental data from ultrasonic signals as wax melts and explores different ways to display the results.« less

The effect of hearing aid signal-processing schemes on acceptable noise levels: perception and prediction.

PubMed

Wu, Yu-Hsiang; Stangl, Elizabeth

2013-01-01

The acceptable noise level (ANL) test determines the maximum noise level that an individual is willing to accept while listening to speech. The first objective of the present study was to systematically investigate the effect of wide dynamic range compression processing (WDRC), and its combined effect with digital noise reduction (DNR) and directional processing (DIR), on ANL. Because ANL represents the lowest signal-to-noise ratio (SNR) that a listener is willing to accept, the second objective was to examine whether the hearing aid output SNR could predict aided ANL across different combinations of hearing aid signal-processing schemes. Twenty-five adults with sensorineural hearing loss participated in the study. ANL was measured monaurally in two unaided and seven aided conditions, in which the status of the hearing aid processing schemes (enabled or disabled) and the location of noise (front or rear) were manipulated. The hearing aid output SNR was measured for each listener in each condition using a phase-inversion technique. The aided ANL was predicted by unaided ANL and hearing aid output SNR, under the assumption that the lowest acceptable SNR at the listener's eardrum is a constant across different ANL test conditions. Study results revealed that, on average, WDRC increased (worsened) ANL by 1.5 dB, while DNR and DIR decreased (improved) ANL by 1.1 and 2.8 dB, respectively. Because the effects of WDRC and DNR on ANL were opposite in direction but similar in magnitude, the ANL of linear/DNR-off was not significantly different from that of WDRC/DNR-on. The results further indicated that the pattern of ANL change across different aided conditions was consistent with the pattern of hearing aid output SNR change created by processing schemes. Compared with linear processing, WDRC creates a noisier sound image and makes listeners less willing to accept noise. However, this negative effect on noise acceptance can be offset by DNR, regardless of microphone mode. The hearing aid output SNR derived using the phase-inversion technique can predict aided ANL across different combinations of signal-processing schemes. These results suggest a close relationship between aided ANL, signal-processing scheme, and hearing aid output SNR.

Correction of complex nonlinear signal response from a pixel array detector

PubMed Central

van Driel, Tim Brandt; Herrmann, Sven; Carini, Gabriella; Nielsen, Martin Meedom; Lemke, Henrik Till

2015-01-01

The pulsed free-electron laser light sources represent a new challenge to photon area detectors due to the intrinsic spontaneous X-ray photon generation process that makes single-pulse detection necessary. Intensity fluctuations up to 100% between individual pulses lead to high linearity requirements in order to distinguish small signal changes. In real detectors, signal distortions as a function of the intensity distribution on the entire detector can occur. Here a robust method to correct this nonlinear response in an area detector is presented for the case of exposures to similar signals. The method is tested for the case of diffuse scattering from liquids where relevant sub-1% signal changes appear on the same order as artifacts induced by the detector electronics. PMID:25931072

Correction of complex nonlinear signal response from a pixel array detector.

PubMed

van Driel, Tim Brandt; Herrmann, Sven; Carini, Gabriella; Nielsen, Martin Meedom; Lemke, Henrik Till

2015-05-01

The pulsed free-electron laser light sources represent a new challenge to photon area detectors due to the intrinsic spontaneous X-ray photon generation process that makes single-pulse detection necessary. Intensity fluctuations up to 100% between individual pulses lead to high linearity requirements in order to distinguish small signal changes. In real detectors, signal distortions as a function of the intensity distribution on the entire detector can occur. Here a robust method to correct this nonlinear response in an area detector is presented for the case of exposures to similar signals. The method is tested for the case of diffuse scattering from liquids where relevant sub-1% signal changes appear on the same order as artifacts induced by the detector electronics.

Multivariate detrending of fMRI signal drifts for real-time multiclass pattern classification.

PubMed

Lee, Dongha; Jang, Changwon; Park, Hae-Jeong

2015-03-01

Signal drift in functional magnetic resonance imaging (fMRI) is an unavoidable artifact that limits classification performance in multi-voxel pattern analysis of fMRI. As conventional methods to reduce signal drift, global demeaning or proportional scaling disregards regional variations of drift, whereas voxel-wise univariate detrending is too sensitive to noisy fluctuations. To overcome these drawbacks, we propose a multivariate real-time detrending method for multiclass classification that involves spatial demeaning at each scan and the recursive detrending of drifts in the classifier outputs driven by a multiclass linear support vector machine. Experiments using binary and multiclass data showed that the linear trend estimation of the classifier output drift for each class (a weighted sum of drifts in the class-specific voxels) was more robust against voxel-wise artifacts that lead to inconsistent spatial patterns and the effect of online processing than voxel-wise detrending. The classification performance of the proposed method was significantly better, especially for multiclass data, than that of voxel-wise linear detrending, global demeaning, and classifier output detrending without demeaning. We concluded that the multivariate approach using classifier output detrending of fMRI signals with spatial demeaning preserves spatial patterns, is less sensitive than conventional methods to sample size, and increases classification performance, which is a useful feature for real-time fMRI classification. Copyright © 2014 Elsevier Inc. All rights reserved.

Non Linear Programming (NLP) Formulation for Quantitative Modeling of Protein Signal Transduction Pathways

PubMed Central

Morris, Melody K.; Saez-Rodriguez, Julio; Lauffenburger, Douglas A.; Alexopoulos, Leonidas G.

2012-01-01

Modeling of signal transduction pathways plays a major role in understanding cells' function and predicting cellular response. Mathematical formalisms based on a logic formalism are relatively simple but can describe how signals propagate from one protein to the next and have led to the construction of models that simulate the cells response to environmental or other perturbations. Constrained fuzzy logic was recently introduced to train models to cell specific data to result in quantitative pathway models of the specific cellular behavior. There are two major issues in this pathway optimization: i) excessive CPU time requirements and ii) loosely constrained optimization problem due to lack of data with respect to large signaling pathways. Herein, we address both issues: the former by reformulating the pathway optimization as a regular nonlinear optimization problem; and the latter by enhanced algorithms to pre/post-process the signaling network to remove parts that cannot be identified given the experimental conditions. As a case study, we tackle the construction of cell type specific pathways in normal and transformed hepatocytes using medium and large-scale functional phosphoproteomic datasets. The proposed Non Linear Programming (NLP) formulation allows for fast optimization of signaling topologies by combining the versatile nature of logic modeling with state of the art optimization algorithms. PMID:23226239

Non Linear Programming (NLP) formulation for quantitative modeling of protein signal transduction pathways.

PubMed

Mitsos, Alexander; Melas, Ioannis N; Morris, Melody K; Saez-Rodriguez, Julio; Lauffenburger, Douglas A; Alexopoulos, Leonidas G

2012-01-01

Modeling of signal transduction pathways plays a major role in understanding cells' function and predicting cellular response. Mathematical formalisms based on a logic formalism are relatively simple but can describe how signals propagate from one protein to the next and have led to the construction of models that simulate the cells response to environmental or other perturbations. Constrained fuzzy logic was recently introduced to train models to cell specific data to result in quantitative pathway models of the specific cellular behavior. There are two major issues in this pathway optimization: i) excessive CPU time requirements and ii) loosely constrained optimization problem due to lack of data with respect to large signaling pathways. Herein, we address both issues: the former by reformulating the pathway optimization as a regular nonlinear optimization problem; and the latter by enhanced algorithms to pre/post-process the signaling network to remove parts that cannot be identified given the experimental conditions. As a case study, we tackle the construction of cell type specific pathways in normal and transformed hepatocytes using medium and large-scale functional phosphoproteomic datasets. The proposed Non Linear Programming (NLP) formulation allows for fast optimization of signaling topologies by combining the versatile nature of logic modeling with state of the art optimization algorithms.

Research in Stochastic Processes and their Applications

DTIC Science & Technology

1993-01-01

goal is to learn how Gaussian and linear signal processing methodologies should be adapted to deal with non-Gaussian regimes. Part III continues the... smoothi fmictions in /I, ami we have a chain C ... C tir C ... C /I’) C 11_ C ... C 1t_, C_ ... C ¢’, 10 4o = fH,; H =H;, H, (Hilbert space). 4ý is a Fr

Exploitation of RF-DNA for Device Classification and Verification Using GRLVQI Processing

DTIC Science & Technology

2012-12-01

5 FLD Fisher’s Linear Discriminant . . . . . . . . . . . . . . . . . . . 6 kNN K-Nearest Neighbor...Neighbor ( kNN ), Support Vector Machine (SVM), and simple cross-correlation techniques [40, 57, 82, 88, 94, 95]. The RF-DNA fingerprinting research in...Expansion and the Dis- crete Gabor Transform on a Non-Separable Lattice”. 2000 IEEE Int’l Conf on Acoustics, Speech , and Signal Processing (ICASSP00

Signal Processing for Radar Target Tracking and Identification

DTIC Science & Technology

1996-12-01

Computes the likelihood for various potential jump moves. 12. matrix_mult.m: Parallel implementation of linear algebra ... Elementary Lineary Algebra with Applications, John Wiley k Sons, Inc., New York, 1987. [9] A. K. Bhattacharyya, and D. L. Sengupta, Radar Cross...Miller, ’Target Tracking and Recognition Using Jump-Diffusion Processes," ARO’s 11th Army Conf. on Applied Mathemat- ics and Computing, June 8-11

A tone analyzer based on a piezoelectric polymer and organic thin film transistors.

PubMed

Hsu, Yu-Jen; Kymissis, Ioannis

2012-12-01

A tone analyzer is demonstrated using a distributed resonator architecture on a tensioned piezoelectric polyvinyledene diuoride (PVDF) sheet. This sheet is used as both the resonator and detection element. Two architectures are demonstrated; one uses distributed, directly addressed elements as a proof of concept, and the other integrates organic thin film transistor-based transimpedance amplifiers directly with the PVDF to convert the piezoelectric charge signal into a current signal. The PVDF sheet material is instrumented along its length, and the amplitude response at 15 sites is recorded and analyzed as a function of the frequency of excitation. The determination of the dominant component of an incoming tone is demonstrated using linear system decomposition of the time-averaged response of the sheet and is performed without any time domain analysis. This design allows for the determination of the spectral composition of a sound using the mechanical signal processing provided by the amplitude response and eliminates the need for time-domain downstream signal processing of the incoming signal.

Imaging synthetic aperture radar

DOEpatents

Burns, Bryan L.; Cordaro, J. Thomas

1997-01-01

A linear-FM SAR imaging radar method and apparatus to produce a real-time image by first arranging the returned signals into a plurality of subaperture arrays, the columns of each subaperture array having samples of dechirped baseband pulses, and further including a processing of each subaperture array to obtain coarse-resolution in azimuth, then fine-resolution in range, and lastly, to combine the processed subapertures to obtain the final fine-resolution in azimuth. Greater efficiency is achieved because both the transmitted signal and a local oscillator signal mixed with the returned signal can be varied on a pulse-to-pulse basis as a function of radar motion. Moreover, a novel circuit can adjust the sampling location and the A/D sample rate of the combined dechirped baseband signal which greatly reduces processing time and hardware. The processing steps include implementing a window function, stabilizing either a central reference point and/or all other points of a subaperture with respect to doppler frequency and/or range as a function of radar motion, sorting and compressing the signals using a standard fourier transforms. The stabilization of each processing part is accomplished with vector multiplication using waveforms generated as a function of radar motion wherein these waveforms may be synthesized in integrated circuits. Stabilization of range migration as a function of doppler frequency by simple vector multiplication is a particularly useful feature of the invention; as is stabilization of azimuth migration by correcting for spatially varying phase errors prior to the application of an autofocus process.

Multichannel Detection in High-Performance Liquid Chromatography.

ERIC Educational Resources Information Center

Miller, James C.; And Others

1982-01-01

A linear photodiode array is used as the photodetector element in a new ultraviolet-visible detection system for high-performance liquid chromatography (HPLC). Using a computer network, the system processes eight different chromatographic signals simultaneously in real-time and acquires spectra manually/automatically. Applications in fast HPLC…

A Random Walk into Optical Signal Processing and Integrated Optofluidics

NASA Astrophysics Data System (ADS)

Baylor, Martha-Elizabeth

2013-04-01

As a young child, I knew that I wanted to be a paleontologist. My parents, both artists, did their best to encourage me in my quest to dig for dinosaurs. However, decisions during my late high school and early college years serendipitously shifted my path so that I ended up pursuing a career in applied physics. In particular, my career path has been centered in optics with an emphasis on holography and signal processing. This talk will discuss my research in the areas of opto-electronic blind source separation and holographic photopolymers as well as the non-linear path that has gotten me to this point.

Bayesian estimation of self-similarity exponent

NASA Astrophysics Data System (ADS)

Makarava, Natallia; Benmehdi, Sabah; Holschneider, Matthias

2011-08-01

In this study we propose a Bayesian approach to the estimation of the Hurst exponent in terms of linear mixed models. Even for unevenly sampled signals and signals with gaps, our method is applicable. We test our method by using artificial fractional Brownian motion of different length and compare it with the detrended fluctuation analysis technique. The estimation of the Hurst exponent of a Rosenblatt process is shown as an example of an H-self-similar process with non-Gaussian dimensional distribution. Additionally, we perform an analysis with real data, the Dow-Jones Industrial Average closing values, and analyze its temporal variation of the Hurst exponent.

Ultrasensitive surveillance of sensors and processes

DOEpatents

Wegerich, Stephan W.; Jarman, Kristin K.; Gross, Kenneth C.

2001-01-01

A method and apparatus for monitoring a source of data for determining an operating state of a working system. The method includes determining a sensor (or source of data) arrangement associated with monitoring the source of data for a system, activating a method for performing a sequential probability ratio test if the data source includes a single data (sensor) source, activating a second method for performing a regression sequential possibility ratio testing procedure if the arrangement includes a pair of sensors (data sources) with signals which are linearly or non-linearly related; activating a third method for performing a bounded angle ratio test procedure if the sensor arrangement includes multiple sensors and utilizing at least one of the first, second and third methods to accumulate sensor signals and determining the operating state of the system.

Ultrasensitive surveillance of sensors and processes

DOEpatents

Wegerich, Stephan W.; Jarman, Kristin K.; Gross, Kenneth C.

1999-01-01

A method and apparatus for monitoring a source of data for determining an operating state of a working system. The method includes determining a sensor (or source of data) arrangement associated with monitoring the source of data for a system, activating a method for performing a sequential probability ratio test if the data source includes a single data (sensor) source, activating a second method for performing a regression sequential possibility ratio testing procedure if the arrangement includes a pair of sensors (data sources) with signals which are linearly or non-linearly related; activating a third method for performing a bounded angle ratio test procedure if the sensor arrangement includes multiple sensors and utilizing at least one of the first, second and third methods to accumulate sensor signals and determining the operating state of the system.

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

van Driel, Tim Brandt; Herrmann, Sven; Carini, Gabriella

The pulsed free-electron laser light sources represent a new challenge to photon area detectors due to the intrinsic spontaneous X-ray photon generation process that makes single-pulse detection necessary. Intensity fluctuations up to 100% between individual pulses lead to high linearity requirements in order to distinguish small signal changes. In real detectors, signal distortions as a function of the intensity distribution on the entire detector can occur. Here a robust method to correct this nonlinear response in an area detector is presented for the case of exposures to similar signals. The method is tested for the case of diffuse scattering frommore » liquids where relevant sub-1% signal changes appear on the same order as artifacts induced by the detector electronics.« less

Experimental demonstration of a quantum router

PubMed Central

Yuan, X. X.; Ma, J.-J.; Hou, P.-Y.; Chang, X.-Y.; Zu, C.; Duan, L.-M.

2015-01-01

The router is a key element for a network. We describe a scheme to realize genuine quantum routing of single-photon pulses based on cascading of conditional quantum gates in a Mach-Zehnder interferometer and report a proof-of-principle experiment for its demonstration using linear optics quantum gates. The polarization of the control photon routes in a coherent way the path of the signal photon while preserving the qubit state of the signal photon represented by its polarization. We demonstrate quantum nature of this router by showing entanglement generated between the initially unentangled control and signal photons, and confirm that the qubit state of the signal photon is well preserved by the router through quantum process tomography. PMID:26197928

Effects of sources on time-domain finite difference models.

PubMed

Botts, Jonathan; Savioja, Lauri

2014-07-01

Recent work on excitation mechanisms in acoustic finite difference models focuses primarily on physical interpretations of observed phenomena. This paper offers an alternative view by examining the properties of models from the perspectives of linear algebra and signal processing. Interpretation of a simulation as matrix exponentiation clarifies the separate roles of sources as boundaries and signals. Boundary conditions modify the matrix and thus its modal structure, and initial conditions or source signals shape the solution, but not the modal structure. Low-frequency artifacts are shown to follow from eigenvalues and eigenvectors of the matrix, and previously reported artifacts are predicted from eigenvalue estimates. The role of source signals is also briefly discussed.

Higgs boson production in the littlest Higgs model with T-parity at the ILC

NASA Astrophysics Data System (ADS)

Han, Jinzhong; Yang, Guang; Meng, Ming; Wang, Weijian; Li, Jingyun

2018-04-01

We investigate the Higgs boson production processes e+e‑→ ZH, e+e‑→ νν¯H, e+e‑→ tt¯H, e+e‑→ ZHH and e+e‑→ νν¯HH in the littlest Higgs model with T-parity (LHT) at the International Linear Collider (ILC). We calculate the LHT model predictions on the production rate of these processes at the ILC in the case of (un)polarized beams and the signal strengths of the production processes ZH and νν¯H with Higgs decaying to bb¯(gg,γγ). In the allowed parameter space, we find that the signal strengths μgg is most likely approach to the expected precision of the ILC.

A bunch to bucket phase detector for the RHIC LLRF upgrade platform

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

Smith, K.S.; Harvey, M.; Hayes, T.

2011-03-28

As part of the overall development effort for the RHIC LLRF Upgrade Platform [1,2,3], a generic four channel 16 bit Analog-to-Digital Converter (ADC) daughter module was developed to provide high speed, wide dynamic range digitizing and processing of signals from DC to several hundred megahertz. The first operational use of this card was to implement the bunch to bucket phase detector for the RHIC LLRF beam control feedback loops. This paper will describe the design and performance features of this daughter module as a bunch to bucket phase detector, and also provide an overview of its place within the overallmore » LLRF platform architecture as a high performance digitizer and signal processing module suitable to a variety of applications. In modern digital control and signal processing systems, ADCs provide the interface between the analog and digital signal domains. Once digitized, signals are then typically processed using algorithms implemented in field programmable gate array (FPGA) logic, general purpose processors (GPPs), digital signal processors (DSPs) or a combination of these. For the recently developed and commissioned RHIC LLRF Upgrade Platform, we've developed a four channel ADC daughter module based on the Linear Technology LTC2209 16 bit, 160 MSPS ADC and the Xilinx V5FX70T FPGA. The module is designed to be relatively generic in application, and with minimal analog filtering on board, is capable of processing signals from DC to 500 MHz or more. The module's first application was to implement the bunch to bucket phase detector (BTB-PD) for the RHIC LLRF system. The same module also provides DC digitizing of analog processed BPM signals used by the LLRF system for radial feedback.« less

Welding quality evaluation of resistance spot welding using the time-varying inductive reactance signal

NASA Astrophysics Data System (ADS)

Zhang, Hongjie; Hou, Yanyan; Yang, Tao; Zhang, Qian; Zhao, Jian

2018-05-01

In the spot welding process, a high alternating current is applied, resulting in a time-varying electromagnetic field surrounding the welder. When measuring the welding voltage signal, the impedance of the measuring circuit consists of two parts: dynamic resistance relating to weld nugget nucleation event and inductive reactance caused by mutual inductance. The aim of this study is to develop a method to acquire the dynamic reactance signal and to discuss the possibility of using this signal to evaluate the weld quality. For this purpose, a series of experiments were carried out. The reactance signals under different welding conditions were compared and the results showed that the morphological feature of the reactance signal was closely related to the welding current and it was also significantly influenced by some abnormal welding conditions. Some features were extracted from the reactance signal and combined to construct weld nugget strength and diameter prediction models based on the radial basis function (RBF) neural network. In addition, several features were also used to monitor the expulsion in the welding process by using Fisher linear discriminant analysis. The results indicated that using the dynamic reactance signal to evaluate weld quality is possible and feasible.

Singular value decomposition based impulsive noise reduction in multi-frequency phase-sensitive demodulation of electrical impedance tomography

NASA Astrophysics Data System (ADS)

Hao, Zhenhua; Cui, Ziqiang; Yue, Shihong; Wang, Huaxiang

2018-06-01

As an important means in electrical impedance tomography (EIT), multi-frequency phase-sensitive demodulation (PSD) can be viewed as a matched filter for measurement signals and as an optimal linear filter in the case of Gaussian-type noise. However, the additive noise usually possesses impulsive noise characteristics, so it is a challenging task to reduce the impulsive noise in multi-frequency PSD effectively. In this paper, an approach for impulsive noise reduction in multi-frequency PSD of EIT is presented. Instead of linear filters, a singular value decomposition filter is employed as the pre-stage filtering module prior to PSD, which has advantages of zero phase shift, little distortion, and a high signal-to-noise ratio (SNR) in digital signal processing. Simulation and experimental results demonstrated that the proposed method can effectively eliminate the influence of impulsive noise in multi-frequency PSD, and it was capable of achieving a higher SNR and smaller demodulation error.

Signal and noise extraction from analog memory elements for neuromorphic computing.

PubMed

Gong, N; Idé, T; Kim, S; Boybat, I; Sebastian, A; Narayanan, V; Ando, T

2018-05-29

Dense crossbar arrays of non-volatile memory (NVM) can potentially enable massively parallel and highly energy-efficient neuromorphic computing systems. The key requirements for the NVM elements are continuous (analog-like) conductance tuning capability and switching symmetry with acceptable noise levels. However, most NVM devices show non-linear and asymmetric switching behaviors. Such non-linear behaviors render separation of signal and noise extremely difficult with conventional characterization techniques. In this study, we establish a practical methodology based on Gaussian process regression to address this issue. The methodology is agnostic to switching mechanisms and applicable to various NVM devices. We show tradeoff between switching symmetry and signal-to-noise ratio for HfO 2 -based resistive random access memory. Then, we characterize 1000 phase-change memory devices based on Ge 2 Sb 2 Te 5 and separate total variability into device-to-device variability and inherent randomness from individual devices. These results highlight the usefulness of our methodology to realize ideal NVM devices for neuromorphic computing.

Modelling the 3D post-seismic deformation signal of the Maule 2010 earthquake: Viscosity heterogeneity or non-linear creep?

NASA Astrophysics Data System (ADS)

Peña, C.; Heidbach, O.; Moreno, M.; Li, S.; Bedford, J. R.; Oncken, O.

2017-12-01

The surface deformation associated with the 2010 Mw 8.8 Maule earthquake, Chile was recorded in great detail before, during and after the event. The quality of the post-seismic continuous GPS time series has facilitated a number of studies that have modelled the horizontal signal with a combination of after-slip and viscoelastic relaxation using linear Newtonian rheology. Li et al. (2017, GRL), one of the first studies that also looked into the details of the vertical post-seismic signal, showed that a homogeneous viscosity structure cannot well explain the vertical signal, but that with a heterogeneous viscosity distribution producing a better fit. It is, however, difficult to argue why viscous rock properties should change significantly with distance to the trench. Thus, here we investigate if a non-linear, strain-rate dependent power-law can fit the post-seismic signal in all three components - in particular the vertical one. We use the first 6 years of post-seismic cGPS data and investigate with a 2D geomechanical-numerical model along a profile at 36°S if non-linear creep can explain the deformation signal as well using reasonable rock properties and a temperature field derived for this region from Springer (1999). The 2D model geometry considers the slab as well as the Moho geometry. Our results show that with our model the post-seismic surface deformation signal can be reproduced as well as in the study of Li et al. (2017). These findings suggest that the largest deformations are produced by dislocation creep. Such a process would take place below the Andes ( 40 km depth) at the interface between the deeper, colder crust and the olivine-rich upper mantle, where the lowest effective viscosity results from the relaxation of tensional stresses imposed by the co-seismic displacement. Additionally, we present preliminary results from a 3D geomechanical-numerical model with the same rheology that provides more details of the post-seismic deformation especially along strike the subduction zone.

Application of the GNU Radio platform in the multistatic radar

NASA Astrophysics Data System (ADS)

Szlachetko, Boguslaw; Lewandowski, Andrzej

2009-06-01

This document presents the application of the Software Defined Radio-based platform in the multistatic radar. This platform consists of four-sensor linear antenna, Universal Software Radio Peripheral (USRP) hardware (radio frequency frontend) and GNU-Radio PC software. The paper provides information about architecture of digital signal processing performed by USRP's FPGA (digital down converting blocks) and PC host (implementation of the multichannel digital beamforming). The preliminary results of the signal recording performed by our experimental platform are presented.

Expansion of linear range of Pound-Drever-Hall signal.

PubMed

Miyoki, Shinji; Telada, Souich; Uchiyama, Takashi

2010-10-01

We propose new solutions for expanding the linear signal range between the laser frequency deviation (or mirror position) and the voltage signal derived by the Pound-Drever-Hall (PDH) method for optical Fabry-Perot cavity resonance control. One solution is to perform not in-phase demodulation but near-Q-phase demodulation. Another solution is to take a suitable combination of signals demodulated by odd-harmonic modulation frequencies in the in phase. Although the PDH signal sensitivity will be diminished, the PDH signal linear range can be extended. From a practical standpoint, it is desirable that a sideband frequency for the PDH method is near the FP cavity resonance.

Separating higher-order nonlinearities in transient absorption microscopy

NASA Astrophysics Data System (ADS)

Wilson, Jesse W.; Anderson, Miguel; Park, Jong Kang; Fischer, Martin C.; Warren, Warren S.

2015-08-01

The transient absorption response of melanin is a promising optically-accessible biomarker for distinguishing malignant melanoma from benign pigmented lesions, as demonstrated by earlier experiments on thin sections from biopsied tissue. The technique has also been demonstrated in vivo, but the higher optical intensity required for detecting these signals from backscattered light introduces higher-order nonlinearities in the transient response of melanin. These components that are higher than linear with respect to the pump or the probe introduce intensity-dependent changes to the overall response that complicate data analysis. However, our data also suggest these nonlinearities might be advantageous to in vivo imaging, in that different types of melanins have different nonlinear responses. Therefore, methods to separate linear from nonlinear components in transient absorption measurements might provide additional information to aid in the diagnosis of melanoma. We will discuss numerical methods for analyzing the various nonlinear contributions to pump-probe signals, with the ultimate objective of real time analysis using digital signal processing techniques. To that end, we have replaced the lock-in amplifier in our pump-probe microscope with a high-speed data acquisition board, and reprogrammed the coprocessor field-programmable gate array (FPGA) to perform lock-in detection. The FPGA lock-in offers better performance than the commercial instrument, in terms of both signal to noise ratio and speed. In addition, the flexibility of the digital signal processing approach enables demodulation of more complicated waveforms, such as spread-spectrum sequences, which has the potential to accelerate microscopy methods that rely on slow relaxation phenomena, such as photo-thermal and phosphorescence lifetime imaging.

The response of a linear monostable system and its application in parameters estimation for PSK signals

NASA Astrophysics Data System (ADS)

Duan, Chaowei; Zhan, Yafeng

2016-03-01

The output characteristics of a linear monostable system driven with a periodic signal and an additive white Gaussian noise are studied in this paper. Theoretical analysis shows that the output signal-to-noise ratio (SNR) decreases monotonously with the increasing noise intensity but the output SNR-gain is stable. Inspired by this high SNR-gain phenomenon, this paper applies the linear monostable system in the parameters estimation algorithm for phase shift keying (PSK) signals and improves the estimation performance.

Information analysis of posterior canal afferents in the turtle, Trachemys scripta elegans.

PubMed

Rowe, Michael H; Neiman, Alexander B

2012-01-24

We have used sinusoidal and band-limited Gaussian noise stimuli along with information measures to characterize the linear and non-linear responses of morpho-physiologically identified posterior canal (PC) afferents and to examine the relationship between mutual information rate and other physiological parameters. Our major findings are: 1) spike generation in most PC afferents is effectively a stochastic renewal process, and spontaneous discharges are fully characterized by their first order statistics; 2) a regular discharge, as measured by normalized coefficient of variation (cv*), reduces intrinsic noise in afferent discharges at frequencies below the mean firing rate; 3) coherence and mutual information rates, calculated from responses to band-limited Gaussian noise, are jointly determined by gain and intrinsic noise (discharge regularity), the two major determinants of signal to noise ratio in the afferent response; 4) measures of optimal non-linear encoding were only moderately greater than optimal linear encoding, indicating that linear stimulus encoding is limited primarily by internal noise rather than by non-linearities; and 5) a leaky integrate and fire model reproduces these results and supports the suggestion that the combination of high discharge regularity and high discharge rates serves to extend the linear encoding range of afferents to higher frequencies. These results provide a framework for future assessments of afferent encoding of signals generated during natural head movements and for comparison with coding strategies used by other sensory systems. This article is part of a Special Issue entitled: Neural Coding. Copyright © 2011 Elsevier B.V. All rights reserved.

Switched periodic systems in discrete time: stability and input-output norms

NASA Astrophysics Data System (ADS)

Bolzern, Paolo; Colaneri, Patrizio

2013-07-01

This paper deals with the analysis of stability and the characterisation of input-output norms for discrete-time periodic switched linear systems. Such systems consist of a network of time-periodic linear subsystems sharing the same state vector and an exogenous switching signal that triggers the jumps between the subsystems. The overall system exhibits a complex dynamic behaviour due to the interplay between the time periodicity of the subsystem parameters and the switching signal. Both arbitrary switching signals and signals satisfying a dwell-time constraint are considered. Linear matrix inequality conditions for stability and guaranteed H2 and H∞ performances are provided. The results heavily rely on the merge of the theory of linear periodic systems and recent developments on switched linear time-invariant systems.

Comparisons of linear and nonlinear pyramid schemes for signal and image processing

NASA Astrophysics Data System (ADS)

Morales, Aldo W.; Ko, Sung-Jea

1997-04-01

Linear filters banks are being used extensively in image and video applications. New research results in wavelet applications for compression and de-noising are constantly appearing in the technical literature. On the other hand, non-linear filter banks are also being used regularly in image pyramid algorithms. There are some inherent advantages in using non-linear filters instead of linear filters when non-Gaussian processes are present in images. However, a consistent way of comparing performance criteria between these two schemes has not been fully developed yet. In this paper a recently discovered tool, sample selection probabilities, is used to compare the behavior of linear and non-linear filters. In the conversion from weights of order statistics (OS) filters to coefficients of the impulse response is obtained through these probabilities. However, the reverse problem: the conversion from coefficients of the impulse response to the weights of OS filters is not yet fully understood. One of the reasons for this difficulty is the highly non-linear nature of the partitions and generating function used. In the present paper the problem is posed as an optimization of integer linear programming subject to constraints directly obtained from the coefficients of the impulse response. Although the technique to be presented in not completely refined, it certainly appears to be promising. Some results will be shown.

Radioastronomic signal processing cores for the SKA radio telescope

NASA Astrophysics Data System (ADS)

Comorett, G.; Chiarucc, S.; Belli, C.

Modern radio telescopes require the processing of wideband signals, with sample rates from tens of MHz to tens of GHz, and are composed from hundreds up to a million of individual antennas. Digital signal processing of these signals include digital receivers (the digital equivalent of the heterodyne receiver), beamformers, channelizers, spectrometers. FPGAs present the advantage of providing a relatively low power consumption, relative to GPUs or dedicated computers, a wide signal data path, and high interconnectivity. Efficient algorithms have been developed for these applications. Here we will review some of the signal processing cores developed for the SKA telescope. The LFAA beamformer/channelizer architecture is based on an oversampling channelizer, where the channelizer output sampling rate and channel spacing can be set independently. This is useful where an overlap between adjacent channels is required to provide an uniform spectral coverage. The architecture allows for an efficient and distributed channelization scheme, with a final resolution corresponding to a million of spectral channels, minimum leakage and high out-of-band rejection. An optimized filter design procedure is used to provide an equiripple response with a very large number of spectral channels. A wideband digital receiver has been designed in order to select the processed bandwidth of the SKA Mid receiver. The receiver extracts a 2.5 MHz bandwidth form a 14 GHz input bandwidth. The design allows for non-integer ratios between the input and output sampling rates, with a resource usage comparable to that of a conventional decimating digital receiver. Finally, some considerations on quantization of radioastronomic signals are presented. Due to the stochastic nature of the signal, quantization using few data bits is possible. Good accuracies and dynamic range are possible even with 2-3 bits, but the nonlinearity in the correlation process must be corrected in post-processing. With at least 6 bits it is possible to have a very linear response of the instrument, with nonlinear terms below 80 dB, providing the signal amplitude is kept within bounds.

Estimation of source location and ground impedance using a hybrid multiple signal classification and Levenberg-Marquardt approach

NASA Astrophysics Data System (ADS)

Tam, Kai-Chung; Lau, Siu-Kit; Tang, Shiu-Keung

2016-07-01

A microphone array signal processing method for locating a stationary point source over a locally reactive ground and for estimating ground impedance is examined in detail in the present study. A non-linear least square approach using the Levenberg-Marquardt method is proposed to overcome the problem of unknown ground impedance. The multiple signal classification method (MUSIC) is used to give the initial estimation of the source location, while the technique of forward backward spatial smoothing is adopted as a pre-processer of the source localization to minimize the effects of source coherence. The accuracy and robustness of the proposed signal processing method are examined. Results show that source localization in the horizontal direction by MUSIC is satisfactory. However, source coherence reduces drastically the accuracy in estimating the source height. The further application of Levenberg-Marquardt method with the results from MUSIC as the initial inputs improves significantly the accuracy of source height estimation. The present proposed method provides effective and robust estimation of the ground surface impedance.

Blind source separation by sparse decomposition

NASA Astrophysics Data System (ADS)

Zibulevsky, Michael; Pearlmutter, Barak A.

2000-04-01

The blind source separation problem is to extract the underlying source signals from a set of their linear mixtures, where the mixing matrix is unknown. This situation is common, eg in acoustics, radio, and medical signal processing. We exploit the property of the sources to have a sparse representation in a corresponding signal dictionary. Such a dictionary may consist of wavelets, wavelet packets, etc., or be obtained by learning from a given family of signals. Starting from the maximum a posteriori framework, which is applicable to the case of more sources than mixtures, we derive a few other categories of objective functions, which provide faster and more robust computations, when there are an equal number of sources and mixtures. Our experiments with artificial signals and with musical sounds demonstrate significantly better separation than other known techniques.

Correction of complex nonlinear signal response from a pixel array detector

DOE PAGES

van Driel, Tim Brandt; Herrmann, Sven; Carini, Gabriella; ...

2015-04-22

The pulsed free-electron laser light sources represent a new challenge to photon area detectors due to the intrinsic spontaneous X-ray photon generation process that makes single-pulse detection necessary. Intensity fluctuations up to 100% between individual pulses lead to high linearity requirements in order to distinguish small signal changes. In real detectors, signal distortions as a function of the intensity distribution on the entire detector can occur. Here a robust method to correct this nonlinear response in an area detector is presented for the case of exposures to similar signals. The method is tested for the case of diffuse scattering frommore » liquids where relevant sub-1% signal changes appear on the same order as artifacts induced by the detector electronics.« less

A Sounding Rocket Experiment for the Chromospheric Lyman-Alpha Spectro-Polarimeter (CLASP)

NASA Astrophysics Data System (ADS)

Kubo, M.; Kano, R.; Kobayashi, K.; Bando, T.; Narukage, N.; Ishikawa, R.; Tsuneta, S.; Katsukawa, Y.; Ishikawa, S.; Suematsu, Y.; Hara, H.; Shimizu, T.; Sakao, T.; Ichimoto, K.; Goto, M.; Holloway, T.; Winebarger, A.; Cirtain, J.; De Pontieu, B.; Casini, R.; Auchère, F.; Trujillo Bueno, J.; Manso Sainz, R.; Belluzzi, L.; Asensio Ramos, A.; Štěpán, J.; Carlsson, M.

2014-10-01

A sounding-rocket experiment called the Chromospheric Lyman-Alpha Spectro-Polarimeter (CLASP) is presently under development to measure the linear polarization profiles in the hydrogen Lyman-alpha (Lyα) line at 121.567 nm. CLASP is a vacuum-UV (VUV) spectropolarimeter to aim for first detection of the linear polarizations caused by scattering processes and the Hanle effect in the Lyα line with high accuracy (0.1%). This is a fist step for exploration of magnetic fields in the upper chromosphere and transition region of the Sun. Accurate measurements of the linear polarization signals caused by scattering processes and the Hanle effect in strong UV lines like Lyα are essential to explore with future solar telescopes the strength and structures of the magnetic field in the upper chromosphere and transition region of the Sun. The CLASP proposal has been accepted by NASA in 2012, and the flight is planned in 2015.

An Over 90 dB Intra-Scene Single-Exposure Dynamic Range CMOS Image Sensor Using a 3.0 μm Triple-Gain Pixel Fabricated in a Standard BSI Process.

PubMed

Takayanagi, Isao; Yoshimura, Norio; Mori, Kazuya; Matsuo, Shinichiro; Tanaka, Shunsuke; Abe, Hirofumi; Yasuda, Naoto; Ishikawa, Kenichiro; Okura, Shunsuke; Ohsawa, Shinji; Otaka, Toshinori

2018-01-12

To respond to the high demand for high dynamic range imaging suitable for moving objects with few artifacts, we have developed a single-exposure dynamic range image sensor by introducing a triple-gain pixel and a low noise dual-gain readout circuit. The developed 3 μm pixel is capable of having three conversion gains. Introducing a new split-pinned photodiode structure, linear full well reaches 40 ke - . Readout noise under the highest pixel gain condition is 1 e - with a low noise readout circuit. Merging two signals, one with high pixel gain and high analog gain, and the other with low pixel gain and low analog gain, a single exposure dynamic rage (SEHDR) signal is obtained. Using this technology, a 1/2.7", 2M-pixel CMOS image sensor has been developed and characterized. The image sensor also employs an on-chip linearization function, yielding a 16-bit linear signal at 60 fps, and an intra-scene dynamic range of higher than 90 dB was successfully demonstrated. This SEHDR approach inherently mitigates the artifacts from moving objects or time-varying light sources that can appear in the multiple exposure high dynamic range (MEHDR) approach.

An Over 90 dB Intra-Scene Single-Exposure Dynamic Range CMOS Image Sensor Using a 3.0 μm Triple-Gain Pixel Fabricated in a Standard BSI Process †

PubMed Central

Takayanagi, Isao; Yoshimura, Norio; Mori, Kazuya; Matsuo, Shinichiro; Tanaka, Shunsuke; Abe, Hirofumi; Yasuda, Naoto; Ishikawa, Kenichiro; Okura, Shunsuke; Ohsawa, Shinji; Otaka, Toshinori

2018-01-01

To respond to the high demand for high dynamic range imaging suitable for moving objects with few artifacts, we have developed a single-exposure dynamic range image sensor by introducing a triple-gain pixel and a low noise dual-gain readout circuit. The developed 3 μm pixel is capable of having three conversion gains. Introducing a new split-pinned photodiode structure, linear full well reaches 40 ke−. Readout noise under the highest pixel gain condition is 1 e− with a low noise readout circuit. Merging two signals, one with high pixel gain and high analog gain, and the other with low pixel gain and low analog gain, a single exposure dynamic rage (SEHDR) signal is obtained. Using this technology, a 1/2.7”, 2M-pixel CMOS image sensor has been developed and characterized. The image sensor also employs an on-chip linearization function, yielding a 16-bit linear signal at 60 fps, and an intra-scene dynamic range of higher than 90 dB was successfully demonstrated. This SEHDR approach inherently mitigates the artifacts from moving objects or time-varying light sources that can appear in the multiple exposure high dynamic range (MEHDR) approach. PMID:29329210

A Compressed Sensing Based Ultra-Wideband Communication System

DTIC Science & Technology

2009-06-01

principle, most of the processing at the receiver can be moved to the transmitter—where energy consumption and computation are sufficient for many advanced...extended to continuous time signals. We use ∗ to denote the convolution process in a linear time-invariant (LTI) system. Assume that there is an analog...Filter Channel Low Rate A/D Processing Sparse Bit Sequence UWB Pulse Generator α̂ Waves)(RadioGHz 5 MHz125 θ Ψ Φ y θ̂ 1 ˆ arg min s.t. yθ

Deep neural networks: A promising tool for fault characteristic mining and intelligent diagnosis of rotating machinery with massive data

NASA Astrophysics Data System (ADS)

Jia, Feng; Lei, Yaguo; Lin, Jing; Zhou, Xin; Lu, Na

2016-05-01

Aiming to promptly process the massive fault data and automatically provide accurate diagnosis results, numerous studies have been conducted on intelligent fault diagnosis of rotating machinery. Among these studies, the methods based on artificial neural networks (ANNs) are commonly used, which employ signal processing techniques for extracting features and further input the features to ANNs for classifying faults. Though these methods did work in intelligent fault diagnosis of rotating machinery, they still have two deficiencies. (1) The features are manually extracted depending on much prior knowledge about signal processing techniques and diagnostic expertise. In addition, these manual features are extracted according to a specific diagnosis issue and probably unsuitable for other issues. (2) The ANNs adopted in these methods have shallow architectures, which limits the capacity of ANNs to learn the complex non-linear relationships in fault diagnosis issues. As a breakthrough in artificial intelligence, deep learning holds the potential to overcome the aforementioned deficiencies. Through deep learning, deep neural networks (DNNs) with deep architectures, instead of shallow ones, could be established to mine the useful information from raw data and approximate complex non-linear functions. Based on DNNs, a novel intelligent method is proposed in this paper to overcome the deficiencies of the aforementioned intelligent diagnosis methods. The effectiveness of the proposed method is validated using datasets from rolling element bearings and planetary gearboxes. These datasets contain massive measured signals involving different health conditions under various operating conditions. The diagnosis results show that the proposed method is able to not only adaptively mine available fault characteristics from the measured signals, but also obtain superior diagnosis accuracy compared with the existing methods.

Wireless control system for two-axis linear oscillating motion applying CBR technology

NASA Astrophysics Data System (ADS)

Kuzyakov, O. N.; Andreeva, M. A.

2018-03-01

The paper presents the aspects of elaborating a movement control system. The system is to implement determination of movement characteristics of the object controlled, which performs an oscillating linear motion in a two-axis direction. The system has an electronic-optical principle of action: light receivers are attached to a controlled object, and a laser light emitter is attached to a static construction. While the object performs movement along the construction, the light emitter signal is registered by light receivers, based on which determination of the object position and characteristic of its movement are performed. An algorithm of system implementation is elaborated. Signal processing is performed on the basis of the case-based reasoning method. The system is to be used in machine-building industry in controlling relative displacement of the dynamic object or its assembly.

An Intrinsically Digital Amplification Scheme for Hearing Aids

NASA Astrophysics Data System (ADS)

Blamey, Peter J.; Macfarlane, David S.; Steele, Brenton R.

2005-12-01

Results for linear and wide-dynamic range compression were compared with a new 64-channel digital amplification strategy in three separate studies. The new strategy addresses the requirements of the hearing aid user with efficient computations on an open-platform digital signal processor (DSP). The new amplification strategy is not modeled on prior analog strategies like compression and linear amplification, but uses statistical analysis of the signal to optimize the output dynamic range in each frequency band independently. Using the open-platform DSP processor also provided the opportunity for blind trial comparisons of the different processing schemes in BTE and ITE devices of a high commercial standard. The speech perception scores and questionnaire results show that it is possible to provide improved audibility for sound in many narrow frequency bands while simultaneously improving comfort, speech intelligibility in noise, and sound quality.

Cosmic non-TEM radiation and synthetic feed array sensor system in ASIC mixed signal technology

NASA Astrophysics Data System (ADS)

Centureli, F.; Scotti, G.; Tommasino, P.; Trifiletti, A.; Romano, F.; Cimmino, R.; Saitto, A.

2014-08-01

The paper deals with the opportunity to introduce "Not strictly TEM waves" Synthetic detection Method (NTSM), consisting in a Three Axis Digital Beam Processing (3ADBP), to enhance the performances of radio telescope and sensor systems. Current Radio Telescopes generally use the classic 3D "TEM waves" approximation Detection Method, which consists in a linear tomography process (Single or Dual axis beam forming processing) neglecting the small z component. The Synthetic FEED ARRAY three axis Sensor SYSTEM is an innovative technique using a synthetic detection of the generic "NOT strictly TEM Waves radiation coming from the Cosmo, which processes longitudinal component of Angular Momentum too. Than the simultaneous extraction from radiation of both the linear and quadratic information component, may reduce the complexity to reconstruct the Early Universe in the different requested scales. This next order approximation detection of the observed cosmologic processes, may improve the efficacy of the statistical numerical model used to elaborate the same information acquired. The present work focuses on detection of such waves at carrier frequencies in the bands ranging from LF to MMW. The work shows in further detail the new generation of on line programmable and reconfigurable Mixed Signal ASIC technology that made possible the innovative Synthetic Sensor. Furthermore the paper shows the ability of such technique to increase the Radio Telescope Array Antenna performances.

Predicting Bradycardia in Preterm Infants Using Point Process Analysis of Heart Rate.

PubMed

Gee, Alan H; Barbieri, Riccardo; Paydarfar, David; Indic, Premananda

2017-09-01

Episodes of bradycardia are common and recur sporadically in preterm infants, posing a threat to the developing brain and other vital organs. We hypothesize that bradycardias are a result of transient temporal destabilization of the cardiac autonomic control system and that fluctuations in the heart rate signal might contain information that precedes bradycardia. We investigate infant heart rate fluctuations with a novel application of point process theory. In ten preterm infants, we estimate instantaneous linear measures of the heart rate signal, use these measures to extract statistical features of bradycardia, and propose a simplistic framework for prediction of bradycardia. We present the performance of a prediction algorithm using instantaneous linear measures (mean area under the curve = 0.79 ± 0.018) for over 440 bradycardia events. The algorithm achieves an average forecast time of 116 s prior to bradycardia onset (FPR = 0.15). Our analysis reveals that increased variance in the heart rate signal is a precursor of severe bradycardia. This increase in variance is associated with an increase in power from low content dynamics in the LF band (0.04-0.2 Hz) and lower multiscale entropy values prior to bradycardia. Point process analysis of the heartbeat time series reveals instantaneous measures that can be used to predict infant bradycardia prior to onset. Our findings are relevant to risk stratification, predictive monitoring, and implementation of preventative strategies for reducing morbidity and mortality associated with bradycardia in neonatal intensive care units.

The DCU: the detector control unit of the SAFARI instrument onboard SPICA

NASA Astrophysics Data System (ADS)

Clénet, A.; Ravera, L.; Bertrand, B.; Cros, A.; Hou, R.; Jackson, B. D.; van Leeuwen, B. J.; Van Loon, D.; Parot, Y.; Pointecouteau, E.; Sournac, A.; Ta, N.

2012-09-01

The SpicA FAR infrared Instrument (SAFARI) is a European instrument for the infrared domain telescope SPICA, a JAXA space mission. The SAFARI detectors are Transistor Edge Sensors (TES) arranged in 3 matrixes. The TES front end electronic is based on Superconducting Quantum Interference Devices (SQUIDs) and it does the readout of the 3500 detectors with Frequency Division Multiplexing (FDM) type architecture. The Detector Control Unit (DCU), contributed by IRAP, manages the readout of the TES by computing and providing the AC-bias signals (1 - 3 MHz) to the TES and by computing the demodulation of the returning signals. The SQUID being highly non-linear, the DCU has also to provide a feedback signal to increase the SQUID dynamic. Because of the propagation delay in the cables and the processing time, a classic feedback will not be stable for AC-bias frequencies up to 3 MHz. The DCU uses a specific technique to compensate for those delays: the BaseBand FeedBack (BBFB). This digital data processing is done for the 3500 pixels in parallel. Thus, to keep the DCU power budget within its allocation we have to specifically optimize the architecture of the digital circuit with respect to the power consumption. In this paper we will mainly present the DCU architecture. We will particularly focus on the BBFB technique used to linearize the SQUID and on the optimization done to reduce the power consumption of the digital processing circuit.

Digital algorithms for parallel pipelined single-detector homodyne fringe counting in laser interferometry

NASA Astrophysics Data System (ADS)

Rerucha, Simon; Sarbort, Martin; Hola, Miroslava; Cizek, Martin; Hucl, Vaclav; Cip, Ondrej; Lazar, Josef

2016-12-01

The homodyne detection with only a single detector represents a promising approach in the interferometric application which enables a significant reduction of the optical system complexity while preserving the fundamental resolution and dynamic range of the single frequency laser interferometers. We present the design, implementation and analysis of algorithmic methods for computational processing of the single-detector interference signal based on parallel pipelined processing suitable for real time implementation on a programmable hardware platform (e.g. the FPGA - Field Programmable Gate Arrays or the SoC - System on Chip). The algorithmic methods incorporate (a) the single detector signal (sine) scaling, filtering, demodulations and mixing necessary for the second (cosine) quadrature signal reconstruction followed by a conic section projection in Cartesian plane as well as (a) the phase unwrapping together with the goniometric and linear transformations needed for the scale linearization and periodic error correction. The digital computing scheme was designed for bandwidths up to tens of megahertz which would allow to measure the displacements at the velocities around half metre per second. The algorithmic methods were tested in real-time operation with a PC-based reference implementation that employed the advantage pipelined processing by balancing the computational load among multiple processor cores. The results indicate that the algorithmic methods are suitable for a wide range of applications [3] and that they are bringing the fringe counting interferometry closer to the industrial applications due to their optical setup simplicity and robustness, computational stability, scalability and also a cost-effectiveness.

Linearized Programming of Memristors for Artificial Neuro-Sensor Signal Processing

PubMed Central

Yang, Changju; Kim, Hyongsuk

2016-01-01

A linearized programming method of memristor-based neural weights is proposed. Memristor is known as an ideal element to implement a neural synapse due to its embedded functions of analog memory and analog multiplication. Its resistance variation with a voltage input is generally a nonlinear function of time. Linearization of memristance variation about time is very important for the easiness of memristor programming. In this paper, a method utilizing an anti-serial architecture for linear programming is proposed. The anti-serial architecture is composed of two memristors with opposite polarities. It linearizes the variation of memristance due to complimentary actions of two memristors. For programming a memristor, additional memristor with opposite polarity is employed. The linearization effect of weight programming of an anti-serial architecture is investigated and memristor bridge synapse which is built with two sets of anti-serial memristor architecture is taken as an application example of the proposed method. Simulations are performed with memristors of both linear drift model and nonlinear model. PMID:27548186

Linearized Programming of Memristors for Artificial Neuro-Sensor Signal Processing.

PubMed

Yang, Changju; Kim, Hyongsuk

2016-08-19

A linearized programming method of memristor-based neural weights is proposed. Memristor is known as an ideal element to implement a neural synapse due to its embedded functions of analog memory and analog multiplication. Its resistance variation with a voltage input is generally a nonlinear function of time. Linearization of memristance variation about time is very important for the easiness of memristor programming. In this paper, a method utilizing an anti-serial architecture for linear programming is proposed. The anti-serial architecture is composed of two memristors with opposite polarities. It linearizes the variation of memristance due to complimentary actions of two memristors. For programming a memristor, additional memristor with opposite polarity is employed. The linearization effect of weight programming of an anti-serial architecture is investigated and memristor bridge synapse which is built with two sets of anti-serial memristor architecture is taken as an application example of the proposed method. Simulations are performed with memristors of both linear drift model and nonlinear model.

Nonlinear Estimation of Discrete-Time Signals Under Random Observation Delay

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

Caballero-Aguila, R.; Jimenez-Lopez, J. D.; Hermoso-Carazo, A.

2008-11-06

This paper presents an approximation to the nonlinear least-squares estimation problem of discrete-time stochastic signals using nonlinear observations with additive white noise which can be randomly delayed by one sampling time. The observation delay is modelled by a sequence of independent Bernoulli random variables whose values, zero or one, indicate that the real observation arrives on time or it is delayed and, hence, the available measurement to estimate the signal is not up-to-date. Assuming that the state-space model generating the signal is unknown and only the covariance functions of the processes involved in the observation equation are ready for use,more » a filtering algorithm based on linear approximations of the real observations is proposed.« less

3-D readout-electronics packaging for high-bandwidth massively paralleled imager

DOEpatents

Kwiatkowski, Kris; Lyke, James

2007-12-18

Dense, massively parallel signal processing electronics are co-packaged behind associated sensor pixels. Microchips containing a linear or bilinear arrangement of photo-sensors, together with associated complex electronics, are integrated into a simple 3-D structure (a "mirror cube"). An array of photo-sensitive cells are disposed on a stacked CMOS chip's surface at a 45.degree. angle from light reflecting mirror surfaces formed on a neighboring CMOS chip surface. Image processing electronics are held within the stacked CMOS chip layers. Electrical connections couple each of said stacked CMOS chip layers and a distribution grid, the connections for distributing power and signals to components associated with each stacked CSMO chip layer.

A distributed code for color in natural scenes derived from center-surround filtered cone signals

PubMed Central

Kellner, Christian J.; Wachtler, Thomas

2013-01-01

In the retina of trichromatic primates, chromatic information is encoded in an opponent fashion and transmitted to the lateral geniculate nucleus (LGN) and visual cortex via parallel pathways. Chromatic selectivities of neurons in the LGN form two separate clusters, corresponding to two classes of cone opponency. In the visual cortex, however, the chromatic selectivities are more distributed, which is in accordance with a population code for color. Previous studies of cone signals in natural scenes typically found opponent codes with chromatic selectivities corresponding to two directions in color space. Here we investigated how the non-linear spatio-chromatic filtering in the retina influences the encoding of color signals. Cone signals were derived from hyper-spectral images of natural scenes and preprocessed by center-surround filtering and rectification, resulting in parallel ON and OFF channels. Independent Component Analysis (ICA) on these signals yielded a highly sparse code with basis functions that showed spatio-chromatic selectivities. In contrast to previous analyses of linear transformations of cone signals, chromatic selectivities were not restricted to two main chromatic axes, but were more continuously distributed in color space, similar to the population code of color in the early visual cortex. Our results indicate that spatio-chromatic processing in the retina leads to a more distributed and more efficient code for natural scenes. PMID:24098289

Improved measurement linearity and precision for AMCW time-of-flight range imaging cameras.

PubMed

Payne, Andrew D; Dorrington, Adrian A; Cree, Michael J; Carnegie, Dale A

2010-08-10

Time-of-flight range imaging systems utilizing the amplitude modulated continuous wave (AMCW) technique often suffer from measurement nonlinearity due to the presence of aliased harmonics within the amplitude modulation signals. Typically a calibration is performed to correct these errors. We demonstrate an alternative phase encoding approach that attenuates the harmonics during the sampling process, thereby improving measurement linearity in the raw measurements. This mitigates the need to measure the system's response or calibrate for environmental changes. In conjunction with improved linearity, we demonstrate that measurement precision can also be increased by reducing the duty cycle of the amplitude modulated illumination source (while maintaining overall illumination power).

A new class of random processes with application to helicopter noise

NASA Technical Reports Server (NTRS)

Hardin, Jay C.; Miamee, A. G.

1989-01-01

The concept of dividing random processes into classes (e.g., stationary, locally stationary, periodically correlated, and harmonizable) has long been employed. A new class of random processes is introduced which includes many of these processes as well as other interesting processes which fall into none of the above classes. Such random processes are denoted as linearly correlated. This class is shown to include the familiar stationary and periodically correlated processes as well as many other, both harmonizable and non-harmonizable, nonstationary processes. When a process is linearly correlated for all t and harmonizable, its two-dimensional power spectral density S(x) (omega 1, omega 2) is shown to take a particularly simple form, being non-zero only on lines such that omega 1 to omega 2 = + or - r(k) where the r(k's) are (not necessarily equally spaced) roots of a characteristic function. The relationship of such processes to the class of stationary processes is examined. In addition, the application of such processes in the analysis of typical helicopter noise signals is described.

A new class of random processes with application to helicopter noise

NASA Technical Reports Server (NTRS)

Hardin, Jay C.; Miamee, A. G.

1989-01-01

The concept of dividing random processes into classes (e.g., stationary, locally stationary, periodically correlated, and harmonizable) has long been employed. A new class of random processes is introduced which includes many of these processes as well as other interesting processes which fall into none of the above classes. Such random processes are denoted as linearly correlated. This class is shown to include the familiar stationary and periodically correlated processes as well as many other, both harmonizable and non-harmonizable, nonstationary processes. When a process is linearly correlated for all t and harmonizable, its two-dimensional power spectral density S(x)(omega 1, omega 2) is shown to take a particularly simple form, being non-zero only on lines such that omega 1 to omega 2 = + or - r(k) where the r(k's) are (not necessarily equally spaced) roots of a characteristic function. The relationship of such processes to the class of stationary processes is examined. In addition, the application of such processes in the analysis of typical helicopter noise signals is described.

Run charts revisited: a simulation study of run chart rules for detection of non-random variation in health care processes.

PubMed

Anhøj, Jacob; Olesen, Anne Vingaard

2014-01-01

A run chart is a line graph of a measure plotted over time with the median as a horizontal line. The main purpose of the run chart is to identify process improvement or degradation, which may be detected by statistical tests for non-random patterns in the data sequence. We studied the sensitivity to shifts and linear drifts in simulated processes using the shift, crossings and trend rules for detecting non-random variation in run charts. The shift and crossings rules are effective in detecting shifts and drifts in process centre over time while keeping the false signal rate constant around 5% and independent of the number of data points in the chart. The trend rule is virtually useless for detection of linear drift over time, the purpose it was intended for.

Grid-Independent Compressive Imaging and Fourier Phase Retrieval

ERIC Educational Resources Information Center

Liao, Wenjing

2013-01-01

This dissertation is composed of two parts. In the first part techniques of band exclusion(BE) and local optimization(LO) are proposed to solve linear continuum inverse problems independently of the grid spacing. The second part is devoted to the Fourier phase retrieval problem. Many situations in optics, medical imaging and signal processing call…

Signal Detection Methods and Discriminant Analysis Applied to Categorization of Newspaper and Government Documents: A Preliminary Study.

ERIC Educational Resources Information Center

Ng, Kwong Bor; Rieh, Soo Young; Kantor, Paul

2000-01-01

Discussion of natural language processing focuses on experiments using linear discriminant analysis to distinguish "Wall Street Journal" texts from "Federal Register" tests using information about the frequency of occurrence of word boundaries, sentence boundaries, and punctuation marks. Displays and interprets results in terms…

Electrochemical Probing through a Redox Capacitor To Acquire Chemical Information on Biothiols

PubMed Central

2016-01-01

The acquisition of chemical information is a critical need for medical diagnostics, food/environmental monitoring, and national security. Here, we report an electrochemical information processing approach that integrates (i) complex electrical inputs/outputs, (ii) mediators to transduce the electrical I/O into redox signals that can actively probe the chemical environment, and (iii) a redox capacitor that manipulates signals for information extraction. We demonstrate the capabilities of this chemical information processing strategy using biothiols because of the emerging importance of these molecules in medicine and because their distinct chemical properties allow evaluation of hypothesis-driven information probing. We show that input sequences can be tailored to probe for chemical information both qualitatively (step inputs probe for thiol-specific signatures) and quantitatively. Specifically, we observed picomolar limits of detection and linear responses to concentrations over 5 orders of magnitude (1 pM–0.1 μM). This approach allows the capabilities of signal processing to be extended for rapid, robust, and on-site analysis of chemical information. PMID:27385047

Electrochemical Probing through a Redox Capacitor To Acquire Chemical Information on Biothiols.

PubMed

Liu, Zhengchun; Liu, Yi; Kim, Eunkyoung; Bentley, William E; Payne, Gregory F

2016-07-19

The acquisition of chemical information is a critical need for medical diagnostics, food/environmental monitoring, and national security. Here, we report an electrochemical information processing approach that integrates (i) complex electrical inputs/outputs, (ii) mediators to transduce the electrical I/O into redox signals that can actively probe the chemical environment, and (iii) a redox capacitor that manipulates signals for information extraction. We demonstrate the capabilities of this chemical information processing strategy using biothiols because of the emerging importance of these molecules in medicine and because their distinct chemical properties allow evaluation of hypothesis-driven information probing. We show that input sequences can be tailored to probe for chemical information both qualitatively (step inputs probe for thiol-specific signatures) and quantitatively. Specifically, we observed picomolar limits of detection and linear responses to concentrations over 5 orders of magnitude (1 pM-0.1 μM). This approach allows the capabilities of signal processing to be extended for rapid, robust, and on-site analysis of chemical information.

Integrated Sensing and Processing (ISP) Phase 2: Demonstration and Evaluation for Distributed Sensor Networks and Missile Seeker Systems

DTIC Science & Technology

2007-05-29

International Conference Acoustics Speech and Signal Processing (ICASSP 2007) conference 15 − 20 April 2007 in Honolulu, Hawaii. 1. E. Near Term...from the sensor measured in feet. The detection performance of the footstep in the presence of interfering speech was characterized in previously...investigation, we developed a simple piecewise linear approximation to the probability of detection curve with no interfering speech . This approximation was

New instrument for on-line viscosity measurement of fermentation media.

PubMed

Picque, D; Corrieu, G

1988-01-01

In an attempt to resolve the difficult problem of on-line determination of the viscosity of non-Newtonian fermentation media, the authors have used a vibrating rod sensor mounted on a bioreactor. The sensor signal decreases nonlinearly with increased apparent viscosity. Electronic filtering of the signal damps the interfering effect of aeration and mechanical agitation. Sensor drift is very low (0.03% of measured value per hour). On the rheological level the sensor is primarily an empirical tool that must be specifically calibrated for each fermentation process. Once this is accomplished, it becomes possible to establish linear or second-degree correlations between the electrical signal from the sensor and the essential parameters of the fermentation process in question (pH of a fermented milk during acidification, concentration of extra cellular polysaccharide). In addition, by applying the power law to describe the rheological behavior of fermentation media, we observe a second-order polynomial correlation between the sensor signal and the behavior index (n).

Computation of linear acceleration through an internal model in the macaque cerebellum

PubMed Central

Laurens, Jean; Meng, Hui; Angelaki, Dora E.

2013-01-01

A combination of theory and behavioral findings has supported a role for internal models in the resolution of sensory ambiguities and sensorimotor processing. Although the cerebellum has been proposed as a candidate for implementation of internal models, concrete evidence from neural responses is lacking. Here we exploit un-natural motion stimuli, which induce incorrect self-motion perception and eye movements, to explore the neural correlates of an internal model proposed to compensate for Einstein’s equivalence principle and generate neural estimates of linear acceleration and gravity. We show that caudal cerebellar vermis Purkinje cells and cerebellar nuclei neurons selective for actual linear acceleration also encode erroneous linear acceleration, as expected from the internal model hypothesis, even when no actual linear acceleration occurs. These findings provide strong evidence that the cerebellum might be involved in the implementation of internal models that mimic physical principles to interpret sensory signals, as previously hypothesized by theorists. PMID:24077562

Signal processing for distributed sensor concept: DISCO

NASA Astrophysics Data System (ADS)

Rafailov, Michael K.

2007-04-01

Distributed Sensor concept - DISCO proposed for multiplication of individual sensor capabilities through cooperative target engagement. DISCO relies on ability of signal processing software to format, to process and to transmit and receive sensor data and to exploit those data in signal synthesis process. Each sensor data is synchronized formatted, Signal-to-Noise Ration (SNR) enhanced and distributed inside of the sensor network. Signal processing technique for DISCO is Recursive Adaptive Frame Integration of Limited data - RAFIL technique that was initially proposed [1] as a way to improve the SNR, reduce data rate and mitigate FPA correlated noise of an individual sensor digital video-signal processing. In Distributed Sensor Concept RAFIL technique is used in segmented way, when constituencies of the technique are spatially and/or temporally separated between transmitters and receivers. Those constituencies include though not limited to two thresholds - one is tuned for optimum probability of detection, the other - to manage required false alarm rate, and limited frame integration placed somewhere between the thresholds as well as formatters, conventional integrators and more. RAFIL allows a non-linear integration that, along with SNR gain, provides system designers more capability where cost, weight, or power considerations limit system data rate, processing, or memory capability [2]. DISCO architecture allows flexible optimization of SNR gain, data rates and noise suppression on sensor's side and limited integration, re-formatting and final threshold on node's side. DISCO with Recursive Adaptive Frame Integration of Limited data may have flexible architecture that allows segmenting the hardware and software to be best suitable for specific DISCO applications and sensing needs - whatever it is air-or-space platforms, ground terminals or integration of sensors network.

Biosensor Architectures for High-Fidelity Reporting of Cellular Signaling

PubMed Central

Dushek, Omer; Lellouch, Annemarie C.; Vaux, David J.; Shahrezaei, Vahid

2014-01-01

Understanding mechanisms of information processing in cellular signaling networks requires quantitative measurements of protein activities in living cells. Biosensors are molecular probes that have been developed to directly track the activity of specific signaling proteins and their use is revolutionizing our understanding of signal transduction. The use of biosensors relies on the assumption that their activity is linearly proportional to the activity of the signaling protein they have been engineered to track. We use mechanistic mathematical models of common biosensor architectures (single-chain FRET-based biosensors), which include both intramolecular and intermolecular reactions, to study the validity of the linearity assumption. As a result of the classic mechanism of zero-order ultrasensitivity, we find that biosensor activity can be highly nonlinear so that small changes in signaling protein activity can give rise to large changes in biosensor activity and vice versa. This nonlinearity is abolished in architectures that favor the formation of biosensor oligomers, but oligomeric biosensors produce complicated FRET states. Based on this finding, we show that high-fidelity reporting is possible when a single-chain intermolecular biosensor is used that cannot undergo intramolecular reactions and is restricted to forming dimers. We provide phase diagrams that compare various trade-offs, including observer effects, which further highlight the utility of biosensor architectures that favor intermolecular over intramolecular binding. We discuss challenges in calibrating and constructing biosensors and highlight the utility of mathematical models in designing novel probes for cellular signaling. PMID:25099816

Progress and opportunities in EELS and EDS tomography.

PubMed

Collins, Sean M; Midgley, Paul A

2017-09-01

Electron tomography using energy loss and X-ray spectroscopy in the electron microscope continues to develop in rapidly evolving and diverse directions, enabling new insight into the three-dimensional chemistry and physics of nanoscale volumes. Progress has been made recently in improving reconstructions from EELS and EDS signals in electron tomography by applying compressed sensing methods, characterizing new detector technologies in detail, deriving improved models of signal generation, and exploring machine learning approaches to signal processing. These disparate threads can be brought together in a cohesive framework in terms of a model-based approach to analytical electron tomography. Models incorporate information on signal generation and detection as well as prior knowledge of structures in the spectrum image data. Many recent examples illustrate the flexibility of this approach and its feasibility for addressing challenges in non-linear or limited signals in EELS and EDS tomography. Further work in combining multiple imaging and spectroscopy modalities, developing synergistic data acquisition, processing, and reconstruction approaches, and improving the precision of quantitative spectroscopic tomography will expand the frontiers of spatial resolution, dose limits, and maximal information recovery. Copyright © 2017 Elsevier B.V. All rights reserved.

Out-Phased Array Linearized Signaling (OPALS): A Practical Approach to Physical Layer Encryption

DTIC Science & Technology

2015-10-26

Out-Phased Array Linearized Signaling ( OPALS ): A Practical Approach to Physical Layer Encryption Eric Tollefson, Bruce R. Jordan Jr., and Joseph D... OPALS ) which provides a practical approach to physical-layer encryption through spatial masking. Our approach modifies just the transmitter to employ...of the channel. With Out-Phased Array Linearized Signaling ( OPALS ), we propose a new masking technique that has some advantages of each of the

Sparsity-Cognizant Algorithms with Applications to Communications, Signal Processing, and the Smart Grid

NASA Astrophysics Data System (ADS)

Zhu, Hao

Sparsity plays an instrumental role in a plethora of scientific fields, including statistical inference for variable selection, parsimonious signal representations, and solving under-determined systems of linear equations - what has led to the ground-breaking result of compressive sampling (CS). This Thesis leverages exciting ideas of sparse signal reconstruction to develop sparsity-cognizant algorithms, and analyze their performance. The vision is to devise tools exploiting the 'right' form of sparsity for the 'right' application domain of multiuser communication systems, array signal processing systems, and the emerging challenges in the smart power grid. Two important power system monitoring tasks are addressed first by capitalizing on the hidden sparsity. To robustify power system state estimation, a sparse outlier model is leveraged to capture the possible corruption in every datum, while the problem nonconvexity due to nonlinear measurements is handled using the semidefinite relaxation technique. Different from existing iterative methods, the proposed algorithm approximates well the global optimum regardless of the initialization. In addition, for enhanced situational awareness, a novel sparse overcomplete representation is introduced to capture (possibly multiple) line outages, and develop real-time algorithms for solving the combinatorially complex identification problem. The proposed algorithms exhibit near-optimal performance while incurring only linear complexity in the number of lines, which makes it possible to quickly bring contingencies to attention. This Thesis also accounts for two basic issues in CS, namely fully-perturbed models and the finite alphabet property. The sparse total least-squares (S-TLS) approach is proposed to furnish CS algorithms for fully-perturbed linear models, leading to statistically optimal and computationally efficient solvers. The S-TLS framework is well motivated for grid-based sensing applications and exhibits higher accuracy than existing sparse algorithms. On the other hand, exploiting the finite alphabet of unknown signals emerges naturally in communication systems, along with sparsity coming from the low activity of each user. Compared to approaches only accounting for either one of the two, joint exploitation of both leads to statistically optimal detectors with improved error performance.

Auxin-BR Interaction Regulates Plant Growth and Development

PubMed Central

Tian, Huiyu; Lv, Bingsheng; Ding, Tingting; Bai, Mingyi; Ding, Zhaojun

2018-01-01

Plants develop a high flexibility to alter growth, development, and metabolism to adapt to the ever-changing environments. Multiple signaling pathways are involved in these processes and the molecular pathways to transduce various developmental signals are not linear but are interconnected by a complex network and even feedback mutually to achieve the final outcome. This review will focus on two important plant hormones, auxin and brassinosteroid (BR), based on the most recent progresses about these two hormone regulated plant growth and development in Arabidopsis, and highlight the cross-talks between these two phytohormones. PMID:29403511

n-Iterative Exponential Forgetting Factor for EEG Signals Parameter Estimation

PubMed Central

Palma Orozco, Rosaura

2018-01-01

Electroencephalograms (EEG) signals are of interest because of their relationship with physiological activities, allowing a description of motion, speaking, or thinking. Important research has been developed to take advantage of EEG using classification or predictor algorithms based on parameters that help to describe the signal behavior. Thus, great importance should be taken to feature extraction which is complicated for the Parameter Estimation (PE)–System Identification (SI) process. When based on an average approximation, nonstationary characteristics are presented. For PE the comparison of three forms of iterative-recursive uses of the Exponential Forgetting Factor (EFF) combined with a linear function to identify a synthetic stochastic signal is presented. The one with best results seen through the functional error is applied to approximate an EEG signal for a simple classification example, showing the effectiveness of our proposal. PMID:29568310

Seismic Linear Noise Attenuation with Use of Radial Transform

NASA Astrophysics Data System (ADS)

Szymańska-Małysa, Żaneta

2018-03-01

One of the goals of seismic data processing is to attenuate the recorded noise in order to enable correct interpretation of the image. Radial transform has been used as a very effective tool in the attenuation of various types of linear noise, both numerical and real (such as ground roll, direct waves, head waves, guided waves etc). The result of transformation from offset - time (X - T) domain into apparent velocity - time (R - T) domain is frequency separation between reflections and linear events. In this article synthetic and real seismic shot gathers were examined. One example was targeted at far offset area of dataset where reflections and noise had similar apparent velocities and frequency bands. Another example was a result of elastic modelling where linear artefacts were produced. Bandpass filtering and scaling operation executed in radial domain attenuated all discussed types of linear noise very effectively. After noise reduction all further processing steps reveal better results, especially velocity analysis, migration and stacking. In all presented cases signal-to-noise ratio was significantly increased and reflections covered previously by noise were revealed. Power spectra of filtered seismic records preserved real dynamics of reflections.

A SOUND SOURCE LOCALIZATION TECHNIQUE TO SUPPORT SEARCH AND RESCUE IN LOUD NOISE ENVIRONMENTS

NASA Astrophysics Data System (ADS)

Yoshinaga, Hiroshi; Mizutani, Koichi; Wakatsuki, Naoto

At some sites of earthquakes and other disasters, rescuers search for people buried under rubble by listening for the sounds which they make. Thus developing a technique to localize sound sources amidst loud noise will support such search and rescue operations. In this paper, we discuss an experiment performed to test an array signal processing technique which searches for unperceivable sound in loud noise environments. Two speakers simultaneously played a noise of a generator and a voice decreased by 20 dB (= 1/100 of power) from the generator noise at an outdoor space where cicadas were making noise. The sound signal was received by a horizontally set linear microphone array 1.05 m in length and consisting of 15 microphones. The direction and the distance of the voice were computed and the sound of the voice was extracted and played back as an audible sound by array signal processing.

Visual Detection Under Uncertainty Operates Via an Early Static, Not Late Dynamic, Non-Linearity

PubMed Central

Neri, Peter

2010-01-01

Signals in the environment are rarely specified exactly: our visual system may know what to look for (e.g., a specific face), but not its exact configuration (e.g., where in the room, or in what orientation). Uncertainty, and the ability to deal with it, is a fundamental aspect of visual processing. The MAX model is the current gold standard for describing how human vision handles uncertainty: of all possible configurations for the signal, the observer chooses the one corresponding to the template associated with the largest response. We propose an alternative model in which the MAX operation, which is a dynamic non-linearity (depends on multiple inputs from several stimulus locations) and happens after the input stimulus has been matched to the possible templates, is replaced by an early static non-linearity (depends only on one input corresponding to one stimulus location) which is applied before template matching. By exploiting an integrated set of analytical and experimental tools, we show that this model is able to account for a number of empirical observations otherwise unaccounted for by the MAX model, and is more robust with respect to the realistic limitations imposed by the available neural hardware. We then discuss how these results, currently restricted to a simple visual detection task, may extend to a wider range of problems in sensory processing. PMID:21212835

Effects of optical attenuation, heat diffusion, and acoustic coherence in photoacoustic signals produced by nanoparticles

NASA Astrophysics Data System (ADS)

Alba-Rosales, J. E.; Ramos-Ortiz, G.; Escamilla-Herrera, L. F.; Reyes-Ramírez, B.; Polo-Parada, L.; Gutiérrez-Juárez, G.

2018-04-01

The behavior of the photoacoustic signal produced by nanoparticles as a function of their concentration was studied in detail. As the concentration of nanoparticles is increased in a sample, the peak-to-peak photoacoustic amplitude increases linearly up to a certain value, after which an asymptotic saturated behavior is observed. To elucidate the mechanisms responsible for these observations, we evaluate the effects of nanoparticles concentration, the optical attenuation, and the effects of heat propagation from nano-sources to their surroundings. We found that the saturation effect of the photoacoustic signal as a function of the concentration of nanoparticles is explained by a combination of two different mechanisms. As has been suggested previously, but not modeled correctly, the most important mechanism is attributed to optical attenuation. The second mechanism is due to an interference destructive process attributed to the superimposition of the photoacoustic amplitudes generated for each nanoparticle, and this explanation is reinforced through our experimental and simulations results; based on this, it is found that the linear behavior of the photoacoustic amplitude could be restricted to optical densities ≤0.5.

Equivalence of linear canonical transform domains to fractional Fourier domains and the bicanonical width product: a generalization of the space-bandwidth product.

PubMed

Oktem, Figen S; Ozaktas, Haldun M

2010-08-01

Linear canonical transforms (LCTs) form a three-parameter family of integral transforms with wide application in optics. We show that LCT domains correspond to scaled fractional Fourier domains and thus to scaled oblique axes in the space-frequency plane. This allows LCT domains to be labeled and ordered by the corresponding fractional order parameter and provides insight into the evolution of light through an optical system modeled by LCTs. If a set of signals is highly confined to finite intervals in two arbitrary LCT domains, the space-frequency (phase space) support is a parallelogram. The number of degrees of freedom of this set of signals is given by the area of this parallelogram, which is equal to the bicanonical width product but usually smaller than the conventional space-bandwidth product. The bicanonical width product, which is a generalization of the space-bandwidth product, can provide a tighter measure of the actual number of degrees of freedom, and allows us to represent and process signals with fewer samples.

A simple two-stage model predicts response time distributions.

PubMed

Carpenter, R H S; Reddi, B A J; Anderson, A J

2009-08-15

The neural mechanisms underlying reaction times have previously been modelled in two distinct ways. When stimuli are hard to detect, response time tends to follow a random-walk model that integrates noisy sensory signals. But studies investigating the influence of higher-level factors such as prior probability and response urgency typically use highly detectable targets, and response times then usually correspond to a linear rise-to-threshold mechanism. Here we show that a model incorporating both types of element in series - a detector integrating noisy afferent signals, followed by a linear rise-to-threshold performing decision - successfully predicts not only mean response times but, much more stringently, the observed distribution of these times and the rate of decision errors over a wide range of stimulus detectability. By reconciling what previously may have seemed to be conflicting theories, we are now closer to having a complete description of reaction time and the decision processes that underlie it.

Acquisition and Tracking Behavior of Phase-Locked Loops

NASA Technical Reports Server (NTRS)

Viterbi, A. J.

1958-01-01

Phase-locked or APC loops have found increasing applications in recent years as tracking filters, synchronizing devices, and narrowband FM discriminators. Considerable work has been performed to determine the noise-squelching properties of the loop when it is operating in or near phase lock and is functioning as a linear coherent detector. However, insufficient consideration has been devoted to the non-linear behavior of the loop when it is out of lock and in the process of pulling in. Experimental evidence has indicated that there is a strong tendency for phase-locked loops to achieve lock under most circumstances. However, the analysis which has appeared in the literature iis limited to the acquisition of a constant frequency reference signal with only one phase-locked loop filter configuration. This work represents an investigation of frequency acquisition properties of phase-locked loops for a variety of reference-signal behavior and loop configurations

Low sidelobe level and high time resolution for metallic ultrasonic testing with linear-chirp-Golay coded excitation

NASA Astrophysics Data System (ADS)

Zhang, Jiaying; Gang, Tie; Ye, Chaofeng; Cong, Sen

2018-04-01

Linear-chirp-Golay (LCG)-coded excitation combined with pulse compression is proposed in this paper to improve the time resolution and suppress sidelobe in ultrasonic testing. The LCG-coded excitation is binary complementary pair Golay signal with linear-chirp signal applied on every sub pulse. Compared with conventional excitation which is a common ultrasonic testing method using a brief narrow pulse as exciting signal, the performances of LCG-coded excitation, in terms of time resolution improvement and sidelobe suppression, are studied via numerical and experimental investigations. The numerical simulations are implemented using Matlab K-wave toolbox. It is seen from the simulation results that time resolution of LCG excitation is 35.5% higher and peak sidelobe level (PSL) is 57.6 dB lower than linear-chirp excitation with 2.4 MHz chirp bandwidth and 3 μs time duration. In the B-scan experiment, time resolution of LCG excitation is higher and PSL is lower than conventional brief pulse excitation and chirp excitation. In terms of time resolution, LCG-coded signal has better performance than chirp signal. Moreover, the impact of chirp bandwidth on LCG-coded signal is less than that on chirp signal. In addition, the sidelobe of LCG-coded signal is lower than that of chirp signal with pulse compression.

Intelligent Automatic Right-Left Sign Lamp Based on Brain Signal Recognition System

NASA Astrophysics Data System (ADS)

Winda, A.; Sofyan; Sthevany; Vincent, R. S.

2017-12-01

Comfort as a part of the human factor, plays important roles in nowadays advanced automotive technology. Many of the current technologies go in the direction of automotive driver assistance features. However, many of the driver assistance features still require physical movement by human to enable the features. In this work, the proposed method is used in order to make certain feature to be functioning without any physical movement, instead human just need to think about it in their mind. In this work, brain signal is recorded and processed in order to be used as input to the recognition system. Right-Left sign lamp based on the brain signal recognition system can potentially replace the button or switch of the specific device in order to make the lamp work. The system then will decide whether the signal is ‘Right’ or ‘Left’. The decision of the Right-Left side of brain signal recognition will be sent to a processing board in order to activate the automotive relay, which will be used to activate the sign lamp. Furthermore, the intelligent system approach is used to develop authorized model based on the brain signal. Particularly Support Vector Machines (SVMs)-based classification system is used in the proposed system to recognize the Left-Right of the brain signal. Experimental results confirm the effectiveness of the proposed intelligent Automatic brain signal-based Right-Left sign lamp access control system. The signal is processed by Linear Prediction Coefficient (LPC) and Support Vector Machines (SVMs), and the resulting experiment shows the training and testing accuracy of 100% and 80%, respectively.

Scene Analysis: Non-Linear Spatial Filtering for Automatic Target Detection.

DTIC Science & Technology

1982-12-01

In this thesis, a method for two-dimensional pattern recognition was developed and tested. The method included a global search scheme for candidate...test global switch TYPEO Creating negative video file only.W 11=0 12=256 13=512 14=768 GO 70 2 1 TYPE" Creating negative and horizontally flipped video...purpose was to develop a base of image processing software for the AFIT Digital Signal Processing Laboratory NOVA- ECLIPSE minicomputer system, for

The application of charge-coupled device processors in automatic-control systems

NASA Technical Reports Server (NTRS)

Mcvey, E. S.; Parrish, E. A., Jr.

1977-01-01

The application of charge-coupled device (CCD) processors to automatic-control systems is suggested. CCD processors are a new form of semiconductor component with the unique ability to process sampled signals on an analog basis. Specific implementations of controllers are suggested for linear time-invariant, time-varying, and nonlinear systems. Typical processing time should be only a few microseconds. This form of technology may become competitive with microprocessors and minicomputers in addition to supplementing them.

Smoke detection

DOEpatents

Warmack, Robert J. Bruce; Wolf, Dennis A.; Frank, Steven Shane

2016-09-06

Various apparatus and methods for smoke detection are disclosed. In one embodiment, a method of training a classifier for a smoke detector comprises inputting sensor data from a plurality of tests into a processor. The sensor data is processed to generate derived signal data corresponding to the test data for respective tests. The derived signal data is assigned into categories comprising at least one fire group and at least one non-fire group. Linear discriminant analysis (LDA) training is performed by the processor. The derived signal data and the assigned categories for the derived signal data are inputs to the LDA training. The output of the LDA training is stored in a computer readable medium, such as in a smoke detector that uses LDA to determine, based on the training, whether present conditions indicate the existence of a fire.

Smoke detection

DOEpatents

Warmack, Robert J. Bruce; Wolf, Dennis A.; Frank, Steven Shane

2015-10-27

Various apparatus and methods for smoke detection are disclosed. In one embodiment, a method of training a classifier for a smoke detector comprises inputting sensor data from a plurality of tests into a processor. The sensor data is processed to generate derived signal data corresponding to the test data for respective tests. The derived signal data is assigned into categories comprising at least one fire group and at least one non-fire group. Linear discriminant analysis (LDA) training is performed by the processor. The derived signal data and the assigned categories for the derived signal data are inputs to the LDA training. The output of the LDA training is stored in a computer readable medium, such as in a smoke detector that uses LDA to determine, based on the training, whether present conditions indicate the existence of a fire.

Human Language Technology: Opportunities and Challenges

DTIC Science & Technology

2005-01-01

because of the connections to and reliance on signal processing. Audio diarization critically includes indexing of speakers [12], since speaker ...to reduce inter- speaker variability in training. Standard techniques include vocal-tract length normalization, adaptation of acoustic models using...maximum likelihood linear regression (MLLR), and speaker -adaptive training based on MLLR. The acoustic models are mixtures of Gaussians, typically with

An Evaluation of Frequency Transposition for Hearing-Impaired School-Age Children

ERIC Educational Resources Information Center

Smith, Jenny; Dann, Marilyn; Brown, P. Margaret

2009-01-01

A key objective when fitting hearing aids to children is to maximize the audibility of high frequency speech cues which are critical in the understanding of spoken English. Recent advances in digital signal processing have enabled the development of hearing aids which offer linear frequency transposition as a new way of accessing these important…

Local numerical modelling of ultrasonic guided waves in linear and nonlinear media

NASA Astrophysics Data System (ADS)

Packo, Pawel; Radecki, Rafal; Kijanka, Piotr; Staszewski, Wieslaw J.; Uhl, Tadeusz; Leamy, Michael J.

2017-04-01

Nonlinear ultrasonic techniques provide improved damage sensitivity compared to linear approaches. The combination of attractive properties of guided waves, such as Lamb waves, with unique features of higher harmonic generation provides great potential for characterization of incipient damage, particularly in plate-like structures. Nonlinear ultrasonic structural health monitoring techniques use interrogation signals at frequencies other than the excitation frequency to detect changes in structural integrity. Signal processing techniques used in non-destructive evaluation are frequently supported by modeling and numerical simulations in order to facilitate problem solution. This paper discusses known and newly-developed local computational strategies for simulating elastic waves, and attempts characterization of their numerical properties in the context of linear and nonlinear media. A hybrid numerical approach combining advantages of the Local Interaction Simulation Approach (LISA) and Cellular Automata for Elastodynamics (CAFE) is proposed for unique treatment of arbitrary strain-stress relations. The iteration equations of the method are derived directly from physical principles employing stress and displacement continuity, leading to an accurate description of the propagation in arbitrarily complex media. Numerical analysis of guided wave propagation, based on the newly developed hybrid approach, is presented and discussed in the paper for linear and nonlinear media. Comparisons to Finite Elements (FE) are also discussed.

An approach to source characterization of tremor signals associated with eruptions and lahars

NASA Astrophysics Data System (ADS)

Kumagai, Hiroyuki; Mothes, Patricia; Ruiz, Mario; Maeda, Yuta

2015-11-01

Tremor signals are observed in association with eruption activity and lahar descents. Reduced displacement ( D R) derived from tremor signals has been used to quantify tremor sources. However, tremor duration is not considered in D R, which makes it difficult to compare D R values estimated for different tremor episodes. We propose application of the amplitude source location (ASL) method to characterize the sources of tremor signals. We used this method to estimate the tremor source location and source amplitude from high-frequency (5-10 Hz) seismic amplitudes under the assumption of isotropic S-wave radiation. We considered the source amplitude to be the maximum value during tremor. We estimated the cumulative source amplitude ( I s) as the offset value of the time-integrated envelope of the vertical seismogram of tremor corrected for geometrical spreading and medium attenuation in the 5-10-Hz band. For eruption tremor signals, we also estimated the cumulative source pressure ( I p) from an infrasonic envelope waveform corrected for geometrical spreading. We studied these parameters of tremor signals associated with eruptions and lahars and explosion events at Tungurahua volcano, Ecuador. We identified two types of eruption tremor at Tungurahua: noise-like inharmonic waveforms and harmonic oscillatory signals. We found that I s increased linearly with increasing source amplitude for lahar tremor signals and explosion events, but I s increased exponentially with increasing source amplitude for inharmonic eruption tremor signals. The source characteristics of harmonic eruption tremor signals differed from those of inharmonic tremor signals. We found a linear relation between I s and I p for both explosion events and eruption tremor. Because I p may be proportional to the total mass involved during an eruption episode, this linear relation suggests that I s may be useful to quantify eruption size. The I s values we estimated for inharmonic eruption tremor were consistent with previous estimates of volumes of tephra fallout. The scaling relations among source parameters that we identified will contribute to our understanding of the dynamic processes associated with eruptions and lahars. This new approach is applicable in analyzing tremor sources in real time and may contribute to early assessment of the size of eruptions and lahars.

A Doppler centroid estimation algorithm for SAR systems optimized for the quasi-homogeneous source

NASA Technical Reports Server (NTRS)

Jin, Michael Y.

1989-01-01

Radar signal processing applications frequently require an estimate of the Doppler centroid of a received signal. The Doppler centroid estimate is required for synthetic aperture radar (SAR) processing. It is also required for some applications involving target motion estimation and antenna pointing direction estimation. In some cases, the Doppler centroid can be accurately estimated based on available information regarding the terrain topography, the relative motion between the sensor and the terrain, and the antenna pointing direction. Often, the accuracy of the Doppler centroid estimate can be improved by analyzing the characteristics of the received SAR signal. This kind of signal processing is also referred to as clutterlock processing. A Doppler centroid estimation (DCE) algorithm is described which contains a linear estimator optimized for the type of terrain surface that can be modeled by a quasi-homogeneous source (QHS). Information on the following topics is presented: (1) an introduction to the theory of Doppler centroid estimation; (2) analysis of the performance characteristics of previously reported DCE algorithms; (3) comparison of these analysis results with experimental results; (4) a description and performance analysis of a Doppler centroid estimator which is optimized for a QHS; and (5) comparison of the performance of the optimal QHS Doppler centroid estimator with that of previously reported methods.

Monitoring temperatures in coal conversion and combustion processes via ultrasound

NASA Astrophysics Data System (ADS)

Gopalsami, N.; Raptis, A. C.; Mulcahey, T. P.

1980-02-01

The state of the art of instrumentation for monitoring temperatures in coal conversion and combustion systems is examined. The instrumentation types studied include thermocouples, radiation pyrometers, and acoustical thermometers. The capabilities and limitations of each type are reviewed. A feasibility study of the ultrasonic thermometry is described. A mathematical model of a pulse-echo ultrasonic temperature measurement system is developed using linear system theory. The mathematical model lends itself to the adaptation of generalized correlation techniques for the estimation of propagation delays. Computer simulations are made to test the efficacy of the signal processing techniques for noise-free as well as noisy signals. Based on the theoretical study, acoustic techniques to measure temperature in reactors and combustors are feasible.

Simulated bi-SQUID Arrays Performing Direction Finding

DTIC Science & Technology

2015-09-01

First, we applied the multiple signal classification ( MUSIC ) algorithm on linearly polarized signals. We included multiple signals in the output...both of the same frequency and different fre- quencies. Next, we explored a modified MUSIC algorithm called dimensionality reduction MUSIC (DR- MUSIC ... MUSIC algorithm is able to determine the AoA from the simulated SQUID data for linearly polarized signals. The MUSIC algorithm could accurately find

A highly linear fully integrated powerline filter for biopotential acquisition systems.

PubMed

Alzaher, Hussain A; Tasadduq, Noman; Mahnashi, Yaqub

2013-10-01

Powerline interference is one of the most dominant problems in detection and processing of biopotential signals. This work presents a new fully integrated notch filter exhibiting high linearity and low power consumption. High filter linearity is preserved utilizing active-RC approach while IC implementation is achieved through replacing passive resistors by R-2R ladders achieving area saving of approximately 120 times. The filter design is optimized for low power operation using an efficient circuit topology and an ultra-low power operational amplifier. Fully differential implementation of the proposed filter shows notch depth of 43 dB (78 dB for 4th-order) with THD of better than -70 dB while consuming about 150 nW from 1.5 V supply.

On the use of fractional order PK-PD models

NASA Astrophysics Data System (ADS)

Ionescu, Clara; Copot, Dana

2017-01-01

Quantifying and controlling depth of anesthesia is a challenging process due to lack of measurement technology for direct effects of drug supply into the body. Efforts are being made to develop new sensor techniques and new horizons are explored for modeling this intricate process. This paper introduces emerging tools available on the ‘engineering market’ imported from the area of fractional calculus. A novel interpretation of the classical drug-effect curve is given, enabling linear control. This enables broadening the horizon of signal processing and control techniques and suggests future research lines.

System and Method for Generating a Frequency Modulated Linear Laser Waveform

NASA Technical Reports Server (NTRS)

Pierrottet, Diego F. (Inventor); Petway, Larry B. (Inventor); Amzajerdian, Farzin (Inventor); Barnes, Bruce W. (Inventor); Lockard, George E. (Inventor); Hines, Glenn D. (Inventor)

2017-01-01

A system for generating a frequency modulated linear laser waveform includes a single frequency laser generator to produce a laser output signal. An electro-optical modulator modulates the frequency of the laser output signal to define a linear triangular waveform. An optical circulator passes the linear triangular waveform to a band-pass optical filter to filter out harmonic frequencies created in the waveform during modulation of the laser output signal, to define a pure filtered modulated waveform having a very narrow bandwidth. The optical circulator receives the pure filtered modulated laser waveform and transmits the modulated laser waveform to a target.

System and Method for Generating a Frequency Modulated Linear Laser Waveform

NASA Technical Reports Server (NTRS)

Pierrottet, Diego F. (Inventor); Petway, Larry B. (Inventor); Amzajerdian, Farzin (Inventor); Barnes, Bruce W. (Inventor); Lockard, George E. (Inventor); Hines, Glenn D. (Inventor)

2014-01-01

A system for generating a frequency modulated linear laser waveform includes a single frequency laser generator to produce a laser output signal. An electro-optical modulator modulates the frequency of the laser output signal to define a linear triangular waveform. An optical circulator passes the linear triangular waveform to a band-pass optical filter to filter out harmonic frequencies created in the waveform during modulation of the laser output signal, to define a pure filtered modulated waveform having a very narrow bandwidth. The optical circulator receives the pure filtered modulated laser waveform and transmits the modulated laser waveform to a target.

Affine Transform to Reform Pixel Coordinates of EOG Signals for Controlling Robot Manipulators Using Gaze Motions

PubMed Central

Rusydi, Muhammad Ilhamdi; Sasaki, Minoru; Ito, Satoshi

2014-01-01

Biosignals will play an important role in building communication between machines and humans. One of the types of biosignals that is widely used in neuroscience are electrooculography (EOG) signals. An EOG has a linear relationship with eye movement displacement. Experiments were performed to construct a gaze motion tracking method indicated by robot manipulator movements. Three operators looked at 24 target points displayed on a monitor that was 40 cm in front of them. Two channels (Ch1 and Ch2) produced EOG signals for every single eye movement. These signals were converted to pixel units by using the linear relationship between EOG signals and gaze motion distances. The conversion outcomes were actual pixel locations. An affine transform method is proposed to determine the shift of actual pixels to target pixels. This method consisted of sequences of five geometry processes, which are translation-1, rotation, translation-2, shear and dilatation. The accuracy was approximately 0.86° ± 0.67° in the horizontal direction and 0.54° ± 0.34° in the vertical. This system successfully tracked the gaze motions not only in direction, but also in distance. Using this system, three operators could operate a robot manipulator to point at some targets. This result shows that the method is reliable in building communication between humans and machines using EOGs. PMID:24919013

Suppression of stimulus artifact contaminating electrically evoked electromyography.

PubMed

Liu, Jie; Li, Sheng; Li, Xiaoyan; Klein, Cliff; Rymer, William Z; Zhou, Ping

2014-01-01

Electrical stimulation of muscle or nerve is a very useful technique for understanding of muscle activity and its pathological changes for both diagnostic and therapeutic purposes. During electrical stimulation of a muscle, the recorded M wave is often contaminated by a stimulus artifact. The stimulus artifact must be removed for appropriate analysis and interpretation of M waves. The objective of this study was to develop a novel software based method to remove stimulus artifacts contaminating or superimposing with electrically evoked surface electromyography (EMG) or M wave signals. The multiple stage method uses a series of signal processing techniques, including highlighting and detection of stimulus artifacts using Savitzky-Golay filtering, estimation of the artifact contaminated region with Otsu thresholding, and reconstruction of such region using signal interpolation and smoothing. The developed method was tested using M wave signals recorded from biceps brachii muscles by a linear surface electrode array. To evaluate the performance, a series of semi-synthetic signals were constructed from clean M wave and stimulus artifact recordings with different degrees of overlap between them. The effectiveness of the developed method was quantified by a significant increase in correlation coefficient and a significant decrease in root mean square error between the clean M wave and the reconstructed M wave, compared with those between the clean M wave and the originally contaminated signal. The validity of the developed method was also demonstrated when tested on each channel's M wave recording using a linear electrode array. The developed method can suppress stimulus artifacts contaminating M wave recordings.

Characterization of real-world vibration sources with a view toward optimal energy harvesting architectures

NASA Astrophysics Data System (ADS)

Rantz, Robert; Roundy, Shad

2016-04-01

A tremendous amount of research has been performed on the design and analysis of vibration energy harvester architectures with the goal of optimizing power output; most studies assume idealized input vibrations without paying much attention to whether such idealizations are broadly representative of real sources. These "idealized input signals" are typically derived from the expected nature of the vibrations produced from a given source. Little work has been done on corroborating these expectations by virtue of compiling a comprehensive list of vibration signals organized by detailed classifications. Vibration data representing 333 signals were collected from the NiPS Laboratory "Real Vibration" database, processed, and categorized according to the source of the signal (e.g. animal, machine, etc.), the number of dominant frequencies, the nature of the dominant frequencies (e.g. stationary, band-limited noise, etc.), and other metrics. By categorizing signals in this way, the set of idealized vibration inputs commonly assumed for harvester input can be corroborated and refined, and heretofore overlooked vibration input types have motivation for investigation. An initial qualitative analysis of vibration signals has been undertaken with the goal of determining how often a standard linear oscillator based harvester is likely the optimal architecture, and how often a nonlinear harvester with a cubic stiffness function might provide improvement. Although preliminary, the analysis indicates that in at least 23% of cases, a linear harvester is likely optimal and in no more than 53% of cases would a nonlinear cubic stiffness based harvester provide improvement.

Signal Detection Techniques for Diagnostic Monitoring of Space Shuttle Main Engine Turbomachinery

NASA Technical Reports Server (NTRS)

Coffin, Thomas; Jong, Jen-Yi

1986-01-01

An investigation to develop, implement, and evaluate signal analysis techniques for the detection and classification of incipient mechanical failures in turbomachinery is reviewed. A brief description of the Space Shuttle Main Engine (SSME) test/measurement program is presented. Signal analysis techniques available to describe dynamic measurement characteristics are reviewed. Time domain and spectral methods are described, and statistical classification in terms of moments is discussed. Several of these waveform analysis techniques have been implemented on a computer and applied to dynamc signals. A laboratory evaluation of the methods with respect to signal detection capability is described. A unique coherence function (the hyper-coherence) was developed through the course of this investigation, which appears promising as a diagnostic tool. This technique and several other non-linear methods of signal analysis are presented and illustrated by application. Software for application of these techniques has been installed on the signal processing system at the NASA/MSFC Systems Dynamics Laboratory.

Continuous and Cuffless Blood Pressure Monitoring Based on ECG and SpO2 Signals ByUsing Microsoft Visual C Sharp.

PubMed

Younessi Heravi, M A; Khalilzadeh, M A; Joharinia, S

2014-03-01

One of the main problems especially in operating room and monitoring devices is measurement of Blood Pressure (BP) by sphygmomanometer cuff. Objective :In this study we designed a new method to measure BP changes continuously for detecting information between cuff inflation times by using vital signals in monitoring devices. This will be achieved by extraction of the time difference between each cardiac cycle and a relative pulse wave. Finger pulse and ECG signals in lead I were recorded by a monitoring device. The output of monitoring device wasinserted in a computer by serial network communication. A software interface (Microsoft Visual C#.NET ) was used to display and process the signals in the computer. Time difference between each cardiac cycle and pulse signal was calculated throughout R wave detection in ECG and peak of pulse signal by the software. The relation between time difference in two waves and BP was determined then the coefficients of equation were obtained in different physical situations. The results of estimating BP were compared with the results of sphygmomanometer method and the error rate was calculated. In this study, 25 subjects participated among them 15 were male and 10 were female. The results showed that BP was linearly related to time difference. Average of coefficient correlation was 0.9±0.03 for systolic and 0.82±0.04 for diastolic blood pressure. The highest error percentage was calculated 8% for male and 11% for female group. Significant difference was observed between the different physical situation and arm movement changes. The relationship between time difference and age was estimated in a linear relationship with a correlation coefficient of 0.76. By determining linear relation values with high accuracy, BP can be measured with insignificant error. Therefore it can be suggested as a new method to measure the blood pressure continuously.

Power Amplifier Linearizer for High Frequency Medical Ultrasound Applications

PubMed Central

Choi, Hojong; Jung, Hayong; Shung, K. Kirk

2015-01-01

Power amplifiers (PAs) are used to produce high-voltage excitation signals to drive ultrasonic transducers. A larger dynamic range of linear PAs allows higher contrast resolution, a highly desirable characteristic in ultrasonic imaging. The linearity of PAs can be improved by reducing the nonlinear harmonic distortion components of high-voltage output signals. In this paper, a linearizer circuit is proposed to reduce output signal harmonics when working in conjunction with a PA. The PA performance with and without the linearizer was measured by comparing the output power 1-dB compression point (OP1dB), and the second- and third-order harmonic distortions (HD2 and HD3, respectively). The results show that the PA with the linearizer circuit had higher OP1dB (31.7 dB) and lower HD2 (−61.0 dB) and HD3 (−42.7 dB) compared to those of the PA alone (OP1dB (27.1 dB), HD2 (−38.2 dB), and HD3 (−36.8 dB)) at 140 MHz. A pulse-echo measurement was also performed to further evaluate the capability of the linearizer circuit. The HD2 of the echo signal received by the transducer using a PA with the linearizer (−24.8 dB) was lower than that obtained for the PA alone (−16.6 dB). The linearizer circuit is capable of improving the linearity performance of PA by lowering harmonic distortions. PMID:26622209

Super-resolution imaging using multi- electrode CMUTs: theoretical design and simulation using point targets.

PubMed

You, Wei; Cretu, Edmond; Rohling, Robert

2013-11-01

This paper investigates a low computational cost, super-resolution ultrasound imaging method that leverages the asymmetric vibration mode of CMUTs. Instead of focusing on the broadband received signal on the entire CMUT membrane, we utilize the differential signal received on the left and right part of the membrane obtained by a multi-electrode CMUT structure. The differential signal reflects the asymmetric vibration mode of the CMUT cell excited by the nonuniform acoustic pressure field impinging on the membrane, and has a resonant component in immersion. To improve the resolution, we propose an imaging method as follows: a set of manifold matrices of CMUT responses for multiple focal directions are constructed off-line with a grid of hypothetical point targets. During the subsequent imaging process, the array sequentially steers to multiple angles, and the amplitudes (weights) of all hypothetical targets at each angle are estimated in a maximum a posteriori (MAP) process with the manifold matrix corresponding to that angle. Then, the weight vector undergoes a directional pruning process to remove the false estimation at other angles caused by the side lobe energy. Ultrasound imaging simulation is performed on ring and linear arrays with a simulation program adapted with a multi-electrode CMUT structure capable of obtaining both average and differential received signals. Because the differential signals from all receiving channels form a more distinctive temporal pattern than the average signals, better MAP estimation results are expected than using the average signals. The imaging simulation shows that using differential signals alone or in combination with the average signals produces better lateral resolution than the traditional phased array or using the average signals alone. This study is an exploration into the potential benefits of asymmetric CMUT responses for super-resolution imaging.

Broadband unidirectional ultrasound propagation

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

Sinha, Dipen N.; Pantea, Cristian

A passive, linear arrangement of a sonic crystal-based apparatus and method including a 1D sonic crystal, a nonlinear medium, and an acoustic low-pass filter, for permitting unidirectional broadband ultrasound propagation as a collimated beam for underwater, air or other fluid communication, are described. The signal to be transmitted is first used to modulate a high-frequency ultrasonic carrier wave which is directed into the sonic crystal side of the apparatus. The apparatus processes the modulated signal, whereby the original low-frequency signal exits the apparatus as a collimated beam on the side of the apparatus opposite the sonic crystal. The sonic crystalmore » provides a bandpass acoustic filter through which the modulated high-frequency ultrasonic signal passes, and the nonlinear medium demodulates the modulated signal and recovers the low-frequency sound beam. The low-pass filter removes remaining high-frequency components, and contributes to the unidirectional property of the apparatus.« less

A Self-Calibrating Radar Sensor System for Measuring Vital Signs.

PubMed

Huang, Ming-Chun; Liu, Jason J; Xu, Wenyao; Gu, Changzhan; Li, Changzhi; Sarrafzadeh, Majid

2016-04-01

Vital signs (i.e., heartbeat and respiration) are crucial physiological signals that are useful in numerous medical applications. The process of measuring these signals should be simple, reliable, and comfortable for patients. In this paper, a noncontact self-calibrating vital signs monitoring system based on the Doppler radar is presented. The system hardware and software were designed with a four-tiered layer structure. To enable accurate vital signs measurement, baseband signals in the radar sensor were modeled and a framework for signal demodulation was proposed. Specifically, a signal model identification method was formulated into a quadratically constrained l1 minimization problem and solved using the upper bound and linear matrix inequality (LMI) relaxations. The performance of the proposed system was comprehensively evaluated using three experimental sets, and the results indicated that this system can be used to effectively measure human vital signs.

Reconstruction of cellular signal transduction networks using perturbation assays and linear programming.

PubMed

Knapp, Bettina; Kaderali, Lars

2013-01-01

Perturbation experiments for example using RNA interference (RNAi) offer an attractive way to elucidate gene function in a high throughput fashion. The placement of hit genes in their functional context and the inference of underlying networks from such data, however, are challenging tasks. One of the problems in network inference is the exponential number of possible network topologies for a given number of genes. Here, we introduce a novel mathematical approach to address this question. We formulate network inference as a linear optimization problem, which can be solved efficiently even for large-scale systems. We use simulated data to evaluate our approach, and show improved performance in particular on larger networks over state-of-the art methods. We achieve increased sensitivity and specificity, as well as a significant reduction in computing time. Furthermore, we show superior performance on noisy data. We then apply our approach to study the intracellular signaling of human primary nave CD4(+) T-cells, as well as ErbB signaling in trastuzumab resistant breast cancer cells. In both cases, our approach recovers known interactions and points to additional relevant processes. In ErbB signaling, our results predict an important role of negative and positive feedback in controlling the cell cycle progression.

THE MAGNETIC SENSITIVITY OF THE Mg ii k LINE TO THE JOINT ACTION OF HANLE, ZEEMAN, AND MAGNETO-OPTICAL EFFECTS

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

Ballester, E. Alsina; Bueno, J. Trujillo; Belluzzi, L., E-mail: ealsina@iac.es, E-mail: jtb@iac.es, E-mail: belluzzi@irsol.ch

2016-11-10

We highlight the main results of a radiative transfer investigation on the magnetic sensitivity of the solar Mg ii k resonance line at 2795.5 Å, accounting for the joint action of the Hanle and Zeeman effects as well as partial frequency redistribution phenomena. We confirm that at the line center, the linear polarization signals produced by scattering processes are measurable, and that they are sensitive, via the Hanle effect, to magnetic fields with strengths between 5 and 50 G, approximately. We also show that the Zeeman effect produces conspicuous circular polarization signals, especially for longitudinal fields stronger than 50 G,more » which can be used to estimate the magnetization of the solar chromosphere via the familiar magnetograph formula. The most novel result is that magneto-optical effects produce, in the wings of the line, a decrease of the Q / I scattering polarization pattern and the appearance of U / I signals (i.e., a rotation of the plane of linear polarization). This sensitivity of the Q / I and U / I wing signals to both weak (∼5 G) and stronger magnetic fields expands the scientific interest of the Mg ii k line for probing the chromosphere in quiet and active regions of the Sun.« less

Evaluation of interaction dynamics of concurrent processes

NASA Astrophysics Data System (ADS)

Sobecki, Piotr; Białasiewicz, Jan T.; Gross, Nicholas

2017-03-01

The purpose of this paper is to present the wavelet tools that enable the detection of temporal interactions of concurrent processes. In particular, the determination of interaction coherence of time-varying signals is achieved using a complex continuous wavelet transform. This paper has used electrocardiogram (ECG) and seismocardiogram (SCG) data set to show multiple continuous wavelet analysis techniques based on Morlet wavelet transform. MATLAB Graphical User Interface (GUI), developed in the reported research to assist in quick and simple data analysis, is presented. These software tools can discover the interaction dynamics of time-varying signals, hence they can reveal their correlation in phase and amplitude, as well as their non-linear interconnections. The user-friendly MATLAB GUI enables effective use of the developed software what enables to load two processes under investigation, make choice of the required processing parameters, and then perform the analysis. The software developed is a useful tool for researchers who have a need for investigation of interaction dynamics of concurrent processes.

Self-Calibrating and Remote Programmable Signal Conditioning Amplifier System and Method

NASA Technical Reports Server (NTRS)

Medelius, Pedro J. (Inventor); Hallberg, Carl G. (Inventor); Simpson, Howard J., III (Inventor); Thayer, Stephen W. (Inventor)

1998-01-01

A self-calibrating, remote programmable signal conditioning amplifier system employs information read from a memory attached to a measurement transducer for automatic calibration. The signal conditioning amplifier is self-calibrated on a continuous basis through use of a dual input path arrangement, with each path containing a multiplexer and a programmable amplifier. A digital signal processor controls operation of the system such that a transducer signal is applied to one of the input paths, while one or more calibration signals are applied to the second input path. Once the second path is calibrated, the digital signal processor switches the transducer signal to the second path. and then calibrates the first path. This process is continually repeated so that each path is calibrated on an essentially continuous basis. Dual output paths are also employed which are calibrated in the same manner. The digital signal processor also allows the implementation of a variety of digital filters which are either programmed into the system or downloaded by an operator, and performs up to eighth order linearization.

Filtering of the Radon transform to enhance linear signal features via wavelet pyramid decomposition

NASA Astrophysics Data System (ADS)

Meckley, John R.

1995-09-01

The information content in many signal processing applications can be reduced to a set of linear features in a 2D signal transform. Examples include the narrowband lines in a spectrogram, ship wakes in a synthetic aperture radar image, and blood vessels in a medical computer-aided tomography scan. The line integrals that generate the values of the projections of the Radon transform can be characterized as a bank of matched filters for linear features. This localization of energy in the Radon transform for linear features can be exploited to enhance these features and to reduce noise by filtering the Radon transform with a filter explicitly designed to pass only linear features, and then reconstructing a new 2D signal by inverting the new filtered Radon transform (i.e., via filtered backprojection). Previously used methods for filtering the Radon transform include Fourier based filtering (a 2D elliptical Gaussian linear filter) and a nonlinear filter ((Radon xfrm)**y with y >= 2.0). Both of these techniques suffer from the mismatch of the filter response to the true functional form of the Radon transform of a line. The Radon transform of a line is not a point but is a function of the Radon variables (rho, theta) and the total line energy. This mismatch leads to artifacts in the reconstructed image and a reduction in achievable processing gain. The Radon transform for a line is computed as a function of angle and offset (rho, theta) and the line length. The 2D wavelet coefficients are then compared for the Haar wavelets and the Daubechies wavelets. These filter responses are used as frequency filters for the Radon transform. The filtering is performed on the wavelet pyramid decomposition of the Radon transform by detecting the most likely positions of lines in the transform and then by convolving the local area with the appropriate response and zeroing the pyramid coefficients outside of the response area. The response area is defined to contain 95% of the total wavelet coefficient energy. The detection algorithm provides an estimate of the line offset, orientation, and length that is then used to index the appropriate filter shape. Additional wavelet pyramid decomposition is performed in areas of high energy to refine the line position estimate. After filtering, the new Radon transform is generated by inverting the wavelet pyramid. The Radon transform is then inverted by filtered backprojection to produce the final 2D signal estimate with the enhanced linear features. The wavelet-based method is compared to both the Fourier and the nonlinear filtering with examples of sparse and dense shapes in imaging, acoustics and medical tomography with test images of noisy concentric lines, a real spectrogram of a blow fish (a very nonstationary spectrum), and the Shepp Logan Computer Tomography phantom image. Both qualitative and derived quantitative measures demonstrate the improvement of wavelet-based filtering. Additional research is suggested based on these results. Open questions include what level(s) to use for detection and filtering because multiple-level representations exist. The lower levels are smoother at reduced spatial resolution, while the higher levels provide better response to edges. Several examples are discussed based on analytical and phenomenological arguments.

Equalization of nonlinear transmission impairments by maximum-likelihood-sequence estimation in digital coherent receivers.

PubMed

Khairuzzaman, Md; Zhang, Chao; Igarashi, Koji; Katoh, Kazuhiro; Kikuchi, Kazuro

2010-03-01

We describe a successful introduction of maximum-likelihood-sequence estimation (MLSE) into digital coherent receivers together with finite-impulse response (FIR) filters in order to equalize both linear and nonlinear fiber impairments. The MLSE equalizer based on the Viterbi algorithm is implemented in the offline digital signal processing (DSP) core. We transmit 20-Gbit/s quadrature phase-shift keying (QPSK) signals through a 200-km-long standard single-mode fiber. The bit-error rate performance shows that the MLSE equalizer outperforms the conventional adaptive FIR filter, especially when nonlinear impairments are predominant.

Identification of the structure parameters using short-time non-stationary stochastic excitation

NASA Astrophysics Data System (ADS)

Jarczewska, Kamila; Koszela, Piotr; Śniady, PaweŁ; Korzec, Aleksandra

2011-07-01

In this paper, we propose an approach to the flexural stiffness or eigenvalue frequency identification of a linear structure using a non-stationary stochastic excitation process. The idea of the proposed approach lies within time domain input-output methods. The proposed method is based on transforming the dynamical problem into a static one by integrating the input and the output signals. The output signal is the structure reaction, i.e. structure displacements due to the short-time, irregular load of random type. The systems with single and multiple degrees of freedom, as well as continuous systems are considered.

Time reversal of optically carried radiofrequency signals in the microsecond range.

PubMed

Linget, H; Morvan, L; Le Gouët, J-L; Louchet-Chauvet, A

2013-03-01

The time-reversal (TR) protocol we implement in an erbium-doped YSO crystal is based on photon echoes but avoids the storage of the signal to be processed. Unlike other approaches implying digitizing or highly dispersive optical fibers, the proposed scheme reaches the μs range and potentially offers high bandwidth, both required for RADAR applications. In this Letter, we demonstrate faithful reversal of arbitrary pulse sequences with 6 μs duration and 10 MHz bandwidth. To the best of our knowledge, this is the first demonstration of TR via linear filtering in a programmable material.

Application of a Statistical Linear Time-Varying System Model of High Grazing Angle Sea Clutter for Computing Interference Power

DTIC Science & Technology

2017-12-08

1088793. 3. R. Price and P. E. Green, Jr., “Signal processing in radar astronomy – communication via fluctuating multipath media,” rept. 234, MIT...Lincoln Laboratory (October 1960). 4. P. E. Green, Jr., “Radar astronomy measurement techniques,” rept. 282, MIT Lincoln Laboratory (December 1962). 5. A

Random numbers from vacuum fluctuations

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

Shi, Yicheng; Kurtsiefer, Christian, E-mail: christian.kurtsiefer@gmail.com; Center for Quantum Technologies, National University of Singapore, 3 Science Drive 2, Singapore 117543

2016-07-25

We implement a quantum random number generator based on a balanced homodyne measurement of vacuum fluctuations of the electromagnetic field. The digitized signal is directly processed with a fast randomness extraction scheme based on a linear feedback shift register. The random bit stream is continuously read in a computer at a rate of about 480 Mbit/s and passes an extended test suite for random numbers.

Model predictive control of non-linear systems over networks with data quantization and packet loss.

PubMed

Yu, Jimin; Nan, Liangsheng; Tang, Xiaoming; Wang, Ping

2015-11-01

This paper studies the approach of model predictive control (MPC) for the non-linear systems under networked environment where both data quantization and packet loss may occur. The non-linear controlled plant in the networked control system (NCS) is represented by a Tagaki-Sugeno (T-S) model. The sensed data and control signal are quantized in both links and described as sector bound uncertainties by applying sector bound approach. Then, the quantized data are transmitted in the communication networks and may suffer from the effect of packet losses, which are modeled as Bernoulli process. A fuzzy predictive controller which guarantees the stability of the closed-loop system is obtained by solving a set of linear matrix inequalities (LMIs). A numerical example is given to illustrate the effectiveness of the proposed method. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Reservoir Computing Beyond Memory-Nonlinearity Trade-off.

PubMed

Inubushi, Masanobu; Yoshimura, Kazuyuki

2017-08-31

Reservoir computing is a brain-inspired machine learning framework that employs a signal-driven dynamical system, in particular harnessing common-signal-induced synchronization which is a widely observed nonlinear phenomenon. Basic understanding of a working principle in reservoir computing can be expected to shed light on how information is stored and processed in nonlinear dynamical systems, potentially leading to progress in a broad range of nonlinear sciences. As a first step toward this goal, from the viewpoint of nonlinear physics and information theory, we study the memory-nonlinearity trade-off uncovered by Dambre et al. (2012). Focusing on a variational equation, we clarify a dynamical mechanism behind the trade-off, which illustrates why nonlinear dynamics degrades memory stored in dynamical system in general. Moreover, based on the trade-off, we propose a mixture reservoir endowed with both linear and nonlinear dynamics and show that it improves the performance of information processing. Interestingly, for some tasks, significant improvements are observed by adding a few linear dynamics to the nonlinear dynamical system. By employing the echo state network model, the effect of the mixture reservoir is numerically verified for a simple function approximation task and for more complex tasks.

Design and Analysis of a Neuromemristive Reservoir Computing Architecture for Biosignal Processing

PubMed Central

Kudithipudi, Dhireesha; Saleh, Qutaiba; Merkel, Cory; Thesing, James; Wysocki, Bryant

2016-01-01

Reservoir computing (RC) is gaining traction in several signal processing domains, owing to its non-linear stateful computation, spatiotemporal encoding, and reduced training complexity over recurrent neural networks (RNNs). Previous studies have shown the effectiveness of software-based RCs for a wide spectrum of applications. A parallel body of work indicates that realizing RNN architectures using custom integrated circuits and reconfigurable hardware platforms yields significant improvements in power and latency. In this research, we propose a neuromemristive RC architecture, with doubly twisted toroidal structure, that is validated for biosignal processing applications. We exploit the device mismatch to implement the random weight distributions within the reservoir and propose mixed-signal subthreshold circuits for energy efficiency. A comprehensive analysis is performed to compare the efficiency of the neuromemristive RC architecture in both digital(reconfigurable) and subthreshold mixed-signal realizations. Both Electroencephalogram (EEG) and Electromyogram (EMG) biosignal benchmarks are used for validating the RC designs. The proposed RC architecture demonstrated an accuracy of 90 and 84% for epileptic seizure detection and EMG prosthetic finger control, respectively. PMID:26869876

A data processing method based on tracking light spot for the laser differential confocal component parameters measurement system

NASA Astrophysics Data System (ADS)

Shao, Rongjun; Qiu, Lirong; Yang, Jiamiao; Zhao, Weiqian; Zhang, Xin

2013-12-01

We have proposed the component parameters measuring method based on the differential confocal focusing theory. In order to improve the positioning precision of the laser differential confocal component parameters measurement system (LDDCPMS), the paper provides a data processing method based on tracking light spot. To reduce the error caused by the light point moving in collecting the axial intensity signal, the image centroiding algorithm is used to find and track the center of Airy disk of the images collected by the laser differential confocal system. For weakening the influence of higher harmonic noises during the measurement, Gaussian filter is used to process the axial intensity signal. Ultimately the zero point corresponding to the focus of the objective in a differential confocal system is achieved by linear fitting for the differential confocal axial intensity data. Preliminary experiments indicate that the method based on tracking light spot can accurately collect the axial intensity response signal of the virtual pinhole, and improve the anti-interference ability of system. Thus it improves the system positioning accuracy.

Architecture and settings optimization procedure of a TES frequency domain multiplexed readout firmware

NASA Astrophysics Data System (ADS)

Clenet, A.; Ravera, L.; Bertrand, B.; den Hartog, R.; Jackson, B.; van Leeuwen, B.-J.; van Loon, D.; Parot, Y.; Pointecouteau, E.; Sournac, A.

2014-11-01

IRAP is developing the readout electronics of the SPICA-SAFARI's TES bolometer arrays. Based on the frequency domain multiplexing technique the readout electronics provides the AC-signals to voltage-bias the detectors; it demodulates the data; and it computes a feedback to linearize the detection chain. The feedback is computed with a specific technique, so called baseband feedback (BBFB) which ensures that the loop is stable even with long propagation and processing delays (i.e. several μ s) and with fast signals (i.e. frequency carriers of the order of 5 MHz). To optimize the power consumption we took advantage of the reduced science signal bandwidth to decouple the signal sampling frequency and the data processing rate. This technique allowed a reduction of the power consumption of the circuit by a factor of 10. Beyond the firmware architecture the optimization of the instrument concerns the characterization routines and the definition of the optimal parameters. Indeed, to operate an array TES one has to properly define about 21000 parameters. We defined a set of procedures to automatically characterize these parameters and find out the optimal settings.

Nanometer-scale displacement sensing using self-mixing interferometry with a correlation-based signal processing technique

NASA Astrophysics Data System (ADS)

Hast, J.; Okkonen, M.; Heikkinen, H.; Krehut, L.; Myllylä, R.

2006-06-01

A self-mixing interferometer is proposed to measure nanometre-scale optical path length changes in the interferometer's external cavity. As light source, the developed technique uses a blue emitting GaN laser diode. An external reflector, a silicon mirror, driven by a piezo nanopositioner is used to produce an interference signal which is detected with the monitor photodiode of the laser diode. Changing the optical path length of the external cavity introduces a phase difference to the interference signal. This phase difference is detected using a signal processing algorithm based on Pearson's correlation coefficient and cubic spline interpolation techniques. The results show that the average deviation between the measured and actual displacements of the silicon mirror is 3.1 nm in the 0-110 nm displacement range. Moreover, the measured displacements follow linearly the actual displacement of the silicon mirror. Finally, the paper considers the effects produced by the temperature and current stability of the laser diode as well as dispersion effects in the external cavity of the interferometer. These reduce the sensor's measurement accuracy especially in long-term measurements.

The transfer function of neuron spike.

PubMed

Palmieri, Igor; Monteiro, Luiz H A; Miranda, Maria D

2015-08-01

The mathematical modeling of neuronal signals is a relevant problem in neuroscience. The complexity of the neuron behavior, however, makes this problem a particularly difficult task. Here, we propose a discrete-time linear time-invariant (LTI) model with a rational function in order to represent the neuronal spike detected by an electrode located in the surroundings of the nerve cell. The model is presented as a cascade association of two subsystems: one that generates an action potential from an input stimulus, and one that represents the medium between the cell and the electrode. The suggested approach employs system identification and signal processing concepts, and is dissociated from any considerations about the biophysical processes of the neuronal cell, providing a low-complexity alternative to model the neuronal spike. The model is validated by using in vivo experimental readings of intracellular and extracellular signals. A computational simulation of the model is presented in order to assess its proximity to the neuronal signal and to observe the variability of the estimated parameters. The implications of the results are discussed in the context of spike sorting. Copyright © 2015 Elsevier Ltd. All rights reserved.

Intensity-Curvature Measurement Approaches for the Diagnosis of Magnetic Resonance Imaging Brain Tumors.

PubMed

Ciulla, Carlo; Veljanovski, Dimitar; Rechkoska Shikoska, Ustijana; Risteski, Filip A

2015-11-01

This research presents signal-image post-processing techniques called Intensity-Curvature Measurement Approaches with application to the diagnosis of human brain tumors detected through Magnetic Resonance Imaging (MRI). Post-processing of the MRI of the human brain encompasses the following model functions: (i) bivariate cubic polynomial, (ii) bivariate cubic Lagrange polynomial, (iii) monovariate sinc, and (iv) bivariate linear. The following Intensity-Curvature Measurement Approaches were used: (i) classic-curvature, (ii) signal resilient to interpolation, (iii) intensity-curvature measure and (iv) intensity-curvature functional. The results revealed that the classic-curvature, the signal resilient to interpolation and the intensity-curvature functional are able to add additional information useful to the diagnosis carried out with MRI. The contribution to the MRI diagnosis of our study are: (i) the enhanced gray level scale of the tumor mass and the well-behaved representation of the tumor provided through the signal resilient to interpolation, and (ii) the visually perceptible third dimension perpendicular to the image plane provided through the classic-curvature and the intensity-curvature functional.

Intensity-Curvature Measurement Approaches for the Diagnosis of Magnetic Resonance Imaging Brain Tumors

PubMed Central

Ciulla, Carlo; Veljanovski, Dimitar; Rechkoska Shikoska, Ustijana; Risteski, Filip A.

2015-01-01

This research presents signal-image post-processing techniques called Intensity-Curvature Measurement Approaches with application to the diagnosis of human brain tumors detected through Magnetic Resonance Imaging (MRI). Post-processing of the MRI of the human brain encompasses the following model functions: (i) bivariate cubic polynomial, (ii) bivariate cubic Lagrange polynomial, (iii) monovariate sinc, and (iv) bivariate linear. The following Intensity-Curvature Measurement Approaches were used: (i) classic-curvature, (ii) signal resilient to interpolation, (iii) intensity-curvature measure and (iv) intensity-curvature functional. The results revealed that the classic-curvature, the signal resilient to interpolation and the intensity-curvature functional are able to add additional information useful to the diagnosis carried out with MRI. The contribution to the MRI diagnosis of our study are: (i) the enhanced gray level scale of the tumor mass and the well-behaved representation of the tumor provided through the signal resilient to interpolation, and (ii) the visually perceptible third dimension perpendicular to the image plane provided through the classic-curvature and the intensity-curvature functional. PMID:26644943

Vestibular signals in macaque extrastriate visual cortex are functionally appropriate for heading perception

PubMed Central

Liu, Sheng; Angelaki, Dora E.

2009-01-01

Visual and vestibular signals converge onto the dorsal medial superior temporal area (MSTd) of the macaque extrastriate visual cortex, which is thought to be involved in multisensory heading perception for spatial navigation. Peripheral otolith information, however, is ambiguous and cannot distinguish linear accelerations experienced during self-motion from those due to changes in spatial orientation relative to gravity. Here we show that, unlike peripheral vestibular sensors but similar to lobules 9 and 10 of the cerebellar vermis (nodulus and uvula), MSTd neurons respond selectively to heading and not to changes in orientation relative to gravity. In support of a role in heading perception, MSTd vestibular responses are also dominated by velocity-like temporal dynamics, which might optimize sensory integration with visual motion information. Unlike the cerebellar vermis, however, MSTd neurons also carry a spatial orientation-independent rotation signal from the semicircular canals, which could be useful in compensating for the effects of head rotation on the processing of optic flow. These findings show that vestibular signals in MSTd are appropriately processed to support a functional role in multisensory heading perception. PMID:19605631

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

Warmack, Robert J. Bruce; Wolf, Dennis A.; Frank, Steven Shane

Various apparatus and methods for smoke detection are disclosed. In one embodiment, a method of training a classifier for a smoke detector comprises inputting sensor data from a plurality of tests into a processor. The sensor data is processed to generate derived signal data corresponding to the test data for respective tests. The derived signal data is assigned into categories comprising at least one fire group and at least one non-fire group. Linear discriminant analysis (LDA) training is performed by the processor. The derived signal data and the assigned categories for the derived signal data are inputs to the LDAmore » training. The output of the LDA training is stored in a computer readable medium, such as in a smoke detector that uses LDA to determine, based on the training, whether present conditions indicate the existence of a fire.« less

Pulse Shaped Constant Envelope 8-PSK Modulation Study

NASA Technical Reports Server (NTRS)

Tao, Jianping; Horan, Sheila

1997-01-01

This report provides simulation results for constant envelope pulse shaped 8 Level Phase Shift Keying (8 PSK) modulation for end to end system performance. In order to increase bandwidth utilization, pulse shaping is applied to signals before they are modulated. This report provides simulation results of power spectra and measurement of bit errors produced by pulse shaping in a non-linear channel with Additive White Gaussian Noise (AWGN). The pulse shaping filters can placed before (Type B) or after (Type A) signals are modulated. Three kinds of baseband filters, 5th order Butterworth, 3rd order Bessel and Square-Root Raised Cosine with different BTs or roll off factors, are utilized in the simulations. The simulations were performed on a Signal Processing Worksystem (SPW).

Modulated microwave microscopy and probes used therewith

DOEpatents

Lai, Keji; Kelly, Michael; Shen, Zhi-Xun

2012-09-11

A microwave microscope including a probe tip electrode vertically positionable over a sample and projecting downwardly from the end of a cantilever. A transmission line connecting the tip electrode to the electronic control system extends along the cantilever and is separated from a ground plane at the bottom of the cantilever by a dielectric layer. The probe tip may be vertically tapped near or at the sample surface at a low frequency and the microwave signal reflected from the tip/sample interaction is demodulated at the low frequency. Alternatively, a low-frequency electrical signal is also a non-linear electrical element associated with the probe tip to non-linearly interact with the applied microwave signal and the reflected non-linear microwave signal is detected at the low frequency. The non-linear element may be semiconductor junction formed near the apex of the probe tip or be an FET formed at the base of a semiconducting tip.

Sparse signals recovered by non-convex penalty in quasi-linear systems.

PubMed

Cui, Angang; Li, Haiyang; Wen, Meng; Peng, Jigen

2018-01-01

The goal of compressed sensing is to reconstruct a sparse signal under a few linear measurements far less than the dimension of the ambient space of the signal. However, many real-life applications in physics and biomedical sciences carry some strongly nonlinear structures, and the linear model is no longer suitable. Compared with the compressed sensing under the linear circumstance, this nonlinear compressed sensing is much more difficult, in fact also NP-hard, combinatorial problem, because of the discrete and discontinuous nature of the [Formula: see text]-norm and the nonlinearity. In order to get a convenience for sparse signal recovery, we set the nonlinear models have a smooth quasi-linear nature in this paper, and study a non-convex fraction function [Formula: see text] in this quasi-linear compressed sensing. We propose an iterative fraction thresholding algorithm to solve the regularization problem [Formula: see text] for all [Formula: see text]. With the change of parameter [Formula: see text], our algorithm could get a promising result, which is one of the advantages for our algorithm compared with some state-of-art algorithms. Numerical experiments show that our method performs much better than some state-of-the-art methods.

A wavelet-based ECG delineation algorithm for 32-bit integer online processing

PubMed Central

2011-01-01

Background Since the first well-known electrocardiogram (ECG) delineator based on Wavelet Transform (WT) presented by Li et al. in 1995, a significant research effort has been devoted to the exploitation of this promising method. Its ability to reliably delineate the major waveform components (mono- or bi-phasic P wave, QRS, and mono- or bi-phasic T wave) would make it a suitable candidate for efficient online processing of ambulatory ECG signals. Unfortunately, previous implementations of this method adopt non-linear operators such as root mean square (RMS) or floating point algebra, which are computationally demanding. Methods This paper presents a 32-bit integer, linear algebra advanced approach to online QRS detection and P-QRS-T waves delineation of a single lead ECG signal, based on WT. Results The QRS detector performance was validated on the MIT-BIH Arrhythmia Database (sensitivity Se = 99.77%, positive predictive value P+ = 99.86%, on 109010 annotated beats) and on the European ST-T Database (Se = 99.81%, P+ = 99.56%, on 788050 annotated beats). The ECG delineator was validated on the QT Database, showing a mean error between manual and automatic annotation below 1.5 samples for all fiducial points: P-onset, P-peak, P-offset, QRS-onset, QRS-offset, T-peak, T-offset, and a mean standard deviation comparable to other established methods. Conclusions The proposed algorithm exhibits reliable QRS detection as well as accurate ECG delineation, in spite of a simple structure built on integer linear algebra. PMID:21457580

A wavelet-based ECG delineation algorithm for 32-bit integer online processing.

PubMed

Di Marco, Luigi Y; Chiari, Lorenzo

2011-04-03

Since the first well-known electrocardiogram (ECG) delineator based on Wavelet Transform (WT) presented by Li et al. in 1995, a significant research effort has been devoted to the exploitation of this promising method. Its ability to reliably delineate the major waveform components (mono- or bi-phasic P wave, QRS, and mono- or bi-phasic T wave) would make it a suitable candidate for efficient online processing of ambulatory ECG signals. Unfortunately, previous implementations of this method adopt non-linear operators such as root mean square (RMS) or floating point algebra, which are computationally demanding. This paper presents a 32-bit integer, linear algebra advanced approach to online QRS detection and P-QRS-T waves delineation of a single lead ECG signal, based on WT. The QRS detector performance was validated on the MIT-BIH Arrhythmia Database (sensitivity Se = 99.77%, positive predictive value P+ = 99.86%, on 109010 annotated beats) and on the European ST-T Database (Se = 99.81%, P+ = 99.56%, on 788050 annotated beats). The ECG delineator was validated on the QT Database, showing a mean error between manual and automatic annotation below 1.5 samples for all fiducial points: P-onset, P-peak, P-offset, QRS-onset, QRS-offset, T-peak, T-offset, and a mean standard deviation comparable to other established methods. The proposed algorithm exhibits reliable QRS detection as well as accurate ECG delineation, in spite of a simple structure built on integer linear algebra.

Instantaneous and Frequency-Warped Signal Processing Techniques for Auditory Source Separation.

NASA Astrophysics Data System (ADS)

Wang, Avery Li-Chun

This thesis summarizes several contributions to the areas of signal processing and auditory source separation. The philosophy of Frequency-Warped Signal Processing is introduced as a means for separating the AM and FM contributions to the bandwidth of a complex-valued, frequency-varying sinusoid p (n), transforming it into a signal with slowly-varying parameters. This transformation facilitates the removal of p (n) from an additive mixture while minimizing the amount of damage done to other signal components. The average winding rate of a complex-valued phasor is explored as an estimate of the instantaneous frequency. Theorems are provided showing the robustness of this measure. To implement frequency tracking, a Frequency-Locked Loop algorithm is introduced which uses the complex winding error to update its frequency estimate. The input signal is dynamically demodulated and filtered to extract the envelope. This envelope may then be remodulated to reconstruct the target partial, which may be subtracted from the original signal mixture to yield a new, quickly-adapting form of notch filtering. Enhancements to the basic tracker are made which, under certain conditions, attain the Cramer -Rao bound for the instantaneous frequency estimate. To improve tracking, the novel idea of Harmonic -Locked Loop tracking, using N harmonically constrained trackers, is introduced for tracking signals, such as voices and certain musical instruments. The estimated fundamental frequency is computed from a maximum-likelihood weighting of the N tracking estimates, making it highly robust. The result is that harmonic signals, such as voices, can be isolated from complex mixtures in the presence of other spectrally overlapping signals. Additionally, since phase information is preserved, the resynthesized harmonic signals may be removed from the original mixtures with relatively little damage to the residual signal. Finally, a new methodology is given for designing linear-phase FIR filters which require a small fraction of the computational power of conventional FIR implementations. This design strategy is based on truncated and stabilized IIR filters. These signal-processing methods have been applied to the problem of auditory source separation, resulting in voice separation from complex music that is significantly better than previous results at far lower computational cost.

An SVM-based solution for fault detection in wind turbines.

PubMed

Santos, Pedro; Villa, Luisa F; Reñones, Aníbal; Bustillo, Andres; Maudes, Jesús

2015-03-09

Research into fault diagnosis in machines with a wide range of variable loads and speeds, such as wind turbines, is of great industrial interest. Analysis of the power signals emitted by wind turbines for the diagnosis of mechanical faults in their mechanical transmission chain is insufficient. A successful diagnosis requires the inclusion of accelerometers to evaluate vibrations. This work presents a multi-sensory system for fault diagnosis in wind turbines, combined with a data-mining solution for the classification of the operational state of the turbine. The selected sensors are accelerometers, in which vibration signals are processed using angular resampling techniques and electrical, torque and speed measurements. Support vector machines (SVMs) are selected for the classification task, including two traditional and two promising new kernels. This multi-sensory system has been validated on a test-bed that simulates the real conditions of wind turbines with two fault typologies: misalignment and imbalance. Comparison of SVM performance with the results of artificial neural networks (ANNs) shows that linear kernel SVM outperforms other kernels and ANNs in terms of accuracy, training and tuning times. The suitability and superior performance of linear SVM is also experimentally analyzed, to conclude that this data acquisition technique generates linearly separable datasets.

Predicting the performance of linear optical detectors in free space laser communication links

NASA Astrophysics Data System (ADS)

Farrell, Thomas C.

2018-05-01

While the fundamental performance limit for optical communications is set by the quantum nature of light, in practical systems background light, dark current, and thermal noise of the electronics also degrade performance. In this paper, we derive a set of equations predicting the performance of PIN diodes and linear mode avalanche photo diodes (APDs) in the presence of such noise sources. Electrons generated by signal, background, and dark current shot noise are well modeled in PIN diodes as Poissonian statistical processes. In APDs, on the other hand, the amplifying effects of the device result in statistics that are distinctly non-Poissonian. Thermal noise is well modeled as Gaussian. In this paper, we appeal to the central limit theorem and treat both the variability of the signal and the sum of noise sources as Gaussian. Comparison against Monte-Carlo simulation of PIN diode performance (where we do model shot noise with draws from a Poissonian distribution) validates the legitimacy of this approximation. On-off keying, M-ary pulse position, and binary differential phase shift keying modulation are modeled. We conclude with examples showing how the equations may be used in a link budget to estimate the performance of optical links using linear receivers.

Dynamics of chromatic visual system processing differ in complexity between children and adults.

PubMed

Boon, Mei Ying; Suttle, Catherine M; Henry, Bruce I; Dain, Stephen J

2009-06-30

Measures of chromatic contrast sensitivity in children are lower than those of adults. This may be related to immaturities in signal processing at or near threshold. We have found that children's VEPs in response to low contrast supra-threshold chromatic stimuli are more intra-individually variable than those recorded from adults. Here, we report on linear and nonlinear analyses of chromatic VEPs recorded from children and adults. Two measures of signal-to-noise ratio are similar between the adults and children, suggesting that relatively high noise is unlikely to account for the poor clarity of negative and positive peak components in the children's VEPs. Nonlinear analysis indicates higher complexity of adults' than children's chromatic VEPs, at levels of chromatic contrast around and well above threshold.

Optical apparatus for laser scattering by objects having complex shapes

DOEpatents

Ellingson, William A.; Visher, Robert J.

2006-11-14

Apparatus for observing and measuring in realtime surface and subsurface characteristics of objects having complex shapes includes an optical fiber bundle having first and second opposed ends. The first end includes a linear array of fibers, where the ends of adjacent fibers are in contact and are aligned perpendicular to the surface of the object being studied. The second ends of some of the fibers are in the form of a polished ferrule forming a multi-fiber optical waveguide for receiving laser light. The second ends of the remaining fibers are formed into a linear array suitable for direct connection to a detector, such as a linear CMOS-based optical detector. The output data is analyzed using digital signal processing for the detection of anomalies such as cracks, voids, inclusions and other defects.

Wideband FM Demodulation and Multirate Frequency Transformations

DTIC Science & Technology

2016-12-15

FM signals. 2.2.1 Adaptive Linear Predictive IF Tracking For a pure FM signal, the IF demodulation approach employing adaptive filters was proposed...desired signal. As summarized in [5], the prediction error filter is given by: E (z) = 1− L∑ l=1 goptl z −l, (8) 2 Approved for public release...assumption and the further assumption that the message signal remains es- sentially invariant over the sampling range of the linear prediction filter , we end

Time-Frequency Analysis of Non-Stationary Biological Signals with Sparse Linear Regression Based Fourier Linear Combiner.

PubMed

Wang, Yubo; Veluvolu, Kalyana C

2017-06-14

It is often difficult to analyze biological signals because of their nonlinear and non-stationary characteristics. This necessitates the usage of time-frequency decomposition methods for analyzing the subtle changes in these signals that are often connected to an underlying phenomena. This paper presents a new approach to analyze the time-varying characteristics of such signals by employing a simple truncated Fourier series model, namely the band-limited multiple Fourier linear combiner (BMFLC). In contrast to the earlier designs, we first identified the sparsity imposed on the signal model in order to reformulate the model to a sparse linear regression model. The coefficients of the proposed model are then estimated by a convex optimization algorithm. The performance of the proposed method was analyzed with benchmark test signals. An energy ratio metric is employed to quantify the spectral performance and results show that the proposed method Sparse-BMFLC has high mean energy (0.9976) ratio and outperforms existing methods such as short-time Fourier transfrom (STFT), continuous Wavelet transform (CWT) and BMFLC Kalman Smoother. Furthermore, the proposed method provides an overall 6.22% in reconstruction error.

Self-amplified CMOS image sensor using a current-mode readout circuit

NASA Astrophysics Data System (ADS)

Santos, Patrick M.; de Lima Monteiro, Davies W.; Pittet, Patrick

2014-05-01

The feature size of the CMOS processes decreased during the past few years and problems such as reduced dynamic range have become more significant in voltage-mode pixels, even though the integration of more functionality inside the pixel has become easier. This work makes a contribution on both sides: the possibility of a high signal excursion range using current-mode circuits together with functionality addition by making signal amplification inside the pixel. The classic 3T pixel architecture was rebuild with small modifications to integrate a transconductance amplifier providing a current as an output. The matrix with these new pixels will operate as a whole large transistor outsourcing an amplified current that will be used for signal processing. This current is controlled by the intensity of the light received by the matrix, modulated pixel by pixel. The output current can be controlled by the biasing circuits to achieve a very large range of output signal levels. It can also be controlled with the matrix size and this permits a very high degree of freedom on the signal level, observing the current densities inside the integrated circuit. In addition, the matrix can operate at very small integration times. Its applications would be those in which fast imaging processing, high signal amplification are required and low resolution is not a major problem, such as UV image sensors. Simulation results will be presented to support: operation, control, design, signal excursion levels and linearity for a matrix of pixels that was conceived using this new concept of sensor.

Experimental quantification of the true efficiency of carbon nanotube thin-film thermophones.

PubMed

Bouman, Troy M; Barnard, Andrew R; Asgarisabet, Mahsa

2016-03-01

Carbon nanotube thermophones can create acoustic waves from 1 Hz to 100 kHz. The thermoacoustic effect that allows for this non-vibrating sound source is naturally inefficient. Prior efforts have not explored their true efficiency (i.e., the ratio of the total acoustic power to the electrical input power). All previous works have used the ratio of sound pressure to input electrical power. A method for true power efficiency measurement is shown using a fully anechoic technique. True efficiency data are presented for three different drive signal processing techniques: standard alternating current (AC), direct current added to alternating current (DCAC), and amplitude modulation of an alternating current (AMAC) signal. These signal processing techniques are needed to limit the frequency doubling non-linear effects inherent to carbon nanotube thermophones. Each type of processing affects the true efficiency differently. Using a 72 W(rms) input signal, the measured efficiency ranges were 4.3 × 10(-6) - 319 × 10(-6), 1.7 × 10(-6) - 308 × 10(-6), and 1.2 × 10(-6) - 228 × 10(-6)% for AC, DCAC, and AMAC, respectively. These data were measured in the frequency range of 100 Hz to 10 kHz. In addition, the effects of these processing techniques relative to sound quality are presented in terms of total harmonic distortion.

Sensory integration of a light touch reference in human standing balance.

PubMed

Assländer, Lorenz; Smith, Craig P; Reynolds, Raymond F

2018-01-01

In upright stance, light touch of a space-stationary touch reference reduces spontaneous sway. Moving the reference evokes sway responses which exhibit non-linear behavior that has been attributed to sensory reweighting. Reweighting refers to a change in the relative contribution of sensory cues signaling body sway in space and light touch cues signaling finger position with respect to the body. Here we test the hypothesis that the sensory fusion process involves a transformation of light touch signals into the same reference frame as other sensory inputs encoding body sway in space, or vice versa. Eight subjects lightly gripped a robotic manipulandum which moved in a circular arc around the ankle joint. A pseudo-randomized motion sequence with broad spectral characteristics was applied at three amplitudes. The stimulus was presented at two different heights and therefore different radial distances, which were matched in terms of angular motion. However, the higher stimulus evoked a significantly larger sway response, indicating that the response was not matched to stimulus angular motion. Instead, the body sway response was strongly related to the horizontal translation of the manipulandum. The results suggest that light touch is integrated as the horizontal distance between body COM and the finger. The data were well explained by a model with one feedback loop minimizing changes in horizontal COM-finger distance. The model further includes a second feedback loop estimating the horizontal finger motion and correcting the first loop when the touch reference is moving. The second loop includes the predicted transformation of sensory signals into the same reference frame and a non-linear threshold element that reproduces the non-linear sway responses, thus providing a mechanism that can explain reweighting.

Sensory integration of a light touch reference in human standing balance

PubMed Central

Smith, Craig P.; Reynolds, Raymond F.

2018-01-01

In upright stance, light touch of a space-stationary touch reference reduces spontaneous sway. Moving the reference evokes sway responses which exhibit non-linear behavior that has been attributed to sensory reweighting. Reweighting refers to a change in the relative contribution of sensory cues signaling body sway in space and light touch cues signaling finger position with respect to the body. Here we test the hypothesis that the sensory fusion process involves a transformation of light touch signals into the same reference frame as other sensory inputs encoding body sway in space, or vice versa. Eight subjects lightly gripped a robotic manipulandum which moved in a circular arc around the ankle joint. A pseudo-randomized motion sequence with broad spectral characteristics was applied at three amplitudes. The stimulus was presented at two different heights and therefore different radial distances, which were matched in terms of angular motion. However, the higher stimulus evoked a significantly larger sway response, indicating that the response was not matched to stimulus angular motion. Instead, the body sway response was strongly related to the horizontal translation of the manipulandum. The results suggest that light touch is integrated as the horizontal distance between body COM and the finger. The data were well explained by a model with one feedback loop minimizing changes in horizontal COM-finger distance. The model further includes a second feedback loop estimating the horizontal finger motion and correcting the first loop when the touch reference is moving. The second loop includes the predicted transformation of sensory signals into the same reference frame and a non-linear threshold element that reproduces the non-linear sway responses, thus providing a mechanism that can explain reweighting. PMID:29874252

A Machine Learning Approach to the Detection of Pilot's Reaction to Unexpected Events Based on EEG Signals

PubMed Central

Cyran, Krzysztof A.

2018-01-01

This work considers the problem of utilizing electroencephalographic signals for use in systems designed for monitoring and enhancing the performance of aircraft pilots. Systems with such capabilities are generally referred to as cognitive cockpits. This article provides a description of the potential that is carried by such systems, especially in terms of increasing flight safety. Additionally, a neuropsychological background of the problem is presented. Conducted research was focused mainly on the problem of discrimination between states of brain activity related to idle but focused anticipation of visual cue and reaction to it. Especially, a problem of selecting a proper classification algorithm for such problems is being examined. For that purpose an experiment involving 10 subjects was planned and conducted. Experimental electroencephalographic data was acquired using an Emotiv EPOC+ headset. Proposed methodology involved use of a popular method in biomedical signal processing, the Common Spatial Pattern, extraction of bandpower features, and an extensive test of different classification algorithms, such as Linear Discriminant Analysis, k-nearest neighbors, and Support Vector Machines with linear and radial basis function kernels, Random Forests, and Artificial Neural Networks. PMID:29849544

Optimized linear motor and digital PID controller setup used in Mössbauer spectrometer

NASA Astrophysics Data System (ADS)

Kohout, Pavel; Kouřil, Lukáš; Navařík, Jakub; Novák, Petr; Pechoušek, Jiří

2014-10-01

Optimization of a linear motor and digital PID controller setup used in a Mössbauer spectrometer is presented. Velocity driving system with a digital PID feedback subsystem was developed in the LabVIEW graphical environment and deployed on the sbRIO real-time hardware device (National Instruments). The most important data acquisition processes are performed as real-time deterministic tasks on an FPGA chip. Velocity transducer of a double loudspeaker type with a power amplifier circuit is driven by the system. Series of calibration measurements were proceeded to find the optimal setup of the P, I, D parameters together with velocity error signal analysis. The shape and given signal characteristics of the velocity error signal are analyzed in details. Remote applications for controlling and monitoring the PID system from computer or smart phone, respectively, were also developed. The best setup and P, I, D parameters were set and calibration spectrum of α-Fe sample with an average nonlinearity of the velocity scale below 0.08% was collected. Furthermore, the width of the spectral line below 0.30 mm/s was observed. Powerful and complex velocity driving system was designed.

A Novel Offset Cancellation Based on Parasitic-Insensitive Switched-Capacitor Sensing Circuit for the Out-of-Plane Single-Gimbaled Decoupled CMOS-MEMS Gyroscope

PubMed Central

Chang, Ming-Hui; Huang, Han-Pang

2013-01-01

This paper presents a novel parasitic-insensitive switched-capacitor (PISC) sensing circuit design in order to obtain high sensitivity and ultra linearity and reduce the parasitic effect for the out-of-plane single-gimbaled decoupled CMOS-MEMS gyroscope (SGDG). According to the simulation results, the proposed PISC circuit has better sensitivity and high linearity in a wide dynamic range. Experimental results also show a better performance. In addition, the PISC circuit can use signal processing to cancel the offset and noise. Thus, this circuit is very suitable for gyroscope measurement. PMID:23493122

Short cavity active mode locking fiber laser for optical sensing and imaging

NASA Astrophysics Data System (ADS)

Lee, Hwi Don; Han, Ga Hee; Jeong, Syung Won; Jeong, Myung Yung; Kim, Chang-Seok; Shin, Jun Geun; Lee, Byeong Ha; Eom, Tae Joong

2014-05-01

We demonstrate a highly linear wavenumber- swept active mode locking (AML) fiber laser for optical sensing and imaging without any wavenumber-space resampling process. In this all-electric AML wavenumber-swept mechanism, a conventional wavelength selection filter is eliminated and, instead, the suitable programmed electric modulation signal is directly applied to the gain medium. Various types of wavenumber (or wavelength) tunings can be implemented because of the filter-less cavity configuration. Therefore, we successfully demonstrate a linearly wavenumber-swept AML fiber laser with 26.5 mW of output power to obtain an in-vivo OCT image at the 100 kHz swept rate.

AlN based piezoelectric micromirror.

PubMed

Shao, Jian; Li, Qi; Feng, Chuhuan; Li, Wei; Yu, Hongbin

2018-03-01

Aiming to pursue a micromirror possessing many desired characteristics, such as linear control, low power consumption, fast response, and easy fabrication, a new piezoelectric actuation strategy is presented. Different from conventional piezoelectric actuation cases, we first propose using AlN film as the active layer for actuating the micromirror. Owing to its good CMOS compatible deposition and patterning techniques, the AlN based piezoelectric micromirror has been successfully fabricated with a modified silicon-on-insulator-based microelectromechanical system (MEMS) process. At the same time, various mirror movement modes operating at high frequencies and excellent linear relationship between the movement and the control signal both have been experimentally demonstrated.

Development of semiconductor tracking: The future linear collider case

NASA Astrophysics Data System (ADS)

Savoy-Navarro, Aurore

2011-04-01

An active R&D on silicon tracking for the linear collider, SiLC, is pursued since several years to develop the new generation of large area silicon trackers for the future linear collider(s). The R&D objectives on new sensors, new front end processing of the signal, and the related mechanical and integration challenges for building such large detectors within the proposed detector concepts are described. Synergies and differences with the LHC construction and upgrades are explained. The differences between the linear collider projects, namely the international linear collider, ILC, and the compact linear collider, CLIC, are discussed as well. Two final objectives are presented for the construction of this important sub-detector for the future linear collider experiments: a relatively short term design based on micro-strips combined or not with a gaseous central tracker and a longer term design based on an all-pixel tracker.The R&D objectives on sensors include single sided micro-strips as baseline for the shorter term with the strips from large wafers (at least 6 in), 200 μm thick, 50 μm pitch and the edgeless and alignment friendly options. This work is conducted by SiLC in collaboration with three technical research centers in Italy, Finland, and Spain and HPK. SiLC is studied as well, using advanced Si sensor technologies for higher granularity trackers especially short strips and pixels all based on 3D technology. New Deep Sub-Micron CMOS mix mode (analog and digital) FE and readout electronics are developed to fully process the detector signals currently adapted to the ILC cycle. It is a high-level processing and a fully programmable ASIC; highly fault tolerant. In its latest version, handling 128 channels will equip these next coming years larger size silicon tracking prototypes at test beams. Connection of the FEE chip on the silicon detector especially in the strip case is a major issue. Very preliminary results with inline pitch adapter based on wiring were just achieved. Bump-bonding or 3D vertical interconnect is the other SiLC R&D objective. The goal is to simplify the overall architecture and decrease the material budget of these devices. Three tracking concepts are briefly discussed, two of which are part of the ILC Letter of Intent of the ILD and SiD detector concepts. These last years, SiLC successfully performed beam tests to experience and test these R&D lines.

Signal processing and calibration procedures for in situ diode-laser absorption spectroscopy.

PubMed

Werle, P W; Mazzinghi, P; D'Amato, F; De Rosa, M; Maurer, K; Slemr, F

2004-07-01

Gas analyzers based on tunable diode-laser spectroscopy (TDLS) provide high sensitivity, fast response and highly specific in situ measurements of several atmospheric trace gases simultaneously. Under optimum conditions even a shot noise limited performance can be obtained. For field applications outside the laboratory practical limitations are important. At ambient mixing ratios below a few parts-per-billion spectrometers become more and more sensitive towards noise, interference, drift effects and background changes associated with low level signals. It is the purpose of this review to address some of the problems which are encountered at these low levels and to describe a signal processing strategy for trace gas monitoring and a concept for in situ system calibration applicable for tunable diode-laser spectroscopy. To meet the requirement of quality assurance for field measurements and monitoring applications, procedures to check the linearity according to International Standard Organization regulations are described and some measurements of calibration functions are presented and discussed.

Suppression of Stimulus Artifact Contaminating Electrically Evoked Electromyography

PubMed Central

Liu, Jie; Li, Sheng; Li, Xiaoyan; Klein, Cliff; Rymer, William Z.; Zhou, Ping

2013-01-01

Background Electrical stimulation of muscle or nerve is a very useful technique for understanding of muscle activity and its pathological changes for both diagnostic and therapeutic purposes. During electrical stimulation of a muscle, the recorded M wave is often contaminated by a stimulus artifact. The stimulus artifact must be removed for appropriate analysis and interpretation of M waves. Objectives The objective of this study was to develop a novel software based method to remove stimulus artifacts contaminating or superimposing with electrically evoked surface electromyography (EMG) or M wave signals. Methods The multiple stage method uses a series of signal processing techniques, including highlighting and detection of stimulus artifacts using the Savitzky-Golay filtering, estimation of the artifact contaminated region with the Otsu thresholding, and reconstruction of such region using signal interpolation and smoothing. The developed method was tested using M wave signals recorded from biceps brachii muscles by a linear surface electrode array. To evaluate the performance, a series of semi-synthetic signals were constructed from clean M wave and stimulus artifact recordings with different degrees of overlap between them. Results The effectiveness of the developed method was quantified by a significant increase in correlation coefficient and a significant decrease in root mean square error between the clean M wave and the reconstructed M wave, compared with those between the clean M wave and the originally contaminated signal. The validity of the developed method was also demonstrated when tested on each channel’s M wave recording using the linear electrode array. Conclusions The developed method can suppress stimulus artifacts contaminating M wave recordings. PMID:24419021

Ion-neutral Clustering of Bile Acids in Electrospray Ionization Across UPLC Flow Regimes

NASA Astrophysics Data System (ADS)

Brophy, Patrick; Broeckling, Corey D.; Murphy, James; Prenni, Jessica E.

2018-02-01

Bile acid authentic standards were used as model compounds to quantitatively evaluate complex in-source phenomenon on a UPLC-ESI-TOF-MS operated in the negative mode. Three different diameter columns and a ceramic-based microfluidic separation device were utilized, allowing for detailed descriptions of bile acid behavior across a wide range of flow regimes and instantaneous concentrations. A custom processing algorithm based on correlation analysis was developed to group together all ion signals arising from a single compound; these grouped signals produce verified compound spectra for each bile acid at each on-column mass loading. Significant adduction was observed for all bile acids investigated under all flow regimes and across a wide range of bile acid concentrations. The distribution of bile acid containing clusters was found to depend on the specific bile acid species, solvent flow rate, and bile acid concentration. Relative abundancies of each cluster changed non-linearly with concentration. It was found that summing all MS level (low collisional energy) ions and ion-neutral adducts arising from a single compound improves linearity across the concentration range (0.125-5 ng on column) and increases the sensitivity of MS level quantification. The behavior of each cluster roughly follows simple equilibrium processes consistent with our understanding of electrospray ionization mechanisms and ion transport processes occurring in atmospheric pressure interfaces. [Figure not available: see fulltext.

Demonstration of optical computing logics based on binary decision diagram.

PubMed

Lin, Shiyun; Ishikawa, Yasuhiko; Wada, Kazumi

2012-01-16

Optical circuits are low power consumption and fast speed alternatives for the current information processing based on transistor circuits. However, because of no transistor function available in optics, the architecture for optical computing should be chosen that optics prefers. One of which is Binary Decision Diagram (BDD), where signal is processed by sending an optical signal from the root through a serial of switching nodes to the leaf (terminal). Speed of optical computing is limited by either transmission time of optical signals from the root to the leaf or switching time of a node. We have designed and experimentally demonstrated 1-bit and 2-bit adders based on the BDD architecture. The switching nodes are silicon ring resonators with a modulation depth of 10 dB and the states are changed by the plasma dispersion effect. The quality, Q of the rings designed is 1500, which allows fast transmission of signal, e.g., 1.3 ps calculated by a photon escaping time. A total processing time is thus analyzed to be ~9 ps for a 2-bit adder and would scales linearly with the number of bit. It is two orders of magnitude faster than the conventional CMOS circuitry, ~ns scale of delay. The presented results show the potential of fast speed optical computing circuits.

A 24-GHz portable FMCW radar with continuous beam steering phased array (Conference Presentation)

NASA Astrophysics Data System (ADS)

Peng, Zhengyu; Li, Changzhi

2017-05-01

A portable 24-GHz frequency-modulated continuous-wave (FMCW) radar with continuous beam steering phased array is presented. This board-level integrated radar system consists of a phased array antenna, a radar transceiver and a baseband. The phased array used by the receiver is a 4-element linear array. The beam of the phased array can be continuously steered with a range of ±30° on the H-plane through an array of vector controllers. The vector controller is based on the concept of vector sum with binary-phase-shift attenuators. Each vector controller is capable of independently controlling the phase and the amplitude of each element of the linear array. The radar transceiver is based on the six-port technique. A free-running voltage controlled oscillator (VCO) is controlled by an analog "sawtooth" voltage generator to produce frequency-modulated chirp signal. This chirp signal is used as the transmitter signal, as well as the local oscillator (LO) signal to drive the six-port circuit. The transmitter antenna is a single patch antenna. In the baseband, the beat signal of the FMCW radar is detected by the six-port circuit and then processed by a laptop in real time. Experiments have been performed to reveal the capabilities of the proposed radar system for applications including indoor inverse synthetic aperture radar (ISAR) imaging, vital sign detection, and short-range navigation, etc. (This abstract is for the profiles session.)

Study on the description method of upper limb's muscle force levels during simulated in-orbit operations

NASA Astrophysics Data System (ADS)

Zhao, Yan; Li, DongXu; Liu, ZhiZhen; Liu, Liang

2013-03-01

The dexterous upper limb serves as the most important tool for astronauts to implement in-orbit experiments and operations. This study developed a simulated weightlessness experiment and invented new measuring equipment to quantitatively evaluate the muscle ability of the upper limb. Isometric maximum voluntary contractions (MVCs) and surface electromyography (sEMG) signals of right-handed pushing at the three positions were measured for eleven subjects. In order to enhance the comprehensiveness and accuracy of muscle force assessment, the study focused on signal processing techniques. We applied a combination method, which consists of time-, frequency-, and bi-frequency-domain analyses. Time- and frequency-domain analyses estimated the root mean square (RMS) and median frequency (MDF) of sEMG signals, respectively. Higher order spectra (HOS) of bi-frequency domain evaluated the maximum bispectrum amplitude ( B max), Gaussianity level (Sg) and linearity level (S l ) of sEMG signals. Results showed that B max, S l , and RMS values all increased as force increased. MDF and Sg values both declined as force increased. The research demonstrated that the combination method is superior to the conventional time- and frequency-domain analyses. The method not only described sEMG signal amplitude and power spectrum, but also deeper characterized phase coupling information and non-Gaussianity and non-linearity levels of sEMG, compared to two conventional analyses. The finding from the study can aid ergonomist to estimate astronaut muscle performance, so as to optimize in-orbit operation efficacy and minimize musculoskeletal injuries.

A comparative robustness evaluation of feedforward neurofilters

NASA Technical Reports Server (NTRS)

Troudet, Terry; Merrill, Walter

1993-01-01

A comparative performance and robustness analysis is provided for feedforward neurofilters trained with back propagation to filter additive white noise. The signals used in this analysis are simulated pitch rate responses to typical pilot command inputs for a modern fighter aircraft model. Various configurations of nonlinear and linear neurofilters are trained to estimate exact signal values from input sequences of noisy sampled signal values. In this application, nonlinear neurofiltering is found to be more efficient than linear neurofiltering in removing the noise from responses of the nominal vehicle model, whereas linear neurofiltering is found to be more robust in the presence of changes in the vehicle dynamics. The possibility of enhancing neurofiltering through hybrid architectures based on linear and nonlinear neuroprocessing is therefore suggested as a way of taking advantage of the robustness of linear neurofiltering, while maintaining the nominal performance advantage of nonlinear neurofiltering.

Event-driven processing for hardware-efficient neural spike sorting

NASA Astrophysics Data System (ADS)

Liu, Yan; Pereira, João L.; Constandinou, Timothy G.

2018-02-01

Objective. The prospect of real-time and on-node spike sorting provides a genuine opportunity to push the envelope of large-scale integrated neural recording systems. In such systems the hardware resources, power requirements and data bandwidth increase linearly with channel count. Event-based (or data-driven) processing can provide here a new efficient means for hardware implementation that is completely activity dependant. In this work, we investigate using continuous-time level-crossing sampling for efficient data representation and subsequent spike processing. Approach. (1) We first compare signals (synthetic neural datasets) encoded with this technique against conventional sampling. (2) We then show how such a representation can be directly exploited by extracting simple time domain features from the bitstream to perform neural spike sorting. (3) The proposed method is implemented in a low power FPGA platform to demonstrate its hardware viability. Main results. It is observed that considerably lower data rates are achievable when using 7 bits or less to represent the signals, whilst maintaining the signal fidelity. Results obtained using both MATLAB and reconfigurable logic hardware (FPGA) indicate that feature extraction and spike sorting accuracies can be achieved with comparable or better accuracy than reference methods whilst also requiring relatively low hardware resources. Significance. By effectively exploiting continuous-time data representation, neural signal processing can be achieved in a completely event-driven manner, reducing both the required resources (memory, complexity) and computations (operations). This will see future large-scale neural systems integrating on-node processing in real-time hardware.

Locating hydrothermal acoustic sources at Old Faithful Geyser using Matched Field Processing

NASA Astrophysics Data System (ADS)

Cros, E.; Roux, P.; Vandemeulebrouck, J.; Kedar, S.

2011-10-01

In 1992, a large and dense array of geophones was placed around the geyser vent of Old Faithful, in the Yellowstone National Park, to determine the origin of the seismic hydrothermal noise recorded at the surface of the geyser and to understand its dynamics. Old Faithful Geyser (OFG) is a small-scale hydrothermal system where a two-phase flow mixture erupts every 40 to 100 min in a high continuous vertical jet. Using Matched Field Processing (MFP) techniques on 10-min-long signal, we localize the source of the seismic pulses recorded at the surface of the geyser. Several MFP approaches are compared in this study, the frequency-incoherent and frequency-coherent approach, as well as the linear Bartlett processing and the non-linear Minimum Variance Distorsionless Response (MVDR) processing. The different MFP techniques used give the same source position with better focalization in the case of the MVDR processing. The retrieved source position corresponds to the geyser conduit at a depth of 12 m and the localization is in good agreement with in situ measurements made at Old Faithful in past studies.

VEGA: A low-power front-end ASIC for large area multi-linear X-ray silicon drift detectors: Design and experimental characterization

NASA Astrophysics Data System (ADS)

Ahangarianabhari, Mahdi; Macera, Daniele; Bertuccio, Giuseppe; Malcovati, Piero; Grassi, Marco

2015-01-01

We present the design and the first experimental characterization of VEGA, an Application Specific Integrated Circuit (ASIC) designed to read out large area monolithic linear Silicon Drift Detectors (SDD's). VEGA consists of an analog and a digital/mixed-signal section to accomplish all the functionalities and specifications required for high resolution X-ray spectroscopy in the energy range between 500 eV and 50 keV. The analog section includes a charge sensitive preamplifier, a shaper with 3-bit digitally selectable shaping times from 1.6 μs to 6.6 μs and a peak stretcher/sample-and-hold stage. The digital/mixed-signal section includes an amplitude discriminator with coarse and fine threshold level setting, a peak discriminator and a logic circuit to fulfill pile-up rejection, signal sampling, trigger generation, channel reset and the preamplifier and discriminators disabling functionalities. A Serial Peripherical Interface (SPI) is integrated in VEGA for loading and storing all configuration parameters in an internal register within few microseconds. The VEGA ASIC has been designed and manufactured in 0.35 μm CMOS mixed-signal technology in single and 32 channel versions with dimensions of 200 μm×500 μm per channel. A minimum intrinsic Equivalent Noise Charge (ENC) of 12 electrons r.m.s. at 3.6 μs peaking time and room temperature is measured and the linearity error is between -0.9% and +0.6% in the whole input energy range. The total power consumption is 481 μW and 420 μW per channel for the single and 32 channels version, respectively. A comparison with other ASICs for X-ray SDD's shows that VEGA has a suitable low noise and offers high functionality as ADC-ready signal processing but at a power consumption that is a factor of four lower than other similar existing ASICs.

Waveshaping electronic circuit

NASA Technical Reports Server (NTRS)

Harper, T. P.

1971-01-01

Circuit provides output signal with sinusoidal function in response to bipolar transition of input signal. Instantaneous transition shapes into linear rate of change and linear rate of change shapes into sinusoidal rate of change. Circuit contains only active components; therefore, compatibility with integrated circuit techniques is assured.

Quantification of crystalline cellulose in lignocellulosic biomass using sum frequency generation (SFG) vibration spectroscopy and comparison with other analytical methods.

PubMed

Barnette, Anna L; Lee, Christopher; Bradley, Laura C; Schreiner, Edward P; Park, Yong Bum; Shin, Heenae; Cosgrove, Daniel J; Park, Sunkyu; Kim, Seong H

2012-07-01

The non-centrosymmetry requirement of sum frequency generation (SFG) vibration spectroscopy allows the detection and quantification of crystalline cellulose in lignocellulose biomass without spectral interferences from hemicelluloses and lignin. This paper shows a correlation between the amount of crystalline cellulose in biomass and the SFG signal intensity. Model biomass samples were prepared by mixing commercially available cellulose, xylan, and lignin to defined concentrations. The SFG signal intensity was found sensitive to a wide range of crystallinity, but varied non-linearly with the mass fraction of cellulose in the samples. This might be due to the matrix effects such as light scattering and absorption by xylan and lignin, as well as the non-linear density dependence of the SFG process itself. Comparison with other techniques such as XRD, FT-Raman, FT-IR and NMR demonstrate that SFG can be a complementary and sensitive tool to assess crystalline cellulose in biomass. Copyright © 2012 Elsevier Ltd. All rights reserved.

Direction detection thresholds of passive self-motion in artistic gymnasts.

PubMed

Hartmann, Matthias; Haller, Katia; Moser, Ivan; Hossner, Ernst-Joachim; Mast, Fred W

2014-04-01

In this study, we compared direction detection thresholds of passive self-motion in the dark between artistic gymnasts and controls. Twenty-four professional female artistic gymnasts (ranging from 7 to 20 years) and age-matched controls were seated on a motion platform and asked to discriminate the direction of angular (yaw, pitch, roll) and linear (leftward-rightward) motion. Gymnasts showed lower thresholds for the linear leftward-rightward motion. Interestingly, there was no difference for the angular motions. These results show that the outstanding self-motion abilities in artistic gymnasts are not related to an overall higher sensitivity in self-motion perception. With respect to vestibular processing, our results suggest that gymnastic expertise is exclusively linked to superior interpretation of otolith signals when no change in canal signals is present. In addition, thresholds were overall lower for the older (14-20 years) than for the younger (7-13 years) participants, indicating the maturation of vestibular sensitivity from childhood to adolescence.

OPTICAL INFORMATION PROCESSING: Modulation—spectral analysis of an image transmitted across a distorting medium

NASA Astrophysics Data System (ADS)

Zubov, Vladimir A.; Mironova, T. V.

1998-05-01

The task of simultaneous determination of the structure and characteristics of a two-dimensional amplitude—phase signal and a two-dimensional complex transfer or instrumental function is considered. The solution is based on determination of four independent intensity distributions of spectral representations of the signal Isr(ωx, ωy) subjected to the action of the transfer function, of the signal Ismr(ωx, ωy which) has experienced additional modulation applied in a certain manner and the action of the transfer function, of the signal Isrn(ωx, ωy) representing the signal Isr(ωx, ωy) with certain additional modulation at the output, and of the signal Ismrn(ωx, ωy) which is the signal Ismr(ωx, ωy) with certain additional modulation at the output. These intensity distributions make it possible to calculate the amplitude and phase components of the image being analysed and of the transfer function. Additional modulations should in some way ensure visualisation of the phase information. A specific type of additional spatial modulation, in the form of linear amplitude, is discussed.

Method and system for detecting a failure or performance degradation in a dynamic system such as a flight vehicle

NASA Technical Reports Server (NTRS)

Miller, Robert H. (Inventor); Ribbens, William B. (Inventor)

2003-01-01

A method and system for detecting a failure or performance degradation in a dynamic system having sensors for measuring state variables and providing corresponding output signals in response to one or more system input signals are provided. The method includes calculating estimated gains of a filter and selecting an appropriate linear model for processing the output signals based on the input signals. The step of calculating utilizes one or more models of the dynamic system to obtain estimated signals. The method further includes calculating output error residuals based on the output signals and the estimated signals. The method also includes detecting one or more hypothesized failures or performance degradations of a component or subsystem of the dynamic system based on the error residuals. The step of calculating the estimated values is performed optimally with respect to one or more of: noise, uncertainty of parameters of the models and un-modeled dynamics of the dynamic system which may be a flight vehicle or financial market or modeled financial system.

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

Lau, Sarah J.; Moore, David G.; Stair, Sarah L.

Ultrasonic analysis is being explored as a way to capture events during melting of highly dispersive wax. Typical events include temperature changes in the material, phase transition of the material, surface flows and reformations, and void filling as the material melts. Melt tests are performed with wax to evaluate the usefulness of different signal processing algorithms in capturing event data. Several algorithm paths are being pursued. The first looks at changes in the velocity of the signal through the material. This is only appropriate when the changes from one ultrasonic signal to the next can be represented by a linearmore » relationship, which is not always the case. The second tracks changes in the frequency content of the signal. The third algorithm tracks changes in the temporal moments of a signal over a full test. This method does not require that the changes in the signal be represented by a linear relationship, but attaching changes in the temporal moments to physical events can be difficult. This study describes the algorithm paths applied to experimental data from ultrasonic signals as wax melts and explores different ways to display the results.« less

Noise Reduction of Ocean-Bottom Pressure Data Toward Real-Time Tsunami Forecasting

NASA Astrophysics Data System (ADS)

Tsushima, H.; Hino, R.

2008-12-01

We discuss a method of noise reduction of ocean-bottom pressure data to be fed into the near-field tsunami forecasting scheme proposed by Tsushima et al. [2008a]. In their scheme, the pressure data is processed in real time as follows: (1) removing ocean tide components by subtracting the sea-level variation computed from a theoretical tide model, (2) applying low-pass digital filter to remove high-frequency fluctuation due to seismic waves, and (3) removing DC-offset and linear-trend component to determine a baseline of relative sea level. However, it turns out this simple method is not always successful in extracting tsunami waveforms from the data, when the observed amplitude is ~1cm. For disaster mitigation, accurate forecasting of small tsunamis is important as well as large tsunamis. Since small tsunami events occur frequently, successful tsunami forecasting of those events are critical to obtain public reliance upon tsunami warnings. As a test case, we applied the data-processing described above to the bottom pressure records containing tsunami with amplitude less than 1 cm which was generated by the 2003 Off-Fukushima earthquake occurring in the Japan Trench subduction zone. The observed pressure variation due to the ocean tide is well explained by the calculated tide signals from NAO99Jb model [Matsumoto et al., 2000]. However, the tide components estimated by BAYTAP-G [Tamura et al., 1991] from the pressure data is more appropriate for predicting and removing the ocean tide signals. In the pressure data after removing the tide variations, there remain pressure fluctuations with frequencies ranging from about 0.1 to 1 mHz and with amplitudes around ~10 cm. These fluctuations distort the estimation of zero-level and linear trend to define relative sea-level variation, which is treated as tsunami waveform in the subsequent analysis. Since the linear trend is estimated from the data prior to the origin time of the earthquake, an artificial linear trend is produced in the processed waveform. This artificial linear trend degrades the accuracy of the tsunami forecasting, although the forecasting result is expected to be robust against the existence of short-period noise [Tsushima et al., 2008a]. Since the bottom pressure show gradual increase (or decrease) in the tsunami source region [Tsushima et al., 2008b], it is important to remove the linear trend not related to the tsunami generation from the data before fed into the analysis. Therefore, the reduction of the noise in sub-mHz band is critical for the forecasting small tsunamis. Applying a kind of frequency filters to eliminate this noise cannot be a solution for this problem because actual tsunami signals may also contain components of this frequency band. We investigate whether any statistical modelings of the noise are effective for reducing the sub-mHz noise.

Bayesian least squares deconvolution

NASA Astrophysics Data System (ADS)

Asensio Ramos, A.; Petit, P.

2015-11-01

Aims: We develop a fully Bayesian least squares deconvolution (LSD) that can be applied to the reliable detection of magnetic signals in noise-limited stellar spectropolarimetric observations using multiline techniques. Methods: We consider LSD under the Bayesian framework and we introduce a flexible Gaussian process (GP) prior for the LSD profile. This prior allows the result to automatically adapt to the presence of signal. We exploit several linear algebra identities to accelerate the calculations. The final algorithm can deal with thousands of spectral lines in a few seconds. Results: We demonstrate the reliability of the method with synthetic experiments and we apply it to real spectropolarimetric observations of magnetic stars. We are able to recover the magnetic signals using a small number of spectral lines, together with the uncertainty at each velocity bin. This allows the user to consider if the detected signal is reliable. The code to compute the Bayesian LSD profile is freely available.

Relationship Between Maximum Tsunami Amplitude and Duration of Signal

NASA Astrophysics Data System (ADS)

Kim, Yoo Yin; Whitmore, Paul M.

2014-12-01

All available tsunami observations at tide gauges situated along the North American coast were examined to determine if there is any clear relationship between maximum amplitude and signal duration. In total, 89 historical tsunami recordings generated by 13 major earthquakes between 1952 and 2011 were investigated. Tidal variations were filtered out of the signal and the duration between the arrival time and the time at which the signals drops and stays below 0.3 m amplitude was computed. The processed tsunami time series were evaluated and a linear least-squares fit with a 95 % confidence interval was examined to compare tsunami durations with maximum tsunami amplitude in the study region. The confidence interval is roughly 20 h over the range of maximum tsunami amplitudes in which we are interested. This relatively large confidence interval likely results from variations in local resonance effects, late-arriving reflections, and other effects.

Non-linear dynamic compensation system

NASA Technical Reports Server (NTRS)

Lin, Yu-Hwan (Inventor); Lurie, Boris J. (Inventor)

1992-01-01

A non-linear dynamic compensation subsystem is added in the feedback loop of a high precision optical mirror positioning control system to smoothly alter the control system response bandwidth from a relatively wide response bandwidth optimized for speed of control system response to a bandwidth sufficiently narrow to reduce position errors resulting from the quantization noise inherent in the inductosyn used to measure mirror position. The non-linear dynamic compensation system includes a limiter for limiting the error signal within preselected limits, a compensator for modifying the limiter output to achieve the reduced bandwidth response, and an adder for combining the modified error signal with the difference between the limited and unlimited error signals. The adder output is applied to control system motor so that the system response is optimized for accuracy when the error signal is within the preselected limits, optimized for speed of response when the error signal is substantially beyond the preselected limits and smoothly varied therebetween as the error signal approaches the preselected limits.

Linear motor drive system for continuous-path closed-loop position control of an object

DOEpatents

Barkman, William E.

1980-01-01

A precision numerical controlled servo-positioning system is provided for continuous closed-loop position control of a machine slide or platform driven by a linear-induction motor. The system utilizes filtered velocity feedback to provide system stability required to operate with a system gain of 100 inches/minute/0.001 inch of following error. The filtered velocity feedback signal is derived from the position output signals of a laser interferometer utilized to monitor the movement of the slide. Air-bearing slides mounted to a stable support are utilized to minimize friction and small irregularities in the slideway which would tend to introduce positioning errors. A microprocessor is programmed to read command and feedback information and converts this information into the system following error signal. This error signal is summed with the negative filtered velocity feedback signal at the input of a servo amplifier whose output serves as the drive power signal to the linear motor position control coil.

Luminance and chromatic signals interact differently with melanopsin activation to control the pupil light response.

PubMed

Barrionuevo, Pablo A; Cao, Dingcai

2016-09-01

Intrinsically photosensitive retinal ganglion cells (ipRGCs) express the photopigment melanopsin. These cells receive afferent inputs from rods and cones, which provide inputs to the postreceptoral visual pathways. It is unknown, however, how melanopsin activation is integrated with postreceptoral signals to control the pupillary light reflex. This study reports human flicker pupillary responses measured using stimuli generated with a five-primary photostimulator that selectively modulated melanopsin, rod, S-, M-, and L-cone excitations in isolation, or in combination to produce postreceptoral signals. We first analyzed the light adaptation behavior of melanopsin activation and rod and cones signals. Second, we determined how melanopsin is integrated with postreceptoral signals by testing with cone luminance, chromatic blue-yellow, and chromatic red-green stimuli that were processed by magnocellular (MC), koniocellular (KC), and parvocellular (PC) pathways, respectively. A combined rod and melanopsin response was also measured. The relative phase of the postreceptoral signals was varied with respect to the melanopsin phase. The results showed that light adaptation behavior for all conditions was weaker than typical Weber adaptation. Melanopsin activation combined linearly with luminance, S-cone, and rod inputs, suggesting the locus of integration with MC and KC signals was retinal. The melanopsin contribution to phasic pupil responses was lower than luminance contributions, but much higher than S-cone contributions. Chromatic red-green modulation interacted with melanopsin activation nonlinearly as described by a "winner-takes-all" process, suggesting the integration with PC signals might be mediated by a postretinal site.

Multi-parametric polymer-based potentiometric analytical microsystem for future manned space missions.

PubMed

Calvo-López, Antonio; Puyol, Mar; Casalta, Joan Manel; Alonso-Chamarro, Julián

2017-12-01

The construction and evaluation of a Cyclic Olefin Copolymer (COC)-based continuous flow potentiometric microanalyzer to simultaneously monitor potassium, chloride and nitrate ions in samples from an on-board water recycling process expected to be installed in future manned space missions is presented. The main goals accomplished in this work address the specific required characteristics for a miniaturized on-line monitoring system to control water quality in such missions. To begin with, the integration of three ion-selective electrodes (ISEs) and a reference electrode in a compact microfluidic platform that incorporates a simple automatic autocalibration process allows obtaining information about the concentration of the three ions with optimal analytical response characteristics, but moreover with low reagents consumption and therefore with few waste generation, which is critical for this specific application. By a simple signal processing (signal removal) the chloride ion interference on the nitrate electrode response can be eliminated. Furthermore, all fluidics management is performed by computer-controlled microvalves and micropumps, so no manual intervention of the crew is necessary. The analytical features provided by the microsystem after the optimization process were a linear range from 6.3 to 630 mg L -1 and a detection limit of 0.51 mg L -1 for the potassium electrode, a linear range from 10 to 1000 mg L -1 and a detection limit of 1.58 mg L -1 for the chloride electrode and a linear range from 10 to 1000 mg L -1 and a detection limit of 3.37 mg L -1 for the nitrate electrode with a reproducibility (RSD) of 4%, 2% and 3% respectively. Sample throughput was 12 h -1 with a reagent consumptions lower than 2 mL per analysis. Copyright © 2017 Elsevier B.V. All rights reserved.

A Digital Lock-In Amplifier for Use at Temperatures of up to 200 °C

PubMed Central

Cheng, Jingjing; Xu, Yingjun; Wu, Lei; Wang, Guangwei

2016-01-01

Weak voltage signals cannot be reliably measured using currently available logging tools when these tools are subject to high-temperature (up to 200 °C) environments for prolonged periods. In this paper, we present a digital lock-in amplifier (DLIA) capable of operating at temperatures of up to 200 °C. The DLIA contains a low-noise instrument amplifier and signal acquisition and the corresponding signal processing electronics. The high-temperature stability of the DLIA is achieved by designing system-in-package (SiP) and multi-chip module (MCM) components with low thermal resistances. An effective look-up-table (LUT) method was developed for the lock-in amplifier algorithm, to decrease the complexity of the calculations and generate less heat than the traditional way. The performance of the design was tested by determining the linearity, gain, Q value, and frequency characteristic of the DLIA between 25 and 200 °C. The maximal nonlinear error in the linearity of the DLIA working at 200 °C was about 1.736% when the equivalent input was a sine wave signal with an amplitude of between 94.8 and 1896.0 nV and a frequency of 800 kHz. The tests showed that the DLIA proposed could work effectively in high-temperature environments up to 200 °C. PMID:27845710

Mutual information estimation for irregularly sampled time series

NASA Astrophysics Data System (ADS)

Rehfeld, K.; Marwan, N.; Heitzig, J.; Kurths, J.

2012-04-01

For the automated, objective and joint analysis of time series, similarity measures are crucial. Used in the analysis of climate records, they allow for a complimentary, unbiased view onto sparse datasets. The irregular sampling of many of these time series, however, makes it necessary to either perform signal reconstruction (e.g. interpolation) or to develop and use adapted measures. Standard linear interpolation comes with an inevitable loss of information and bias effects. We have recently developed a Gaussian kernel-based correlation algorithm with which the interpolation error can be substantially lowered, but this would not work should the functional relationship in a bivariate setting be non-linear. We therefore propose an algorithm to estimate lagged auto and cross mutual information from irregularly sampled time series. We have extended the standard and adaptive binning histogram estimators and use Gaussian distributed weights in the estimation of the (joint) probabilities. To test our method we have simulated linear and nonlinear auto-regressive processes with Gamma-distributed inter-sampling intervals. We have then performed a sensitivity analysis for the estimation of actual coupling length, the lag of coupling and the decorrelation time in the synthetic time series and contrast our results to the performance of a signal reconstruction scheme. Finally we applied our estimator to speleothem records. We compare the estimated memory (or decorrelation time) to that from a least-squares estimator based on fitting an auto-regressive process of order 1. The calculated (cross) mutual information results are compared for the different estimators (standard or adaptive binning) and contrasted with results from signal reconstruction. We find that the kernel-based estimator has a significantly lower root mean square error and less systematic sampling bias than the interpolation-based method. It is possible that these encouraging results could be further improved by using non-histogram mutual information estimators, like k-Nearest Neighbor or Kernel-Density estimators, but for short (<1000 points) and irregularly sampled datasets the proposed algorithm is already a great improvement.

On the Hilbert-Huang Transform Theoretical Foundation

NASA Technical Reports Server (NTRS)

Kizhner, Semion; Blank, Karin; Huang, Norden E.

2004-01-01

The Hilbert-Huang Transform [HHT] is a novel empirical method for spectrum analysis of non-linear and non-stationary signals. The HHT is a recent development and much remains to be done to establish the theoretical foundation of the HHT algorithms. This paper develops the theoretical foundation for the convergence of the HHT sifting algorithm and it proves that the finest spectrum scale will always be the first generated by the HHT Empirical Mode Decomposition (EMD) algorithm. The theoretical foundation for cutting an extrema data points set into two parts is also developed. This then allows parallel signal processing for the HHT computationally complex sifting algorithm and its optimization in hardware.

A Novel Approach to Noise-Filtering Based on a Gain-Scheduling Neural Network Architecture

NASA Technical Reports Server (NTRS)

Troudet, T.; Merrill, W.

1994-01-01

A gain-scheduling neural network architecture is proposed to enhance the noise-filtering efficiency of feedforward neural networks, in terms of both nominal performance and robustness. The synergistic benefits of the proposed architecture are demonstrated and discussed in the context of the noise-filtering of signals that are typically encountered in aerospace control systems. The synthesis of such a gain-scheduled neurofiltering provides the robustness of linear filtering, while preserving the nominal performance advantage of conventional nonlinear neurofiltering. Quantitative performance and robustness evaluations are provided for the signal processing of pitch rate responses to typical pilot command inputs for a modern fighter aircraft model.

Cubic spline interpolation with overlapped window and data reuse for on-line Hilbert Huang transform biomedical microprocessor.

PubMed

Chang, Nai-Fu; Chiang, Cheng-Yi; Chen, Tung-Chien; Chen, Liang-Gee

2011-01-01

On-chip implementation of Hilbert-Huang transform (HHT) has great impact to analyze the non-linear and non-stationary biomedical signals on wearable or implantable sensors for the real-time applications. Cubic spline interpolation (CSI) consumes the most computation in HHT, and is the key component for the HHT processor. In tradition, CSI in HHT is usually performed after the collection of a large window of signals, and the long latency violates the realtime requirement of the applications. In this work, we propose to keep processing the incoming signals on-line with small and overlapped data windows without sacrificing the interpolation accuracy. 58% multiplication and 73% division of CSI are saved after the data reuse between the data windows.

Analytical approximations to the Hotelling trace for digital x-ray detectors

NASA Astrophysics Data System (ADS)

Clarkson, Eric; Pineda, Angel R.; Barrett, Harrison H.

2001-06-01

The Hotelling trace is the signal-to-noise ratio for the ideal linear observer in a detection task. We provide an analytical approximation for this figure of merit when the signal is known exactly and the background is generated by a stationary random process, and the imaging system is an ideal digital x-ray detector. This approximation is based on assuming that the detector is infinite in extent. We test this approximation for finite-size detectors by comparing it to exact calculations using matrix inversion of the data covariance matrix. After verifying the validity of the approximation under a variety of circumstances, we use it to generate plots of the Hotelling trace as a function of pairs of parameters of the system, the signal and the background.

500 GHz Optical Sampler for Advancing Nonlinear Processing with Generalized Optical Pulses

DTIC Science & Technology

2015-10-19

that obtainable with electronics. Wide bandwidth  pulses have a variety of applications such as in microwave signal processing,  ultra ‐ wideband ...fiber‐based entangled photon source, the first  ultra ‐fast low‐loss single photon switch, and the first  telecom‐band linear optics C‐Not gate. We

Control logic to track the outputs of a command generator or randomly forced target

NASA Technical Reports Server (NTRS)

Trankle, T. L.; Bryson, A. E., Jr.

1977-01-01

A procedure is presented for synthesizing time-invariant control logic to cause the outputs of a linear plant to track the outputs of an unforced (or randomly forced) linear dynamic system. The control logic uses feed-forward of the reference system state variables and feedback of the plant state variables. The feed-forward gains are obtained from the solution of a linear algebraic matrix equation of the Liapunov type. The feedback gains are the usual regulator gains, determined to stabilize (or augment the stability of) the plant, possibly including integral control. The method is applied here to the design of control logic for a second-order servomechanism to follow a linearly increasing (ramp) signal, an unstable third-order system with two controls to track two separate ramp signals, and a sixth-order system with two controls to track a constant signal and an exponentially decreasing signal (aircraft landing-flare or glide-slope-capture with constant velocity).

Decomposition of Near-Infrared Spectroscopy Signals Using Oblique Subspace Projections: Applications in Brain Hemodynamic Monitoring.

PubMed

Caicedo, Alexander; Varon, Carolina; Hunyadi, Borbala; Papademetriou, Maria; Tachtsidis, Ilias; Van Huffel, Sabine

2016-01-01

Clinical data is comprised by a large number of synchronously collected biomedical signals that are measured at different locations. Deciphering the interrelationships of these signals can yield important information about their dependence providing some useful clinical diagnostic data. For instance, by computing the coupling between Near-Infrared Spectroscopy signals (NIRS) and systemic variables the status of the hemodynamic regulation mechanisms can be assessed. In this paper we introduce an algorithm for the decomposition of NIRS signals into additive components. The algorithm, SIgnal DEcomposition base on Obliques Subspace Projections (SIDE-ObSP), assumes that the measured NIRS signal is a linear combination of the systemic measurements, following the linear regression model y = Ax + ϵ . SIDE-ObSP decomposes the output such that, each component in the decomposition represents the sole linear influence of one corresponding regressor variable. This decomposition scheme aims at providing a better understanding of the relation between NIRS and systemic variables, and to provide a framework for the clinical interpretation of regression algorithms, thereby, facilitating their introduction into clinical practice. SIDE-ObSP combines oblique subspace projections (ObSP) with the structure of a mean average system in order to define adequate signal subspaces. To guarantee smoothness in the estimated regression parameters, as observed in normal physiological processes, we impose a Tikhonov regularization using a matrix differential operator. We evaluate the performance of SIDE-ObSP by using a synthetic dataset, and present two case studies in the field of cerebral hemodynamics monitoring using NIRS. In addition, we compare the performance of this method with other system identification techniques. In the first case study data from 20 neonates during the first 3 days of life was used, here SIDE-ObSP decoupled the influence of changes in arterial oxygen saturation from the NIRS measurements, facilitating the use of NIRS as a surrogate measure for cerebral blood flow (CBF). The second case study used data from a 3-years old infant under Extra Corporeal Membrane Oxygenation (ECMO), here SIDE-ObSP decomposed cerebral/peripheral tissue oxygenation, as a sum of the partial contributions from different systemic variables, facilitating the comparison between the effects of each systemic variable on the cerebral/peripheral hemodynamics.

Fiber optical assembly for fluorescence spectrometry

DOEpatents

Carpenter, II, Robert W.; Rubenstein, Richard; Piltch, Martin; Gray, Perry

2010-12-07

A system for analyzing a sample for the presence of an analyte in a sample. The system includes a sample holder for containing the sample; an excitation source, such as a laser, and at least one linear array radially disposed about the sample holder. Radiation from the excitation source is directed to the sample, and the radiation induces fluorescent light in the sample. Each linear array includes a plurality of fused silica optical fibers that receive the fluorescent light and transmits a fluorescent light signal from the first end to an optical end port of the linear array. An end port assembly having a photo-detector is optically coupled to the optical end port. The photo-detector detects the fluorescent light signal and converts the fluorescent light signal into an electrical signal.

2D non-separable linear canonical transform (2D-NS-LCT) based cryptography

NASA Astrophysics Data System (ADS)

Zhao, Liang; Muniraj, Inbarasan; Healy, John J.; Malallah, Ra'ed; Cui, Xiao-Guang; Ryle, James P.; Sheridan, John T.

2017-05-01

The 2D non-separable linear canonical transform (2D-NS-LCT) can describe a variety of paraxial optical systems. Digital algorithms to numerically evaluate the 2D-NS-LCTs are not only important in modeling the light field propagations but also of interest in various signal processing based applications, for instance optical encryption. Therefore, in this paper, for the first time, a 2D-NS-LCT based optical Double-random- Phase-Encryption (DRPE) system is proposed which offers encrypting information in multiple degrees of freedom. Compared with the traditional systems, i.e. (i) Fourier transform (FT); (ii) Fresnel transform (FST); (iii) Fractional Fourier transform (FRT); and (iv) Linear Canonical transform (LCT), based DRPE systems, the proposed system is more secure and robust as it encrypts the data with more degrees of freedom with an augmented key-space.

SPECIAL ISSUE ON OPTICAL PROCESSING OF INFORMATION: Optoelectronic processors with scanning CCD photodetectors

NASA Astrophysics Data System (ADS)

Esepkina, N. A.; Lavrov, A. P.; Anan'ev, M. N.; Blagodarnyi, V. S.; Ivanov, S. I.; Mansyrev, M. I.; Molodyakov, S. A.

1995-10-01

Two new types of optoelectronic radio-signal processors were investigated. Charge-coupled device (CCD) photodetectors are used in these processors under continuous scanning conditions, i.e. in a time delay and storage mode. One of these processors is based on a CCD photodetector array with a reference-signal amplitude transparency and the other is an adaptive acousto-optical signal processor with linear frequency modulation. The processor with the transparency performs multichannel discrete—analogue convolution of an input signal with a corresponding kernel of the transformation determined by the transparency. If a light source is an array of light-emitting diodes of special (stripe) geometry, the optical stages of the processor can be made from optical fibre components and the whole processor then becomes a rigid 'sandwich' (a compact hybrid optoelectronic microcircuit). A report is given also of a study of a prototype processor with optical fibre components for the reception of signals from a system with antenna aperture synthesis, which forms a radio image of the Earth.

A road map for multi-way calibration models.

PubMed

Escandar, Graciela M; Olivieri, Alejandro C

2017-08-07

A large number of experimental applications of multi-way calibration are known, and a variety of chemometric models are available for the processing of multi-way data. While the main focus has been directed towards three-way data, due to the availability of various instrumental matrix measurements, a growing number of reports are being produced on order signals of increasing complexity. The purpose of this review is to present a general scheme for selecting the appropriate data processing model, according to the properties exhibited by the multi-way data. In spite of the complexity of the multi-way instrumental measurements, simple criteria can be proposed for model selection, based on the presence and number of the so-called multi-linearity breaking modes (instrumental modes that break the low-rank multi-linearity of the multi-way arrays), and also on the existence of mutually dependent instrumental modes. Recent literature reports on multi-way calibration are reviewed, with emphasis on the models that were selected for data processing.

Active disturbance rejection controller for chemical reactor

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

Both, Roxana; Dulf, Eva H.; Muresan, Cristina I., E-mail: roxana.both@aut.utcluj.ro

2015-03-10

In the petrochemical industry, the synthesis of 2 ethyl-hexanol-oxo-alcohols (plasticizers alcohol) is of high importance, being achieved through hydrogenation of 2 ethyl-hexenal inside catalytic trickle bed three-phase reactors. For this type of processes the use of advanced control strategies is suitable due to their nonlinear behavior and extreme sensitivity to load changes and other disturbances. Due to the complexity of the mathematical model an approach was to use a simple linear model of the process in combination with an advanced control algorithm which takes into account the model uncertainties, the disturbances and command signal limitations like robust control. However themore » resulting controller is complex, involving cost effective hardware. This paper proposes a simple integer-order control scheme using a linear model of the process, based on active disturbance rejection method. By treating the model dynamics as a common disturbance and actively rejecting it, active disturbance rejection control (ADRC) can achieve the desired response. Simulation results are provided to demonstrate the effectiveness of the proposed method.« less

Analysis of the PLL phase error in presence of simulated ionospheric scintillation events

NASA Astrophysics Data System (ADS)

Forte, B.

2012-01-01

The functioning of standard phase locked loops (PLL), including those used to track radio signals from Global Navigation Satellite Systems (GNSS), is based on a linear approximation which holds in presence of small phase errors. Such an approximation represents a reasonable assumption in most of the propagation channels. However, in presence of a fading channel the phase error may become large, making the linear approximation no longer valid. The PLL is then expected to operate in a non-linear regime. As PLLs are generally designed and expected to operate in their linear regime, whenever the non-linear regime comes into play, they will experience a serious limitation in their capability to track the corresponding signals. The phase error and the performance of a typical PLL embedded into a commercial multiconstellation GNSS receiver were analyzed in presence of simulated ionospheric scintillation. Large phase errors occurred during scintillation-induced signal fluctuations although cycle slips only occurred during the signal re-acquisition after a loss of lock. Losses of lock occurred whenever the signal faded below the minimumC/N0threshold allowed for tracking. The simulations were performed for different signals (GPS L1C/A, GPS L2C, GPS L5 and Galileo L1). L5 and L2C proved to be weaker than L1. It appeared evident that the conditions driving the PLL phase error in the specific case of GPS receivers in presence of scintillation-induced signal perturbations need to be evaluated in terms of the combination of the minimumC/N0 tracking threshold, lock detector thresholds, possible cycle slips in the tracking PLL and accuracy of the observables (i.e. the error propagation onto the observables stage).

Development of a GCR Event-based Risk Model

NASA Technical Reports Server (NTRS)

Cucinotta, Francis A.; Ponomarev, Artem L.; Plante, Ianik; Carra, Claudio; Kim, Myung-Hee

2009-01-01

A goal at NASA is to develop event-based systems biology models of space radiation risks that will replace the current dose-based empirical models. Complex and varied biochemical signaling processes transmit the initial DNA and oxidative damage from space radiation into cellular and tissue responses. Mis-repaired damage or aberrant signals can lead to genomic instability, persistent oxidative stress or inflammation, which are causative of cancer and CNS risks. Protective signaling through adaptive responses or cell repopulation is also possible. We are developing a computational simulation approach to galactic cosmic ray (GCR) effects that is based on biological events rather than average quantities such as dose, fluence, or dose equivalent. The goal of the GCR Event-based Risk Model (GERMcode) is to provide a simulation tool to describe and integrate physical and biological events into stochastic models of space radiation risks. We used the quantum multiple scattering model of heavy ion fragmentation (QMSFRG) and well known energy loss processes to develop a stochastic Monte-Carlo based model of GCR transport in spacecraft shielding and tissue. We validated the accuracy of the model by comparing to physical data from the NASA Space Radiation Laboratory (NSRL). Our simulation approach allows us to time-tag each GCR proton or heavy ion interaction in tissue including correlated secondary ions often of high multiplicity. Conventional space radiation risk assessment employs average quantities, and assumes linearity and additivity of responses over the complete range of GCR charge and energies. To investigate possible deviations from these assumptions, we studied several biological response pathway models of varying induction and relaxation times including the ATM, TGF -Smad, and WNT signaling pathways. We then considered small volumes of interacting cells and the time-dependent biophysical events that the GCR would produce within these tissue volumes to estimate how GCR event rates mapped to biological signaling induction and relaxation times. We considered several hypotheses related to signaling and cancer risk, and then performed simulations for conditions where aberrant or adaptive signaling would occur on long-duration space mission. Our results do not support the conventional assumptions of dose, linearity and additivity. A discussion on how event-based systems biology models, which focus on biological signaling as the mechanism to propagate damage or adaptation, can be further developed for cancer and CNS space radiation risk projections is given.

LSST camera readout chip ASPIC: test tools

NASA Astrophysics Data System (ADS)

Antilogus, P.; Bailly, Ph; Jeglot, J.; Juramy, C.; Lebbolo, H.; Martin, D.; Moniez, M.; Tocut, V.; Wicek, F.

2012-02-01

The LSST camera will have more than 3000 video-processing channels. The readout of this large focal plane requires a very compact readout chain. The correlated ''Double Sampling technique'', which is generally used for the signal readout of CCDs, is also adopted for this application and implemented with the so called ''Dual Slope integrator'' method. We have designed and implemented an ASIC for LSST: the Analog Signal Processing asIC (ASPIC). The goal is to amplify the signal close to the output, in order to maximize signal to noise ratio, and to send differential outputs to the digitization. Others requirements are that each chip should process the output of half a CCD, that is 8 channels and should operate at 173 K. A specific Back End board has been designed especially for lab test purposes. It manages the clock signals, digitizes the analog differentials outputs of ASPIC and stores data into a memory. It contains 8 ADCs (18 bits), 512 kwords memory and an USB interface. An FPGA manages all signals from/to all components on board and generates the timing sequence for ASPIC. Its firmware is written in Verilog and VHDL languages. Internals registers permit to define various tests parameters of the ASPIC. A Labview GUI allows to load or update these registers and to check a proper operation. Several series of tests, including linearity, noise and crosstalk, have been performed over the past year to characterize the ASPIC at room and cold temperature. At present, the ASPIC, Back-End board and CCD detectors are being integrated to perform a characterization of the whole readout chain.

The impact of global signal regression on resting state correlations: Are anti-correlated networks introduced?

PubMed Central

Murphy, Kevin; Birn, Rasmus M.; Handwerker, Daniel A.; Jones, Tyler B.; Bandettini, Peter A.

2009-01-01

Low-frequency fluctuations in fMRI signal have been used to map several consistent resting state networks in the brain. Using the posterior cingulate cortex as a seed region, functional connectivity analyses have found not only positive correlations in the default mode network but negative correlations in another resting state network related to attentional processes. The interpretation is that the human brain is intrinsically organized into dynamic, anti-correlated functional networks. Global variations of the BOLD signal are often considered nuisance effects and are commonly removed using a general linear model (GLM) technique. This global signal regression method has been shown to introduce negative activation measures in standard fMRI analyses. The topic of this paper is whether such a correction technique could be the cause of anti-correlated resting state networks in functional connectivity analyses. Here we show that, after global signal regression, correlation values to a seed voxel must sum to a negative value. Simulations also show that small phase differences between regions can lead to spurious negative correlation values. A combination breath holding and visual task demonstrates that the relative phase of global and local signals can affect connectivity measures and that, experimentally, global signal regression leads to bell-shaped correlation value distributions, centred on zero. Finally, analyses of negatively correlated networks in resting state data show that global signal regression is most likely the cause of anti-correlations. These results call into question the interpretation of negatively correlated regions in the brain when using global signal regression as an initial processing step. PMID:18976716

The impact of global signal regression on resting state correlations: are anti-correlated networks introduced?

PubMed

Murphy, Kevin; Birn, Rasmus M; Handwerker, Daniel A; Jones, Tyler B; Bandettini, Peter A

2009-02-01

Low-frequency fluctuations in fMRI signal have been used to map several consistent resting state networks in the brain. Using the posterior cingulate cortex as a seed region, functional connectivity analyses have found not only positive correlations in the default mode network but negative correlations in another resting state network related to attentional processes. The interpretation is that the human brain is intrinsically organized into dynamic, anti-correlated functional networks. Global variations of the BOLD signal are often considered nuisance effects and are commonly removed using a general linear model (GLM) technique. This global signal regression method has been shown to introduce negative activation measures in standard fMRI analyses. The topic of this paper is whether such a correction technique could be the cause of anti-correlated resting state networks in functional connectivity analyses. Here we show that, after global signal regression, correlation values to a seed voxel must sum to a negative value. Simulations also show that small phase differences between regions can lead to spurious negative correlation values. A combination breath holding and visual task demonstrates that the relative phase of global and local signals can affect connectivity measures and that, experimentally, global signal regression leads to bell-shaped correlation value distributions, centred on zero. Finally, analyses of negatively correlated networks in resting state data show that global signal regression is most likely the cause of anti-correlations. These results call into question the interpretation of negatively correlated regions in the brain when using global signal regression as an initial processing step.

Dual-polarization phase shift processing with the Python ARM Radar Toolkit

NASA Astrophysics Data System (ADS)

Collis, S. M.; Lang, T. J.; Mühlbauer, K.; Helmus, J.; North, K.

2016-12-01

Weather radars that measure backscatter returns at two orthogonal polarizations can give unique insight into storm macro and microphysics. Phase shift between the two polarizations caused by anisotropy in the liquid water path can be used as a constraint in rainfall rate and drop size distribution retrievals, and has the added benefit of being robust to attenuation and radar calibration. The measurement is complicated, however, by the impact of phase shift on backscatter in the presence of large drops and when the pulse volume is not filled uniformly by scatterers (known as partial beam filling). This has led to a signal processing challenge of separating the underlying desired signal from the transient signal, a challenge that has attracted many diverse solutions. To this end, the Python-ARM Radar Toolkit (Py-ART) [1] becomes increasingly important. By providing an open architecture for implementation of retrieval techniques, Py-ART has attracted three very different approaches to the phase processing problem: a fully variational technique, a finite impulse response filter technique [2], and a technique based on a linear programming [3]. These either exist within the toolkit or in another open source package that uses the Py-ART architecture. This presentation will provide an overview of differential phase and specific differential phase observed at C- and S-band frequencies, the signal processing behind the three aforementioned techniques, and some examples of their application. The goal of this presentation is to highlight the importance of open source architectures such as Py-ART for geophysical retrievals. [1] Helmus, J.J. & Collis, S.M., (2016). The Python ARM Radar Toolkit (Py-ART), a Library for Working with Weather Radar Data in the Python Programming Language. JORS. 4(1), p.e25. DOI: http://doi.org/10.5334/jors.119[2] Timothy J. Lang, David A. Ahijevych, Stephen W. Nesbitt, Richard E. Carbone, Steven A. Rutledge, and Robert Cifelli, 2007: Radar-Observed Characteristics of Precipitating Systems during NAME 2004. J. Climate, 20, 1713-1733. doi: http://dx.doi.org/10.1175/JCLI4082.1[3] Scott E. Giangrande, Robert McGraw, and Lei Lei, 2013: An Application of Linear Programming to Polarimetric Radar Differential Phase Processing. JTECH. 30, 1716-1729, doi: 10.1175/JTECH-D-12-00147.1.

Front-end Design and Characterization for the ν-Angra Nuclear Reactor Monitoring Detector

NASA Astrophysics Data System (ADS)

Dornelas, T. I.; Araújo, F. T. H.; Cerqueira, A. S.; Costa, J. A.; Nóbrega, R. A.

2016-07-01

The Neutrinos Angra (ν-Angra) Experiment aims to construct an antineutrinos detection device capable of monitoring the Angra dos Reis nuclear reactor activity. Nuclear reactors are intense sources of antineutrinos, and the thermal power released in the fission process is directly related to the flow rate of these particles. The antineutrinos energy spectrum also provides valuable information on the nuclear source isotopic composition. The proposed detector will be equipped with photomultipliers tubes (PMT) which will be readout by a custom Amplifier-Shaper-Discriminator circuit designed to condition its output signals to the acquisition modules to be digitized and processed by an FPGA. The readout circuit should be sensitive to single photoelectron signals, process fast signals, with a full-width-half-amplitude of about 5 ns, have a narrow enough output pulse width to detect both particles coming out from the inverse beta decay (bar nue+p → n + e+), and its output amplitude should be linear to the number of photoelectrons generated inside the PMT, used for energy estimation. In this work, some of the main PMT characteristics are measured and a new readout circuit is proposed, described and characterized.

Quantitative evaluation of photoplethysmographic artifact reduction for pulse oximetry

NASA Astrophysics Data System (ADS)

Hayes, Matthew J.; Smith, Peter R.

1999-01-01

Motion artefact corruption of pulse oximeter output, causing both measurement inaccuracies and false alarm conditions, is a primary restriction in the current clinical practice and future applications of this useful technique. Artefact reduction in photoplethysmography (PPG), and therefore by application in pulse oximetry, is demonstrated using a novel non-linear methodology recently proposed by the authors. The significance of these processed PPG signals for pulse oximetry measurement is discussed, with particular attention to the normalization inherent in the artefact reduction process. Quantitative experimental investigation of the performance of PPG artefact reduction is then utilized to evaluate this technology for application to pulse oximetry. While the successfully demonstrated reduction of severe artefacts may widen the applicability of all PPG technologies and decrease the occurrence of pulse oximeter false alarms, the observed reduction of slight artefacts suggests that many such effects may go unnoticed in clinical practice. The signal processing and output averaging used in most commercial oximeters can incorporate these artefact errors into the output, while masking the true PPG signal corruption. It is therefore suggested that PPG artefact reduction should be incorporated into conventional pulse oximetry measurement, even in the absence of end-user artefact problems.

Signal dependence of inter-pixel capacitance in hybridized HgCdTe H2RG arrays for use in James Webb space telescope's NIRcam

NASA Astrophysics Data System (ADS)

Donlon, Kevan; Ninkov, Zoran; Baum, Stefi

2016-08-01

Interpixel capacitance (IPC) is a deterministic electronic coupling by which signal generated in one pixel is measured in neighboring pixels. Examination of dark frames from test NIRcam arrays corroborates earlier results and simulations illustrating a signal dependent coupling. When the signal on an individual pixel is larger, the fractional coupling to nearest neighbors is lesser than when the signal is lower. Frames from test arrays indicate a drop in average coupling from approximately 1.0% at low signals down to approximately 0.65% at high signals depending on the particular array in question. The photometric ramifications for this non-uniformity are not fully understood. This non-uniformity intro-duces a non-linearity in the current mathematical model for IPC coupling. IPC coupling has been mathematically formalized as convolution by a blur kernel. Signal dependence requires that the blur kernel be locally defined as a function of signal intensity. Through application of a signal dependent coupling kernel, the IPC coupling can be modeled computationally. This method allows for simultaneous knowledge of the intrinsic parameters of the image scene, the result of applying a constant IPC, and the result of a signal dependent IPC. In the age of sub-pixel precision in astronomy these effects must be properly understood and accounted for in order for the data to accurately represent the object of observation. Implementation of this method is done through python scripted processing of images. The introduction of IPC into simulated frames is accomplished through convolution of the image with a blur kernel whose parameters are themselves locally defined functions of the image. These techniques can be used to enhance the data processing pipeline for NIRcam.

Relationship Among Signal Fidelity, Hearing Loss, and Working Memory for Digital Noise Suppression.

PubMed

Arehart, Kathryn; Souza, Pamela; Kates, James; Lunner, Thomas; Pedersen, Michael Syskind

2015-01-01

This study considered speech modified by additive babble combined with noise-suppression processing. The purpose was to determine the relative importance of the signal modifications, individual peripheral hearing loss, and individual cognitive capacity on speech intelligibility and speech quality. The participant group consisted of 31 individuals with moderate high-frequency hearing loss ranging in age from 51 to 89 years (mean = 69.6 years). Speech intelligibility and speech quality were measured using low-context sentences presented in babble at several signal-to-noise ratios. Speech stimuli were processed with a binary mask noise-suppression strategy with systematic manipulations of two parameters (error rate and attenuation values). The cumulative effects of signal modification produced by babble and signal processing were quantified using an envelope-distortion metric. Working memory capacity was assessed with a reading span test. Analysis of variance was used to determine the effects of signal processing parameters on perceptual scores. Hierarchical linear modeling was used to determine the role of degree of hearing loss and working memory capacity in individual listener response to the processed noisy speech. The model also considered improvements in envelope fidelity caused by the binary mask and the degradations to envelope caused by error and noise. The participants showed significant benefits in terms of intelligibility scores and quality ratings for noisy speech processed by the ideal binary mask noise-suppression strategy. This benefit was observed across a range of signal-to-noise ratios and persisted when up to a 30% error rate was introduced into the processing. Average intelligibility scores and average quality ratings were well predicted by an objective metric of envelope fidelity. Degree of hearing loss and working memory capacity were significant factors in explaining individual listener's intelligibility scores for binary mask processing applied to speech in babble. Degree of hearing loss and working memory capacity did not predict listeners' quality ratings. The results indicate that envelope fidelity is a primary factor in determining the combined effects of noise and binary mask processing for intelligibility and quality of speech presented in babble noise. Degree of hearing loss and working memory capacity are significant factors in explaining variability in listeners' speech intelligibility scores but not in quality ratings.

Linear and Non-linear Information Flows In Rainfall Field

NASA Astrophysics Data System (ADS)

Molini, A.; La Barbera, P.; Lanza, L. G.

The rainfall process is the result of a complex framework of non-linear dynamical in- teractions between the different components of the atmosphere. It preserves the com- plexity and the intermittent features of the generating system in space and time as well as the strong dependence of these properties on the scale of observations. The understanding and quantification of how the non-linearity of the generating process comes to influence the single rain events constitute relevant research issues in the field of hydro-meteorology, especially in those applications where a timely and effective forecasting of heavy rain events is able to reduce the risk of failure. This work focuses on the characterization of the non-linear properties of the observed rain process and on the influence of these features on hydrological models. Among the goals of such a survey is the research of regular structures of the rainfall phenomenon and the study of the information flows within the rain field. The research focuses on three basic evo- lution directions for the system: in time, in space and between the different scales. In fact, the information flows that force the system to evolve represent in general a connection between the different locations in space, the different instants in time and, unless assuming the hypothesis of scale invariance is verified "a priori", the different characteristic scales. A first phase of the analysis is carried out by means of classic statistical methods, then a survey of the information flows within the field is devel- oped by means of techniques borrowed from the Information Theory, and finally an analysis of the rain signal in the time and frequency domains is performed, with par- ticular reference to its intermittent structure. The methods adopted in this last part of the work are both the classic techniques of statistical inference and a few procedures for the detection of non-linear and non-stationary features within the process starting from measured data.

Studies with spike initiators - Linearization by noise allows continuous signal modulation in neural networks

NASA Technical Reports Server (NTRS)

Yu, Xiaolong; Lewis, Edwin R.

1989-01-01

It is shown that noise can be an important element in the translation of neuronal generator potentials (summed inputs) to neuronal spike trains (outputs), creating or expanding a range of amplitudes over which the spike rate is proportional to the generator potential amplitude. Noise converts the basically nonlinear operation of a spike initiator into a nearly linear modulation process. This linearization effect of noise is examined in a simple intuitive model of a static threshold and in a more realistic computer simulation of spike initiator based on the Hodgkin-Huxley (HH) model. The results are qualitatively similar; in each case larger noise amplitude results in a larger range of nearly linear modulation. The computer simulation of the HH model with noise shows linear and nonlinear features that were earlier observed in spike data obtained from the VIIIth nerve of the bullfrog. This suggests that these features can be explained in terms of spike initiator properties, and it also suggests that the HH model may be useful for representing basic spike initiator properties in vertebrates.

Detecting determinism with improved sensitivity in time series: rank-based nonlinear predictability score.

PubMed

Naro, Daniel; Rummel, Christian; Schindler, Kaspar; Andrzejak, Ralph G

2014-09-01

The rank-based nonlinear predictability score was recently introduced as a test for determinism in point processes. We here adapt this measure to time series sampled from time-continuous flows. We use noisy Lorenz signals to compare this approach against a classical amplitude-based nonlinear prediction error. Both measures show an almost identical robustness against Gaussian white noise. In contrast, when the amplitude distribution of the noise has a narrower central peak and heavier tails than the normal distribution, the rank-based nonlinear predictability score outperforms the amplitude-based nonlinear prediction error. For this type of noise, the nonlinear predictability score has a higher sensitivity for deterministic structure in noisy signals. It also yields a higher statistical power in a surrogate test of the null hypothesis of linear stochastic correlated signals. We show the high relevance of this improved performance in an application to electroencephalographic (EEG) recordings from epilepsy patients. Here the nonlinear predictability score again appears of higher sensitivity to nonrandomness. Importantly, it yields an improved contrast between signals recorded from brain areas where the first ictal EEG signal changes were detected (focal EEG signals) versus signals recorded from brain areas that were not involved at seizure onset (nonfocal EEG signals).

Detecting determinism with improved sensitivity in time series: Rank-based nonlinear predictability score

NASA Astrophysics Data System (ADS)

Naro, Daniel; Rummel, Christian; Schindler, Kaspar; Andrzejak, Ralph G.

2014-09-01

The rank-based nonlinear predictability score was recently introduced as a test for determinism in point processes. We here adapt this measure to time series sampled from time-continuous flows. We use noisy Lorenz signals to compare this approach against a classical amplitude-based nonlinear prediction error. Both measures show an almost identical robustness against Gaussian white noise. In contrast, when the amplitude distribution of the noise has a narrower central peak and heavier tails than the normal distribution, the rank-based nonlinear predictability score outperforms the amplitude-based nonlinear prediction error. For this type of noise, the nonlinear predictability score has a higher sensitivity for deterministic structure in noisy signals. It also yields a higher statistical power in a surrogate test of the null hypothesis of linear stochastic correlated signals. We show the high relevance of this improved performance in an application to electroencephalographic (EEG) recordings from epilepsy patients. Here the nonlinear predictability score again appears of higher sensitivity to nonrandomness. Importantly, it yields an improved contrast between signals recorded from brain areas where the first ictal EEG signal changes were detected (focal EEG signals) versus signals recorded from brain areas that were not involved at seizure onset (nonfocal EEG signals).

Large angle solid state position sensitive x-ray detector system

DOEpatents

Kurtz, David S.; Ruud, Clay O.

1998-01-01

A method and apparatus for x-ray measurement of certain properties of a solid material. In distinction to known methods and apparatus, this invention employs a specific fiber-optic bundle configuration, termed a reorganizer, itself known for other uses, for coherently transmitting visible light originating from the scintillation of diffracted x-radiation from the solid material gathered along a substantially one dimensional linear arc, to a two-dimensional photo-sensor array. The two-dimensional photodetector array, with its many closely packed light sensitive pixels, is employed to process the information contained in the diffracted radiation and present the information in the form of a conventional x-ray diffraction spectrum. By this arrangement, the angular range of the combined detector faces may be increased without loss of angular resolution. Further, the prohibitively expensive coupling together of a large number of individual linear diode photodetectors, which would be required to process signals generated by the diffracted radiation, is avoided.

Fast digital zooming system using directionally adaptive image interpolation and restoration.

PubMed

Kang, Wonseok; Jeon, Jaehwan; Yu, Soohwan; Paik, Joonki

2014-01-01

This paper presents a fast digital zooming system for mobile consumer cameras using directionally adaptive image interpolation and restoration methods. The proposed interpolation algorithm performs edge refinement along the initially estimated edge orientation using directionally steerable filters. Either the directionally weighted linear or adaptive cubic-spline interpolation filter is then selectively used according to the refined edge orientation for removing jagged artifacts in the slanted edge region. A novel image restoration algorithm is also presented for removing blurring artifacts caused by the linear or cubic-spline interpolation using the directionally adaptive truncated constrained least squares (TCLS) filter. Both proposed steerable filter-based interpolation and the TCLS-based restoration filters have a finite impulse response (FIR) structure for real time processing in an image signal processing (ISP) chain. Experimental results show that the proposed digital zooming system provides high-quality magnified images with FIR filter-based fast computational structure.

Development of flank wear model of cutting tool by using adaptive feedback linear control system on machining AISI D2 steel and AISI 4340 steel

NASA Astrophysics Data System (ADS)

Orra, Kashfull; Choudhury, Sounak K.

2016-12-01

The purpose of this paper is to build an adaptive feedback linear control system to check the variation of cutting force signal to improve the tool life. The paper discusses the use of transfer function approach in improving the mathematical modelling and adaptively controlling the process dynamics of the turning operation. The experimental results shows to be in agreement with the simulation model and error obtained is less than 3%. The state space approach model used in this paper successfully check the adequacy of the control system through controllability and observability test matrix and can be transferred from one state to another by appropriate input control in a finite time. The proposed system can be implemented to other machining process under varying range of cutting conditions to improve the efficiency and observability of the system.

Real time microcontroller implementation of an adaptive myoelectric filter.

PubMed

Bagwell, P J; Chappell, P H

1995-03-01

This paper describes a real time digital adaptive filter for processing myoelectric signals. The filter time constant is automatically selected by the adaptation algorithm, giving a significant improvement over linear filters for estimating the muscle force and controlling a prosthetic device. Interference from mains sources often produces problems for myoelectric processing, and so 50 Hz and all harmonic frequencies are reduced by an averaging filter and differential process. This makes practical electrode placement and contact less critical and time consuming. An economic real time implementation is essential for a prosthetic controller, and this is achieved using an Intel 80C196KC microcontroller.

Pair Production of the Doubly Charged Leptons Associated with a Gauge Boson γ or Z in e+e- and γγ Collisions at Future Linear Colliders

NASA Astrophysics Data System (ADS)

Zeng, Qing-Guo; Ji, Li; Yang, Shuo

2015-03-01

In this paper, we investigate the production of a pair of doubly charged leptons associated with a gauge boson V(γ or Z) at future linear colliders via e+e- and γγ collisions. The numerical results show that the possible signals of the doubly charged leptons may be detected via the processes e+e- → VX++X-- and γγ → VX++X-- at future ILC or CLIC experiments. Supported in part by the National Natural Science Foundation of China under Grants Nos. 11275088, 11205023, 11375248 and the Program for Liaoning Excellent Talents in University under Grant No. LJQ2014135

An optimal control approach to the design of moving flight simulators

NASA Technical Reports Server (NTRS)

Sivan, R.; Ish-Shalom, J.; Huang, J.-K.

1982-01-01

An abstract flight simulator design problem is formulated in the form of an optimal control problem, which is solved for the linear-quadratic-Gaussian special case using a mathematical model of the vestibular organs. The optimization criterion used is the mean-square difference between the physiological outputs of the vestibular organs of the pilot in the aircraft and the pilot in the simulator. The dynamical equations are linearized, and the output signal is modeled as a random process with rational power spectral density. The method described yields the optimal structure of the simulator's motion generator, or 'washout filter'. A two-degree-of-freedom flight simulator design, including single output simulations, is presented.

Demonstration of Detection and Ranging Using Solvable Chaos

NASA Technical Reports Server (NTRS)

Corron, Ned J.; Stahl, Mark T.; Blakely, Jonathan N.

2013-01-01

Acoustic experiments demonstrate a novel approach to ranging and detection that exploits the properties of a solvable chaotic oscillator. This nonlinear oscillator includes an ordinary differential equation and a discrete switching condition. The chaotic waveform generated by this hybrid system is used as the transmitted waveform. The oscillator admits an exact analytic solution that can be written as the linear convolution of binary symbols and a single basis function. This linear representation enables coherent reception using a simple analog matched filter and without need for digital sampling or signal processing. An audio frequency implementation of the transmitter and receiver is described. Successful acoustic ranging measurements are presented to demonstrate the viability of the approach.

Linearly polarized vector modes: enabling MIMO-free mode-division multiplexing.

PubMed

Wang, Lixian; Nejad, Reza Mirzaei; Corsi, Alessandro; Lin, Jiachuan; Messaddeq, Younès; Rusch, Leslie; LaRochelle, Sophie

2017-05-15

We experimentally investigate mode-division multiplexing in an elliptical ring core fiber (ERCF) that supports linearly polarized vector modes (LPV). Characterization show that the ERCF exhibits good polarization maintaining properties over eight LPV modes with effective index difference larger than 1 × 10 -4 . The ERCF further displays stable mode power and polarization extinction ratio when subjected to external perturbations. Crosstalk between the LPV modes, after propagating through 0.9 km ERCF, is below -14 dB. By using six LPV modes as independent data channels, we achieved the transmission of 32 Gbaud QPSK over 0.9 km ERCF without any multiple-input-multiple-output (MIMO) or polarization-division multiplexing (PDM) signal processing.

Stability and time-domain analysis of the dispersive tristability in microresonators under modal coupling

NASA Astrophysics Data System (ADS)

Dumeige, Yannick; Féron, Patrice

2011-10-01

Coupled nonlinear resonators have potential applications for the integration of multistable photonic devices. The dynamic properties of two coupled-mode nonlinear microcavities made of Kerr material are studied by linear stability analysis. Using a suitable combination of the modal coupling rate and the frequency detuning, it is possible to obtain configurations where a hysteresis loop is included inside other bistable cycles. We show that a single resonator with two modes both linearly and nonlinearly coupled via the cross-Kerr effect can have a multistable behavior. This could be implemented in semiconductor nonlinear whispering-gallery-mode microresonators under modal coupling for all optical signal processing or ternary optical logic applications.

Non-Linearity in Wide Dynamic Range CMOS Image Sensors Utilizing a Partial Charge Transfer Technique.

PubMed

Shafie, Suhaidi; Kawahito, Shoji; Halin, Izhal Abdul; Hasan, Wan Zuha Wan

2009-01-01

The partial charge transfer technique can expand the dynamic range of a CMOS image sensor by synthesizing two types of signal, namely the long and short accumulation time signals. However the short accumulation time signal obtained from partial transfer operation suffers of non-linearity with respect to the incident light. In this paper, an analysis of the non-linearity in partial charge transfer technique has been carried, and the relationship between dynamic range and the non-linearity is studied. The results show that the non-linearity is caused by two factors, namely the current diffusion, which has an exponential relation with the potential barrier, and the initial condition of photodiodes in which it shows that the error in the high illumination region increases as the ratio of the long to the short accumulation time raises. Moreover, the increment of the saturation level of photodiodes also increases the error in the high illumination region.

Automatic identification of epileptic seizures from EEG signals using linear programming boosting.

PubMed

Hassan, Ahnaf Rashik; Subasi, Abdulhamit

2016-11-01

Computerized epileptic seizure detection is essential for expediting epilepsy diagnosis and research and for assisting medical professionals. Moreover, the implementation of an epilepsy monitoring device that has low power and is portable requires a reliable and successful seizure detection scheme. In this work, the problem of automated epilepsy seizure detection using singe-channel EEG signals has been addressed. At first, segments of EEG signals are decomposed using a newly proposed signal processing scheme, namely complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN). Six spectral moments are extracted from the CEEMDAN mode functions and train and test matrices are formed afterward. These matrices are fed into the classifier to identify epileptic seizures from EEG signal segments. In this work, we implement an ensemble learning based machine learning algorithm, namely linear programming boosting (LPBoost) to perform classification. The efficacy of spectral features in the CEEMDAN domain is validated by graphical and statistical analyses. The performance of CEEMDAN is compared to those of its predecessors to further inspect its suitability. The effectiveness and the appropriateness of LPBoost are demonstrated as opposed to the commonly used classification models. Resubstitution and 10 fold cross-validation error analyses confirm the superior algorithm performance of the proposed scheme. The algorithmic performance of our epilepsy seizure identification scheme is also evaluated against state-of-the-art works in the literature. Experimental outcomes manifest that the proposed seizure detection scheme performs better than the existing works in terms of accuracy, sensitivity, specificity, and Cohen's Kappa coefficient. It can be anticipated that owing to its use of only one channel of EEG signal, the proposed method will be suitable for device implementation, eliminate the onus of clinicians for analyzing a large bulk of data manually, and expedite epilepsy diagnosis. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Nonlinear ultrasonic wave modulation for online fatigue crack detection

NASA Astrophysics Data System (ADS)

Sohn, Hoon; Lim, Hyung Jin; DeSimio, Martin P.; Brown, Kevin; Derriso, Mark

2014-02-01

This study presents a fatigue crack detection technique using nonlinear ultrasonic wave modulation. Ultrasonic waves at two distinctive driving frequencies are generated and corresponding ultrasonic responses are measured using permanently installed lead zirconate titanate (PZT) transducers with a potential for continuous monitoring. Here, the input signal at the lower driving frequency is often referred to as a 'pumping' signal, and the higher frequency input is referred to as a 'probing' signal. The presence of a system nonlinearity, such as a crack formation, can provide a mechanism for nonlinear wave modulation, and create spectral sidebands around the frequency of the probing signal. A signal processing technique combining linear response subtraction (LRS) and synchronous demodulation (SD) is developed specifically to extract the crack-induced spectral sidebands. The proposed crack detection method is successfully applied to identify actual fatigue cracks grown in metallic plate and complex fitting-lug specimens. Finally, the effect of pumping and probing frequencies on the amplitude of the first spectral sideband is investigated using the first sideband spectrogram (FSS) obtained by sweeping both pumping and probing signals over specified frequency ranges.

Signal-to-noise ratio and spectral linewidth improvements between 1.5 and 7 Tesla in proton echo-planar spectroscopic imaging.

PubMed

Otazo, Ricardo; Mueller, Bryon; Ugurbil, Kamil; Wald, Lawrence; Posse, Stefan

2006-12-01

This study characterizes gains in sensitivity and spectral resolution of proton echo-planar spectroscopic imaging (PEPSI) with increasing magnetic field strength (B(0)). Signal-to-noise ratio (SNR) per unit volume and unit time, and intrinsic linewidth (LW) of N-acetyl-aspartate (NAA), creatine (Cr), and choline (Cho) were measured with PEPSI at 1.5, 3, 4, and 7 Tesla on scanners that shared a similar software and hardware platform, using circularly polarized (CP) and eight-channel phased-array (PA) head coils. Data were corrected for relaxation effects and processed with a time-domain matched filter (MF) adapted to each B(0). The SNR and LW measured with PEPSI were very similar to those measured with conventional point-resolved spectroscopy (PRESS) SI. Measurements with the CP coil demonstrated a nearly linear SNR gain with respect to B(0) in central brain regions. For the PA coil, the SNR-B(0) relationship was less than linear, but there was a substantial SNR increase in comparison to the CP coil. The LW in units of ppm decreased with B(0), resulting in improved spectral resolution. These studies using PEPSI demonstrated linear gains in SNR with respect to B(0), consistent with theoretical expectations, and a decrease in ppm LW with increasing B(0).

Deep Independence Network Analysis of Structural Brain Imaging: Application to Schizophrenia

PubMed Central

Castro, Eduardo; Hjelm, R. Devon; Plis, Sergey M.; Dinh, Laurent; Turner, Jessica A.; Calhoun, Vince D.

2016-01-01

Linear independent component analysis (ICA) is a standard signal processing technique that has been extensively used on neuroimaging data to detect brain networks with coherent brain activity (functional MRI) or covarying structural patterns (structural MRI). However, its formulation assumes that the measured brain signals are generated by a linear mixture of the underlying brain networks and this assumption limits its ability to detect the inherent nonlinear nature of brain interactions. In this paper, we introduce nonlinear independent component estimation (NICE) to structural MRI data to detect abnormal patterns of gray matter concentration in schizophrenia patients. For this biomedical application, we further addressed the issue of model regularization of nonlinear ICA by performing dimensionality reduction prior to NICE, together with an appropriate control of the complexity of the model and the usage of a proper approximation of the probability distribution functions of the estimated components. We show that our results are consistent with previous findings in the literature, but we also demonstrate that the incorporation of nonlinear associations in the data enables the detection of spatial patterns that are not identified by linear ICA. Specifically, we show networks including basal ganglia, cerebellum and thalamus that show significant differences in patients versus controls, some of which show distinct nonlinear patterns. PMID:26891483

An SVM-Based Solution for Fault Detection in Wind Turbines

PubMed Central

Santos, Pedro; Villa, Luisa F.; Reñones, Aníbal; Bustillo, Andres; Maudes, Jesús

2015-01-01

Research into fault diagnosis in machines with a wide range of variable loads and speeds, such as wind turbines, is of great industrial interest. Analysis of the power signals emitted by wind turbines for the diagnosis of mechanical faults in their mechanical transmission chain is insufficient. A successful diagnosis requires the inclusion of accelerometers to evaluate vibrations. This work presents a multi-sensory system for fault diagnosis in wind turbines, combined with a data-mining solution for the classification of the operational state of the turbine. The selected sensors are accelerometers, in which vibration signals are processed using angular resampling techniques and electrical, torque and speed measurements. Support vector machines (SVMs) are selected for the classification task, including two traditional and two promising new kernels. This multi-sensory system has been validated on a test-bed that simulates the real conditions of wind turbines with two fault typologies: misalignment and imbalance. Comparison of SVM performance with the results of artificial neural networks (ANNs) shows that linear kernel SVM outperforms other kernels and ANNs in terms of accuracy, training and tuning times. The suitability and superior performance of linear SVM is also experimentally analyzed, to conclude that this data acquisition technique generates linearly separable datasets. PMID:25760051

New methods of data calibration for high power-aperture lidar.

PubMed

Guan, Sai; Yang, Guotao; Chang, Qihai; Cheng, Xuewu; Yang, Yong; Gong, Shaohua; Wang, Jihong

2013-03-25

For high power-aperture lidar sounding of wide atmospheric dynamic ranges, as in middle-upper atmospheric probing, photomultiplier tubes' (PMT) pulse pile-up effects and signal-induced noise (SIN) complicates the extraction of information from lidar return signal, especially from metal layers' fluorescence signal. Pursuit for sophisticated description of metal layers' characteristics at far range (80~130km) with one PMT of high quantum efficiency (QE) and good SNR, contradicts the requirements for signals of wide linear dynamic range (i.e. from approximate 10(2) to 10(8) counts/s). In this article, Substantial improvements on experimental simulation of Lidar signals affected by PMT are reported to evaluate the PMTs' distortions in our High Power-Aperture Sodium LIDAR system. A new method for pile-up calibration is proposed by taking into account PMT and High Speed Data Acquisition Card as an Integrated Black-Box, as well as a new experimental method for identifying and removing SIN from the raw Lidar signals. Contradiction between the limited linear dynamic range of raw signal (55~80km) and requirements for wider acceptable linearity has been effectively solved, without complicating the current lidar system. Validity of these methods was demonstrated by applying calibrated data to retrieve atmospheric parameters (i.e. atmospheric density, temperature and sodium absolutely number density), in comparison with measurements of TIMED satellite and atmosphere model. Good agreements are obtained between results derived from calibrated signal and reference measurements where differences of atmosphere density, temperature are less than 5% in the stratosphere and less than 10K from 30km to mesosphere, respectively. Additionally, approximate 30% changes are shown in sodium concentration at its peak value. By means of the proposed methods to revert the true signal independent of detectors, authors approach a new balance between maintaining the linearity of adequate signal (20-110km) and guaranteeing good SNR (i.e. 10(4):1 around 90km) without debasing QE, in one single detecting channel. For the first time, PMT in photon-counting mode is independently applied to subtract reliable information of atmospheric parameters with wide acceptable linearity over an altitude range from stratosphere up to lower thermosphere (20-110km).

Feasibility of an ultra-low power digital signal processor platform as a basis for a fully implantable brain-computer interface system.

PubMed

Wang, Po T; Gandasetiawan, Keulanna; McCrimmon, Colin M; Karimi-Bidhendi, Alireza; Liu, Charles Y; Heydari, Payam; Nenadic, Zoran; Do, An H

2016-08-01

A fully implantable brain-computer interface (BCI) can be a practical tool to restore independence to those affected by spinal cord injury. We envision that such a BCI system will invasively acquire brain signals (e.g. electrocorticogram) and translate them into control commands for external prostheses. The feasibility of such a system was tested by implementing its benchtop analogue, centered around a commercial, ultra-low power (ULP) digital signal processor (DSP, TMS320C5517, Texas Instruments). A suite of signal processing and BCI algorithms, including (de)multiplexing, Fast Fourier Transform, power spectral density, principal component analysis, linear discriminant analysis, Bayes rule, and finite state machine was implemented and tested in the DSP. The system's signal acquisition fidelity was tested and characterized by acquiring harmonic signals from a function generator. In addition, the BCI decoding performance was tested, first with signals from a function generator, and subsequently using human electroencephalogram (EEG) during eyes opening and closing task. On average, the system spent 322 ms to process and analyze 2 s of data. Crosstalk (<;-65 dB) and harmonic distortion (~1%) were minimal. Timing jitter averaged 49 μs per 1000 ms. The online BCI decoding accuracies were 100% for both function generator and EEG data. These results show that a complex BCI algorithm can be executed on an ULP DSP without compromising performance. This suggests that the proposed hardware platform may be used as a basis for future, fully implantable BCI systems.

Core signalling motif displaying multistability through multi-state enzymes.

PubMed

Feng, Song; Sáez, Meritxell; Wiuf, Carsten; Feliu, Elisenda; Soyer, Orkun S

2016-10-01

Bistability, and more generally multistability, is a key system dynamics feature enabling decision-making and memory in cells. Deciphering the molecular determinants of multistability is thus crucial for a better understanding of cellular pathways and their (re)engineering in synthetic biology. Here, we show that a key motif found predominantly in eukaryotic signalling systems, namely a futile signalling cycle, can display bistability when featuring a two-state kinase. We provide necessary and sufficient mathematical conditions on the kinetic parameters of this motif that guarantee the existence of multiple steady states. These conditions foster the intuition that bistability arises as a consequence of competition between the two states of the kinase. Extending from this result, we find that increasing the number of kinase states linearly translates into an increase in the number of steady states in the system. These findings reveal, to our knowledge, a new mechanism for the generation of bistability and multistability in cellular signalling systems. Further the futile cycle featuring a two-state kinase is among the smallest bistable signalling motifs. We show that multi-state kinases and the described competition-based motif are part of several natural signalling systems and thereby could enable them to implement complex information processing through multistability. These results indicate that multi-state kinases in signalling systems are readily exploited by natural evolution and could equally be used by synthetic approaches for the generation of multistable information processing systems at the cellular level. © 2016 The Authors.

Coherent detection in optical fiber systems.

PubMed

Ip, Ezra; Lau, Alan Pak Tao; Barros, Daniel J F; Kahn, Joseph M

2008-01-21

The drive for higher performance in optical fiber systems has renewed interest in coherent detection. We review detection methods, including noncoherent, differentially coherent, and coherent detection, as well as a hybrid method. We compare modulation methods encoding information in various degrees of freedom (DOF). Polarization-multiplexed quadrature-amplitude modulation maximizes spectral efficiency and power efficiency, by utilizing all four available DOF, the two field quadratures in the two polarizations. Dual-polarization homodyne or heterodyne downconversion are linear processes that can fully recover the received signal field in these four DOF. When downconverted signals are sampled at the Nyquist rate, compensation of transmission impairments can be performed using digital signal processing (DSP). Linear impairments, including chromatic dispersion and polarization-mode dispersion, can be compensated quasi-exactly using finite impulse response filters. Some nonlinear impairments, such as intra-channel four-wave mixing and nonlinear phase noise, can be compensated partially. Carrier phase recovery can be performed using feedforward methods, even when phase-locked loops may fail due to delay constraints. DSP-based compensation enables a receiver to adapt to time-varying impairments, and facilitates use of advanced forward-error-correction codes. We discuss both single- and multi-carrier system implementations. For a given modulation format, using coherent detection, they offer fundamentally the same spectral efficiency and power efficiency, but may differ in practice, because of different impairments and implementation details. With anticipated advances in analog-to-digital converters and integrated circuit technology, DSP-based coherent receivers at bit rates up to 100 Gbit/s should become practical within the next few years.

Equalizer design techniques for dispersive cables with application to the SPS wideband kicker

NASA Astrophysics Data System (ADS)

Platt, Jason; Hofle, Wolfgang; Pollock, Kristin; Fox, John

2017-10-01

A wide-band vertical instability feedback control system in development at CERN requires 1-1.5 GHz of bandwidth for the entire processing chain, from the beam pickups through the feedback signal digital processing to the back-end power amplifiers and kicker structures. Dispersive effects in cables, amplifiers, pickup and kicker elements can result in distortions in the time domain signal as it proceeds through the processing system, and deviations from linear phase response reduce the allowable bandwidth for the closed-loop feedback system. We have developed an equalizer analog circuit that compensates for these dispersive effects. Here we present a design technique for the construction of an analog equalizer that incorporates the effect of parasitic circuit elements in the equalizer to increase the fidelity of the implemented equalizer. Finally, we show results from the measurement of an assembled backend equalizer that corrects for dispersive elements in the cables over a bandwidth of 10-1000 MHz.

Application of higher order SVD to vibration-based system identification and damage detection

NASA Astrophysics Data System (ADS)

Chao, Shu-Hsien; Loh, Chin-Hsiung; Weng, Jian-Huang

2012-04-01

Singular value decomposition (SVD) is a powerful linear algebra tool. It is widely used in many different signal processing methods, such principal component analysis (PCA), singular spectrum analysis (SSA), frequency domain decomposition (FDD), subspace identification and stochastic subspace identification method ( SI and SSI ). In each case, the data is arranged appropriately in matrix form and SVD is used to extract the feature of the data set. In this study three different algorithms on signal processing and system identification are proposed: SSA, SSI-COV and SSI-DATA. Based on the extracted subspace and null-space from SVD of data matrix, damage detection algorithms can be developed. The proposed algorithm is used to process the shaking table test data of the 6-story steel frame. Features contained in the vibration data are extracted by the proposed method. Damage detection can then be investigated from the test data of the frame structure through subspace-based and nullspace-based damage indices.

Compressed digital holography: from micro towards macro

NASA Astrophysics Data System (ADS)

Schretter, Colas; Bettens, Stijn; Blinder, David; Pesquet-Popescu, Béatrice; Cagnazzo, Marco; Dufaux, Frédéric; Schelkens, Peter

2016-09-01

signal processing methods from software-driven computer engineering and applied mathematics. The compressed sensing theory in particular established a practical framework for reconstructing the scene content using few linear combinations of complex measurements and a sparse prior for regularizing the solution. Compressed sensing found direct applications in digital holography for microscopy. Indeed, the wave propagation phenomenon in free space mixes in a natural way the spatial distribution of point sources from the 3-dimensional scene. As the 3-dimensional scene is mapped to a 2-dimensional hologram, the hologram samples form a compressed representation of the scene as well. This overview paper discusses contributions in the field of compressed digital holography at the micro scale. Then, an outreach on future extensions towards the real-size macro scale is discussed. Thanks to advances in sensor technologies, increasing computing power and the recent improvements in sparse digital signal processing, holographic modalities are on the verge of practical high-quality visualization at a macroscopic scale where much higher resolution holograms must be acquired and processed on the computer.

Simultaneous spectrophotometric determination of indacaterol and glycopyrronium in a newly approved pharmaceutical formulation using different signal processing techniques of ratio spectra

NASA Astrophysics Data System (ADS)

Abdel Ghany, Maha F.; Hussein, Lobna A.; Magdy, Nancy; Yamani, Hend Z.

2016-03-01

Three spectrophotometric methods have been developed and validated for determination of indacaterol (IND) and glycopyrronium (GLY) in their binary mixtures and novel pharmaceutical dosage form. The proposed methods are considered to be the first methods to determine the investigated drugs simultaneously. The developed methods are based on different signal processing techniques of ratio spectra namely; Numerical Differentiation (ND), Savitsky-Golay (SG) and Fourier Transform (FT). The developed methods showed linearity over concentration range 1-30 and 10-35 (μg/mL) for IND and GLY, respectively. The accuracy calculated as percentage recoveries were in the range of 99.00%-100.49% with low value of RSD% (< 1.5%) demonstrating an excellent accuracy of the proposed methods. The developed methods were proved to be specific, sensitive and precise for quality control of the investigated drugs in their pharmaceutical dosage form without the need for any separation process.

Focal activation of primary visual cortex following supra-choroidal electrical stimulation of the retina: Intrinsic signal imaging and linear model analysis.

PubMed

Cloherty, Shaun L; Hietanen, Markus A; Suaning, Gregg J; Ibbotson, Michael R

2010-01-01

We performed optical intrinsic signal imaging of cat primary visual cortex (Area 17 and 18) while delivering bipolar electrical stimulation to the retina by way of a supra-choroidal electrode array. Using a general linear model (GLM) analysis we identified statistically significant (p < 0.01) activation in a localized region of cortex following supra-threshold electrical stimulation at a single retinal locus. (1) demonstrate that intrinsic signal imaging combined with linear model analysis provides a powerful tool for assessing cortical responses to prosthetic stimulation, and (2) confirm that supra-choroidal electrical stimulation can achieve localized activation of the cortex consistent with focal activation of the retina.

Design of a Multi-Channel Front-End Readout ASIC With Low Noise and Large Dynamic Input Range for APD-Based PET Imaging

NASA Astrophysics Data System (ADS)

Fang, X. C.; Hu-Guo, Ch.; Ollivier-Henry, N.; Brasse, D.; Hu, Y.

2010-06-01

This paper represents the design of a low-noise, wide band multi-channel readout integrated circuit (IC) used as front end readout electronics of avalanche photo diodes (APD) dedicated to a small animal positron emission tomography (PET) system. The first ten-channel prototype chip (APD-Chip) of the analog parts has been designed and fabricated in a 0.35 μm CMOS process. Every channel of the APD_Chip includes a charge-sensitive preamplifier (CSA), a CR-(RC)2 shaper, and an analog buffer. In a channel, the CSA reads charge signals (10 bits dynamic range) from an APD array having 10 pF of capacitance per pixel. A linearized degenerated differential pair which ensures high linearity in all dynamical range is used as the high feedback resistor for preventing pile up of signals. The designed CSA has the capability of compensating automatically up to 200 nA leakage current from the detector. The CR-(RC)2 shaper filters and shapes the output signal of the CSA. An equivalent input noise charge obtained from test is 275 e -+ 10 e-/pF. In this paper the prototype is presented for both its theoretical analysis and its test results.

Techniques for the Enhancement of Linear Predictive Speech Coding in Adverse Conditions

NASA Astrophysics Data System (ADS)

Wrench, Alan A.

Available from UMI in association with The British Library. Requires signed TDF. The Linear Prediction model was first applied to speech two and a half decades ago. Since then it has been the subject of intense research and continues to be one of the principal tools in the analysis of speech. Its mathematical tractability makes it a suitable subject for study and its proven success in practical applications makes the study worthwhile. The model is known to be unsuited to speech corrupted by background noise. This has led many researchers to investigate ways of enhancing the speech signal prior to Linear Predictive analysis. In this thesis this body of work is extended. The chosen application is low bit-rate (2.4 kbits/sec) speech coding. For this task the performance of the Linear Prediction algorithm is crucial because there is insufficient bandwidth to encode the error between the modelled speech and the original input. A review of the fundamentals of Linear Prediction and an independent assessment of the relative performance of methods of Linear Prediction modelling are presented. A new method is proposed which is fast and facilitates stability checking, however, its stability is shown to be unacceptably poorer than existing methods. A novel supposition governing the positioning of the analysis frame relative to a voiced speech signal is proposed and supported by observation. The problem of coding noisy speech is examined. Four frequency domain speech processing techniques are developed and tested. These are: (i) Combined Order Linear Prediction Spectral Estimation; (ii) Frequency Scaling According to an Aural Model; (iii) Amplitude Weighting Based on Perceived Loudness; (iv) Power Spectrum Squaring. These methods are compared with the Recursive Linearised Maximum a Posteriori method. Following on from work done in the frequency domain, a time domain implementation of spectrum squaring is developed. In addition, a new method of power spectrum estimation is developed based on the Minimum Variance approach. This new algorithm is shown to be closely related to Linear Prediction but produces slightly broader spectral peaks. Spectrum squaring is applied to both the new algorithm and standard Linear Prediction and their relative performance is assessed. (Abstract shortened by UMI.).

Shaping charge excitations in chiral edge states with a time-dependent gate voltage

NASA Astrophysics Data System (ADS)

Misiorny, Maciej; Fève, Gwendal; Splettstoesser, Janine

2018-02-01

We study a coherent conductor supporting a single edge channel in which alternating current pulses are created by local time-dependent gating and sent on a beam-splitter realized by a quantum point contact. The current response to the gate voltage in this setup is intrinsically linear. Based on a fully self-consistent treatment employing a Floquet scattering theory, we analyze the effect of different voltage shapes and frequencies, as well as the role of the gate geometry on the injected signal. In particular, we highlight the impact of frequency-dependent screening on the process of shaping the current signal. The feasibility of creating true single-particle excitations with this method is confirmed by investigating the suppression of excess noise, which is otherwise created by additional electron-hole pair excitations in the current signal.

Development and Analysis of Closed Cycle Circulator Elements.

DTIC Science & Technology

1980-05-01

circuits are mounted on cards accessible through a hinged rear panel for service or adjustments. Cards may be removed in groups of 3 for servicing without...voltage signal is processed in such a way that it became linearly related to velocity of the gas flow. The use of these modules ensures the frequency...most important idiagnostic to be measured optically. This test is broken down into two categories: a medium homogeneity category *1 in which

Homogenization via Sequential Projection to Nested Subspaces Spanned by Orthogonal Scaling and Wavelet Orthonormal Families of Functions

DTIC Science & Technology

2008-07-01

operators in Hilbert spaces. The homogenization procedure through successive multi- resolution projections is presented, followed by a numerical example of...is intended to be essentially self-contained. The mathematical ( Greenberg 1978; Gilbert 2006) and signal processing (Strang and Nguyen 1995...literature listed in the references. The ideas behind multi-resolution analysis unfold from the theory of linear operators in Hilbert spaces (Davis 1975

Optical monitor for real time thickness change measurements via lateral-translation induced phase-stepping interferometry

DOEpatents

Rushford, Michael C.

2002-01-01

An optical monitoring instrument monitors etch depth and etch rate for controlling a wet-etching process. The instrument provides means for viewing through the back side of a thick optic onto a nearly index-matched interface. Optical baffling and the application of a photoresist mask minimize spurious reflections to allow for monitoring with extremely weak signals. A Wollaston prism enables linear translation for phase stepping.

Sensory Information Processing and Symbolic Computation

DTIC Science & Technology

1973-12-31

plague all image deblurring methods when working with high signal to noise ratios, is that of a ringing or ghost image phenomenon which surrounds high...Figure 11 The Impulse Response of an All-Pass Random Phase Filter 24 Figure 12 (a) Unsmoothed Log Spectra of the Sentence "The pipe began to...of automatic deblurring of images, linear predictive coding of speech and the refinement and application of mathematical models of human vision and

Effects of Age, Gender and Hemispheric Location on T2 Hypointensity in the Pulvinar at 3T.

PubMed

White, Matthew L; Zhang, Yan; Helvey, Jason T; Yu, Fang; Omojola, Matthew F

2014-12-01

Pulvinar signal intensity decrease on T2-weighted images has been reported in some neurological abnormalities. We aimed to define the normal T2 signal hypointensity pattern present in the pulvinar to avoid erroneous radiological interpretation. One hundred and forty-two subjects (54 men and 88 women; age range 9-91 years) with unremarkable brain 3T MR findings were enrolled. MR images were analyzed with regard to signal intensity of the pulvinar relative to the thalamus on fluid attenuated inversion recovery images. Effects of age, gender and hemispheric location on the degree of T2 hypointensity were statistically analyzed. The statistical association was measured between the pattern of signal changes in the pulvinar region and that in the putamen and the globus pallidus. We detected a linear signal decrease in the pulvinar region with age. The male subjects had a more rapid decrease of signal with age than female subjects. The right pulvinar region had a higher chance of hypointensity compared to the left. A positive linear association was found when signal change from the pulvinar region was compared with signal in the putamen and globus pallidus. We detected a linear signal decrease with age in the pulvinar. The physiological signal features of the pulvinar also depend on gender and hemispheric lateralization. The pattern of signal change in the pulvinar is similar to but not the same as that in the putamen and globus pallidus.

Techniques for blade tip clearance measurements with capacitive probes

NASA Astrophysics Data System (ADS)

Steiner, Alexander

2000-07-01

This article presents a proven but advantageous concept for blade tip clearance evaluation in turbomachinery. The system is based on heavy duty probes and a high frequency (HF) and amplifying electronic unit followed by a signal processing unit. Measurements are taken under high temperature and other severe conditions such as ionization. Every single blade can be observed. The signals are digitally filtered and linearized in real time. The electronic set-up is highly integrated. Miniaturized versions of the electronic units exist. The small and robust units can be used in turbo engines in flight. With several probes at different angles in one radial plane further information is available. Shaft eccentricity or blade oscillations can be calculated.

Input reconstruction for networked control systems subject to deception attacks and data losses on control signals

NASA Astrophysics Data System (ADS)

Keller, J. Y.; Chabir, K.; Sauter, D.

2016-03-01

State estimation of stochastic discrete-time linear systems subject to unknown inputs or constant biases has been widely studied but no work has been dedicated to the case where a disturbance switches between unknown input and constant bias. We show that such disturbance can affect a networked control system subject to deception attacks and data losses on the control signals transmitted by the controller to the plant. This paper proposes to estimate the switching disturbance from an augmented state version of the intermittent unknown input Kalman filter recently developed by the authors. Sufficient stochastic stability conditions are established when the arrival binary sequence of data losses follows a Bernoulli random process.

The Thirty Gigahertz Instrument Receiver for the QUIJOTE Experiment: Preliminary Polarization Measurements and Systematic-Error Analysis.

PubMed

Casas, Francisco J; Ortiz, David; Villa, Enrique; Cano, Juan L; Cagigas, Jaime; Pérez, Ana R; Aja, Beatriz; Terán, J Vicente; de la Fuente, Luisa; Artal, Eduardo; Hoyland, Roger; Génova-Santos, Ricardo

2015-08-05

This paper presents preliminary polarization measurements and systematic-error characterization of the Thirty Gigahertz Instrument receiver developed for the QUIJOTE experiment. The instrument has been designed to measure the polarization of Cosmic Microwave Background radiation from the sky, obtaining the Q, U, and I Stokes parameters of the incoming signal simultaneously. Two kinds of linearly polarized input signals have been used as excitations in the polarimeter measurement tests in the laboratory; these show consistent results in terms of the Stokes parameters obtained. A measurement-based systematic-error characterization technique has been used in order to determine the possible sources of instrumental errors and to assist in the polarimeter calibration process.

Long-period fiber gratings as ultrafast optical differentiators.

PubMed

Kulishov, Mykola; Azaña, José

2005-10-15

It is demonstrated that a single, uniform long-period fiber grating (LPFG) working in the linear regime inherently behaves as an ultrafast optical temporal differentiator. Specifically, we show that the output temporal waveform in the core mode of a LPFG providing full energy coupling into the cladding mode is proportional to the first derivative of the optical temporal signal (e.g., optical pulse) launched at the input of the LPFG. Moreover, a LPFG providing full energy recoupling back from the cladding mode into the core mode inherently implements second-order temporal differentiation. Our numerical results have confirmed the feasibility of this simple, all-fiber approach to processing optical signals with temporal features in the picosecond and subpicosecond ranges.

BCI Competition IV – Data Set I: Learning Discriminative Patterns for Self-Paced EEG-Based Motor Imagery Detection

PubMed Central

Zhang, Haihong; Guan, Cuntai; Ang, Kai Keng; Wang, Chuanchu

2012-01-01

Detecting motor imagery activities versus non-control in brain signals is the basis of self-paced brain-computer interfaces (BCIs), but also poses a considerable challenge to signal processing due to the complex and non-stationary characteristics of motor imagery as well as non-control. This paper presents a self-paced BCI based on a robust learning mechanism that extracts and selects spatio-spectral features for differentiating multiple EEG classes. It also employs a non-linear regression and post-processing technique for predicting the time-series of class labels from the spatio-spectral features. The method was validated in the BCI Competition IV on Dataset I where it produced the lowest prediction error of class labels continuously. This report also presents and discusses analysis of the method using the competition data set. PMID:22347153

Chromospheric LAyer SpectroPolarimeter (CLASP2)

NASA Technical Reports Server (NTRS)

Narukage, Noriyuki; Cirtain, Jonathan W.; Ishikawa, Ryoko; Trujillo-Bueno, Javier; De Pontieu, Bart; Kubo, Masahito; Ishikawa, Shinnosuke; Kano, Ryohei; Suematsu, Yoshinori; Yoshida, Masaki;

Solution-Processed Flexible Organic Ferroelectric Phototransistor.

PubMed

Zhao, Qiang; Wang, Hanlin; Jiang, Lang; Zhen, Yonggang; Dong, Huanli; Hu, Wenping

2017-12-20

In this article, we demonstrate ferroelectric insulator, P(VDF-TrFE), can be integrated with red light sensitive polymeric semiconductor, P(DPP-TzBT), toward ferroelectric organic phototransistors (OPTs). This ferroelectricity-modulated phototransistor possesses different nonvolatile and tunable dark current states due to P(VDF-TrFE)'s remnant polarization. As a result, the OPT is endowed with a tunable dark current level ranging from 1 nA to 100 nA. Once the OPT is programmed or electrically polarized, its photo-to-dark (signal-to-noise) ratio can be "flexible" during photodetection process, without gate bias application. This kind of organic ferroelectric phototransistor has great potential in detecting wide ranges of light signals with good linearity. Moreover, its tuning mechanism discussed in this work can be helpful to understand the operation mechanism of organic phototransistor (OPT). It can be promising for novel photodetection application in plastic electronic devices.

All-optical differential equation solver with constant-coefficient tunable based on a single microring resonator.

PubMed

Yang, Ting; Dong, Jianji; Lu, Liangjun; Zhou, Linjie; Zheng, Aoling; Zhang, Xinliang; Chen, Jianping

2014-07-04

Photonic integrated circuits for photonic computing open up the possibility for the realization of ultrahigh-speed and ultra wide-band signal processing with compact size and low power consumption. Differential equations model and govern fundamental physical phenomena and engineering systems in virtually any field of science and engineering, such as temperature diffusion processes, physical problems of motion subject to acceleration inputs and frictional forces, and the response of different resistor-capacitor circuits, etc. In this study, we experimentally demonstrate a feasible integrated scheme to solve first-order linear ordinary differential equation with constant-coefficient tunable based on a single silicon microring resonator. Besides, we analyze the impact of the chirp and pulse-width of input signals on the computing deviation. This device can be compatible with the electronic technology (typically complementary metal-oxide semiconductor technology), which may motivate the development of integrated photonic circuits for optical computing.

All-optical differential equation solver with constant-coefficient tunable based on a single microring resonator

PubMed Central

Yang, Ting; Dong, Jianji; Lu, Liangjun; Zhou, Linjie; Zheng, Aoling; Zhang, Xinliang; Chen, Jianping

2014-01-01

Photonic integrated circuits for photonic computing open up the possibility for the realization of ultrahigh-speed and ultra wide-band signal processing with compact size and low power consumption. Differential equations model and govern fundamental physical phenomena and engineering systems in virtually any field of science and engineering, such as temperature diffusion processes, physical problems of motion subject to acceleration inputs and frictional forces, and the response of different resistor-capacitor circuits, etc. In this study, we experimentally demonstrate a feasible integrated scheme to solve first-order linear ordinary differential equation with constant-coefficient tunable based on a single silicon microring resonator. Besides, we analyze the impact of the chirp and pulse-width of input signals on the computing deviation. This device can be compatible with the electronic technology (typically complementary metal-oxide semiconductor technology), which may motivate the development of integrated photonic circuits for optical computing. PMID:24993440

Overarching framework for data-based modelling

NASA Astrophysics Data System (ADS)

Schelter, Björn; Mader, Malenka; Mader, Wolfgang; Sommerlade, Linda; Platt, Bettina; Lai, Ying-Cheng; Grebogi, Celso; Thiel, Marco

2014-02-01

One of the main modelling paradigms for complex physical systems are networks. When estimating the network structure from measured signals, typically several assumptions such as stationarity are made in the estimation process. Violating these assumptions renders standard analysis techniques fruitless. We here propose a framework to estimate the network structure from measurements of arbitrary non-linear, non-stationary, stochastic processes. To this end, we propose a rigorous mathematical theory that underlies this framework. Based on this theory, we present a highly efficient algorithm and the corresponding statistics that are immediately sensibly applicable to measured signals. We demonstrate its performance in a simulation study. In experiments of transitions between vigilance stages in rodents, we infer small network structures with complex, time-dependent interactions; this suggests biomarkers for such transitions, the key to understand and diagnose numerous diseases such as dementia. We argue that the suggested framework combines features that other approaches followed so far lack.

PI controller design for indirect vector controlled induction motor: A decoupling approach.

PubMed

Jain, Jitendra Kr; Ghosh, Sandip; Maity, Somnath; Dworak, Pawel

2017-09-01

Decoupling of the stator currents is important for smoother torque response of indirect vector controlled induction motors. Typically, feedforward decoupling is used to take care of current coupling that requires exact knowledge of motor parameters, additional circuitry and signal processing. In this paper, a method is proposed to design the regulating proportional-integral gains that minimize coupling without any requirement of the additional decoupler. The variation of the coupling terms for change in load torque is considered as the performance measure. An iterative linear matrix inequality based H ∞ control design approach is used to obtain the controller gains. A comparison between the feedforward and the proposed decoupling schemes is presented through simulation and experimental results. The results show that the proposed scheme is simple yet effective even without additional block or burden on signal processing. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Model cerebellar granule cells can faithfully transmit modulated firing rate signals

PubMed Central

Rössert, Christian; Solinas, Sergio; D'Angelo, Egidio; Dean, Paul; Porrill, John

2014-01-01

A crucial assumption of many high-level system models of the cerebellum is that information in the granular layer is encoded in a linear manner. However, granule cells are known for their non-linear and resonant synaptic and intrinsic properties that could potentially impede linear signal transmission. In this modeling study we analyse how electrophysiological granule cell properties and spike sampling influence information coded by firing rate modulation, assuming no signal-related, i.e., uncorrelated inhibitory feedback (open-loop mode). A detailed one-compartment granule cell model was excited in simulation by either direct current or mossy-fiber synaptic inputs. Vestibular signals were represented as tonic inputs to the flocculus modulated at frequencies up to 20 Hz (approximate upper frequency limit of vestibular-ocular reflex, VOR). Model outputs were assessed using estimates of both the transfer function, and the fidelity of input-signal reconstruction measured as variance-accounted-for. The detailed granule cell model with realistic mossy-fiber synaptic inputs could transmit information faithfully and linearly in the frequency range of the vestibular-ocular reflex. This was achieved most simply if the model neurons had a firing rate at least twice the highest required frequency of modulation, but lower rates were also adequate provided a population of neurons was utilized, especially in combination with push-pull coding. The exact number of neurons required for faithful transmission depended on the precise values of firing rate and noise. The model neurons were also able to combine excitatory and inhibitory signals linearly, and could be replaced by a simpler (modified) integrate-and-fire neuron in the case of high tonic firing rates. These findings suggest that granule cells can in principle code modulated firing-rate inputs in a linear manner, and are thus consistent with the high-level adaptive-filter model of the cerebellar microcircuit. PMID:25352777

Stable propagation of mechanical signals in soft media using stored elastic energy.

PubMed

Raney, Jordan R; Nadkarni, Neel; Daraio, Chiara; Kochmann, Dennis M; Lewis, Jennifer A; Bertoldi, Katia

2016-08-30

Soft structures with rationally designed architectures capable of large, nonlinear deformation present opportunities for unprecedented, highly tunable devices and machines. However, the highly dissipative nature of soft materials intrinsically limits or prevents certain functions, such as the propagation of mechanical signals. Here we present an architected soft system composed of elastomeric bistable beam elements connected by elastomeric linear springs. The dissipative nature of the polymer readily damps linear waves, preventing propagation of any mechanical signal beyond a short distance, as expected. However, the unique architecture of the system enables propagation of stable, nonlinear solitary transition waves with constant, controllable velocity and pulse geometry over arbitrary distances. Because the high damping of the material removes all other linear, small-amplitude excitations, the desired pulse propagates with high fidelity and controllability. This phenomenon can be used to control signals, as demonstrated by the design of soft mechanical diodes and logic gates.

Photonic generation of phase-stable and wideband chirped microwave signals based on phase-locked dual optical frequency combs.

PubMed

Tong, Yitian; Zhou, Qian; Han, Daming; Li, Baiyu; Xie, Weilin; Liu, Zhangweiyi; Qin, Jie; Wang, Xiaocheng; Dong, Yi; Hu, Weisheng

2016-08-15

A photonics-based scheme is presented for generating wideband and phase-stable chirped microwave signals based on two phase-locked combs with fixed and agile repetition rates. By tuning the difference of the two combs' repetition rates and extracting different order comb tones, a wideband linearly frequency-chirped microwave signal with flexible carrier frequency and chirped range is obtained. Owing to the scheme of dual-heterodyne phase transfer and phase-locked loop, extrinsic phase drift and noise induced by the separated optical paths is detected and suppressed efficiently. Linearly frequency-chirped microwave signals from 5 to 15 GHz and 237 to 247 GHz with 30 ms duration are achieved, respectively, contributing to the time-bandwidth product of 3×10⁸. And less than 1.3×10^-5 linearity errors (RMS) are also obtained.

Stable propagation of mechanical signals in soft media using stored elastic energy

PubMed Central

Raney, Jordan R.; Nadkarni, Neel; Daraio, Chiara; Lewis, Jennifer A.; Bertoldi, Katia

2016-01-01

Soft structures with rationally designed architectures capable of large, nonlinear deformation present opportunities for unprecedented, highly tunable devices and machines. However, the highly dissipative nature of soft materials intrinsically limits or prevents certain functions, such as the propagation of mechanical signals. Here we present an architected soft system composed of elastomeric bistable beam elements connected by elastomeric linear springs. The dissipative nature of the polymer readily damps linear waves, preventing propagation of any mechanical signal beyond a short distance, as expected. However, the unique architecture of the system enables propagation of stable, nonlinear solitary transition waves with constant, controllable velocity and pulse geometry over arbitrary distances. Because the high damping of the material removes all other linear, small-amplitude excitations, the desired pulse propagates with high fidelity and controllability. This phenomenon can be used to control signals, as demonstrated by the design of soft mechanical diodes and logic gates. PMID:27519797

A Low Power Linear Phase Programmable Long Delay Circuit.

PubMed

Rodriguez-Villegas, Esther; Logesparan, Lojini; Casson, Alexander J

2014-06-01

A novel linear phase programmable delay is being proposed and implemented in a 0.35 μm CMOS process. The delay line consists of N cascaded cells, each of which delays the input signal by Td/N, where Td is the total line delay. The delay generated by each cell is programmable by changing a clock frequency and is also fully independent of the frequency of the input signal. The total delay hence depends only on the chosen clock frequency and the total number of cascaded cells. The minimum clock frequency is limited by the maximum time a voltage signal can effectively be held by an individual cell. The maximum number of cascaded cells will be limited by the effects of accumulated offset due to transistor mismatch, which eventually will affect the operating mode of the individual transistors in a cell. This latter limitation has however been dealt with in the topology by having an offset compensation mechanism that makes possible having a large number of cascaded cells and hence a long resulting delay. The delay line has been designed for scalp-based neural activity analysis that is predominantly in the sub-100 Hz frequency range. For these signals, the delay generated by a 31-cell cascade has been demonstrated to be programmable from 30 ms to 3 s. Measurement results demonstrate a 31 stage, 50 Hz bandwidth, 0.3 s delay that operates from a 1.1 V supply with power consumption of 270 nW.

Dual Rate Adaptive Control for an Industrial Heat Supply Process Using Signal Compensation Approach

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

Chai, Tianyou; Jia, Yao; Wang, Hong

The industrial heat supply process (HSP) is a highly nonlinear cascaded process which uses a steam valve opening as its control input, the steam flow-rate as its inner loop output and the supply water temperature as its outer loop output. The relationship between the heat exchange rate and the model parameters, such as steam density, entropy, and fouling correction factor and heat exchange efficiency are unknown and nonlinear. Moreover, these model parameters vary in line with steam pressure, ambient temperature and the residuals caused by the quality variations of the circulation water. When the steam pressure and the ambient temperaturemore » are of high values and are subjected to frequent external random disturbances, the supply water temperature and the steam flow-rate would interact with each other and fluctuate a lot. This is also true when the process exhibits unknown characteristic variations of the process dynamics caused by the unexpected changes of the heat exchange residuals. As a result, it is difficult to control the supply water temperature and the rates of changes of steam flow-rate well inside their targeted ranges. In this paper, a novel compensation signal based dual rate adaptive controller is developed by representing the unknown variations of dynamics as unmodeled dynamics. In the proposed controller design, such a compensation signal is constructed and added onto the control signal obtained from the linear deterministic model based feedback control design. Such a compensation signal aims at eliminating the unmodeled dynamics and the rate of changes of the currently sample unmodeled dynamics. A successful industrial application is carried out, where it has been shown that both the supply water temperature and the rate of the changes of the steam flow-rate can be controlled well inside their targeted ranges when the process is subjected to unknown variations of its dynamics.« less

Human Time-Frequency Acuity Beats the Fourier Uncertainty Principle

NASA Astrophysics Data System (ADS)

Oppenheim, Jacob N.; Magnasco, Marcelo O.

2013-01-01

The time-frequency uncertainty principle states that the product of the temporal and frequency extents of a signal cannot be smaller than 1/(4π). We study human ability to simultaneously judge the frequency and the timing of a sound. Our subjects often exceeded the uncertainty limit, sometimes by more than tenfold, mostly through remarkable timing acuity. Our results establish a lower bound for the nonlinearity and complexity of the algorithms employed by our brains in parsing transient sounds, rule out simple “linear filter” models of early auditory processing, and highlight timing acuity as a central feature in auditory object processing.

Imaging Through Random Discrete-Scatterer Dispersive Media

DTIC Science & Technology

2015-08-27

to that of a conventional, continuous, linear - frequency-modulated chirped signal [3]. Chirped train signals are a particular realization of a class of...continuous chirp signals, characterized by linear frequency modulation [3], we assume the time instances tn to be given by 1 tn = τg ( 1− βg n 2Ng ) n...kernel Dn(z) [9] by sincN (z) = (N + 1)−1DN/2(2πz/N). DISTRIBUTION A: Distribution approved for public release. 4 We use the elementary identity5 π sin

Mellin Transform-Based Correction Method for Linear Scale Inconsistency of Intrusion Events Identification in OFPS

NASA Astrophysics Data System (ADS)

Wang, Baocheng; Qu, Dandan; Tian, Qing; Pang, Liping

2018-05-01

For the problem that the linear scale of intrusion signals in the optical fiber pre-warning system (OFPS) is inconsistent, this paper presents a method to correct the scale. Firstly, the intrusion signals are intercepted, and an aggregate of the segments with equal length is obtained. Then, the Mellin transform (MT) is applied to convert them into the same scale. The spectral characteristics are obtained by the Fourier transform. Finally, we adopt back-propagation (BP) neural network to identify intrusion types, which takes the spectral characteristics as input. We carried out the field experiments and collected the optical fiber intrusion signals which contain the picking signal, shoveling signal, and running signal. The experimental results show that the proposed algorithm can effectively improve the recognition accuracy of the intrusion signals.

Fiber-Optic Linear Displacement Sensor Based On Matched Interference Filters

NASA Astrophysics Data System (ADS)

Fuhr, Peter L.; Feener, Heidi C.; Spillman, William B.

1990-02-01

A fiber optic linear displacement sensor has been developed in which a pair of matched interference filters are used to encode linear position on a broadband optical signal as relative intensity variations. As the filters are displaced, the optical beam illuminates varying amounts of each filter. Determination of the relative intensities at each filter pairs' passband is based on measurements acquired with matching filters and photodetectors. Source power variation induced errors are minimized by basing determination of linear position on signal Visibility. A theoretical prediction of the sensor's performance is developed and compared with experiments performed in the near IR spectral region using large core multimode optical fiber.

Raman Lidar MERGE Value-Added Product

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

Newsom, Rob; Goldsmith, John; Sivaraman, Chitra

The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility Raman lidars (RLs) are semi-autonomous, land-based, laser remote sensing systems that provide height- and time-resolved measurements of water vapor mixing ratio, temperature, aerosol backscatter, extinction, and linear depolarization ratio from about 200 m to greater than 10 km AGL. These systems transmit at a wavelength of 355 nm with 300 mJ, ~5 ns pulses, and a pulse repetition frequency of 30 Hz. The receiver incorporates nine detection channels, including two water vapor channels at 408 nm, two nitrogen channels at 387 nm, three elastic channels, and twomore » rotational Raman channels for temperature profiling at 354 and 353 nm. Figure 1 illustrates the layout of the ARM RL receiver system. Backscattered light from the atmosphere enters the telescope and is directed into the receiver system (i.e., aft optics). This signal is then split between a narrow-field-of-view radiometer (NFOV) path (blue) and a wide-field-of-view zenith radiometer (WFOV) path (red). The WFOV (2 mrad) path contains three channels (water vapor, nitrogen, and unpolarized elastic), and the NFOV (0.3 mrad) path contains six channels (water vapor, nitrogen, parallel and perpendicular elastic, and two rotational Raman). All nine detection channels use Electron Tubes 9954B photomultiplier tubes (PMTs). The signals from each of the nine PMTs are acquired using transient data recorders from Licel GbR (Berlin, Germany). The Licel data recorders provide simultaneous measurements of both analog photomultiplier current and photon counts at height resolution of 7.5 m and a time resolution of 10 s. The analog signal provides good linearity in the strong signal regime, but poor sensitivity at low signal levels. Conversely, the photo counting signal provides good sensitivity in the weak signal regime, but is strongly nonlinear at higher signal levels. The advantage in recording both signals is that they can be combined (or merged) into a single signal with improved dynamic range. The process of combining the analog and photon counting data has become known as “gluing” (Whiteman et al., 2006).« less

gpICA: A Novel Nonlinear ICA Algorithm Using Geometric Linearization

NASA Astrophysics Data System (ADS)

Nguyen, Thang Viet; Patra, Jagdish Chandra; Emmanuel, Sabu

2006-12-01

A new geometric approach for nonlinear independent component analysis (ICA) is presented in this paper. Nonlinear environment is modeled by the popular post nonlinear (PNL) scheme. To eliminate the nonlinearity in the observed signals, a novel linearizing method named as geometric post nonlinear ICA (gpICA) is introduced. Thereafter, a basic linear ICA is applied on these linearized signals to estimate the unknown sources. The proposed method is motivated by the fact that in a multidimensional space, a nonlinear mixture is represented by a nonlinear surface while a linear mixture is represented by a plane, a special form of the surface. Therefore, by geometrically transforming the surface representing a nonlinear mixture into a plane, the mixture can be linearized. Through simulations on different data sets, superior performance of gpICA algorithm has been shown with respect to other algorithms.

Determination of multi-GNSS pseudo-absolute code biases and verification of receiver tracking technology

NASA Astrophysics Data System (ADS)

Villiger, Arturo; Schaer, Stefan; Dach, Rolf; Prange, Lars; Jäggi, Adrian

2017-04-01

It is common to handle code biases in the Global Navigation Satellite System (GNSS) data analysis as conventional differential code biases (DCBs): P1-C1, P1-P2, and P2-C2. Due to the increasing number of signals and systems in conjunction with various tracking modes for the different signals (as defined in RINEX3 format), the number of DCBs would increase drastically and the bookkeeping becomes almost unbearable. The Center for Orbit Determination in Europe (CODE) has thus changed its processing scheme to observable-specific signal biases (OSB). This means that for each observation involved all related satellite and receiver biases are considered. The OSB contributions from various ionosphere analyses (geometry-free linear combination) using different observables and frequencies and from clock analyses (ionosphere-free linear combination) are then combined on normal equation level. By this, one consistent set of OSB values per satellite and receiver can be obtained that contains all information needed for GNSS-related processing. This advanced procedure of code bias handling is now also applied to the IGS (International GNSS Service) MGEX (Multi-GNSS Experiment) procedure at CODE. Results for the biases from the legacy IGS solution as well as the CODE MGEX processing (considering GPS, GLONASS, Galileo, BeiDou, and QZSS) are presented. The consistency with the traditional method is confirmed and the new results are discussed regarding the long-term stability. When processing code data, it is essential to know the true observable types in order to correct for the associated biases. CODE has been verifying the receiver tracking technologies for GPS based on estimated DCB multipliers (for the RINEX 2 case). With the change to OSB, the original verification approach was extended to search for the best fitting observable types based on known OSB values. In essence, a multiplier parameter is estimated for each involved GNSS observable type. This implies that we could recover, for receivers tracking a combination of signals, even the factors of these combinations. The verification of the observable types is crucial to identify the correct observable types of RINEX 2 data (which does not contain the signal modulation in comparison to RINEX 3). The correct information of the used observable types is essential for precise point positioning (PPP) applications and GNSS ambiguity resolution. Multi-GNSS OSBs and verified receiver tracking modes are essential to get best possible multi-GNSS solutions for geodynamic purposes and other applications.

Signal quality enhancement using higher order wavelets for ultrasonic TOFD signals from austenitic stainless steel welds.

PubMed

Praveen, Angam; Vijayarekha, K; Abraham, Saju T; Venkatraman, B

2013-09-01

Time of flight diffraction (TOFD) technique is a well-developed ultrasonic non-destructive testing (NDT) method and has been applied successfully for accurate sizing of defects in metallic materials. This technique was developed in early 1970s as a means for accurate sizing and positioning of cracks in nuclear components became very popular in the late 1990s and is today being widely used in various industries for weld inspection. One of the main advantages of TOFD is that, apart from fast technique, it provides higher probability of detection for linear defects. Since TOFD is based on diffraction of sound waves from the extremities of the defect compared to reflection from planar faces as in pulse echo and phased array, the resultant signal would be quite weak and signal to noise ratio (SNR) low. In many cases the defect signal is submerged in this noise making it difficult for detection, positioning and sizing. Several signal processing methods such as digital filtering, Split Spectrum Processing (SSP), Hilbert Transform and Correlation techniques have been developed in order to suppress unwanted noise and enhance the quality of the defect signal which can thus be used for characterization of defects and the material. Wavelet Transform based thresholding techniques have been applied largely for de-noising of ultrasonic signals. However in this paper, higher order wavelets are used for analyzing the de-noising performance for TOFD signals obtained from Austenitic Stainless Steel welds. It is observed that higher order wavelets give greater SNR improvement compared to the lower order wavelets. Copyright © 2013 Elsevier B.V. All rights reserved.

DEMNUni: ISW, Rees-Sciama, and weak-lensing in the presence of massive neutrinos

NASA Astrophysics Data System (ADS)

Carbone, Carmelita; Petkova, Margarita; Dolag, Klaus

2016-07-01

We present, for the first time in the literature, a full reconstruction of the total (linear and non-linear) ISW/Rees-Sciama effect in the presence of massive neutrinos, together with its cross-correlations with CMB-lensing and weak-lensing signals. The present analyses make use of all-sky maps extracted via ray-tracing across the gravitational potential distribution provided by the ``Dark Energy and Massive Neutrino Universe'' (DEMNUni) project, a set of large-volume, high-resolution cosmological N-body simulations, where neutrinos are treated as separate collisionless particles. We correctly recover, at 1-2% accuracy, the linear predictions from CAMB. Concerning the CMB-lensing and weak-lensing signals, we also recover, with similar accuracy, the signal predicted by Boltzmann codes, once non-linear neutrino corrections to HALOFIT are accounted for. Interestingly, in the ISW/Rees-Sciama signal, and its cross correlation with lensing, we find an excess of power with respect to the massless case, due to free streaming neutrinos, roughly at the transition scale between the linear and non-linear regimes. The excess is ~ 5 - 10% at l ~ 100 for the ISW/Rees-Sciama auto power spectrum, depending on the total neutrino mass Mν, and becomes a factor of ~ 4 for Mν = 0.3 eV, at l ~ 600, for the ISW/Rees-Sciama cross power with CMB-lensing. This effect should be taken into account for the correct estimation of the CMB temperature bispectrum in the presence of massive neutrinos.

The cerebellum for jocks and nerds alike.

PubMed

Popa, Laurentiu S; Hewitt, Angela L; Ebner, Timothy J

2014-01-01

Historically the cerebellum has been implicated in the control of movement. However, the cerebellum's role in non-motor functions, including cognitive and emotional processes, has also received increasing attention. Starting from the premise that the uniform architecture of the cerebellum underlies a common mode of information processing, this review examines recent electrophysiological findings on the motor signals encoded in the cerebellar cortex and then relates these signals to observations in the non-motor domain. Simple spike firing of individual Purkinje cells encodes performance errors, both predicting upcoming errors as well as providing feedback about those errors. Further, this dual temporal encoding of prediction and feedback involves a change in the sign of the simple spike modulation. Therefore, Purkinje cell simple spike firing both predicts and responds to feedback about a specific parameter, consistent with computing sensory prediction errors in which the predictions about the consequences of a motor command are compared with the feedback resulting from the motor command execution. These new findings are in contrast with the historical view that complex spikes encode errors. Evaluation of the kinematic coding in the simple spike discharge shows the same dual temporal encoding, suggesting this is a common mode of signal processing in the cerebellar cortex. Decoding analyses show the considerable accuracy of the predictions provided by Purkinje cells across a range of times. Further, individual Purkinje cells encode linearly and independently a multitude of signals, both kinematic and performance errors. Therefore, the cerebellar cortex's capacity to make associations across different sensory, motor and non-motor signals is large. The results from studying how Purkinje cells encode movement signals suggest that the cerebellar cortex circuitry can support associative learning, sequencing, working memory, and forward internal models in non-motor domains.

The cerebellum for jocks and nerds alike

PubMed Central

Popa, Laurentiu S.; Hewitt, Angela L.; Ebner, Timothy J.

2014-01-01

Historically the cerebellum has been implicated in the control of movement. However, the cerebellum's role in non-motor functions, including cognitive and emotional processes, has also received increasing attention. Starting from the premise that the uniform architecture of the cerebellum underlies a common mode of information processing, this review examines recent electrophysiological findings on the motor signals encoded in the cerebellar cortex and then relates these signals to observations in the non-motor domain. Simple spike firing of individual Purkinje cells encodes performance errors, both predicting upcoming errors as well as providing feedback about those errors. Further, this dual temporal encoding of prediction and feedback involves a change in the sign of the simple spike modulation. Therefore, Purkinje cell simple spike firing both predicts and responds to feedback about a specific parameter, consistent with computing sensory prediction errors in which the predictions about the consequences of a motor command are compared with the feedback resulting from the motor command execution. These new findings are in contrast with the historical view that complex spikes encode errors. Evaluation of the kinematic coding in the simple spike discharge shows the same dual temporal encoding, suggesting this is a common mode of signal processing in the cerebellar cortex. Decoding analyses show the considerable accuracy of the predictions provided by Purkinje cells across a range of times. Further, individual Purkinje cells encode linearly and independently a multitude of signals, both kinematic and performance errors. Therefore, the cerebellar cortex's capacity to make associations across different sensory, motor and non-motor signals is large. The results from studying how Purkinje cells encode movement signals suggest that the cerebellar cortex circuitry can support associative learning, sequencing, working memory, and forward internal models in non-motor domains. PMID:24987338

Working memory, age, and hearing loss: susceptibility to hearing aid distortion.

PubMed

Arehart, Kathryn H; Souza, Pamela; Baca, Rosalinda; Kates, James M

2013-01-01

Hearing aids use complex processing intended to improve speech recognition. Although many listeners benefit from such processing, it can also introduce distortion that offsets or cancels intended benefits for some individuals. The purpose of the present study was to determine the effects of cognitive ability (working memory) on individual listeners' responses to distortion caused by frequency compression applied to noisy speech. The present study analyzed a large data set of intelligibility scores for frequency-compressed speech presented in quiet and at a range of signal-to-babble ratios. The intelligibility data set was based on scores from 26 adults with hearing loss with ages ranging from 62 to 92 years. The listeners were grouped based on working memory ability. The amount of signal modification (distortion) caused by frequency compression and noise was measured using a sound quality metric. Analysis of variance and hierarchical linear modeling were used to identify meaningful differences between subject groups as a function of signal distortion caused by frequency compression and noise. Working memory was a significant factor in listeners' intelligibility of sentences presented in babble noise and processed with frequency compression based on sinusoidal modeling. At maximum signal modification (caused by both frequency compression and babble noise), the factor of working memory (when controlling for age and hearing loss) accounted for 29.3% of the variance in intelligibility scores. Combining working memory, age, and hearing loss accounted for a total of 47.5% of the variability in intelligibility scores. Furthermore, as the total amount of signal distortion increased, listeners with higher working memory performed better on the intelligibility task than listeners with lower working memory did. Working memory is a significant factor in listeners' responses to total signal distortion caused by cumulative effects of babble noise and frequency compression implemented with sinusoidal modeling. These results, together with other studies focused on wide-dynamic range compression, suggest that older listeners with hearing loss and poor working memory are more susceptible to distortions caused by at least some types of hearing aid signal-processing algorithms and by noise, and that this increased susceptibility should be considered in the hearing aid fitting process.

Gadolinium deposition in the brain: association with various GBCAs using a generalized additive model.

PubMed

Bae, Sohi; Lee, Ho-Joon; Han, Kyunghwa; Park, Yae-Won; Choi, Yoon Seong; Ahn, Sung Soo; Kim, Jinna; Lee, Seung-Koo

2017-08-01

To determine the relationship between the number of administrations of various gadolinium-based contrast agents (GBCAs) and increased T1 signal intensity in the globus pallidus (GP) and dentate nucleus (DN). This retrospective study included 122 patients who underwent double-dose GBCA-enhanced magnetic resonance imaging. Two radiologists calculated GP-to-thalamus (TH) signal intensity ratio, DN-to-pons signal intensity ratio and relative change (R change ) between the baseline and final examinations. Interobserver agreement was evaluated. The relationships between R change and several factors, including number of each GBCA administrations, were analysed using a generalized additive model. Six patients (4.9%) received linear GBCAs (mean 20.8 number of administration; range 15-30), 44 patients (36.1%) received macrocyclic GBCAs (mean 26.1; range 14-51) and 72 patients (59.0%) received both types of GBCAs (mean 31.5; range 12-65). Interobserver agreement was almost perfect (0.99; 95% CI: 0.99-0.99). R change (DN:pons) was associated with gadodiamide (p = 0.006) and gadopentetate dimeglumine (p < 0.001), but not with other GBCAs. R change (GP:TH) was not associated with GBCA administration. Previous administration of linear agents gadoiamide and gadopentetate dimeglumine is associated with increased T1 signal intensity in the DN, whereas macrocyclic GBCAs do not show an association. • Certain linear GBCAs are associated with T1 signal change in the dentate nucleus. • The signal change is related to the administration number of certain linear GBCAs. • Difference in signal change may reflect differences in stability of agents.

Spatio-temporal Hotelling observer for signal detection from image sequences

PubMed Central

Caucci, Luca; Barrett, Harrison H.; Rodríguez, Jeffrey J.

2010-01-01

Detection of signals in noisy images is necessary in many applications, including astronomy and medical imaging. The optimal linear observer for performing a detection task, called the Hotelling observer in the medical literature, can be regarded as a generalization of the familiar prewhitening matched filter. Performance on the detection task is limited by randomness in the image data, which stems from randomness in the object, randomness in the imaging system, and randomness in the detector outputs due to photon and readout noise, and the Hotelling observer accounts for all of these effects in an optimal way. If multiple temporal frames of images are acquired, the resulting data set is a spatio-temporal random process, and the Hotelling observer becomes a spatio-temporal linear operator. This paper discusses the theory of the spatio-temporal Hotelling observer and estimation of the required spatio-temporal covariance matrices. It also presents a parallel implementation of the observer on a cluster of Sony PLAYSTATION 3 gaming consoles. As an example, we consider the use of the spatio-temporal Hotelling observer for exoplanet detection. PMID:19550494

Spatio-temporal Hotelling observer for signal detection from image sequences.

PubMed

Caucci, Luca; Barrett, Harrison H; Rodriguez, Jeffrey J

2009-06-22

Detection of signals in noisy images is necessary in many applications, including astronomy and medical imaging. The optimal linear observer for performing a detection task, called the Hotelling observer in the medical literature, can be regarded as a generalization of the familiar prewhitening matched filter. Performance on the detection task is limited by randomness in the image data, which stems from randomness in the object, randomness in the imaging system, and randomness in the detector outputs due to photon and readout noise, and the Hotelling observer accounts for all of these effects in an optimal way. If multiple temporal frames of images are acquired, the resulting data set is a spatio-temporal random process, and the Hotelling observer becomes a spatio-temporal linear operator. This paper discusses the theory of the spatio-temporal Hotelling observer and estimation of the required spatio-temporal covariance matrices. It also presents a parallel implementation of the observer on a cluster of Sony PLAYSTATION 3 gaming consoles. As an example, we consider the use of the spatio-temporal Hotelling observer for exoplanet detection.

Efficient nonlinear equalizer for intra-channel nonlinearity compensation for next generation agile and dynamically reconfigurable optical networks.

PubMed

Malekiha, Mahdi; Tselniker, Igor; Plant, David V

2016-02-22

In this work, we propose and experimentally demonstrate a novel low-complexity technique for fiber nonlinearity compensation. We achieved a transmission distance of 2818 km for a 32-GBaud dual-polarization 16QAM signal. For efficient implantation, and to facilitate integration with conventional digital signal processing (DSP) approaches, we independently compensate fiber nonlinearities after linear impairment equalization. Therefore this algorithm can be easily implemented in currently deployed transmission systems after using linear DSP. The proposed equalizer operates at one sample per symbol and requires only one computation step. The structure of the algorithm is based on a first-order perturbation model with quantized perturbation coefficients. Also, it does not require any prior calculation or detailed knowledge of the transmission system. We identified common symmetries between perturbation coefficients to avoid duplicate and unnecessary operations. In addition, we use only a few adaptive filter coefficients by grouping multiple nonlinear terms and dedicating only one adaptive nonlinear filter coefficient to each group. Finally, the complexity of the proposed algorithm is lower than previously studied nonlinear equalizers by more than one order of magnitude.

Study of current-mode active pixel sensor circuits using amorphous InSnZnO thin-film transistor for 50-μm pixel-pitch indirect X-ray imagers

NASA Astrophysics Data System (ADS)

Cheng, Mao-Hsun; Zhao, Chumin; Kanicki, Jerzy

2017-05-01

Current-mode active pixel sensor (C-APS) circuits based on amorphous indium-tin-zinc-oxide thin-film transistors (a-ITZO TFTs) are proposed for indirect X-ray imagers. The proposed C-APS circuits include a combination of a hydrogenated amorphous silicon (a-Si:H) p+-i-n+ photodiode (PD) and a-ITZO TFTs. Source-output (SO) and drain-output (DO) C-APS are investigated and compared. Acceptable signal linearity and high gains are realized for SO C-APS. APS circuit characteristics including voltage gain, charge gain, signal linearity, charge-to-current conversion gain, electron-to-voltage conversion gain are evaluated. The impact of the a-ITZO TFT threshold voltage shifts on C-APS is also considered. A layout for a pixel pitch of 50 μm and an associated fabrication process are suggested. Data line loadings for 4k-resolution X-ray imagers are computed and their impact on circuit performances is taken into consideration. Noise analysis is performed, showing a total input-referred noise of 239 e-.

Supralinear and Supramodal Integration of Visual and Tactile Signals in Rats: Psychophysics and Neuronal Mechanisms.

PubMed

Nikbakht, Nader; Tafreshiha, Azadeh; Zoccolan, Davide; Diamond, Mathew E

2018-02-07

To better understand how object recognition can be triggered independently of the sensory channel through which information is acquired, we devised a task in which rats judged the orientation of a raised, black and white grating. They learned to recognize two categories of orientation: 0° ± 45° ("horizontal") and 90° ± 45° ("vertical"). Each trial required a visual (V), a tactile (T), or a visual-tactile (VT) discrimination; VT performance was better than that predicted by optimal linear combination of V and T signals, indicating synergy between sensory channels. We examined posterior parietal cortex (PPC) and uncovered key neuronal correlates of the behavioral findings: PPC carried both graded information about object orientation and categorical information about the rat's upcoming choice; single neurons exhibited identical responses under the three modality conditions. Finally, a linear classifier of neuronal population firing replicated the behavioral findings. Taken together, these findings suggest that PPC is involved in the supramodal processing of shape. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Ultrafast photon counting applied to resonant scanning STED microscopy.

PubMed

Wu, Xundong; Toro, Ligia; Stefani, Enrico; Wu, Yong

2015-01-01

To take full advantage of fast resonant scanning in super-resolution stimulated emission depletion (STED) microscopy, we have developed an ultrafast photon counting system based on a multigiga sample per second analogue-to-digital conversion chip that delivers an unprecedented 450 MHz pixel clock (2.2 ns pixel dwell time in each scan). The system achieves a large field of view (∼50 × 50 μm) with fast scanning that reduces photobleaching, and advances the time-gated continuous wave STED technology to the usage of resonant scanning with hardware-based time-gating. The assembled system provides superb signal-to-noise ratio and highly linear quantification of light that result in superior image quality. Also, the system design allows great flexibility in processing photon signals to further improve the dynamic range. In conclusion, we have constructed a frontier photon counting image acquisition system with ultrafast readout rate, excellent counting linearity, and with the capacity of realizing resonant-scanning continuous wave STED microscopy with online time-gated detection. © 2014 The Authors Journal of Microscopy © 2014 Royal Microscopical Society.

Synthesis and analysis of discriminators under influence of broadband non-Gaussian noise

NASA Astrophysics Data System (ADS)

Artyushenko, V. M.; Volovach, V. I.

2018-01-01

We considered the problems of the synthesis and analysis of discriminators, when the useful signal is exposed to non-Gaussian additive broadband noise. It is shown that in this case, the discriminator of the tracking meter should contain the nonlinear transformation unit, the characteristics of which are determined by the Fisher information relative to the probability density function of the mixture of non-Gaussian broadband noise and mismatch errors. The parameters of the discriminatory and phase characteristics of the discriminators working under the above conditions are obtained. It is shown that the efficiency of non-linear processing depends on the ratio of power of FM noise to the power of Gaussian noise. The analysis of the information loss of signal transformation caused by the linear section of discriminatory characteristics of the unit of nonlinear transformations of the discriminator is carried out. It is shown that the average slope of the nonlinear transformation characteristic is determined by the Fisher information relative to the probability density function of the mixture of non-Gaussian noise and mismatch errors.

Quaternion-valued echo state networks.

PubMed

Xia, Yili; Jahanchahi, Cyrus; Mandic, Danilo P

2015-04-01

Quaternion-valued echo state networks (QESNs) are introduced to cater for 3-D and 4-D processes, such as those observed in the context of renewable energy (3-D wind modeling) and human centered computing (3-D inertial body sensors). The introduction of QESNs is made possible by the recent emergence of quaternion nonlinear activation functions with local analytic properties, required by nonlinear gradient descent training algorithms. To make QENSs second-order optimal for the generality of quaternion signals (both circular and noncircular), we employ augmented quaternion statistics to introduce widely linear QESNs. To that end, the standard widely linear model is modified so as to suit the properties of dynamical reservoir, typically realized by recurrent neural networks. This allows for a full exploitation of second-order information in the data, contained both in the covariance and pseudocovariances, and a rigorous account of second-order noncircularity (improperness), and the corresponding power mismatch and coupling between the data components. Simulations in the prediction setting on both benchmark circular and noncircular signals and on noncircular real-world 3-D body motion data support the analysis.

Real-time prediction of hand trajectory by ensembles of cortical neurons in primates

NASA Astrophysics Data System (ADS)

Wessberg, Johan; Stambaugh, Christopher R.; Kralik, Jerald D.; Beck, Pamela D.; Laubach, Mark; Chapin, John K.; Kim, Jung; Biggs, S. James; Srinivasan, Mandayam A.; Nicolelis, Miguel A. L.

2000-11-01

Signals derived from the rat motor cortex can be used for controlling one-dimensional movements of a robot arm. It remains unknown, however, whether real-time processing of cortical signals can be employed to reproduce, in a robotic device, the kind of complex arm movements used by primates to reach objects in space. Here we recorded the simultaneous activity of large populations of neurons, distributed in the premotor, primary motor and posterior parietal cortical areas, as non-human primates performed two distinct motor tasks. Accurate real-time predictions of one- and three-dimensional arm movement trajectories were obtained by applying both linear and nonlinear algorithms to cortical neuronal ensemble activity recorded from each animal. In addition, cortically derived signals were successfully used for real-time control of robotic devices, both locally and through the Internet. These results suggest that long-term control of complex prosthetic robot arm movements can be achieved by simple real-time transformations of neuronal population signals derived from multiple cortical areas in primates.

Active elimination of radio frequency interference for improved signal-to-noise ratio for in-situ NMR experiments in strong magnetic field gradients

NASA Astrophysics Data System (ADS)

Ibrahim, M.; Pardi, C. I.; Brown, T. W. C.; McDonald, P. J.

2018-02-01

Improvement in the signal-to-noise ratio of Nuclear Magnetic Resonance (NMR) systems may be achieved either by increasing the signal amplitude or by decreasing the noise. The noise has multiple origins - not all of which are strictly "noise": incoherent thermal noise originating in the probe and pre-amplifiers, probe ring down or acoustic noise and coherent externally broadcast radio frequency transmissions. The last cannot always be shielded in open access experiments. In this paper, we show that pulsed, low radio-frequency data communications are a significant source of broadcast interference. We explore two signal processing methods of de-noising short T2∗ NMR experiments corrupted by these communications: Linear Predictive Coding (LPC) and the Discrete Wavelet Transform (DWT). Results are shown for numerical simulations and experiments conducted under controlled conditions with pseudo radio frequency interference. We show that both the LPC and DWT methods have merit.

Noiseless amplification of weak coherent fields exploiting energy fluctuations of the field

NASA Astrophysics Data System (ADS)

Partanen, Mikko; Häyrynen, Teppo; Oksanen, Jani; Tulkki, Jukka

2012-12-01

Quantum optics dictates that amplification of a pure state by any linear deterministic amplifier always introduces noise in the signal and results in a mixed output state. However, it has recently been shown that noiseless amplification becomes possible if the requirement of a deterministic operation is relaxed. Here we propose and analyze a noiseless amplification scheme where the energy required to amplify the signal originates from the stochastic fluctuations in the field itself. In contrast to previous amplification setups, our setup shows that a signal can be amplified even if no energy is added to the signal from external sources. We investigate the relation between the amplification and its success rate as well as the statistics of the output states after successful and failed amplification processes. Furthermore, we also optimize the setup to find the maximum success rates in terms of the reflectivities of the beam splitters used in the setup and discuss the relation of our setup with the previous setups.

A triaxial accelerometer-based physical-activity recognition via augmented-signal features and a hierarchical recognizer.

PubMed

Khan, Adil Mehmood; Lee, Young-Koo; Lee, Sungyoung Y; Kim, Tae-Seong

2010-09-01

Physical-activity recognition via wearable sensors can provide valuable information regarding an individual's degree of functional ability and lifestyle. In this paper, we present an accelerometer sensor-based approach for human-activity recognition. Our proposed recognition method uses a hierarchical scheme. At the lower level, the state to which an activity belongs, i.e., static, transition, or dynamic, is recognized by means of statistical signal features and artificial-neural nets (ANNs). The upper level recognition uses the autoregressive (AR) modeling of the acceleration signals, thus, incorporating the derived AR-coefficients along with the signal-magnitude area and tilt angle to form an augmented-feature vector. The resulting feature vector is further processed by the linear-discriminant analysis and ANNs to recognize a particular human activity. Our proposed activity-recognition method recognizes three states and 15 activities with an average accuracy of 97.9% using only a single triaxial accelerometer attached to the subject's chest.

Radar modulation classification using time-frequency representation and nonlinear regression

NASA Astrophysics Data System (ADS)

De Luigi, Christophe; Arques, Pierre-Yves; Lopez, Jean-Marc; Moreau, Eric

1999-09-01

In naval electronic environment, pulses emitted by radars are collected by ESM receivers. For most of them the intrapulse signal is modulated by a particular law. To help the classical identification process, a classification and estimation of this modulation law is applied on the intrapulse signal measurements. To estimate with a good accuracy the time-varying frequency of a signal corrupted by an additive noise, one method has been chosen. This method consists on the Wigner distribution calculation, the instantaneous frequency is then estimated by the peak location of the distribution. Bias and variance of the estimator are performed by computed simulations. In a estimated sequence of frequencies, we assume the presence of false and good estimated ones, the hypothesis of Gaussian distribution is made on the errors. A robust non linear regression method, based on the Levenberg-Marquardt algorithm, is thus applied on these estimated frequencies using a Maximum Likelihood Estimator. The performances of the method are tested by using varied modulation laws and different signal to noise ratios.

Solar cycle signal in air temperature in North America - Amplitude, gradient, phase and distribution

NASA Technical Reports Server (NTRS)

Currie, R. G.

1981-01-01

The considered investigation was motivated by three factors. One is related to an extension of single-channel MESA to multi-channel by Strand (1977), Morf et al. (1978), and Jones (1978). MESA is a high-resolution signal processing and spectrum analysis technique due to Burg (1975). The considered developments resulted in the discovery of the 11-year solar cycle signal in the change of the length of day by Currie (1980, 1981). They also led Currie (1981) to study the phase spectrum of the 11-year term in height H of sea level. The investigation tries to clarify the phase relations among the involved parameters. The second factor is connected with an application of the linear time domain technique used by Currie (1981) to temperature records to obtain more accurate information regarding the signal amplitude. The third factor of motivation is related to increases in the number of stations available for an analysis, the greater average length of the records, and the more accurate data set.

Ultrasensitive electrochemical sensing platform based on graphene wrapping SnO2 nanocorals and autonomous cascade DNA duplication strategy.

PubMed

Chen, Ying-Xu; Huang, Ke-Jing; Lin, Feng; Fang, Lin-Xia

2017-12-01

In this work, a sensitive, universal and reusable electrochemical biosensor based on stannic oxide nanocorals-graphene hybrids (SnO 2 NCs-Gr) is developed for target DNA detection by using two kinds of DNA enzymes for signal amplification through an autonomous cascade DNA duplication strategy. A hairpin probe is designed composing of a projecting part at the 3'-end as identification sequence for target, a recognition site for nicking endonuclease, and an 18-carbon shim to stop polymerization process. The designed DNA duplication-incision-replacement process is handled by KF polymerase and endonuclease, then combining with gold nanoparticles as signal carrier for further signal amplification. In the detection system, the electrochemical-chemical-chemical procedure, which uses ferrocene methanol, tris(2-carboxyethyl)phosphine and l-ascorbic acid 2-phosphate as oxidoreduction neurogen, deoxidizer and zymolyte, separately, is applied to amplify detection signal. Benefiting from the multiple signal amplification mechanism, the proposed sensor reveals a good linear connection between the peak current and logarithm of analyte concentration in range of 0.0001-1 × 10 -11 molL -1 with a detection limit of 1.25 × 10 -17 molL -1 (S/N=3). This assay also opens one promising strategy for ultrasensitive determination of other biological molecules for bioanalysis and biomedicine diagnostics. Copyright © 2017 Elsevier B.V. All rights reserved.

A new linear least squares method for T1 estimation from SPGR signals with multiple TRs

NASA Astrophysics Data System (ADS)

Chang, Lin-Ching; Koay, Cheng Guan; Basser, Peter J.; Pierpaoli, Carlo

2009-02-01

The longitudinal relaxation time, T1, can be estimated from two or more spoiled gradient recalled echo x (SPGR) images with two or more flip angles and one or more repetition times (TRs). The function relating signal intensity and the parameters are nonlinear; T1 maps can be computed from SPGR signals using nonlinear least squares regression. A widely-used linear method transforms the nonlinear model by assuming a fixed TR in SPGR images. This constraint is not desirable since multiple TRs are a clinically practical way to reduce the total acquisition time, to satisfy the required resolution, and/or to combine SPGR data acquired at different times. A new linear least squares method is proposed using the first order Taylor expansion. Monte Carlo simulations of SPGR experiments are used to evaluate the accuracy and precision of the estimated T1 from the proposed linear and the nonlinear methods. We show that the new linear least squares method provides T1 estimates comparable in both precision and accuracy to those from the nonlinear method, allowing multiple TRs and reducing computation time significantly.

Velocity interferometer signal de-noising using modified Wiener filter

NASA Astrophysics Data System (ADS)

Rav, Amit; Joshi, K. D.; Roy, Kallol; Kaushik, T. C.

2017-05-01

The accuracy and precision of the non-contact velocity interferometer system for any reflector (VISAR) depends not only on the good optical design and linear optical-to- electrical conversion system, but also on accurate and robust post-processing techniques. The performance of these techniques, such as the phase unwrapping algorithm, depends on the signal-to-noise ratio (SNR) of the recorded signal. In the present work, a novel method of improving the SNR of the recorded VISAR signal, based on the knowledge of the noise characteristic of the signal conversion and recording system, is presented. The proposed method uses a modified Wiener filter, for which the signal power spectrum estimation is obtained using a spectral subtraction method (SSM), and the noise power spectrum estimation is obtained by taking the average of the recorded signal during the period when no target movement is expected. Since the noise power spectrum estimate is dynamic in nature, and obtained for each experimental record individually, the improved signal quality is high. The proposed method is applied to the simulated standard signals, and is not only found to be better than the SSM, but is also less sensitive to the selection of the noise floor during signal power spectrum estimation. Finally, the proposed method is applied to the recorded experimental signal and an improvement in the SNR is reported.

Studies of superresolution range-Doppler imaging

NASA Astrophysics Data System (ADS)

Zhu, Zhaoda; Ye, Zhenru; Wu, Xiaoqing; Yin, Jun; She, Zhishun

1993-02-01

This paper presents three superresolution imaging methods, including the linear prediction data extrapolation DFT (LPDEDFT), the dynamic optimization linear least squares (DOLLS), and the Hopfield neural network nonlinear least squares (HNNNLS). Live data of a metalized scale model B-52 aircraft, mounted on a rotating platform in a microwave anechoic chamber, have in this way been processed, as has a flying Boeing-727 aircraft. The imaging results indicate that, compared to the conventional Fourier method, either higher resolution for the same effective bandwidth of transmitted signals and total rotation angle in imaging, or equal-quality images from smaller bandwidth and total rotation, angle may be obtained by these superresolution approaches. Moreover, these methods are compared in respect of their resolution capability and computational complexity.

High-SNR spectrum measurement based on Hadamard encoding and sparse reconstruction

NASA Astrophysics Data System (ADS)

Wang, Zhaoxin; Yue, Jiang; Han, Jing; Li, Long; Jin, Yong; Gao, Yuan; Li, Baoming

2017-12-01

The denoising capabilities of the H-matrix and cyclic S-matrix based on the sparse reconstruction, employed in the Pixel of Focal Plane Coded Visible Spectrometer for spectrum measurement are investigated, where the spectrum is sparse in a known basis. In the measurement process, the digital micromirror device plays an important role, which implements the Hadamard coding. In contrast with Hadamard transform spectrometry, based on the shift invariability, this spectrometer may have the advantage of a high efficiency. Simulations and experiments show that the nonlinear solution with a sparse reconstruction has a better signal-to-noise ratio than the linear solution and the H-matrix outperforms the cyclic S-matrix whether the reconstruction method is nonlinear or linear.

Radar wideband digital beamforming based on time delay and phase compensation

NASA Astrophysics Data System (ADS)

Fu, Wei; Jiang, Defu

2018-07-01

In conventional phased array radars, analogue time delay devices and phase shifters have been used for wideband beamforming. These methods suffer from insertion losses, gain mismatches and delay variations, and they occupy a large chip area. To solve these problems, a compact architecture of digital array antennas based on subarrays was considered. In this study, the receiving beam patterns of wideband linear frequency modulation (LFM) signals were constructed by applying analogue stretch processing via mixing with delayed reference signals at the subarray level. Subsequently, narrowband digital time delaying and phase compensation of the tone signals were implemented with reduced arithmetic complexity. Due to the differences in amplitudes, phases and time delays between channels, severe performance degradation of the beam patterns occurred without corrections. To achieve good beamforming performance, array calibration was performed in each channel to adjust the amplitude, frequency and phase of the tone signal. Using a field-programmable gate array, wideband LFM signals and finite impulse response filters with continuously adjustable time delays were implemented in a polyphase structure. Simulations and experiments verified the feasibility and effectiveness of the proposed digital beamformer.

Linear and nonlinear transparencies in binocular vision.

PubMed Central

Langley, K; Fleet, D J; Hibbard, P B

1998-01-01

When the product of a vertical square-wave grating (contrast envelope) and a horizontal sinusoidal grating (carrier) are viewed binocularly with different disparity cues they can be perceived transparently at different depths. We found, however, that the transparency was asymmetric; it only occurred when the envelope was perceived to be the overlaying surface. When the same two signals were added, the percept of transparency was symmetrical; either signal could be seen in front of or behind the other at different depths. Differences between these multiplicative and additive signal combinations were examined in two experiments. In one, we measured disparity thresholds for transparency as a function of the spatial frequency of the envelope. In the other, we measured disparity discrimination thresholds. In both experiments the thresholds for the multiplicative condition, unlike the additive condition, showed distinct minima at low envelope frequencies. The different sensitivity curves found for multiplicative and additive signal combinations suggest that different processes mediated the disparity signal. The data are consistent with a two-channel model of binocular matching, with multiple depth cues represented at single retinal locations. PMID:9802240

A boost of confidence: The role of the ventromedial prefrontal cortex in memory, decision-making, and schemas.

PubMed

Hebscher, Melissa; Gilboa, Asaf

2016-09-01

The ventromedial prefrontal cortex (vmPFC) has been implicated in a wide array of functions across multiple domains. In this review, we focus on the vmPFC's involvement in mediating strategic aspects of memory retrieval, memory-related schema functions, and decision-making. We suggest that vmPFC generates a confidence signal that informs decisions and memory-guided behaviour. Confidence is central to these seemingly diverse functions: (1) Strategic retrieval: lesions to the vmPFC impair an early, automatic, and intuitive monitoring process ("feeling of rightness"; FOR) often associated with confabulation (spontaneous reporting of erroneous memories). Critically, confabulators typically demonstrate high levels of confidence in their false memories, suggesting that faulty monitoring following vmPFC damage may lead to indiscriminate confidence signals. (2) Memory schemas: the vmPFC is critically involved in instantiating and maintaining contextually relevant schemas, broadly defined as higher level knowledge structures that encapsulate lower level representational elements. The correspondence between memory retrieval cues and these activated schemas leads to FOR monitoring. Stronger, more elaborate schemas produce stronger FOR and influence confidence in the veracity of memory candidates. (3) Finally, we review evidence on the vmPFC's role in decision-making, extending this role to decision-making during memory retrieval. During non-mnemonic and mnemonic decision-making the vmPFC automatically encodes confidence. Confidence signal in the vmPFC is revealed as a non-linear relationship between a first-order monitoring assessment and second-order action or choice. Attempting to integrate the multiple functions of the vmPFC, we propose a posterior-anterior organizational principle for this region. More posterior vmPFC regions are involved in earlier, automatic, subjective, and contextually sensitive functions, while more anterior regions are involved in controlled actions based on these earlier functions. Confidence signals reflect the non-linear relationship between first-order, posterior-mediated and second-order, anterior-mediated processes and are represented along the entire axis. Copyright © 2016 Elsevier Ltd. All rights reserved.

The research on visual industrial robot which adopts fuzzy PID control algorithm

NASA Astrophysics Data System (ADS)

Feng, Yifei; Lu, Guoping; Yue, Lulin; Jiang, Weifeng; Zhang, Ye

2017-03-01

The control system of six degrees of freedom visual industrial robot based on the control mode of multi-axis motion control cards and PC was researched. For the variable, non-linear characteristics of industrial robot`s servo system, adaptive fuzzy PID controller was adopted. It achieved better control effort. In the vision system, a CCD camera was used to acquire signals and send them to video processing card. After processing, PC controls the six joints` motion by motion control cards. By experiment, manipulator can operate with machine tool and vision system to realize the function of grasp, process and verify. It has influence on the manufacturing of the industrial robot.

Single-Event Transient Testing of Low Dropout PNP Series Linear Voltage Regulators

NASA Technical Reports Server (NTRS)

Adell, Philippe; Allen, Gregory

2013-01-01

As demand for high-speed, on-board, digital-processing integrated circuits on spacecraft increases (field-programmable gate arrays and digital signal processors in particular), the need for the next generation point-of-load (POL) regulator becomes a prominent design issue. Shrinking process nodes have resulted in core rails dropping to values close to 1.0 V, drastically reducing margin to standard switching converters or regulators that power digital ICs. The goal of this task is to perform SET characterization of several commercial POL converters, and provide a discussion of the impact of these results to state-of-the-art digital processing IC through laser and heavy ion testing

Classification of electroencephalograph signals using time-frequency decomposition and linear discriminant analysis

NASA Astrophysics Data System (ADS)

Szuflitowska, B.; Orlowski, P.

2017-08-01

Automated detection system consists of two key steps: extraction of features from EEG signals and classification for detection of pathology activity. The EEG sequences were analyzed using Short-Time Fourier Transform and the classification was performed using Linear Discriminant Analysis. The accuracy of the technique was tested on three sets of EEG signals: epilepsy, healthy and Alzheimer's Disease. The classification error below 10% has been considered a success. The higher accuracy are obtained for new data of unknown classes than testing data. The methodology can be helpful in differentiation epilepsy seizure and disturbances in the EEG signal in Alzheimer's Disease.

Wavelet transform analysis of transient signals: the seismogram and the electrocardiogram

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

Anant, K.S.

1997-06-01

In this dissertation I quantitatively demonstrate how the wavelet transform can be an effective mathematical tool for the analysis of transient signals. The two key signal processing applications of the wavelet transform, namely feature identification and representation (i.e., compression), are shown by solving important problems involving the seismogram and the electrocardiogram. The seismic feature identification problem involved locating in time the P and S phase arrivals. Locating these arrivals accurately (particularly the S phase) has been a constant issue in seismic signal processing. In Chapter 3, I show that the wavelet transform can be used to locate both the Pmore » as well as the S phase using only information from single station three-component seismograms. This is accomplished by using the basis function (wave-let) of the wavelet transform as a matching filter and by processing information across scales of the wavelet domain decomposition. The `pick` time results are quite promising as compared to analyst picks. The representation application involved the compression of the electrocardiogram which is a recording of the electrical activity of the heart. Compression of the electrocardiogram is an important problem in biomedical signal processing due to transmission and storage limitations. In Chapter 4, I develop an electrocardiogram compression method that applies vector quantization to the wavelet transform coefficients. The best compression results were obtained by using orthogonal wavelets, due to their ability to represent a signal efficiently. Throughout this thesis the importance of choosing wavelets based on the problem at hand is stressed. In Chapter 5, I introduce a wavelet design method that uses linear prediction in order to design wavelets that are geared to the signal or feature being analyzed. The use of these designed wavelets in a test feature identification application led to positive results. The methods developed in this thesis; the feature identification methods of Chapter 3, the compression methods of Chapter 4, as well as the wavelet design methods of Chapter 5, are general enough to be easily applied to other transient signals.« less

AnyWave: a cross-platform and modular software for visualizing and processing electrophysiological signals.

PubMed

Colombet, B; Woodman, M; Badier, J M; Bénar, C G

2015-03-15

The importance of digital signal processing in clinical neurophysiology is growing steadily, involving clinical researchers and methodologists. There is a need for crossing the gap between these communities by providing efficient delivery of newly designed algorithms to end users. We have developed such a tool which both visualizes and processes data and, additionally, acts as a software development platform. AnyWave was designed to run on all common operating systems. It provides access to a variety of data formats and it employs high fidelity visualization techniques. It also allows using external tools as plug-ins, which can be developed in languages including C++, MATLAB and Python. In the current version, plug-ins allow computation of connectivity graphs (non-linear correlation h2) and time-frequency representation (Morlet wavelets). The software is freely available under the LGPL3 license. AnyWave is designed as an open, highly extensible solution, with an architecture that permits rapid delivery of new techniques to end users. We have developed AnyWave software as an efficient neurophysiological data visualizer able to integrate state of the art techniques. AnyWave offers an interface well suited to the needs of clinical research and an architecture designed for integrating new tools. We expect this software to strengthen the collaboration between clinical neurophysiologists and researchers in biomedical engineering and signal processing. Copyright © 2015 Elsevier B.V. All rights reserved.

Nonuniform sampling and non-Fourier signal processing methods in multidimensional NMR

PubMed Central

Mobli, Mehdi; Hoch, Jeffrey C.

2017-01-01

Beginning with the introduction of Fourier Transform NMR by Ernst and Anderson in 1966, time domain measurement of the impulse response (the free induction decay, FID) consisted of sampling the signal at a series of discrete intervals. For compatibility with the discrete Fourier transform (DFT), the intervals are kept uniform, and the Nyquist theorem dictates the largest value of the interval sufficient to avoid aliasing. With the proposal by Jeener of parametric sampling along an indirect time dimension, extension to multidimensional experiments employed the same sampling techniques used in one dimension, similarly subject to the Nyquist condition and suitable for processing via the discrete Fourier transform. The challenges of obtaining high-resolution spectral estimates from short data records using the DFT were already well understood, however. Despite techniques such as linear prediction extrapolation, the achievable resolution in the indirect dimensions is limited by practical constraints on measuring time. The advent of non-Fourier methods of spectrum analysis capable of processing nonuniformly sampled data has led to an explosion in the development of novel sampling strategies that avoid the limits on resolution and measurement time imposed by uniform sampling. The first part of this review discusses the many approaches to data sampling in multidimensional NMR, the second part highlights commonly used methods for signal processing of such data, and the review concludes with a discussion of other approaches to speeding up data acquisition in NMR. PMID:25456315

Optimal feedback control successfully explains changes in neural modulations during experiments with brain-machine interfaces.

PubMed

Benyamini, Miri; Zacksenhouse, Miriam

2015-01-01

Recent experiments with brain-machine-interfaces (BMIs) indicate that the extent of neural modulations increased abruptly upon starting to operate the interface, and especially after the monkey stopped moving its hand. In contrast, neural modulations that are correlated with the kinematics of the movement remained relatively unchanged. Here we demonstrate that similar changes are produced by simulated neurons that encode the relevant signals generated by an optimal feedback controller during simulated BMI experiments. The optimal feedback controller relies on state estimation that integrates both visual and proprioceptive feedback with prior estimations from an internal model. The processing required for optimal state estimation and control were conducted in the state-space, and neural recording was simulated by modeling two populations of neurons that encode either only the estimated state or also the control signal. Spike counts were generated as realizations of doubly stochastic Poisson processes with linear tuning curves. The model successfully reconstructs the main features of the kinematics and neural activity during regular reaching movements. Most importantly, the activity of the simulated neurons successfully reproduces the observed changes in neural modulations upon switching to brain control. Further theoretical analysis and simulations indicate that increasing the process noise during normal reaching movement results in similar changes in neural modulations. Thus, we conclude that the observed changes in neural modulations during BMI experiments can be attributed to increasing process noise associated with the imperfect BMI filter, and, more directly, to the resulting increase in the variance of the encoded signals associated with state estimation and the required control signal.