Sample records for signal processing correlation

  1. Multichannel heterodyning for wideband interferometry, correlation and signal processing

    DOEpatents

    Erskine, D.J.

    1999-08-24

    A method is disclosed of signal processing a high bandwidth signal by coherently subdividing it into many narrow bandwidth channels which are individually processed at lower frequencies in a parallel manner. Autocorrelation and correlations can be performed using reference frequencies which may drift slowly with time, reducing cost of device. Coordinated adjustment of channel phases alters temporal and spectral behavior of net signal process more precisely than a channel used individually. This is a method of implementing precision long coherent delays, interferometers, and filters for high bandwidth optical or microwave signals using low bandwidth electronics. High bandwidth signals can be recorded, mathematically manipulated, and synthesized. 50 figs.

  2. Multichannel heterodyning for wideband interferometry, correlation and signal processing

    DOEpatents

    Erskine, David J. (Oakland, CA)

    1999-01-01

    A method of signal processing a high bandwidth signal by coherently subdividing it into many narrow bandwidth channels which are individually processed at lower frequencies in a parallel manner. Autocorrelation and correlations can be performed using reference frequencies which may drift slowly with time, reducing cost of device. Coordinated adjustment of channel phases alters temporal and spectral behavior of net signal process more precisely than a channel used individually. This is a method of implementing precision long coherent delays, interferometers, and filters for high bandwidth optical or microwave signals using low bandwidth electronics. High bandwidth signals can be recorded, mathematically manipulated, and synthesized.

  3. Neural correlates of the automatic processing of threat facial signals.

    PubMed

    Anderson, Adam K; Christoff, Kalina; Panitz, David; De Rosa, Eve; Gabrieli, John D E

    2003-07-01

    The present study examined whether automaticity, defined here as independence from attentional modulation, is a fundamental principle of the neural systems specialized for processing social signals of environmental threat. Attention was focused on either scenes or faces presented in a single overlapping display. Facial expressions were neutral, fearful, or disgusted. Amygdala responses to facial expressions of fear, a signifier of potential physical attack, were not reduced with reduced attention to faces. In contrast, anterior insular responses to facial expressions of disgust, a signifier of potential physical contamination, were reduced with reduced attention. However, reduced attention enhanced the amygdala response to disgust expressions; this enhanced amygdala response to disgust correlated with the magnitude of attentional reduction in the anterior insular response to disgust. These results suggest that automaticity is not fundamental to the processing of all facial signals of threat, but is unique to amygdala processing of fear. Furthermore, amygdala processing of fear was not entirely automatic, coming at the expense of specificity of response. Amygdala processing is thus specific to fear only during attended processing, when cortical processing is undiminished, and more broadly tuned to threat during unattended processing, when cortical processing is diminished. PMID:12843265

  4. Task effects on BOLD signal correlates of implicit syntactic processing

    PubMed Central

    Caplan, David

    2010-01-01

    BOLD signal was measured in sixteen participants who made timed font change detection judgments in visually presented sentences that varied in syntactic structure and the order of animate and inanimate nouns. Behavioral data indicated that sentences were processed to the level of syntactic structure. BOLD signal increased in visual association areas bilaterally and left supramarginal gyrus in the contrast of sentences with object- and subject-extracted relative clauses without font changes in which the animacy order of the nouns biased against the syntactically determined meaning of the sentence. This result differs from the findings in a non-word detection task (Caplan et al, 2008a), in which the same contrast led to increased BOLD signal in the left inferior frontal gyrus. The difference in areas of activation indicates that the sentences were processed differently in the two tasks. These differences were further explored in an eye tracking study using the materials in the two tasks. Issues pertaining to how parsing and interpretive operations are affected by a task that is being performed, and how this might affect BOLD signal correlates of syntactic contrasts, are discussed. PMID:20671983

  5. Model-Based Signal Processing: Correlation Detection With Synthetic Seismograms

    NASA Astrophysics Data System (ADS)

    Rodgers, A.; Harris, D.; Pasyanos, M.; Blair, S.; Matt, R.

    2006-12-01

    Recent applications of correlation methods to seismological problems illustrate the power of coherent signal processing applied to seismic waveforms. Examples of these applications include detection of low amplitude signals buried in ambient noise and cross-correlation of sets of waveforms to form event clusters and accurately measure delay times for event relocation and/or earth structure. These methods rely on the exploitation of the similarity of individual waveforms and have been successfully applied to large sets of empirical observations. However, in cases with little or no empirical event data, such as aseismic regions or exotic event types, correlation methods with observed seismograms will not be possible due to the lack of previously observed similar waveforms. This study uses model-based signals computed for three-dimensional (3D) Earth models to form the basis for correlation detection. Synthetic seismograms are computed for fully 3D models estimated from the Markov Chain Monte-Carlo (MCMC) method. MCMC uses stochastic sampling to fit multiple seismological data sets. Rather than estimate a single "optimal" model, MCMC results in a suite of models that sample the model space and incorporates uncertainty through variability of the models. The variability reflects our ignorance of Earth structure, due to limited resolution, data and modeling errors, and produces variability in the seismic waveform response. Model-based signals are combined using a subspace method where the synthetic signals are decomposed into an orthogonal basis by singular-value decomposition (SVD) and the observed waveforms are represented with a linear combination of a sub-set of eigenvectors (signals) associated with the most significant eigenvalues. We have demonstrated the method by modeling long-period (80-10 seconds) regional seismograms for a moderate (M~5) earthquake near the China-North Korea border. Synthetic seismograms are computed with the Spectral Element Method for a suite of long-wavelength (2 degree) seismic velocity models based on the MCMC method. We are working on higher resolution (1 degree) models for the same region and methods to increase the frequency content of the synthetic seismograms using both 1D reflectivity synthetics and 3D synthetics with a recently developed elastic finite difference code.

  6. Task effects on BOLD signal correlates of implicit syntactic processing

    Microsoft Academic Search

    David Caplan

    2010-01-01

    BOLD signal was measured in 16 participants who made timed font change detection judgments in visually presented sentences that varied in syntactic structure and the order of animate and inanimate nouns. Behavioural data indicated that sentences were processed to the level of syntactic structure. BOLD signal increased in visual association areas bilaterally and left supramarginal gyrus in the contrast of

  7. Queueing up for enzymatic processing: correlated signaling through coupled degradation

    E-print Network

    , we use queueing theory to investigate how `waiting lines' can lead to correlations between protein unanticipated burden on important cellular workhorses. This can lead to the development of `waiting lines a unifying model for describing how `waiting lines' for processing by a common enzyme (the `servers') can

  8. Queueing up for enzymatic processing: correlated signaling through coupled degradation.

    PubMed

    Cookson, Natalie A; Mather, William H; Danino, Tal; Mondragón-Palomino, Octavio; Williams, Ruth J; Tsimring, Lev S; Hasty, Jeff

    2011-01-01

    High-throughput technologies have led to the generation of complex wiring diagrams as a post-sequencing paradigm for depicting the interactions between vast and diverse cellular species. While these diagrams are useful for analyzing biological systems on a large scale, a detailed understanding of the molecular mechanisms that underlie the observed network connections is critical for the further development of systems and synthetic biology. Here, we use queueing theory to investigate how 'waiting lines' can lead to correlations between protein 'customers' that are coupled solely through a downstream set of enzymatic 'servers'. Using the E. coli ClpXP degradation machine as a model processing system, we observe significant cross-talk between two networks that are indirectly coupled through a common set of processors. We further illustrate the implications of enzymatic queueing using a synthetic biology application, in which two independent synthetic networks demonstrate synchronized behavior when common ClpXP machinery is overburdened. Our results demonstrate that such post-translational processes can lead to dynamic connections in cellular networks and may provide a mechanistic understanding of existing but currently inexplicable links. PMID:22186735

  9. An improvement in SAR image interpretability provided by post-correlation signal processing

    NASA Technical Reports Server (NTRS)

    Matthews, N. D.; Kaupp, V. H.; Waite, W. P.; Macdonald, H. C.

    1983-01-01

    A presentation on the basis of subjective analysis of computer-generated SAR imagery depicts the improvement in interpretability obtained by post-correlation signal processing. A parametric study was conducted to determine the improvement in interpretability obtained by the application of signal weighting functions on the post-processed returns. The results suggest that a marked improvement in interpretability results from symmetrizing the exponential distribution of the fading signal. Preliminary analysis indicates that signal weighting improves the contrast ratio between the mean value of adjacent homogeneous regions in a SAR scene.

  10. Digital Signal Processing Using Stream High Performance Computing: A 512-Input Broadband Correlator for Radio Astronomy

    NASA Astrophysics Data System (ADS)

    Kocz, J.; Greenhill, L. J.; Barsdell, B. R.; Price, D.; Bernardi, G.; Bourke, S.; Clark, M. A.; Craig, J.; Dexter, M.; Dowell, J.; Eftekhari, T.; Ellingson, S.; Hallinan, G.; Hartman, J.; Jameson, A.; MacMahon, D.; Taylor, G.; Schinzel, F.; Werthimer, D.

    2015-03-01

    A "large-N" correlator that makes use of Field Programmable Gate Arrays and Graphics Processing Units has been deployed as the digital signal processing system for the Long Wavelength Array station at Owens Valley Radio Observatory (LWA-OV), to enable the Large Aperture Experiment to Detect the Dark Ages (LEDA). The system samples a ˜ 100 MHz baseband and processes signals from 512 antennas (256 dual polarization) over a ˜ 58 MHz instantaneous sub-band, achieving 16.8 Tops s-1 and 0.236 Tbit s-1 throughput in a 9 kW envelope and single rack footprint. The output data rate is 260 MB s-1 for 9-s time averaging of cross-power and 1 s averaging of total power data. At deployment, the LWA-OV correlator was the largest in production in terms of N and is the third largest in terms of complex multiply accumulations, after the Very Large Array and Atacama Large Millimeter Array. The correlator's comparatively fast development time and low cost establish a practical foundation for the scalability of a modular, heterogeneous, computing architecture.

  11. A signal processing method based on a homotopic correlation product applied to speech recognition problems

    NASA Astrophysics Data System (ADS)

    Bianchi, F.; Pocci, P.; Prina-Ricotti, L.

    1981-02-01

    The assumptions used to formulate the processing method, the proposed algorithm, and phoneme recognition test results of a homotopic signal processing method are presented. The hearing system is considered as a box with one imput, that applies a signal whose information content = 500 Kbit/sec, and many thousand outputs, the nerve fibers, having a transmission rate variable between 30 and 400 bit/sec. The signal transmitted by any one fiber is a series of equal impulse. Homotopic representation of a phoneme is available in steady state after 2 to 3 msec. The phoneme patterns are very different, although patterns for the same phoneme from different speakers are similar. Transition patterns between phonemes change rapidly. Recognition rate, using a minicomputer, of all possible combinations of 'a', 'e', 'r' and 'm' is 95.2%.

  12. Correlation method for processing speckles of signals from single-fibre multimode interferometers by using charge-coupled devices

    SciTech Connect

    Kulchin, Yurii N [Presidium of Far East Branch, Russian Academy of Sciences, Vladivostok (Russian Federation); Vitrik, O B; Lantsov, A D [Chair of Physics, Far-Eastern State Technical University, Vladivostok (Russian Federation)

    2006-04-30

    The correlation method for processing signals from a single-fibre multimode interferometer by using a digital charge-coupled device is studied experimentally and theoretically. Optimal conditions are determined for recording multimode interference patterns with charge-coupled devices. It is found that the nonlinearity of characteristics of such devices affects the results of correlation measurements. The method for eliminating this influence is proposed. The correlation method considered in the paper allows one to measure a linear deformation of the interferometer within 0-80 {mu}m with an accuracy of {approx}{+-}3 {mu}m for typical multi-mode fibres with the core diameter 50 {mu}m. (optical fibres and waveguides)

  13. A Wreath Product Group Approach to Signal and Image Processing: Part II | Convolution, Correlation, and Applications

    E-print Network

    Foote, Richard M.

    is multiplicity-free|as is the case with the WPC groups|this matrix multiplication reduces to the multiplication the spectrum of a discrete signal when the underlying group is a WPC group. Recalling that the WPC groups here

  14. Signal from noise: Insights into volcanic system processes from ambient noise correlations

    NASA Astrophysics Data System (ADS)

    Hanson-Hedgecock, Sara

    This first section of dissertation concerns the imaging of the crust and upper most mantle structure of the mid-Miocene volcanic provinces of the Northwestern United States using ambient noise tomography. Chapter 1 introduces the complex tectonic history of the northwestern United States and describes the development of volcanism from the ignimbrite sweep that occurred with the extension of the Basin and Range province, initiation and evolution of the mid-Miocene volcanism of the Steens/Columbia River flood basalts, and mirror-image volcanic tracks of the High Lava Plains, Oregon and Yellowstone-Snake River Plains. Chapter 2 describes in detail the concepts and methods for determining the 3D shear velocity structure in the crust and uppermost mantle from ambient noise correlations. Chapter 3 contains the text and supplementary materials of Hanson-Hedgecock et al. [2012] published in the Geophysical Research Letters that describes the application of the ambient noise methods to the imaging of the Western United States. The second section of this work discusses the results of measuring velocity changes associated with three episodes of increased eruptive activity at Tungurahua in 2010 using ambient noise correlations. The third section of this work discusses the results of using the H/V ratio to measure the level of equipartition of the ambient noise wavefield at Tungurahua in 2010.

  15. Digital Signal Processing

    NSDL National Science Digital Library

    Digital signal processing is a technique that uses digital methods to process signals. Processing a signal means manipulating it to improve it, change it, or alter it as required for some application. Some examples of processes are filtering, modulation and demodulation, mixing, spectrum analysis, compression and decompression, and many others. In the past, most of these processes have been accomplished with analog techniques and circuits. Today, that has changed. While analog processing has not disappeared, it is slowly being replaced by digital processing in most applications. DSP is now used in almost all electronic equipment and knowledge of its operation is critical to an overall knowledge and understanding of electronics. In digital processing, the analog signal to be processed is first converted to digital then processing is done by a computer. The computer output is then converted back to analog. This module describes this process and outlines the most common applications.

  16. Geophysical signal processing

    SciTech Connect

    Robinson, E.A.; Durrani, T.S.

    1986-01-01

    Draws together a number of areas of knowledge to give unified coverage of the subject: the geophysical applications of digital signal processing. The presentation has a strong applications orientation. The coverage connects and unifies several fields, namely wave propagation, digital signal processing, spectral analysis, and computer methods. The book covers many topics in depth.

  17. Analog signal correlator design and operation

    SciTech Connect

    Green, J.B.; Bhushan, M. (Massachusetts Inst. of Tech., Lexington, MA (United States). Lincoln Lab.)

    1991-03-01

    This paper reports on a superconductive tapped delay line, circuits comprising SIS mixers, an L-C integrator and a tunnel junction comparator, and superconductive digital address encoders integrated into a 14-channel analog signal correlator. This 25 {times} 38 mm circuit was fabricated using a Nb/Nb{sub 2}O{sub 5}/Pb tunnel junction process. Preliminary testing of this device indicates the ability to process long duration, wideband waveforms with time-bandwidth products equal to 6000.

  18. From Signal Information Processing

    E-print Network

    information processing systems Encoder a0 X(a0) a1 X(a1) dX (a0,a1) #12;How to choose a distance? o Calculate, but how effectively to they do so? o Systems process information, selectively suppressing irrelevant information and accentuating important information by acting on signals (information filters) o System design

  19. Aircraft Sensors Signal Processing

    Microsoft Academic Search

    J. Bajer; R. Byst?ický; R. Jalovecký; P. Jan?

    The paper deals with possibilities and methods of processing of signals from aircraft sensors. Because of a large amount of\\u000a proceeded data the subject of the paper is limited only to data processing from electrical subsystem of aircraft. Designed\\u000a data acquisition and processing avionic system is based on CANaerospace communication network. Primary function of the system\\u000a is to collect all

  20. signal processing and oral communication

    E-print Network

    Penn, Gerald

    SPOClab signal processing and oral communication Computational Linguistics, 5 December 2012 Frank University of Toronto #12;SPOClab signal processing and oral communication An introduction to SPOClab · SPOClab (Signal Processing and Oral Communication) is a new lab intersecting Computer Science

  1. Signals and Images Image processing

    E-print Network

    Lakey, Joseph D.

    Signals and Images Wavelets Image processing Models and Approximations Data driven approximations;Signals and Images Wavelets Image processing Models and Approximations Data driven approximations or transcendental: Joe Lakey Wavelets Minimize Max #12;Signals and Images Wavelets Image processing Models

  2. Array signal processing

    SciTech Connect

    Haykin, S.; Justice, J.H.; Owsley, N.L.; Yen, J.L.; Kak, A.C.

    1985-01-01

    This is the first book to be devoted completely to array signal processing, a subject that has become increasingly important in recent years. The book consists of six chapters. Chapter 1, which is introductory, reviews some basic concepts in wave propagation. The remaining five chapters deal with the theory and applications of array signal processing in (a) exploration seismology, (b) passive sonar, (c) radar, (d) radio astronomy, and (e) tomographic imaging. The various chapters of the book are self-contained. The book is written by a team of five active researchers, who are specialists in the individual fields covered by the pertinent chapters.

  3. Microsystem for signal processing applications

    NASA Astrophysics Data System (ADS)

    Frankenstein, B.; Froehlich, K.-J.; Hentschel, D.; Reppe, G.

    2005-05-01

    Acoustic monitoring of technological processes requires methods that eliminate noise as much as possible. Sensor-near signal evaluation can contribute substantially. Frequently, a further necessity exists to integrate the measuring technique in the monitored structure. The solution described contains components for analog preprocessing of acoustic signals, their digitization, algorithms for data reduction, and digital communication. The core component is a digital signal processor (DSP). Digital signal processors perform the algorithms necessary for filtering, down sampling, FFT computation and correlation of spectral components particularly effective. A compact, sensor-near signal processing structure was realized. It meets the Match-X standard, which as specified by the German Association for Mechanical and Plant Engineering (VDMA) for development of micro-technical modules, which can be combined to applicaiton specific systems. The solution is based on AL2O3 ceramic components including different signal processing modules as ADC, as well as memory and power supply. An arbitrary waveform generator has been developed and combined with a power amplifier for piezoelectric transducers in a special module. A further module interfaces to these transducers. It contains a multi-channel preamplifier, some high-pass filters for analog signal processing and an ADC-driver. A Bluetooth communication chip for wireless data transmission and a DiscOnChip module are under construction. As a first application, the combustion behavior of safety-relevant contacts is monitored. A special waveform up to 5MHz is produced and sent to the monitored object. The resulting signal form is evaluated with special algorithms, which extract significant parameters of the signal, and transmitted via CAN-bus.

  4. Approximate Signal Processing

    Microsoft Academic Search

    S. Hamid Nawab; Alan V. Oppenheim; Anantha P. Chandrakasan; Joseph M. Winograd; Jeffrey T. Ludwig

    1997-01-01

    It is increasingly important to structure signal processing algorithms and systems to allow fortrading off between the accuracy of results and the utilization of resources in their implementation.In any particular context, there are typically a variety of heuristic approaches to managingthese tradeoffs. One of the objectives of this paper is to suggest that there is the potential fordeveloping a more

  5. OPTIMAL CORRELATION ESTIMATORS FOR QUANTIZED SIGNALS

    SciTech Connect

    Johnson, M. D.; Chou, H. H.; Gwinn, C. R., E-mail: michaeltdh@physics.ucsb.edu, E-mail: cgwinn@physics.ucsb.edu [Department of Physics, University of California, Santa Barbara, CA 93106 (United States)

    2013-03-10

    Using a maximum-likelihood criterion, we derive optimal correlation strategies for signals with and without digitization. We assume that the signals are drawn from zero-mean Gaussian distributions, as is expected in radio-astronomical applications, and we present correlation estimators both with and without a priori knowledge of the signal variances. We demonstrate that traditional estimators of correlation, which rely on averaging products, exhibit large and paradoxical noise when the correlation is strong. However, we also show that these estimators are fully optimal in the limit of vanishing correlation. We calculate the bias and noise in each of these estimators and discuss their suitability for implementation in modern digital correlators.

  6. signal processing and oral communication

    E-print Network

    Penn, Gerald

    SPOClab signal processing and oral communication #12;SPOClab signal processing and oral communication Introduction 2 #12;SPOClab signal processing and oral communication Hey everybody! My name's James Institute of Health) #12;SPOClab signal processing and oral communication · Types of dysarthria are related

  7. Introduction to Communication, Control, and Signal Processing

    NSDL National Science Digital Library

    Oppenheim, Alan

    This course explores ideas involving signals, systems and probabilistic models in the context of communication, control and signal processing applications. The material expands out from the basics in 6.003 and 6.041. The treatment involves aspects of analysis, synthesis, and optimization. Topics covered include:-random processes-correlations-spectral densities-state-space modeling-multirate processing-signal estimation-detection

  8. Adaptive Signal Processing Testbed

    NASA Astrophysics Data System (ADS)

    Parliament, Hugh A.

    1991-09-01

    The design and implementation of a system for the acquisition, processing, and analysis of signal data is described. The initial application for the system is the development and analysis of algorithms for excision of interfering tones from direct sequence spread spectrum communication systems. The system is called the Adaptive Signal Processing Testbed (ASPT) and is an integrated hardware and software system built around the TMS320C30 chip. The hardware consists of a radio frequency data source, digital receiver, and an adaptive signal processor implemented on a Sun workstation. The software components of the ASPT consists of a number of packages including the Sun driver package; UNIX programs that support software development on the TMS320C30 boards; UNIX programs that provide the control, user interaction, and display capabilities for the data acquisition, processing, and analysis components of the ASPT; and programs that perform the ASPT functions including data acquisition, despreading, and adaptive filtering. The performance of the ASPT system is evaluated by comparing actual data rates against their desired values. A number of system limitations are identified and recommendations are made for improvements.

  9. Applications of digital signal processing

    Microsoft Academic Search

    Alan V. Oppenheim

    1978-01-01

    Applications of digital signal processing in telecommunications are considered, taking into account the characteristics of telecommunications systems, aspects of digital transmission, digital switching, digital signal processing in pulse-code modulated transmission terminals, digital signal processing in frequency-division multiplex transmission terminals, the detection of signaling tones, aliased harmonic distortion as a nonlinear phenomenon, echo control, design considerations for digital signal-processing hardware elements,

  10. IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 53, NO. 9, SEPTEMBER 2005 3503 Conditional Correlation as a Measure of Mediated

    E-print Network

    Daunizeau, Jean

    of brain activity, such as functional magnetic resonance imaging (fMRI), electroencephalography (EEG of brain activity [6], [7]. On the other hand, the signals obtained in MEG/EEG are more closely related as a Measure of Mediated Interactivity in fMRI and MEG/EEG Guillaume Marrelec, Jean Daunizeau, Mélanie

  11. signal processing and oral communication

    E-print Network

    Penn, Gerald

    SPOClab signal processing and oral communication #12;SPOClab signal processing and oral Institute of Health) #12;SPOClab signal processing and oral communication · Types of dysarthria are related and oral communication Dysarthria 5 (After Darley et al., 1969) Ataxic Flaccid Hypo- kinetic Hyper- kinetic

  12. Signal Processing:Fourier Signal Processing:Fourier

    E-print Network

    Rimon, Elon

    at frequency location. The spectrum of the periodic signal is discrete: only elements with discrete frequencies nwo (n = 1,3,.....) exist. P 3P 5P 4 1 1 1 f 4/3 4/5 #12;Signal Processing:Fourier The spectrum (Integral) Transform · Tool for aperiodic (transient) signals. · We start from a periodic signal, where we

  13. Optimum combining of residual carrier array signals in correlated noises

    NASA Technical Reports Server (NTRS)

    Liang, R.; Suen, P. H.; Tan, H. H.

    1996-01-01

    An array feed combining system for the recovery of signal-to-noise ratio (SNR) loss due to antenna reflector deformation has been implemented and is currently being evaluated on the Jet Propulsion Laboratory 34-m DSS-13 antenna. The current signal-combining system operates under the assumption that the white Gaussian noise processes in the received signals from different array elements are mutually uncorrelated. However, experimental data at DSS 13 indicate that these noise processes are indeed mutually correlated. The objective of this work is to develop a signal-combining system optimized to account for the mutual correlations between these noise processes. The set of optimum combining weight coefficients that maximizes the combined signal SNR in the correlated noises environment is determined. These optimum weights depend on unknown signal and noise covariance parameters. A maximum-likelihood approach is developed to estimate these unknown parameters to obtain estimates of the optimum weight coefficients based on residual carrier signal samples. The actual combined signal SNR using the estimated weight coefficients is derived and shown to converge to the maximum achievable SNR as the number of signal samples increases. These results are also verified by simulation. A numerical example shows a significant improvement in SNR performance can be obtained, especially when the amount of correlation increases.

  14. Optimum Combining of Residual Carrier Array Signals in Correlated Noises

    NASA Technical Reports Server (NTRS)

    Tan, H. H.; Liang, R.; Suen, P.-H.

    1996-01-01

    An array feed combining system for the recovery of signal-to-noise ratio (SNR) loss due to antenna reflector deformation has been implemented and is currently being evaluated on the Jet Propulsion Laboratory 34-m DSS-13 antenna. The current signal-combining system operates under the assumption that the white Gaussian noise processes in the received signals from different array elements are mutually uncorrelated. However, experimental data at DSS 13 indicate that these noise processes are indeed mutually correlated. The objective of this work is to develop a signal-combining system optimized to account for the mutual correlations between these noise processes. The set of optimum combining weight coefficients that maximizes the combined signal SNR in the correlated noises environment is determined. These optimum weights depend on unknown signal and noise covariance parameters. A maximum-likelihood approach is developed to estimate these unknown parameters to obtain estimates of the optimum weight coefficients based on residual carrier signal samples. The actual combined signal SNR using the estimated weight coefficients is derived and shown to converge to the maximum achievable SNR as the number of signal samples increases. These results are also verified by simulation. A numerical example shows a significant improvement in SNR performance can be obtained, especially when the amount of correlation increases.

  15. A signal processing cell architecture

    Microsoft Academic Search

    M. M. JAMALI; M. M. HUSSAIN; G. A. JULLIEN

    1987-01-01

    A data flow general purpose digital signal processor has been previously developed [1] for real time applications of digital signal processing. The Data Flow Signal Processor (DFSP) is attached to a host computer, and is based on a binary tree structure. It employs two types of cells: processing and arithmetic cells, and utilizes residue number system [2] for arithmetic operations.

  16. Fiber optic signal processing of ultrawideband signals

    NASA Astrophysics Data System (ADS)

    Mathis, Ronald F.; Floyd, William L.; Pappert, Stephen A.; Orazi, Richard J.

    1998-11-01

    Two L-band phase-matched fiber optic delay line channels and a broadband fiber optic RF signal processing filter have been designed, fabricated, tested, and evaluated. These two related RF photonic system development efforts are potentially useful in ELINT signal processing of ultrawideband signal. Specifically, two high performance optical delay lines operating at 1 GHz with a 500 MHz bandwidth have been prototype and show prototyped and show improved dynamic range and environmental phase tracking performance over conventional SAW delay lines. In addition, an eight-tap fiber optic transversal filter using wavelet amplitude weighting has been designed, fabricated, and tested in the 50 MHz to 20 GHz frequency range. A high pass wavelet filter useful for ultrawideband signal detection has been optically implemented, and test result presented for sensitivity and dynamic range are promising.

  17. Long range correlation in earthquake precursory signals

    NASA Astrophysics Data System (ADS)

    Chaudhuri, H.; Barman, C.; Iyengar, A. N. S.; Ghose, D.; Sen, P.; Sinha, B.

    2013-07-01

    Research on earthquake prediction has drawn serious attention of the geophysicist, geologist and investigators in different fields of science across the globe for many decades. Researchers around the world are actively working on recording pre-earthquake changes in non-seismic parameters through a variety of methods that include anomalous changes in geochemical parameters of the Earth's crust, geophysical properties of the lithosphere as well as ionosphere etc. Several works also have been done in India to detect earthquake precursor signals using geochemical and geophysical methods. However, very few works have been done so far in India in this field through the application of nonlinear techniques to the recorded geophysical and geochemical precursory signals for earthquakes. The present paper deals with a short review of the early works on geochemical precursors that have been carried out in India as yet. With a view to detect earthquake precursory signals by means of gas-geochemical method we developed a network of seismo-geochemical monitoring observatories in India in hot springs and mud volcano crater. In the last few years we detected several geochemical anomalies and those were observed prior to some major earthquakes that occurred within a radius of 1500 km from the test sites. In the present paper we have applied nonlinear techniques to the long term, real-time and natural data sets of radon-222 and associated gamma originated out of the terrestrial degassing process of the earth. The results reveal a clear signature of the long range correlation present in the geochemical time series. This approach appears to be a potential tool to explore intrinsic information hidden within the earthquake precursory signals.

  18. Signal processing computational needs

    NASA Astrophysics Data System (ADS)

    Speiser, Jeffrey M.

    1987-11-01

    Previous reviews of signal processing computational needs and their systolic implementation have emphasized the need for a small set of matrix operations, primarily matrix multiplication, orthogonal triangularization, triangular backsolve, singular value decomposition, and the generalized singular value decomposition. Algorithms and architectures for these tasks are sufficiently well understood to begin transitioning from search to exploratory development. Substantial progress has also been reported on parallel algorithms for updating symmetric eigensystems and the singular value decomposition. Another problem which has proved to be easier than expected is inner product computation for high-speed high resolution predictive analog-to-digital conversion. Although inner product computation in a general setting will require O(log n) time via a tree, the special structure of the prediction permits the use of a systolic transversal filter, producing a new predicted value in time O(1). Problem areas which are still in an early stage of study include parallel algorithms for the Wigner-Ville Distribution function, L1 norm approximation, inequality constrained least squares, and the total least squares problem.

  19. Signal Processing Computational Needs

    NASA Astrophysics Data System (ADS)

    Speiser, Jeffrey M.

    1986-04-01

    Previous reviews of signal processing computational needs and their systolic implementation have emphasized the need for a small set of matrix operations, primarily matrix multiplication, orthogonal triangularization, triangular backsolve, singular value decomposition, and the generalized singular value decomposition. Algorithms and architectures for these tasks are sufficiently well understood to begin transitioning from research to exploratory development. Substantial progress has also been reported on parallel algorithms for updating symmetric eigensystems and the singular value decomposition. Another problem which has proved to be easier than expected is inner product computation for high-speed high resolution predictive analog-to-digital conversion. Although inner product computation in a general setting will require 0(log n) time via a tree, the special structure of the prediction problem permits the use of a systolic transversal filter, producing a new predicted value in time 0(1). Problem areas which are still in an early stage of study include parallel algorithms for the Wigner-Ville Distribution function, L1 norm approximation, inequality constrained least squares, and the total least squares problem.

  20. Nanotubes for noisy signal processing

    NASA Astrophysics Data System (ADS)

    Lee, Ian Yenyin

    Nanotubes can process noisy signals. We present two central results in support of this general thesis and make an informed extrapolation that uses nanotubes to improve body armor. The first result is that noise can help nanotubes detect weak signals. The finding confirmed a stochastic-resonance theoretical prediction that noise can enhance detection at the nano-level. Laboratory experiments with nanotubes showed that three types of noise improved three measures of detection. Small amounts of Gaussian, uniform, and Cauchy additive white noise increased mutual-information, cross-correlation, and bit-error-rate measures before degrading them with further increases in noise. Nanotubes can apply this noise-enhancement and nanotube electrical and mechanical properties to improve signal processing. Similar noise enhancement may benefit a proposed nanotube-array cochlear-model spectral processing. The second result is that nanotube antennas can directly detect narrowband electromagnetic (EM) signals. The finding showed that nanotube and thin-wire dipoles are similar: They are resonant and narrowband and can implement linear-array designs if the EM waves in the nanotubes propagate at or near the free-space velocity of light. The nanotube-antenna prediction is based on a Fresnel-zone or near-zone analysis of antenna impedance using a quantum-conductor model. The analysis also predicts a failure to resonate if the nanotube EM-wave propagation is much slower than free-space light propagation. We extrapolate based on applied and theoretical analysis of body armor. Field experiments used a baseball comparison and statistical and other techniques to model body-armor bruising effects. A baseball comparison showed that a large caliber handgun bullet can hit an armored chest as hard as a fast baseball can hit a bare chest. Adaptive fuzzy systems learned to predict a bruise profile directly from the experimental data and also from statistical analysis of the data. Nanotube signal processing should help disguise armor by adapting camouflage to match changing backgrounds while nanotube additives should strengthen armor materials.

  1. Call for Papers IEEE Signal Processing Society

    E-print Network

    Wichmann, Felix

    , and mobile/social/Internet/interactive media. In addition, application-oriented experiments and processing humans are the final consumers of almost all processed audio and visual signals, it is beneficial to use the inherent correlation and interaction of different media (whether naturally captured or computer

  2. Teminology in digital signal processing

    Microsoft Academic Search

    L. Rabiner; J. Cooley; H. Helms; L. Jackson; J. Kaiser; C. Rader; R. Schafer; K. Steiglitz; C. Weinstein

    1972-01-01

    The committee on Digital Signal Processing of the IEEE Group on Audio and Electroacoustics has undertaken the project of recommending terminology for use in papers and texts on digital signal processing. The reasons for this project are twofold. First, the meanings of many terms that are commonly used differ from one author to another. Second, there are many terms that

  3. Signal processing devices and networks

    NASA Astrophysics Data System (ADS)

    Graveline, S. W.

    1985-02-01

    According to an axiom employed with respect to electronic warfare (EW) behavior, system effectiveness increases directly with the amount of information recovered from an intercepted signal. The evolution in EW signal processing capability has proceeded accordingly. After an initiation of EW systems as broadband receivers, the most significant advance was related to the development of digital instantaneous frequency measurement (DIFM) devices. The use of such devices provides significant improvements regarding signal identification and RF measurement to within a few MHz. An even more accurate processing device, the digital RF memory (DRFM), allows frequency characterization to within a few Hz. This invention was made in response to the need to process coherent pulse signals. Attention is given to the generic EW system, the modern EW system, and the generic receiver function for a modern EW system showing typical output signals.

  4. Digital Signal Processing applied to Physical Signals

    E-print Network

    Alberto, Diego; Musa, L

    2011-01-01

    It is well known that many of the scientific and technological discoveries of the XXI century will depend on the capability of processing and understanding a huge quantity of data. With the advent of the digital era, a fully digital and automated treatment can be designed and performed. From data mining to data compression, from signal elaboration to noise reduction, a processing is essential to manage and enhance features of interest after every data acquisition (DAQ) session. In the near future, science will go towards interdisciplinary research. In this work there will be given an example of the application of signal processing to different fields of Physics from nuclear particle detectors to biomedical examinations. In Chapter 1 a brief description of the collaborations that allowed this thesis is given, together with a list of the publications co-produced by the author in these three years. The most important notations, definitions and acronyms used in the work are also provided. In Chapter 2, the last r...

  5. High resolution signal processing

    NASA Astrophysics Data System (ADS)

    Tufts, Donald W.

    1993-08-01

    Motivated by the goal of efficient, effective, high-speed integrated-circuit realization, we have discovered an algorithm for high speed Fourier analysis called the Arithmetic Fourier Transform (AFT). It is based on the number-theoretic method of Mobius inversion, a method that is well suited for integrated-circuit realization. The computation of the AFT can be carried out in parallel, pipelined channels, and the individual operations are very simple to execute and control. Except for a single scaling in each channel, all the operations are additions or subtractions. Thus, it can reduce the required power, volume, and cost. Also, analog switched-capacitor realizations of the AFT have been studied. We have also analyzed the performance of a broad and useful class of data adaptive signal estimation algorithms. This in turn has led to our proposed improvements in the methods. We have used perturbation analysis of the rank-reduced data matrix to calculate its statistical properties. The improvements made have been demonstrated by computer simulation as well as by comparison with the Cramer-Rao Bound.

  6. Signal processing in the context of chaotic signals

    Microsoft Academic Search

    Alan V. Oppenheim; Gregory W. Wornell; Steven H. Isabelle; Kevin M. Cuomo

    1992-01-01

    Signals generated by chaotic systems represent a potentially rich class of signals both for detecting and characterizing physical phenomena and in synthesizing new classes of signals for communications, remote sensing, and a variety of other signal processing applications. Since classical techniques for signal analysis do not exploit the particular structure of chaotic signals there is both a significant challenge and

  7. Long-time Correlations in Electromyography Signals

    NASA Astrophysics Data System (ADS)

    Zurcher, Ulrich; Maynard, Rachel

    2006-10-01

    We have previously reported that the mean-square displacement calculated from electromyography time series of low back muscles exhibit a plateau-like behavior for intermediate times [50 ,ms < t < 0.5 ,s], so that < [xt- x0]^2 > ˜t^0. This behavior is unexpected, and indicates the presence of long-time correlations in the signal. For fractal Brownian motion, the Hurst exponent calculated from the mean-square displacement and the exponent from the spectral density P ( f) ˜1/f^?, ?= 2 H + 1. For the EMG time series y^0i= xi, we have generated iterated time series, yi^n+1 = [y2 i ^n + y2i+1]/2, and have calculated the corresponding time correlation functions, C^n ( t) = < xi+ t^n xi^n>/<(xi^n)^2 >. We find that the correlation functions converge to a simple limit, C(0) = 1, C(1) = -0.5 and C(n) =0 for n >=2. This limit is consistent with the plateau behavior of the mean- square displacement. We discuss the connection between the behavior of the iterated correlation functions and the properties of the spectrum.

  8. Signal Processing in Cognitive Radio

    Microsoft Academic Search

    Jun Ma; Geoffrey Ye Li; Biing Hwang Juang

    2009-01-01

    Cognitive radio allows for usage of licensed frequency bands by unlicensed users. However, these unlicensed (cognitive) users need to monitor the spectrum continuously to avoid possible interference with the licensed (primary) users. Apart from this, cognitive radio is expected to learn from its surroundings and perform functions that best serve its users. Such an adaptive technology naturally presents unique signal-processing

  9. Signal processor for processing ultrasonic receiver signals

    DOEpatents

    Fasching, George E. (Morgantown, WV)

    1980-01-01

    A signal processor is provided which uses an analog integrating circuit in conjunction with a set of digital counters controlled by a precision clock for sampling timing to provide an improved presentation of an ultrasonic transmitter/receiver signal. The signal is sampled relative to the transmitter trigger signal timing at precise times, the selected number of samples are integrated and the integrated samples are transferred and held for recording on a strip chart recorder or converted to digital form for storage. By integrating multiple samples taken at precisely the same time with respect to the trigger for the ultrasonic transmitter, random noise, which is contained in the ultrasonic receiver signal, is reduced relative to the desired useful signal.

  10. Acoustic signal processing toolbox for array processing

    NASA Astrophysics Data System (ADS)

    Pham, Tien; Whipps, Gene T.

    2003-08-01

    The US Army Research Laboratory (ARL) has developed an acoustic signal processing toolbox (ASPT) for acoustic sensor array processing. The intent of this document is to describe the toolbox and its uses. The ASPT is a GUI-based software that is developed and runs under MATLAB. The current version, ASPT 3.0, requires MATLAB 6.0 and above. ASPT contains a variety of narrowband (NB) and incoherent and coherent wideband (WB) direction-of-arrival (DOA) estimation and beamforming algorithms that have been researched and developed at ARL. Currently, ASPT contains 16 DOA and beamforming algorithms. It contains several different NB and WB versions of the MVDR, MUSIC and ESPRIT algorithms. In addition, there are a variety of pre-processing, simulation and analysis tools available in the toolbox. The user can perform simulation or real data analysis for all algorithms with user-defined signal model parameters and array geometries.

  11. EEG Correlates of Self-Referential Processing

    PubMed Central

    Knyazev, Gennady G.

    2013-01-01

    Self-referential processing has been principally investigated using functional magnetic resonance imaging (fMRI). However, understanding of the brain functioning is not possible without careful comparison of the evidence coming from different methodological domains. This paper aims to review electroencephalographic (EEG) studies of self-referential processing and to evaluate how they correspond, complement, or contradict the existing fMRI evidence. There are potentially two approaches to the study of EEG correlates of self-referential processing. Firstly, because simultaneous registration of EEG and fMRI has become possible, the degree of overlap between these two signals in brain regions related to self-referential processing could be determined. Second and more direct approach would be the study of EEG correlates of self-referential processing per se. In this review, I discuss studies, which employed both these approaches and show that in line with fMRI evidence, EEG correlates of self-referential processing are most frequently found in brain regions overlapping with the default network, particularly in the medial prefrontal cortex. In the time domain, the discrimination of self- and others-related information is mostly associated with the P300 ERP component, but sometimes is observed even earlier. In the frequency domain, different frequency oscillations have been shown to contribute to self-referential processing, with spontaneous self-referential mentation being mostly associated with the alpha frequency band. PMID:23761757

  12. PCL-Signal-Processing for Sidelobe Reduction in Case of Periodical Illuminator Signals

    Microsoft Academic Search

    M. Glende

    2006-01-01

    Passive coherent location (PCL-) systems deal with illuminators of opportunity, whose signals are usually not adapted to radar applications. Especially in the case of signal inherent periodicities the target echoes are often covered by sidelobes of clutter. In order to reduce high correlation sidelobes and enable highly accurate range measurements, a signal adaptive filter processing is introduced. Its mathematical description

  13. All-optical implementation of signal processing functions

    NASA Astrophysics Data System (ADS)

    Mohajerin-Ariaei, A.; Ziyadi, M.; Chitgarha, M. R.; Willner, Alan E.

    2015-01-01

    Optical nonlinearities in various materials pose some of the biggest challenges and opportunities in optical communications. Many important functions can be implemented using various forms of photonic nonlinear-interactions. Bit rate tunable all-optical noise mitigation of QPSK data signal and optical channel deaggregtion of QPSK signals are recent applications of nonlinear optical signal processing. In addition, optical tapped-delay-line (TDL) as a key building block in digital signal processing is discussed. Utilizing TDL, optical Nyquist generation of 32-Gbaud QPSK signals, and one/two dimensional optical correlation of 20-Gbaud QPSK signals are performed.

  14. Signal Decomposition for Nonstationary Processes

    NASA Astrophysics Data System (ADS)

    Xie, Min

    1995-01-01

    The main purpose of this dissertation is to explore and develop better signal modeling (decomposition) methods for nonstationary and/or nonlinear dynamic processes. Localization is the main focus. The characteristics of a nonstationary or nonlinear signal are decomposed onto a set of basis functions, either in the phase space spanned by time-frequency coordinates as Gabor proposed, or in the phase space spanned by a set of derivatives of different degree as defined in physics. To deal with time-varying signals, a Multiresolution Parametric Spectral Estimator (MPSE) is proposed together with its theory, techniques and applications. The resolution study provides the characteristics of windowed Fourier transforms, wavelet transforms, fixed resolution parametric spectral estimators, and the newly developed MPSE. Both the theoretical and the experimental results show that, of the above techniques, MPSE is the best in resolution. Furthermore, with proper a priori knowledge, MPSE can yield better resolution than the lower bound defined by the Heisenberg uncertainty principle. The application examples demonstrate the great potential of the MPSE method for tracking and analyzing time-varying processes. To deal with the time-varying characteristics caused by linearization of nonlinear processes, the Radial Basis Function Network (RBFN) is proposed for modeling nonlinear processes from a 'local' to a 'global' level. An equal distance sample rule is proposed for constructing the RBFN. Experiments indicate that the RBFN is a promising method for modeling deterministic chaos as well as stochastic processes, be it linear or nonlinear. The 'local' to 'global' approach of the RBFN also provides great potential for structure adaptation and knowledge accumulation.

  15. Modeling correlation of quantized noise and periodic signals

    Microsoft Academic Search

    André B. J. Kokkeler; André W. Gunst

    2004-01-01

    A model for determining the cross-correlation function of partially correlated noise is presented. In this model a strong interferer is included and represented by a periodic signal common to both channels of the correlator. A general expression for the correlation function is deduced and verified. The power spectrum of a calculated correlation function is compared with a simulation. The results

  16. Photonic Signal Processing of High-Speed Signals Using Fiber Gratings

    NASA Astrophysics Data System (ADS)

    Minasian, Robert A.

    2000-04-01

    Methods for wideband photonic signal processing using fiber delay lines and Bragg grating sampling elements are described. These processors provide new capabilities for the realization of high time-bandwidth operation and high resolution performance. Multiple wavelength techniques with discrete and chirped Bragg gratings are described, which have high capacity signal processing functions using dense parallel signal processing techniques. Both fixed and tunable or reconfigurable processors using wavelength control to change the sampling time are discussed. A range of grating-based signal processors, including high Q microwave filtering, frequency discriminators, widely tunable filters, fast and adaptive signal correlators, and true-time delay beamforming in phased array antennas are described.

  17. Nuclear sensor signal processing circuit

    DOEpatents

    Kallenbach, Gene A. (Bosque Farms, NM); Noda, Frank T. (Albuquerque, NM); Mitchell, Dean J. (Tijeras, NM); Etzkin, Joshua L. (Albuquerque, NM)

    2007-02-20

    An apparatus and method are disclosed for a compact and temperature-insensitive nuclear sensor that can be calibrated with a non-hazardous radioactive sample. The nuclear sensor includes a gamma ray sensor that generates tail pulses from radioactive samples. An analog conditioning circuit conditions the tail-pulse signals from the gamma ray sensor, and a tail-pulse simulator circuit generates a plurality of simulated tail-pulse signals. A computer system processes the tail pulses from the gamma ray sensor and the simulated tail pulses from the tail-pulse simulator circuit. The nuclear sensor is calibrated under the control of the computer. The offset is adjusted using the simulated tail pulses. Since the offset is set to zero or near zero, the sensor gain can be adjusted with a non-hazardous radioactive source such as, for example, naturally occurring radiation and potassium chloride.

  18. Neural correlates of conflict processing.

    PubMed

    West, Robert; Jakubek, Kristin; Wymbs, Nicholas; Perry, Michele; Moore, Kara

    2005-11-01

    In this study we examined the neural correlates of conflict processing in the Stroop, counting, and digit-location tasks using event-related brain potentials (ERPs). The behavioral data revealed robust interference in response time and accuracy for all tasks. The interference effect for response time was greater in the Stroop task than the other tasks; in contrast, the interference effect for response accuracy was greater in the counting tasks than the other tasks. The N450 and sustained potential (SP) were elicited in each task. Partial least-squares (PLS) analysis was used to examine the structural relationships between the ERPs, task design, and behavior. TaskPLS analysis revealed that the N450 and SP were associated with a single latent variable leading to the suggestion that a common set of neural generators was recruited during conflict processing across the tasks and that there were differences between ERPs related to early processing across the three tasks. BehavioralPLS analysis revealed that the amplitude of the SP was positively correlated with response time and accuracy, indicating that this modulation of the ERPs may be related to response selection rather than to conflict resolution. PMID:16082533

  19. Advanced detectors and signal processing

    NASA Technical Reports Server (NTRS)

    Greve, D. W.; Rasky, P. H. L.; Kryder, M. H.

    1986-01-01

    Continued progress is reported toward development of a silicon on garnet technology which would allow fabrication of advanced detection and signal processing circuits on bubble memories. The first integrated detectors and propagation patterns have been designed and incorporated on a new mask set. In addition, annealing studies on spacer layers are performed. Based on those studies, a new double layer spacer is proposed which should reduce contamination of the silicon originating in the substrate. Finally, the magnetic sensitivity of uncontaminated detectors from the last lot of wafers is measured. The measured sensitivity is lower than anticipated but still higher than present magnetoresistive detectors.

  20. Broadband Photonic Signal Processing of LIDAR Noise Waveforms

    Microsoft Academic Search

    Zachary Cole; Randy R. Reibel; Daryn E. Benson; Kristian D. Merkel; W. Randall Babbitt; K. H. Wagner

    2005-01-01

    We present a novel broadband photonic signal processor, capable of sensing and processing a wide variety of waveforms including analog optical noise, for coherent LIDAR range processing. The device relies on the spectral and spatial sensing capabilities of rare-earth ion doped crystals to perform correlative signal processing. The processed results are extracted using a highly-coherent, actively-stabilized low - power frequency-swept

  1. Subsurface conductive isolation of refraction correlative magnetic signals (SCIRCMS)

    E-print Network

    Erck, Eric Stephenson

    2004-11-15

    Isolation of terrestrially-observed magnetic signals by restoring their diffusive loss due to subsurface electrical conductivity sufficiently correlates these signals with those derived from the Alfven ionospheric electron movement of refraction...

  2. ECE 468 Digital Signal Processing 1. History

    E-print Network

    Chen, Ying "Ada"

    : transfer signals, etc. If satellites are used Audio waves electromagnetic waves wireless medium Audio wavesECE 468 Digital Signal Processing 1. History: · Digital signal processing has its roots in 17th. Sound waves digital signals broadcasted/received analogous format and filtered Telecommunications

  3. CMD-3 Liquid Xenon Calorimeter's signals processing

    E-print Network

    CMD-3 Liquid Xenon Calorimeter's signals processing for timing measurements. Leonid Epshtein Budker connected to constitute 264 «towers»; signal of each tower is processed by electronic channel. Liquid Xenon

  4. No-signaling, perfect bipartite dichotomic correlations and local randomness

    SciTech Connect

    Seevinck, M. P. [Institute for Mathematics, Astrophysics and Particle Physics, Faculty of Science and Centre for the History of Philosophy and Science, Faculty of Philosophy, Radboud University Nijmegen (Netherlands)

    2011-03-28

    The no-signaling constraint on bi-partite correlations is reviewed. It is shown that in order to obtain non-trivial Bell-type inequalities that discern no-signaling correlations from more general ones, one must go beyond considering expectation values of products of observables only. A new set of nontrivial no-signaling inequalities is derived which have a remarkably close resemblance to the CHSH inequality, yet are fundamentally different. A set of inequalities by Roy and Singh and Avis et al., which is claimed to be useful for discerning no-signaling correlations, is shown to be trivially satisfied by any correlation whatsoever. Finally, using the set of newly derived no-signaling inequalities a result with potential cryptographic consequences is proven: if different parties use identical devices, then, once they have perfect correlations at spacelike separation between dichotomic observables, they know that because of no-signaling the local marginals cannot but be completely random.

  5. Hot topics: Signal processing in acoustics

    Microsoft Academic Search

    Charles F. Gaumond

    2005-01-01

    Signal processing in acoustics is a multidisciplinary group of people that work in many areas of acoustics. We have chosen two areas that have shown exciting new applications of signal processing to acoustics or have shown exciting and important results from the use of signal processing. In this session, two hot topics are shown: the use of noiselike acoustic fields

  6. Signal Processing for Phased Array Feeds in Radio Astronomical Telescopes

    Microsoft Academic Search

    Brian D. Jeffs; Karl F. Warnick; Jonathan Landon; Jacob Waldron; David Jones; J. Richard Fisher; Roger D. Norrod

    2008-01-01

    Relative to traditional waveguide feeds, phased array feeds (PAFs) for radio telescopes can increase the instrument field of view and sky survey speed. Unique challenges associated with PAF observations, including extremely low signal levels, long-term system gain stability requirements, spatially correlated noise due to mutual coupling, and tight beamshape tolerances, require the development of new array signal processing techniques for

  7. Chaotic classification of electromyographic (EMG) signals via correlation dimension measurement

    Microsoft Academic Search

    M. Bodruzzaman; S. Devgan; S. Kari

    1992-01-01

    A set of intramuscular electromyographic signals were collected from various patient groups during ramp muscle contraction. The signals were collected using a real-time data acquisition system. The signals were tested for their chaotic behavior using spectral analysis and Poincare map techniques. MATLAB based software tools were developed to compute and plot the correlation function for each data set to determine

  8. Signal processing considerations for low signal to noise ratio laser Doppler and phase Doppler signals

    NASA Technical Reports Server (NTRS)

    Ibrahim, K. M.; Wertheimer, G. D.; Bachalo, William D.

    1991-01-01

    The relative performance of current methods used for estimating the phase and the frequency in LDV and phase Doppler applications in low signal to noise ratio conditions is analyzed. These methods include the Fourier analysis and the correlation techniques. Three methods that use the correlation function for frequency and phase estimations are evaluated in terms of accuracy and speed of processing. These methods include: (1) the frequency estimation using zero crossings counting of the auto-correlation function, (2) the Blackman-Tukey method, and (3) the AutoRegressive method (AR). The relative performance of these methods is evaluated and compared with the Fourier analysis method which provides the optimum performance in terms of the Maximum Likelihood (ML) criteria.

  9. Digital Signal Processing Based Biotelemetry Receivers

    NASA Technical Reports Server (NTRS)

    Singh, Avtar; Hines, John; Somps, Chris

    1997-01-01

    This is an attempt to develop a biotelemetry receiver using digital signal processing technology and techniques. The receiver developed in this work is based on recovering signals that have been encoded using either Pulse Position Modulation (PPM) or Pulse Code Modulation (PCM) technique. A prototype has been developed using state-of-the-art digital signal processing technology. A Printed Circuit Board (PCB) is being developed based on the technique and technology described here. This board is intended to be used in the UCSF Fetal Monitoring system developed at NASA. The board is capable of handling a variety of PPM and PCM signals encoding signals such as ECG, temperature, and pressure. A signal processing program has also been developed to analyze the received ECG signal to determine heart rate. This system provides a base for using digital signal processing in biotelemetry receivers and other similar applications.

  10. 998 IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING, VOL. 2, NO. 6, DECEMBER 2008 Canonical Correlation Analysis for Feature-Based

    E-print Network

    Adali, Tulay

    MRI), structural MRI (sMRI), and electroencephalography (EEG) are analyzed separately. However, fusing information, canonical correlation analysis, electroencephalography, independent component anal- ysis, magnetic resonance.g., functional magnetic resonance imaging (fMRI),1 structural MRI (sMRI),2 electroencephalography Manuscript

  11. Analog Signal Correlating Using an Analog-Based Signal Conditioning Front End

    NASA Technical Reports Server (NTRS)

    Prokop, Norman; Krasowski, Michael

    2013-01-01

    This innovation is capable of correlating two analog signals by using an analog-based signal conditioning front end to hard-limit the analog signals through adaptive thresholding into a binary bit stream, then performing the correlation using a Hamming "similarity" calculator function embedded in a one-bit digital correlator (OBDC). By converting the analog signal into a bit stream, the calculation of the correlation function is simplified, and less hardware resources are needed. This binary representation allows the hardware to move from a DSP where instructions are performed serially, into digital logic where calculations can be performed in parallel, greatly speeding up calculations.

  12. Self-adaptive software for signal processing

    Microsoft Academic Search

    Janos Sztipanovits; Gabor Karsai; Ted Bapty

    1998-01-01

    Digital signal processing (DSP) systems are widely used in communication, medical, sonar, radar, equipment health monitoring and many other applications. Frequently, the signal processing system has to meet real-time requirements and provide very large throughput. For example, modern automatic target recognition systems operate with a processing throughput in excess of 10 Gflop per second. In real-time vibration analysis used for

  13. Process Dissociation and Mixture Signal Detection Theory

    ERIC Educational Resources Information Center

    DeCarlo, Lawrence T.

    2008-01-01

    The process dissociation procedure was developed in an attempt to separate different processes involved in memory tasks. The procedure naturally lends itself to a formulation within a class of mixture signal detection models. The dual process model is shown to be a special case. The mixture signal detection model is applied to data from a widely…

  14. A signal oriented stream processing system for pipeline monitoring

    E-print Network

    Tokmouline, Timur

    2006-01-01

    In this thesis, we develop SignalDB, a framework for composing signal processing applications from primitive stream and signal processing operators. SignalDB allows the user to focus on the signal processing task and avoid ...

  15. Pre-earthquake signals: Underlying physical processes

    Microsoft Academic Search

    Friedemann Freund

    2011-01-01

    Prior to large earthquakes the Earth sends out transient signals, sometimes strong, more often subtle and fleeting. These signals may consist of local magnetic field variations, electromagnetic emissions over a wide range of frequencies, a variety of atmospheric and ionospheric phenomena. Great uncertainty exists as to the nature of the processes that could produce such signals, both inside the Earth’s

  16. High-speed and reconfigurable all-optical signal processing for phase and amplitude modulated signals

    NASA Astrophysics Data System (ADS)

    Khaleghi, Salman

    Technology has empowered people in all walks of life to generate, store, and communicate enormous amounts of data. Recent technological advances in high-speed backbone data networks, together with the growing trend toward bandwidth-demanding applications such as data and video sharing, cloud computing, and data collection systems, have created a need for higher capacities in signal transmission and signal processing. Optical communication systems have long benefited from the large bandwidth of optical signals (beyond tera-hertz) to transmit information. Through the use of optical signal processing techniques, this Ph.D. dissertation explores the potential of very-high-speed optics to assist electronics in processing huge amounts of data at high speeds. Optical signal processing brings together various fields of optics and signal processing---nonlinear devices and processes, analog and digital signals, and advanced data modulation formats---to achieve high-speed signal processing functions that can potentially operate at the line rate of fiber optic communications. Information can be encoded in amplitude, phase, wavelength, polarization, and spatial features of an optical wave to achieve high-capacity transmission. Many advances in the key enabling technologies have led to recent research in optical signal processing for digital signals that are encoded in one or more of these dimensions. Optical Kerr nonlinearities have femto-second response times that have been exploited for fast processing of optical signals. Various optical nonlinearities and chromatic dispersions have enabled key sub-system applications such as wavelength conversion, multicasting, multiplexing, demultiplexing, and tunable optical delays. In this Ph.D. dissertation, we employ these recent advances in the enabling technologies for high-speed optical signal processing to demonstrate various techniques that can process phase- and amplitude-encoded optical signals at the line rate of optics. We use nonlinear media, such as highly nonlinear fiber, periodically poled lithium niobate, and semiconductor optical amplifiers, for nonlinear mixing of optical signals. We propose and experimentally demonstrate a novel, fully tunable optical tapped-delay-line that is a key building block for signal processing functions. Applications such as finite impulse response filtering, equalization, correlation (pattern recognition), discrete Fourier transform, digital-to-analog conversion, and flexible optical signal conversion and generation are shown. The phase- and amplitude-preserving nature of the demonstrated techniques, together with their wide-tuning range, allows for processing of optical signals that carry different modulation formats with different data rates. The reconfigurability may apply to future optical networks that carry heterogeneous traffic with different modulation formats and baud rates.

  17. Signal Processing 86 (2006) 360374 Signal processing of acoustic signals in the time domain with

    E-print Network

    Xin, Jack

    , to develop a systematic mathematical framework for sound signal processing based on models of the ear. The biomechanics of the inner ear (cochlea) lend itself well to mathematical formulation ([2,3] among others with an active nonlinear nonlocal cochlear model M. Drew LaMara,Ã?, Jack Xinb , Yingyong Qic a Department

  18. Electronic warfare channelizer signal processing algorithms

    NASA Astrophysics Data System (ADS)

    Wood, Jerry B.; Daugherty, Gregory K.

    1995-06-01

    Passive direction finding is an integral function of EW and ELINT systems. The ability to produce direction-of-arrival information in a timely, accurate manner is strongly influenced by both the direction-finding techniques employed and the processing algorithms. The processing algorithms must detect a signal, classify it as being a signal of interest, extract the signal's parameters, including its direction of arrival, control the receiver, and interface with the system's mission computer. This paper describes a direction-finding receiver that used an optical processor to extract the direction-of-arrival information from the signal environment and the processing algorithms required to support the optical processor.

  19. Bistatic SAR: Signal Processing and Image Formation.

    SciTech Connect

    Wahl, Daniel E.; Yocky, David A.

    2014-10-01

    This report describes the significant processing steps that were used to take the raw recorded digitized signals from the bistatic synthetic aperture RADAR (SAR) hardware built for the NCNS Bistatic SAR project to a final bistatic SAR image. In general, the process steps herein are applicable to bistatic SAR signals that include the direct-path signal and the reflected signal. The steps include preprocessing steps, data extraction to for a phase history, and finally, image format. Various plots and values will be shown at most steps to illustrate the processing for a bistatic COSMO SkyMed collection gathered on June 10, 2013 on Kirtland Air Force Base, New Mexico.

  20. Signal processing in ultrasound. [for diagnostic medicine

    NASA Technical Reports Server (NTRS)

    Le Croissette, D. H.; Gammell, P. M.

    1978-01-01

    Signal is the term used to denote the characteristic in the time or frequency domain of the probing energy of the system. Processing of this signal in diagnostic ultrasound occurs as the signal travels through the ultrasonic and electrical sections of the apparatus. The paper discusses current signal processing methods, postreception processing, display devices, real-time imaging, and quantitative measurements in noninvasive cardiology. The possibility of using deconvolution in a single transducer system is examined, and some future developments using digital techniques are outlined.

  1. Moving target detection via digital time domain correlation of random noise radar signals

    Microsoft Academic Search

    James R. Lievsay; Geoffrey A. Akers

    2011-01-01

    Ultra-wideband random noise radar theoretically has a thumbtack ambiguity function, which cannot be realized due to hardware, processing, and environmental limitations. Velocity estimation using traditional Doppler processing is not practicable for ultra-wideband random noise radar because of the large fractional bandwidth. Through analysis, this paper explores moving target detection using digital correlation processing of random noise signals in the time

  2. Optical signal processing in Radar systems

    Microsoft Academic Search

    Sylvie Tonda-Goldstein; Daniel Dolfi; Aymeric Monsterleet; Stéphane Formont; Jean Chazelas; Jean-Pierre Huignard

    2006-01-01

    Opto-electronic components and their performances are well suited to be integrated in radar systems. In this paper, two optical architectures illustrate functions that are specific to optical processing of microwave signals, i.e., time-delay-based processing and arbitrary waveform generation of large frequency bandwidth signals.

  3. CPSC 526 - Group Project Motion Signal Processing

    Microsoft Academic Search

    Xianglong Chang; Kenneth Rose; Hagit Schechter

    This project is an implementation of the ideas described in Motion Signal Processing (Bruderlin and Williams 1995) in which tech- niques from the image and signal processing domains are applied to motion capture data. Our interface permits users to easily com- bine the separate techniques of motion filtering, multitarget motion interpolation with dynamic timewarping, waveshaping and motion displacement mapping.

  4. INTERACTIVE EC-BASED SIGNAL PROCESSING

    Microsoft Academic Search

    Hideyuki Takagi; Norimasa Hayashida

    We introduce new types of signal processing for which the characteristics of the signal processing filters are designed automatically by interactive evolutionary computation (IEC) based on human perception, such as hearing or vision. We first describe our existing works that use this approach, such as recovering distorted speech and hearing-aid fitting, as well as other related works in this field.

  5. VLSI Signal Processing for Wireless Communication

    Microsoft Academic Search

    Xinming Huang

    Wireless communication system is a heavy dense composition of signal processing techniques with semiconductor technologies. With the ever increasing system capacity and data rate, VLSI design and implementation method for wireless communications becomes more challenging, which urges researchers in signal processing to provide new architectures and efficient algorithms to meet low power and high performance requirements. This paper presents a

  6. Multifractal Fourier detrended cross-correlation analysis of traffic signals

    NASA Astrophysics Data System (ADS)

    Zhao, Xiaojun; Shang, Pengjian; Lin, Aijing; Chen, Gang

    2011-10-01

    Multifractal detrended cross-correlation analysis (MF-DXA) has been developed to detect the long-range power-law cross-correlation of considered signals in the presence of non-stationarity. However, crossovers arising from extrinsic periodic trends make the scaling behavior difficult to analyze. We introduce a Fourier filtering method to eliminate the trend effects and systematically investigate the multifractal cross-correlation of simulated and real traffic signals. The crossover locations are found approximately corresponding to the periods of underlying trend. Traffic velocity on one road and flows on adjacent roads show strong cross-correlation. They also present weak multifractality after periodic trends are removed. The traffic velocity and flow are cross-correlated in opposite directions which is accordant to their actual evolution.

  7. Investigating correlation of oscillatory behaviour between two signals using wavelets

    NASA Astrophysics Data System (ADS)

    Pering, Tom D.; Tamburello, Giancarlo; McGonigle, Andrew J. S.; Hanna, Edward; Aiuppa, Alessandro

    2014-05-01

    Wavelet analysis is becoming more commonplace given the augmentation of computational power over recent decades. Consequently, the use of such techniques is increasing within the geosciences, particularly when investigating the presence of any oscillatory behaviour contained within signals. As such, the ability to investigate correlation of oscillations present between two separate signals has become increasingly necessary. We have developed a technique combining the continuous wavelet transform (CWT) with Spearman's rank correlation coefficient analysis on two signals of equal length and frequency. This is performed by calculating the CWT on the two signals, extracting coefficients from the generated data at each separate scale, followed by computation of correlation between each extracted scale. The result is a clear graphical depiction of links, if any, and strength between oscillations present, with the ability to determine whether signals are in or out of phase with one another. In comparison with alternate approaches, e.g., wavelet coherence, we establish that this technique is simpler to implement and interpret, providing far clearer visual identification of inter-series relationships. We demonstrate this fact using our developed simple and easy-to-use Matlab® code which rapidly executes this procedure, producing two and three dimensional images, with the major emphasis on simplicity of the technique. Subsequently we exhibit the approach on artificially generated signals with known periodicities which are also infused with random noise. Following this the utility of our technique on a number of volcanic, geochemical and climatic signals which contain periodic behaviour is illustrated.

  8. Correlation between primary cilium and Wnt signaling pathway.

    PubMed

    Manli, Zhang; Yanping, Lu; Yali, Li

    2015-03-20

    Primary cilium is a microtubule-based organelle,which develops from the mother centriole of the centrosome. It is an antenna-like structure that anchors at the cell membrance, protruding from the cell surface. Primary cilium acts as a sensory organelle that receives different kinds of signals from the environment and transmits signals to cells to elicit cellular responses. Recent studies have revealed that primary cilium play an important role in transmitting Wnt signaling, which is critical for embryonic development. Dysfunction of primary cilium deregulates Wnt signaling, causing a series of pathological changes in different organs of the embryo, resulting in ciliopathies. In this review, we summarize correlation among primary cilium,Wnt/?-catenin signaling,Wnt/PCP signaling and ciliopathies. Current therapies in ciliopathies are also discussed. Highlights on these researches will encourage the development of Wnt-associated diagnostic tools and therapy for ciliopathies. PMID:25786997

  9. Surface Electromyography Signal Processing and Classification Techniques

    PubMed Central

    Chowdhury, Rubana H.; Reaz, Mamun B. I.; Ali, Mohd Alauddin Bin Mohd; Bakar, Ashrif A. A.; Chellappan, Kalaivani; Chang, Tae. G.

    2013-01-01

    Electromyography (EMG) signals are becoming increasingly important in many applications, including clinical/biomedical, prosthesis or rehabilitation devices, human machine interactions, and more. However, noisy EMG signals are the major hurdles to be overcome in order to achieve improved performance in the above applications. Detection, processing and classification analysis in electromyography (EMG) is very desirable because it allows a more standardized and precise evaluation of the neurophysiological, rehabitational and assistive technological findings. This paper reviews two prominent areas; first: the pre-processing method for eliminating possible artifacts via appropriate preparation at the time of recording EMG signals, and second: a brief explanation of the different methods for processing and classifying EMG signals. This study then compares the numerous methods of analyzing EMG signals, in terms of their performance. The crux of this paper is to review the most recent developments and research studies related to the issues mentioned above. PMID:24048337

  10. Blind deconvolution through digital signal processing

    Microsoft Academic Search

    T. M. Cannon; R. B. Ingebretsen

    1975-01-01

    This paper addresses the problem of deconvolving two signals when both are unknown. The authors call this problem blind deconvolution. The discussion develops two related solutions which can be applied through digital signal processing in certain practical cases. The case of reverberated and resonated sound forms the center of the development. The specific problem of restoring old acoustic recordings provides

  11. Analog signal processing first [educational course

    Microsoft Academic Search

    David C. Munson; Douglas L. Jones

    1999-01-01

    The Department of Electrical and Computer Engineering at the University of Illinois recently adopted new undergraduate curricula. The most radical change was the introduction of ECE 210, Analog Signal Processing, in place of both the sophomore-level circuit analysis course and the junior-level signals and systems course. The new course combines core material from these traditional courses, along with applications such

  12. 242 IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 58, NO. 1, JANUARY 2010 Algebraic Signal Processing Theory

    E-print Network

    Kova?evi?, Jelena

    , or, convolution, spectrum, and Fourier transform. For example, infinite discrete-time signal processing has the dis- crete-time Fourier transform (DTFT) as Fourier transform and the spectrum is periodic242 IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 58, NO. 1, JANUARY 2010 Algebraic Signal

  13. Correlation of core noise obtained by three signal coherence techniques

    NASA Technical Reports Server (NTRS)

    Vonglahn, U.; Krejsa, E. A.

    1982-01-01

    The prediction of frequency content and noise levels of turbofan engine core noise is reexamined as a result of recent test data and a new diagnostic technique. The diagnostic technique, utilizing a three-signal coherence method, is used to obtain core noise spectra for several engines. Similarities and differences of the spectra are discussed. Finally, the three-signal coherence data are correlated, leading to an improved core noise prediction procedure.

  14. Neural Correlates of Cognitive Processes LIDA Module

    E-print Network

    Memphis, University of

    Neural Correlates of Cognitive Processes LIDA Module or Function Cognitive Processes Neural intraparietal Freedman and Assad. 2006 Slipnet Top down processing Hansen et al 2006 Slipnet face nodes PAM nodes PAM-Recognize action situation ­ e.g eating a peanut Mirror neurons in the perisylvian cortical

  15. Fatigue independent amplitude-frequency correlations in EMG signals

    E-print Network

    Siemienski, A; Klajner, P; Siemienski, Adam; Kebel, Alicja; Klajner, Piotr

    2006-01-01

    In order to assess fatigue independent amplitude-frequency correlations in EMG signals we asked nineteen male subjects to perform a series of isometric muscular contractions by extensors of the knee joint. Different amplitudes of the signal were due to randomly varying both the joint moment and the overall amplification factor of the EMG apparatus. Mean and median frequency, RMS and mean absolute value were calculated for every combination of joint moment and amplification at the original sampling rate of 5 kHz and at several simulated lower sampling rates. Negative Spearman and Kendall amplitude-frequency correlation coefficients were found, and they were more pronounced at high sampling rates.

  16. RSFQ Baseband Digital Signal Processing

    NASA Astrophysics Data System (ADS)

    Herr, Anna Yurievna

    Ultra fast switching speed of superconducting digital circuits enable realization of Digital Signal Processors with performance unattainable by any other technology. Based on rapid-single-flux technology (RSFQ) logic, these integrated circuits are capable of delivering high computation capacity up to 30 GOPS on a single processor and very short latency of 0.1ns. There are two main applications of such hardware for practical telecommunication systems: filters for superconducting ADCs operating with digital RF data and recursive filters at baseband. The later of these allows functions such as multiuser detection for 3G WCDMA, equalization and channel precoding for 4G OFDM MIMO, and general blind detection. The performance gain is an increase in the cell capacity, quality of service, and transmitted data rate. The current status of the development of the RSFQ baseband DSP is discussed. Major components with operating speed of 30GHz have been developed. Designs, test results, and future development of the complete systems including cryopackaging and CMOS interface are reviewed.

  17. Detection of anomalous signals in temporally correlated data (Invited)

    NASA Astrophysics Data System (ADS)

    Langbein, J. O.

    2010-12-01

    Detection of transient tectonic signals in data obtained from large geodetic networks requires the ability to detect signals that are both temporally and spatially coherent. In this report I will describe a modification to an existing method that estimates both the coefficients of temporally correlated noise model and an efficient filter based on the noise model. This filter, when applied to the original time-series, effectively whitens (or flattens) the power spectrum. The filtered data provide the means to calculate running averages which are then used to detect deviations from the background trends. For large networks, time-series of signal-to-noise ratio (SNR) can be easily constructed since, by filtering, each of the original time-series has been transformed into one that is closer to having a Gaussian distribution with a variance of 1.0. Anomalous intervals may be identified by counting the number of GPS sites for which the SNR exceeds a specified value. For example, during one time interval, if there were 5 out of 20 time-series with SNR>2, this would be considered anomalous; typically, one would expect at 95% confidence that there would be at least 1 out of 20 time-series with an SNR>2. For time intervals with an anomalously large number of high SNR, the spatial distribution of the SNR is mapped to identify the location of the anomalous signal(s) and their degree of spatial clustering. Estimating the filter that should be used to whiten the data requires modification of the existing methods that employ maximum likelihood estimation to determine the temporal covariance of the data. In these methods, it is assumed that the noise components in the data are a combination of white, flicker and random-walk processes and that they are derived from three different and independent sources. Instead, in this new method, the covariance matrix is constructed assuming that only one source is responsible for the noise and that source can be represented as a white-noise random-number generator convolved with a filter whose spectral properties are frequency (f) independent at its highest frequencies, 1/f at the middle frequencies, and 1/f2 at the lowest frequencies. For data sets with no gaps in their time-series, construction of covariance and inverse covariance matrices is extremely efficient. Application of the above algorithm to real data potentially involves several iterations as small, tectonic signals of interest are often indistinguishable from background noise. Consequently, simply plotting the time-series of each GPS site is used to identify the largest outliers and signals independent of their cause. Any analysis of the background noise levels must factor in these other signals while the gross outliers need to be removed.

  18. Correlating Radio Astronomy Signals with Many-Core Hardware

    Microsoft Academic Search

    Rob V. van Nieuwpoort; John W. Romein

    2011-01-01

    A recent development in radio astronomy is to replace traditional dishes with many small antennas. The signals are combined\\u000a to form one large, virtual telescope. The enormous data streams are cross-correlated to filter out noise. This is especially\\u000a challenging, since the computational demands grow quadratically with the number of data streams. Moreover, the correlator\\u000a is not only computationally intensive, but

  19. Novel sonar signal processing tool using Shannon entropy

    SciTech Connect

    Quazi, A.H. [Code 3122, Naval Undersea Warfare Center, Detachment, New London, Connecticut 06320 (United States)

    1996-06-01

    Traditionally, conventional signal processing extracts information from sonar signals using amplitude, signal energy or frequency domain quantities obtained using spectral analysis techniques. The object is to investigate an alternate approach which is entirely different than that of traditional signal processing. This alternate approach is to utilize the Shannon entropy as a tool for the processing of sonar signals with emphasis on detection, classification, and localization leading to superior sonar system performance. Traditionally, sonar signals are processed coherently, semi-coherently, and incoherently, depending upon the a priori knowledge of the signals and noise. Here, the detection, classification, and localization technique will be based on the concept of the entropy of the random process. Under a constant energy constraint, the entropy of a received process bearing finite number of sample points is maximum when hypothesis H{sub 0} (that the received process consists of noise alone) is true and decreases when correlated signal is present (H{sub 1}). Therefore, the strategy used for detection is: (I) Calculate the entropy of the received data; then, (II) compare the entropy with the maximum value; and, finally, (III) make decision: H{sub 1} is assumed if the difference is large compared to pre-assigned threshold and H{sub 0} is otherwise assumed. The test statistics will be different between entropies under H{sub 0} and H{sub 1}. Here, we shall show the simulated results for detecting stationary and non-stationary signals in noise, and results on detection of defects in a Plexiglas bar using an ultrasonic experiment conducted by Hughes. {copyright} {ital 1996 American Institute of Physics.}

  20. Stochastic Modeling of Correlation Radiometer Signals Brynmor Davis

    E-print Network

    Stochastic Modeling of Correlation Radiometer Signals Brynmor Davis Department of Electrical that these radiometers measure. While polarimetry and interferometry are usually investigated independently by earth-sensing radiometers. Since the model is stationary and Gaussian, it is described completely by its

  1. Signal Processing Issues in Fourier Transform Spectrometers

    Microsoft Academic Search

    Monson H. Hayes

    2002-01-01

    There are a number of interesting and challenging signal processing problems related to the design of a Fourier Transform Spectrometer (FTS). In this project, we look at a few of these problems in two different types of spectrometers-the Geostationary Imaging Fourier Transform Spectrometer (GIFTS), and a Far Infrared (FIR) FTS. One of the si nal processing challenges in GIFTS is

  2. Group-normalized wavelet packet signal processing

    NASA Astrophysics Data System (ADS)

    Shi, Zhuoer; Bao, Zheng

    1997-04-01

    Since the traditional wavelet and wavelet packet coefficients do not exactly represent the strength of signal components at the very time(space)-frequency tilling, group- normalized wavelet packet transform (GNWPT), is presented for nonlinear signal filtering and extraction from the clutter or noise, together with the space(time)-frequency masking technique. The extended F-entropy improves the performance of GNWPT. For perception-based image, soft-logic masking is emphasized to remove the aliasing with edge preserved. Lawton's method for complex valued wavelets construction is extended to generate the complex valued compactly supported wavelet packets for radar signal extraction. This kind of wavelet packets are symmetry and unitary orthogonal. Well-defined wavelet packets are chosen by the analysis remarks on their time-frequency characteristics. For real valued signal processing, such as images and ECG signal, the compactly supported spline or bi- orthogonal wavelet packets are preferred for perfect de- noising and filtering qualities.

  3. Digital signal processing of ultrasonic signals for blood flow measurement.

    PubMed

    Smith, D R; Christmann, H A; Weaver, B L; Betten, W R; Nazarian, R A

    1989-01-01

    This paper describes the application of advanced digital signal processing techniques in a noninvasive ultrasonic Doppler flowmeter used to measure extracorporeal blood flow during open heart surgery. The use of ultrasound to determine blood flow rates started in the 1950's with much of this work focused on measurement of blood flow in a patient by a variety of means, both invasive and noninvasive. Although the use of ultrasonics to measure blood flow is not in itself a new concept, the application of advanced digital signal processing techniques in the system being described has resulted in a unique product for accurate and reliable blood flow measurements. The flowmeter system is intended for use with a centrifugal blood pump and will measure blood flow in the flexible tubing used during surgery to an accuracy of better than +/- 10%. This paper describes the development and implementation of the digital flowmeter and its application to flow measurement. PMID:2663094

  4. An introduction to digital signal processing

    NASA Astrophysics Data System (ADS)

    Karl, John H.

    An introduction to digital signal processing (DSP) is presented for those who need to understand and use DSP without going through a full course of study. The topics addressed include: signals and systems, sampled data and the Z transform, sinusoidal responses of LSI systems, couplets and elementary filters, the discrete Fourier transform, the continuous Fourier integral transform, application of the Fourier transform to DSP, digital filter design, inverse filtering and deconvolution, spectral factorization, power spectral estimation, and multidimensional DSP.

  5. Calibration of Correlation Radiometers Using Pseudo-Random Noise Signals

    PubMed Central

    Pérez, Isaac Ramos; Bosch-Lluis, Xavi; Camps, Adriano; Alvarez, Nereida Rodriguez; Hernandez, Juan Fernando Marchán; Domènech, Enric Valencia; Vernich, Carlos; de la Rosa, Sonia; Pantoja, Sebastián

    2009-01-01

    The calibration of correlation radiometers, and particularly aperture synthesis interferometric radiometers, is a critical issue to ensure their performance. Current calibration techniques are based on the measurement of the cross-correlation of receivers’ outputs when injecting noise from a common noise source requiring a very stable distribution network. For large interferometric radiometers this centralized noise injection approach is very complex from the point of view of mass, volume and phase/amplitude equalization. Distributed noise injection techniques have been proposed as a feasible alternative, but are unable to correct for the so-called “baseline errors” associated with the particular pair of receivers forming the baseline. In this work it is proposed the use of centralized Pseudo-Random Noise (PRN) signals to calibrate correlation radiometers. PRNs are sequences of symbols with a long repetition period that have a flat spectrum over a bandwidth which is determined by the symbol rate. Since their spectrum resembles that of thermal noise, they can be used to calibrate correlation radiometers. At the same time, since these sequences are deterministic, new calibration schemes can be envisaged, such as the correlation of each receiver’s output with a baseband local replica of the PRN sequence, as well as new distribution schemes of calibration signals. This work analyzes the general requirements and performance of using PRN sequences for the calibration of microwave correlation radiometers, and particularizes the study to a potential implementation in a large aperture synthesis radiometer using an optical distribution network. PMID:22454576

  6. A unified approach to sparse signal processing

    NASA Astrophysics Data System (ADS)

    Marvasti, Farokh; Amini, Arash; Haddadi, Farzan; Soltanolkotabi, Mahdi; Khalaj, Babak Hossein; Aldroubi, Akram; Sanei, Saeid; Chambers, Janathon

    2012-12-01

    A unified view of the area of sparse signal processing is presented in tutorial form by bringing together various fields in which the property of sparsity has been successfully exploited. For each of these fields, various algorithms and techniques, which have been developed to leverage sparsity, are described succinctly. The common potential benefits of significant reduction in sampling rate and processing manipulations through sparse signal processing are revealed. The key application domains of sparse signal processing are sampling, coding, spectral estimation, array processing, component analysis, and multipath channel estimation. In terms of the sampling process and reconstruction algorithms, linkages are made with random sampling, compressed sensing, and rate of innovation. The redundancy introduced by channel coding in finite and real Galois fields is then related to over-sampling with similar reconstruction algorithms. The error locator polynomial (ELP) and iterative methods are shown to work quite effectively for both sampling and coding applications. The methods of Prony, Pisarenko, and MUltiple SIgnal Classification (MUSIC) are next shown to be targeted at analyzing signals with sparse frequency domain representations. Specifically, the relations of the approach of Prony to an annihilating filter in rate of innovation and ELP in coding are emphasized; the Pisarenko and MUSIC methods are further improvements of the Prony method under noisy environments. The iterative methods developed for sampling and coding applications are shown to be powerful tools in spectral estimation. Such narrowband spectral estimation is then related to multi-source location and direction of arrival estimation in array processing. Sparsity in unobservable source signals is also shown to facilitate source separation in sparse component analysis; the algorithms developed in this area such as linear programming and matching pursuit are also widely used in compressed sensing. Finally, the multipath channel estimation problem is shown to have a sparse formulation; algorithms similar to sampling and coding are used to estimate typical multicarrier communication channels.

  7. Correlated activity supports efficient cortical processing

    PubMed Central

    Hung, Chou P.; Cui, Ding; Chen, Yueh-peng; Lin, Chia-pei; Levine, Matthew R.

    2015-01-01

    Visual recognition is a computational challenge that is thought to occur via efficient coding. An important concept is sparseness, a measure of coding efficiency. The prevailing view is that sparseness supports efficiency by minimizing redundancy and correlations in spiking populations. Yet, we recently reported that “choristers”, neurons that behave more similarly (have correlated stimulus preferences and spontaneous coincident spiking), carry more generalizable object information than uncorrelated neurons (“soloists”) in macaque inferior temporal (IT) cortex. The rarity of choristers (as low as 6% of IT neurons) indicates that they were likely missed in previous studies. Here, we report that correlation strength is distinct from sparseness (choristers are not simply broadly tuned neurons), that choristers are located in non-granular output layers, and that correlated activity predicts human visual search efficiency. These counterintuitive results suggest that a redundant correlational structure supports efficient processing and behavior. PMID:25610392

  8. Signal Processing Methods Monitor Cranial Pressure

    NASA Technical Reports Server (NTRS)

    2010-01-01

    Dr. Norden Huang, of Goddard Space Flight Center, invented a set of algorithms (called the Hilbert-Huang Transform, or HHT) for analyzing nonlinear and nonstationary signals that developed into a user-friendly signal processing technology for analyzing time-varying processes. At an auction managed by Ocean Tomo Federal Services LLC, licenses of 10 U.S. patents and 1 domestic patent application related to HHT were sold to DynaDx Corporation, of Mountain View, California. DynaDx is now using the licensed NASA technology for medical diagnosis and prediction of brain blood flow-related problems, such as stroke, dementia, and traumatic brain injury.

  9. Remote sensing of ice phenomena from orbit by signal correlation of multiple receiver responses

    NASA Technical Reports Server (NTRS)

    Stacey, J. M.; Johnston, E. J.

    1983-01-01

    The method of signal correlation of microwave responses as applied to the measurement of Earth-surface ice temperatures from orbit is explained and summarized. Ice temperatures are estimated by a correlation function that is derived from the processes of a forward stepwise correlator. Subsets of the post-detected outputs of microwave receiving channels are combined in a multivariate cross-correlation function which operates as a spatial filter and serves to improve the spatial resolution of the thermal gradients in ice structures. The correlator is designed to selectively identify the correlative components among the microwave responses and to strongly suppress or cancel the non-correlative components appearing in the post-detected outputs.

  10. Methodological Framework for Estimating the Correlation Dimension in HRV Signals

    PubMed Central

    Bolea, Juan; Laguna, Pablo; Remartínez, José María; Rovira, Eva; Navarro, Augusto; Bailón, Raquel

    2014-01-01

    This paper presents a methodological framework for robust estimation of the correlation dimension in HRV signals. It includes (i) a fast algorithm for on-line computation of correlation sums; (ii) log-log curves fitting to a sigmoidal function for robust maximum slope estimation discarding the estimation according to fitting requirements; (iii) three different approaches for linear region slope estimation based on latter point; and (iv) exponential fitting for robust estimation of saturation level of slope series with increasing embedded dimension to finally obtain the correlation dimension estimate. Each approach for slope estimation leads to a correlation dimension estimate, called D^2, D^2?, and D^2max. D^2 and D^2max estimate the theoretical value of correlation dimension for the Lorenz attractor with relative error of 4%, and D^2? with 1%. The three approaches are applied to HRV signals of pregnant women before spinal anesthesia for cesarean delivery in order to identify patients at risk for hypotension. D^2 keeps the 81% of accuracy previously described in the literature while D^2? and D^2max approaches reach 91% of accuracy in the same database. PMID:24592284

  11. Ear Modeling and Sound Signal Processing Ear modeling can significantly improve sound signal processing and

    E-print Network

    Xin, Jack

    Ear Modeling and Sound Signal Processing Jack Xin Abstract Ear modeling can significantly improve sound signal processing and the design of hearing devices. Ear models based on mechanics and neu- ral phenomenology of the inner ear (cochlea) form a class of nonlinear nonlocal dispersive partial differential

  12. Unbiased Minimum Variance Estimation Of Correlation Functions Of Random Signals

    Microsoft Academic Search

    Chong-Yung Chi; Wu-Ton Chen

    1990-01-01

    In this paper, we present the unbiased minimum variance estimation of the correlation function, rxx(k), of a wide-sense stationary random signal x(k). However, the obtained theoretical minimum variance estimator, Yxx(k), for rxx(k) is a function of not only x(k) but also the unknown rxx(k) and thus is not computable. Additionally, FXx(k) is not computationally efficient. We, therefore, propose a modified

  13. Acousto-optic signal processing: Theory and implementation

    Microsoft Academic Search

    N. J. Berg; J. N. Lee

    1983-01-01

    An introduction to acousto-optics is provided, taking into account Bragg cell interactions, frequency estimation, correlation, Fourier transformation, a generalized description of acousto-optic interactions, materials and transducer design, acousto-optic modulator design, acousto-optic deflectors, acoustic focusing, and an outlook for acousto-optic device applications. Frequency-domain signal processing is discussed. Applications of acousto-optic techniques to RF spectrum analysis are considered along with coherent detection

  14. Nuclear correlations and the r-process

    E-print Network

    Arcones, A

    2011-01-01

    We show that long-range correlations for nuclear masses have a significant effect on the synthesis of heavy elements by the r-process. As calculated by Delaroche et al. [1], these correlations suppress magic number effects associated with minor shells. This impacts the calculated abundances before the third r-process peak (at mass number A~195), where the abundances are low and form a trough. This trough and the position of the third abundance peak are strongly affected by the masses of nuclei in the transition region between deformed and spherical. Based on different astrophysical environments, our results demonstrate that a microscopic theory of nuclear masses including correlations naturally smoothens the separation energies, thus reducing the trough and improving the agreement with observed solar system abundances.

  15. Nuclear correlations and the r-process

    E-print Network

    A. Arcones; G. F. Bertsch

    2011-12-04

    We show that long-range correlations for nuclear masses have a significant effect on the synthesis of heavy elements by the r-process. As calculated by Delaroche et al. [1], these correlations suppress magic number effects associated with minor shells. This impacts the calculated abundances before the third r-process peak (at mass number A~195), where the abundances are low and form a trough. This trough and the position of the third abundance peak are strongly affected by the masses of nuclei in the transition region between deformed and spherical. Based on different astrophysical environments, our results demonstrate that a microscopic theory of nuclear masses including correlations naturally smoothens the separation energies, thus reducing the trough and improving the agreement with observed solar system abundances.

  16. Nuclear correlations and the r process.

    PubMed

    Arcones, A; Bertsch, G F

    2012-04-13

    We show that long-range correlations for nuclear masses have a significant effect on the synthesis of heavy elements by the r process. As calculated by Delaroche et al. [Phys. Rev. C 81, 014303 (2010)], these correlations suppress magic number effects associated with minor shells. This impacts the calculated abundances before the third r-process peak (at mass number A?195), where the abundances are low and form a trough. This trough and the position of the third abundance peak are strongly affected by the masses of nuclei in the transition region between deformed and spherical. Based on different astrophysical environments, our results demonstrate that a microscopic theory of nuclear masses including correlations naturally smoothens the separation energies, thus reducing the trough and improving the agreement with observed solar system abundances. PMID:22587238

  17. Surveillance of industrial processes with correlated parameters

    DOEpatents

    White, Andrew M. (Skokie, IL); Gross, Kenny C. (Bolingbrook, IL); Kubic, William L. (Sante Fe, NM); Wigeland, Roald A. (Olympia Fields, IL)

    1996-01-01

    A system and method for surveillance of an industrial process. The system and method includes a plurality of sensors monitoring industrial process parameters, devices to convert the sensed data to computer compatible information and a computer which executes computer software directed to analyzing the sensor data to discern statistically reliable alarm conditions. The computer software is executed to remove serial correlation information and then calculate Mahalanobis distribution data to carry out a probability ratio test to determine alarm conditions.

  18. Surveillance of industrial processes with correlated parameters

    DOEpatents

    White, A.M.; Gross, K.C.; Kubic, W.L.; Wigeland, R.A.

    1996-12-17

    A system and method for surveillance of an industrial process are disclosed. The system and method includes a plurality of sensors monitoring industrial process parameters, devices to convert the sensed data to computer compatible information and a computer which executes computer software directed to analyzing the sensor data to discern statistically reliable alarm conditions. The computer software is executed to remove serial correlation information and then calculate Mahalanobis distribution data to carry out a probability ratio test to determine alarm conditions. 10 figs.

  19. Simulating Building Blocks for Spikes Signals Processing

    Microsoft Academic Search

    A. Jimenez-Fernandez; M. Domínguez-Morales; E. Cerezuela-Escudero; R. Paz-Vicente; A. Linares-Barranco; G. Jimenez

    \\u000a In this paper we will explain in depth how we have used Simulink with the addition of Xilinx System Generation to design a\\u000a simulation framework for testing and analyzing neuro-inspired elements for spikes rate coded signals processing. Those elements\\u000a have been designed as building blocks, which represent spikes processing primitives, combining them we have designed more\\u000a complex blocks, which behaves

  20. Digital signal processing in read channels

    Microsoft Academic Search

    Erich F. Haratsch; Z. A. Keirn

    2005-01-01

    Digital signal processing (DSP) has been a key technology in read channels, contributing significantly to the dramatic storage capacity and data rate growth of hard disk drives. This tutorial paper provides an overview of magnetic recording trends, and it discusses the DSP algorithms and architectures that have been employed in read channels for equalization, detection and coding. This paper also

  1. Some important fractional transformations for signal processing

    Microsoft Academic Search

    Adolf W Lohmann; David Mendlovic; Zeev Zalevsky; Rainer G Dorsch

    1996-01-01

    The fractional Fourier transform (FRT), that is useful mathematical and optical tool for signal processing, was defined as a generalization of the conventional Fourier transform. As opposed to the Fourier transform, the Hartley transform is a real (not complex) mathematical transformation and thus might be attractive for various applications. In optics, due to the fact that it is a real

  2. Ionospheric calibration from an array signal processing

    E-print Network

    Langendoen, Koen

    of (traveling) disturbances, the dynamics of the ionosphere can be described by turbulent flow. A deterministicIonospheric calibration from an array signal processing perspective Sebastiaan van der Tol S.vanderTol@its.tudelft.nl Delft University of Technology Calibration and Imaging Workshop 2006 ­ p.1/21 #12;Ionospheric

  3. Nonlinear Cochlear Signal Processing Jont B. Allen

    E-print Network

    Allen, Jont

    Nonlinear Cochlear Signal Processing Jont B. Allen Florham Park, NJ July 19, 2001 Contents 1 Macromechanics 5 1.1 The early history of cochlear modeling. . . . . . . . . . . . . . . . . . . . . . 6 1 of experimental data) 14 2.1 Contemporary history of cochlear modeling . . . . . . . . . . . . . . . . . . . 14 2

  4. International Conference on Signal Processing and Communications

    E-print Network

    Sharma, Vinod

    and Storage Ad-hoc and Sensor Networks Optical Communications and Networks Next Generation Networking & QoS Cyber Physical Systems Multihop and Mesh Networks Vehicular Networks RF Systems for Communications Green in IEEE Xplore. Detection and Estimation Adaptive and Array Signal Processing Compressive Sensing

  5. The processing of periodically sampled multidimensional signals

    Microsoft Academic Search

    R. Mersereau; T. Speake

    1983-01-01

    This paper discusses algorithms for processing multidimensional signals which are sampled on regular, but nonrectangular sampiing lattices. Such sampling lattices are dictated by some applications and may be chosen for others because of their resulting symmetric responses or computational efficiencies. We show that any operation which can be performed on a rectangular lattice can be performed on any regular periodic

  6. Improvement of Signal-to-noise ratios of surface wave signal obtained through ambient noise correlations

    NASA Astrophysics Data System (ADS)

    Weemstra, Cornelis; Boschi, Lapo; Verbeke, Julie

    2013-04-01

    Spectral whitening has become a widely used preprocessing method in the field of ambient seismic noise. Using two years of noise recordings from an array of European stations, we show that an improvement in the signal-to-noise ratio (SNR) of station-station cross-correlations can be obtained using a different form of spectral whitening. This alternative combines spectral whitening with the processing associated with the spatial autocorrelation (SPAC) method (Aki, 1957). The difference between the two techniques is the order of ensemble averaging and normalization. Spectral whitening involves normalization of the cross-spectrum by the individual power for each time-window and subsequent ensemble averaging. SPAC-processing in turn involves ensemble averaging prior to normalization: the ensemble-averaged cross-spectrum is normalized with respect the ensemble averaged power. The SPAC-method relies on the stationarity of the wavefield. In general, the wavefield is only stationary over relatively short time intervals (Okada, 2003). We therefore explain the increased SNR's with this characteristic of the wavefield. [Aki, 1957] Aki, K., 1957, Space and time spectra of stationary stochastic waves, with special reference to microtremors.: Bulletin of the Earthquake Research Institute, University of Tokyo, 35, 415-457. [Okada, 2003] Okada, H., 2003, The microtremor survey method: Society of Exploration Geophysicists. Geophysical Monograph, No. 12.

  7. High Precision Signal Processing Algorithm for White Light Interferometry

    PubMed Central

    Kim, Jeonggon Harrison

    2008-01-01

    A new signal processing algorithm for absolute temperature measurement using white light interferometry has been proposed and investigated theoretically. The proposed algorithm determines the phase delay of an interferometer with very high precision (? one fringe) by identifying the zero order fringe peak of cross-correlation of two fringe scans of white light interferometer. The algorithm features cross-correlation of interferometer fringe scans, hypothesis testing and fine tuning. The hypothesis test looks for a zero order fringe peak candidate about which the cross-correlation is symmetric minimizing the uncertainty of mis-identification. Fine tuning provides the proposed algorithm with high precision sub-sample resolution phase delay estimation capability. The shot noise limited performance of the proposed algorithm has been analyzed using computer simulations. Root-mean-square (RMS) phase error of the estimated zero order fringe peak has been calculated for the changes of three different parameters (SNR, fringe scan sample rate, coherence length of light source). Computer simulations showed that the proposed signal processing algorithm identified the zero order fringe peak with a miss rate of 3 × 10-4 at 31 dB SNR and the extrapolated miss rate at 35 dB was 3 × 10-8. Also, at 35 dB SNR, RMS phase error less than 10-3 fringe was obtained. The proposed signal processing algorithm uses a software approach that is potentially inexpensive, simple and fast.

  8. The Evolution of Signal Processing [From the Editor

    Microsoft Academic Search

    D. Schonfeld

    2010-01-01

    Signal processing is in the midst of a major transition from a focus on classical signals in electrical engineering applications to a much wider usage devoted to the analysis of signals in a broad spectrum of science and engineering disciplines. Signal processing professionals are thus no longer limited to the traditional use of signal processing methodologies in speech, image, video,

  9. Signal processing problems of neurocardiological fluctuations

    NASA Astrophysics Data System (ADS)

    Gingl, Zoltán; Rudas, László; Makra, Péter

    2005-11-01

    The spectral analysis of electrocardiogram (ECG) and blood pressure fluctuations is an important tool both in medical diagnostics and in theories that endeavour to account for the complex, feedbacked patterns of control mechanisms that regulate human circulation. In the case of ECG signals, the information is in the rate of heartbeats, which means that it is not the whole signal but only a so-called RR signal, containing the distances of beats, that serves as the basis of spectral processing. This RR signal is inherently discrete and unevenly sampled, which introduces a number of methodological problems: fast Fourier transformation (FFT) needs even sampling, and this means that some re-sampling (inserting new samples at equal distances) is necessary. In the case of blood pressure signals, the information is both in the amplitude itself and in the rate, consequently both an RR-like and a full recording-based treatment are usable here. In the present paper we review the different interpolation methods used in re-sampling, along with the Lomb periodogram that does not require re-sampling at all, and contrast the results they yield both for a model sine and for real signals. We also argue for a full recording-based treatment of blood pressure fluctuations, as they require no peak detection and thus avoid the artefacts that peak detection may cause.

  10. Suprathreshold stochastic resonance in neural processing tuned by correlation

    NASA Astrophysics Data System (ADS)

    Durrant, Simon; Kang, Yanmei; Stocks, Nigel; Feng, Jianfeng

    2011-07-01

    Suprathreshold stochastic resonance (SSR) is examined in the context of integrate-and-fire neurons, with an emphasis on the role of correlation in the neuronal firing. We employed a model based on a network of spiking neurons which received synaptic inputs modeled by Poisson processes stimulated by a stepped input signal. The smoothed ensemble firing rate provided an output signal, and the mutual information between this signal and the input was calculated for networks with different noise levels and different numbers of neurons. It was found that an SSR effect was present in this context. We then examined a more biophysically plausible scenario where the noise was not controlled directly, but instead was tuned by the correlation between the inputs. The SSR effect remained present in this scenario with nonzero noise providing improved information transmission, and it was found that negative correlation between the inputs was optimal. Finally, an examination of SSR in the context of this model revealed its connection with more traditional stochastic resonance and showed a trade-off between supratheshold and subthreshold components. We discuss these results in the context of existing empirical evidence concerning correlations in neuronal firing.

  11. Invariance algorithms for processing NDE signals

    NASA Astrophysics Data System (ADS)

    Mandayam, Shreekanth; Udpa, Lalita; Udpa, Satish S.; Lord, William

    1996-11-01

    Signals that are obtained in a variety of nondestructive evaluation (NDE) processes capture information not only about the characteristics of the flaw, but also reflect variations in the specimen's material properties. Such signal changes may be viewed as anomalies that could obscure defect related information. An example of this situation occurs during in-line inspection of gas transmission pipelines. The magnetic flux leakage (MFL) method is used to conduct noninvasive measurements of the integrity of the pipe-wall. The MFL signals contain information both about the permeability of the pipe-wall and the dimensions of the flaw. Similar operational effects can be found in other NDE processes. This paper presents algorithms to render NDE signals invariant to selected test parameters, while retaining defect related information. Wavelet transform based neural network techniques are employed to develop the invariance algorithms. The invariance transformation is shown to be a necessary pre-processing step for subsequent defect characterization and visualization schemes. Results demonstrating the successful application of the method are presented.

  12. Stepped-frequency radar signal processing

    NASA Astrophysics Data System (ADS)

    Seyfried, Daniel; Schoebel, Joerg

    2015-01-01

    Stepped-frequency radar is a prominent example of the class of continuous-wave radar systems. Since raw data are recorded in frequency-domain direct investigations referring to the frequency content can be done on the raw data. However, a transformation of these data is required in order to obtain a time-domain representation of the targets illuminated by the radar. In this paper we present different ways of arranging the raw data which then are processed by means of the inverse fast Fourier transform. On the basis of the time-domain result we discuss strengths and weaknesses of each of these data structures. Furthermore, we investigate the influence of phase noise on the time-domain signal by means of an appropriate model implemented in our simulation tool. We also demonstrate the effects of commonly known techniques of digital signal processing, such as windowing and zero-padding of frequency-domain data. Finally we present less commonly known methods, such as the processing gain of the (inverse) fast Fourier transform by means of which the signal to noise ratio of the time-domain signal can be increased.

  13. Contemporary ultrasonic signal processing approaches for nondestructive evaluation of multilayered structures

    Microsoft Academic Search

    Guang-Ming Zhang; David M. Harvey

    2012-01-01

    Various signal processing techniques have been used for the enhancement of defect detection and defect characterisation. Cross-correlation, filtering, autoregressive analysis, deconvolution, neural network, wavelet transform and sparse signal representations have all been applied in attempts to analyse ultrasonic signals. In ultrasonic nondestructive evaluation (NDE) applications, a large number of materials have multilayered structures. NDE of multilayered structures leads to some

  14. Contemporary ultrasonic signal processing approaches for nondestructive evaluation of multilayered structures

    Microsoft Academic Search

    Guang-Ming Zhang; David M. Harvey

    2011-01-01

    Various signal processing techniques have been used for the enhancement of defect detection and defect characterisation. Cross-correlation, filtering, autoregressive analysis, deconvolution, neural network, wavelet transform and sparse signal representations have all been applied in attempts to analyse ultrasonic signals. In ultrasonic nondestructive evaluation (NDE) applications, a large number of materials have multilayered structures. NDE of multilayered structures leads to some

  15. dNSP: A biologically inspired dynamic Neural network approach to Signal Processing

    Microsoft Academic Search

    José Manuel Cano-Izquierdo; Julio Ibarrola; Miguel Pinzolas; Miguel Almonacid

    2008-01-01

    The arriving order of data is one of the intrinsic properties of a signal. Therefore, techniques dealing with this temporal relation are required for identification and signal processing tasks. To perform a classification of the signal according with its temporal characteristics, it would be useful to find a feature vector in which the temporal attributes were embedded. The correlation and

  16. Parallel digital signal processing architectures for image processing

    NASA Astrophysics Data System (ADS)

    Kshirsagar, Shirish P.; Hartley, David A.; Harvey, David M.; Hobson, Clifford A.

    1994-10-01

    This paper describes research into a high speed image processing system using parallel digital signal processors for the processing of electro-optic images. The objective of the system is to reduce the processing time of non-contact type inspection problems including industrial and medical applications. A single processor can not deliver sufficient processing power required for the use of applications hence, a MIMD system is designed and constructed to enable fast processing of electro-optic images. The Texas Instruments TMS320C40 digital signal processor is used due to its high speed floating point CPU and the support for the parallel processing environment. A custom designed VISION bus is provided to transfer images between processors. The system is being applied for solder joint inspection of high technology printed circuit boards.

  17. Signalling and phosphorus: correlations between mate signalling effort and body elemental composition in crickets

    E-print Network

    Elser, Jim

    composition in crickets SUSAN M. BERTRAM, JOHN D. SCHADE & JAMES J. ELSER School of Life Sciences, Arizona produced by male Texas field crickets, Gryllus texensis. Signalling was strongly and positively correlated crickets reared on high-protein diets (45% protein) showed significantly greater nymphal survival, faster

  18. Processing Electromyographic Signals to Recognize Words

    NASA Technical Reports Server (NTRS)

    Jorgensen, C. C.; Lee, D. D.

    2009-01-01

    A recently invented speech-recognition method applies to words that are articulated by means of the tongue and throat muscles but are otherwise not voiced or, at most, are spoken sotto voce. This method could satisfy a need for speech recognition under circumstances in which normal audible speech is difficult, poses a hazard, is disturbing to listeners, or compromises privacy. The method could also be used to augment traditional speech recognition by providing an additional source of information about articulator activity. The method can be characterized as intermediate between (1) conventional speech recognition through processing of voice sounds and (2) a method, not yet developed, of processing electroencephalographic signals to extract unspoken words directly from thoughts. This method involves computational processing of digitized electromyographic (EMG) signals from muscle innervation acquired by surface electrodes under a subject's chin near the tongue and on the side of the subject s throat near the larynx. After preprocessing, digitization, and feature extraction, EMG signals are processed by a neural-network pattern classifier, implemented in software, that performs the bulk of the recognition task as described.

  19. Source and processing effects on noise correlations

    NASA Astrophysics Data System (ADS)

    Fichtner, Andreas

    2014-05-01

    We quantify the effects of spatially heterogeneous noise sources and seismic processing on noise correlation measurements and their sensitivity to Earth structure. Our analysis is based on numerical wavefield simulations in heterogeneous media. This allows us to calculate inter-station correlations for arbitrarily distributed noise sources where - as in the real Earth - different frequencies are generated in different locations. Using adjoint methods, we compute the exact structural sensitivities for a given combination of source distribution, processing scheme, and measurement technique. The key results of our study are as follows: (1) Heterogeneous noise sources and subjective processing, such as the application of spectral whitening, have profound effects on noise correlation wave forms. (2) Nevertheless, narrow-band traveltime measurements are only weakly affected by heterogeneous noise sources and processing. This result is in accord with previous analytical studies, and it explains the similarity of noise and earthquake tomographies that only exploit traveltime information. (3) Spatially heterogeneous noise sources can lead to structural sensitivities that deviate strongly from the classical cigar-shaped sensitivities. Furthermore, the frequency dependence of sensitivity kernels can go far beyond the well-know dependence of the Fresnel zone width on frequency. Our results imply that a meaningful application of modern full waveform inversion methods to noise correlations is not possible unless both the noise source distribution and the processing scheme are properly taken into account. Failure to do so can lead to erroneous misfit quantifications, slow convergence of optimisation schemes, and to the appearance of tomographic artefacts that reflect the incorrect structural sensitivity. These aspects acquire special relevance in the monitoring of subtle changes of subsurface structure that may be polluted when the time dependence of heterogeneous noise sources is ignored.

  20. Signal/noise enhancement strategies for stochastically estimated correlation functions

    E-print Network

    William Detmold; Michael G. Endres

    2014-08-19

    We develop strategies for enhancing the signal/noise ratio for stochastically sampled correlation functions. The techniques are general and offer a wide range of applicability. We demonstrate the potential of the approach with a generic two-state system, and then explore the practical applicability of the method for single hadron correlators in lattice quantum chromodynamics. In the latter case, we determine the ground state energies of the pion, proton, and delta baryon, as well as the ground and first excited state energy of the rho meson using matrices of correlators computed on an exemplary ensemble of anisotropic gauge configurations. In the majority of cases, we find a modest reduction in the statistical uncertainties on extracted energies compared to conventional variational techniques. However, in the case of the delta baryon, we achieve a factor of three reduction in statistical uncertainties. The variety of outcomes achieved for single hadron correlators illustrates an inherent dependence of the method on the properties of the system under consideration and the operator basis from which the correlators are constructed.

  1. Interpretation of AMS-02 results: correlations among dark matter signals

    SciTech Connect

    Simone, Andrea De [CERN, Theory Division, CH-1211 Geneva 23 (Switzerland); Riotto, Antonio [Département de Physique Théorique and Centre for Astroparticle Physics (CAP), 24 quai E. Ansermet, CH-1211 Geneva (Switzerland); Xue, Wei, E-mail: andrea.desimone@sissa.it, E-mail: antonio.riotto@unige.ch, E-mail: wei.xue@sissa.it [SISSA, via Bonomea 265, I-34136 Trieste (Italy)

    2013-05-01

    The AMS-02 collaboration has recently released data on the positron fraction e{sup +}/(e{sup ?}+e{sup +}) up to energies of about 350 GeV. If one insists on interpreting the observed excess as a dark matter signal, then we find it is best described by a TeV-scale dark matter annihilating into ?{sup +}?{sup ?}, although this situation is already severely constrained by gamma-ray measurements.The annihilation into ?{sup +}?{sup ?} is allowed by gamma-rays more than ?{sup +}?{sup ?}, but it gives a poorer fit to AMS-02 data. Moreover, since electroweak corrections induce correlations among the fluxes of stable particles from dark matter annihilations, the recent AMS-02 data imply a well-defined prediction for the correlated flux of antiprotons. Under the assumption that their future measurements will not show any antiproton excess above the background, the dark matter interpretation of the positron rise will possibly be ruled out by only making use of data from a single experiment. This work is the first of a program where we emphasize the role of correlations among dark matter signals.

  2. Nonlinear Cochlear Signal Processing and Phoneme Perception

    NASA Astrophysics Data System (ADS)

    Allen, Jont B.; Régnier, Marion; Phatak, Sandeep; Li, Feipeng

    2009-02-01

    The most important communication signal is human speech. It is helpful to think of speech communication in terms of Claude Shannon's information theory channel model. When thus viewed, it immediately becomes clear that the most complex part of speech communication channel is in auditory system (the receiver). In my opinion, even after years of work, relatively little is know about how the human auditory system decodes speech. Given cochlear damaged, speech scores are greatly reduced, even with tiny amounts of noise. The exact reasons for this SNR-loss presently remain unclear, but I speculate that the source of this must be cochlear outer hair cell temporal processing, not central processing. Specifically, "temporal edge enhancement" of the speech signal and forward masking could easily be modified in such ears, leading to SNR-Loss. What ever the reason, SNR-Loss is the key problem that needs to be fully researched.

  3. Matrix Downdating Techniques For Signal Processing

    NASA Astrophysics Data System (ADS)

    Bojanczyk, Adam W.; Steinhardt, Allan O.

    1988-02-01

    We are concerned with a problem of finding the triangular (Banachiewicz-Cholesky) factor of the covariance matrix after deleting observations from the corresponding linear least squares equations. Such a problem, often referred to as downdating, arises in classical signal processing as well as in various other broad ares of computing. Examples include recursive least squares estimation and filtering with a sliding rectangular window in adaptive signal processing, outlier suppression and robust regression in statistics, and the modification of Hessian matrices in the numerical solution of non-linear equations. Formally the problem can be described as follows: Given an n xn upper triangular matrix L and an n-dimensional vector x such that LTL - xxT > 0 find an n xn lower triangular matrix L such that LLT = LLT - XXT We will look at the following issues relevant to the downdating problem: - stability - rank-1 downdating algorithms - generalization to modifications of a higher rank

  4. Digital signal processing for beam position feedback

    SciTech Connect

    Chung, Y.; Emery, L.; Kirchman, J.

    1992-04-01

    Stabilization of the particle beam position with respect to the focusing optics in the third generation synchrotron light sources is crucial to achieving low emittance and high brightness. For this purpose, global and local beam orbit correction feedbacks will be implemented in the APS storage ring. In this article, the authors discuss application of digital signal processing to particle/photon beam position feedback using the PID (proportional, integral, and derivative) control algorithm.

  5. FPGA-Based Filterbank Implementation for Parallel Digital Signal Processing

    NASA Technical Reports Server (NTRS)

    Berner, Stephan; DeLeon, Phillip

    1999-01-01

    One approach to parallel digital signal processing decomposes a high bandwidth signal into multiple lower bandwidth (rate) signals by an analysis bank. After processing, the subband signals are recombined into a fullband output signal by a synthesis bank. This paper describes an implementation of the analysis and synthesis banks using (Field Programmable Gate Arrays) FPGAs.

  6. Complementary contributions of indeterminism and signaling to quantum correlations

    SciTech Connect

    Hall, Michael J. W. [Theoretical Physics, Research School of Physics and Engineering, Australian National University, Canberra, ACT 0200 (Australia)

    2010-12-15

    Simple quantitative measures of indeterminism and signaling, I and S, are defined for models of statistical correlations. It is shown that any such model satisfies a generalized Bell-type inequality, with tight upper bound B(I,S). This upper bound explicitly quantifies the complementary contributions required from indeterminism and signaling, for modeling any given violation of the standard Bell-Clauser-Horne-Shimony-Holt (Bell-CHSH) inequality. For example, all models of the maximum quantum violation must either assign no more than 80% probability of occurrence to some underlying event, and/or allow a nonlocal change of at least 60% in an underlying marginal probability of one observer in response to a change in measurement setting by a distant observer. The results yield a corresponding complementarity relation between the numbers of local random bits and nonlocal signaling bits required to model a given violation. A stronger relation is conjectured for simulations of singlet states. Signaling appears to be a useful resource only if a 'gap' condition is satisfied, corresponding to being able to nonlocally flip some underlying marginal probability p to its complementary value 1-p.

  7. Digital signal processor and processing method for GPS receivers

    NASA Technical Reports Server (NTRS)

    Thomas, Jr., Jess B. (Inventor)

    1989-01-01

    A digital signal processor and processing method therefor for use in receivers of the NAVSTAR/GLOBAL POSITIONING SYSTEM (GPS) employs a digital carrier down-converter, digital code correlator and digital tracking processor. The digital carrier down-converter and code correlator consists of an all-digital, minimum bit implementation that utilizes digital chip and phase advancers, providing exceptional control and accuracy in feedback phase and in feedback delay. Roundoff and commensurability errors can be reduced to extremely small values (e.g., less than 100 nanochips and 100 nanocycles roundoff errors and 0.1 millichip and 1 millicycle commensurability errors). The digital tracking processor bases the fast feedback for phase and for group delay in the C/A, P.sub.1, and P.sub.2 channels on the L.sub.1 C/A carrier phase thereby maintaining lock at lower signal-to-noise ratios, reducing errors in feedback delays, reducing the frequency of cycle slips and in some cases obviating the need for quadrature processing in the P channels. Simple and reliable methods are employed for data bit synchronization, data bit removal and cycle counting. Improved precision in averaged output delay values is provided by carrier-aided data-compression techniques. The signal processor employs purely digital operations in the sense that exactly the same carrier phase and group delay measurements are obtained, to the last decimal place, every time the same sampled data (i.e., exactly the same bits) are processed.

  8. NOVEL SIGNAL PROCESSING WITH NONLINEAR TRANSMISSION LINES

    SciTech Connect

    D. REAGOR; ET AL

    2000-08-01

    Nonlinear dielectrics offer uniquely strong and tunable nonlinearities that make them attractive for current devices (for example, frequency-agile microwave filters) and for future signal-processing technologies. The goal of this project is to understand pulse propagation on nonlinear coplanar waveguide prototype devices. We have performed time-domain and frequency-domain experimental studies of simple waveguide structures and pursued a theoretical understanding of the propagation of signals on these nonlinear waveguides. To realistically assess the potential applications, we used a time-domain measurement and analysis technique developed during this project to perform a broadband electrodynamics characterization in terms of nonlinear, dispersive, and dissipative effects. We completed a comprehensive study of coplanar waveguides made from high-temperature superconducting thin-film YBa{sub 2}Cu{sub 3}O{sub 7{minus}{delta}} electrodes on nonlinear dielectric single-crystal SrTiO{sub 3} substrates. By using parameters determined from small-signal (linear) transmission characteristics of the waveguides, we develop a model equation that successfully predicts and describes large-signal (nonlinear) behavior.

  9. An intelligent, onboard signal processing payload concept

    SciTech Connect

    Shriver, P. M. (Patrick M.); Harikumar, J. (Jayashree); Briles, S. C. (Scott C.); Gokhale, M. (Maya)

    2003-01-01

    Our approach to onboard processing will enable a quicker return and improved quality of processed data from small, remote-sensing satellites. We describe an intelligent payload concept which processes RF lightning signal data onboard the spacecraft in a power-aware manner. Presently, onboard processing is severely curtailed due to the conventional management of limited resources and power-unaware payload designs. Delays of days to weeks are commonly experienced before raw data is received, processed into a human-usable format, and finally transmitted to the end-user. We enable this resource-critical technology of onboard processing through the concept of Algorithm Power Modulation (APM). APM is a decision process used to execute a specific software algorithm, from a suite of possible algorithms, to make the best use of the available power. The suite of software algorithms chosen for our application is intended to reduce the probability of false alarms through postprocessing. Each algorithm however also has a cost in energy usage. A heuristic decision tree procedure is used which selects an algorithm based on the available power, time allocated, algorithm priority, and algorithm performance. We demonstrate our approach to power-aware onboard processing through a preliminary software simulation.

  10. Radar transponder apparatus and signal processing technique

    SciTech Connect

    Axline, R.M. Jr.; Sloan, G.R.; Spalding, R.E.

    1994-12-31

    An active, phase-coded, time-grating transponder and a synthetic-aperture radar (SAR) and signal processor means, in combination, allow the recognition and location of the transponder (tag) in the SAR image and allow communication of information messages from the transponder to the SAR. The SAR is an illuminating radar having special processing modifications in an image-formation processor to receive an echo from a remote transponder, after the transponder receives and retransmits the SAR illuminations, and to enhance tile transponder`s echo relative to surrounding ground clutter by recognizing special transponder modulations from phase-shifted from the transponder retransmissions. The remote radio-frequency tag also transmits information to the SAR through a single antenna that also serves to receive the SAR illuminations. Unique tag-modulation and SAR signal processing techniques, in combination, allow the detection and precise geographical location of the tag, through the reduction of interfering signals from ground clutter, and allow communication of environmental and status information from said tag to be communicated to said SAR.

  11. Radar transponder apparatus and signal processing technique

    DOEpatents

    Axline, R.M. Jr.; Sloan, G.R.; Spalding, R.E.

    1996-01-23

    An active, phase-coded, time-grating transponder and a synthetic-aperture radar (SAR) and signal processor means, in combination, allow the recognition and location of the transponder (tag) in the SAR image and allow communication of information messages from the transponder to the SAR. The SAR is an illuminating radar having special processing modifications in an image-formation processor to receive an echo from a remote transponder, after the transponder receives and retransmits the SAR illuminations, and to enhance the transponder`s echo relative to surrounding ground clutter by recognizing special transponder modulations from phase-shifted from the transponder retransmissions. The remote radio-frequency tag also transmits information to the SAR through a single antenna that also serves to receive the SAR illuminations. Unique tag-modulation and SAR signal processing techniques, in combination, allow the detection and precise geographical location of the tag through the reduction of interfering signals from ground clutter, and allow communication of environmental and status information from said tag to be communicated to said SAR. 4 figs.

  12. Radar transponder apparatus and signal processing technique

    DOEpatents

    Axline, Jr., Robert M. (Albuquerque, NM); Sloan, George R. (Albuquerque, NM); Spalding, Richard E. (Albuquerque, NM)

    1996-01-01

    An active, phase-coded, time-grating transponder and a synthetic-aperture radar (SAR) and signal processor means, in combination, allow the recognition and location of the transponder (tag) in the SAR image and allow communication of information messages from the transponder to the SAR. The SAR is an illuminating radar having special processing modifications in an image-formation processor to receive an echo from a remote transponder, after the transponder receives and retransmits the SAR illuminations, and to enhance the transponder's echo relative to surrounding ground clutter by recognizing special transponder modulations from phase-shifted from the transponder retransmissions. The remote radio-frequency tag also transmits information to the SAR through a single antenna that also serves to receive the SAR illuminations. Unique tag-modulation and SAR signal processing techniques, in combination, allow the detection and precise geographical location of the tag through the reduction of interfering signals from ground clutter, and allow communication of environmental and status information from said tag to be communicated to said SAR.

  13. Unique portable signal acquisition/processing station

    SciTech Connect

    Garron, R.D.; Azevedo, S.G.

    1983-05-16

    At Lawrence Livermore National Laboratory, there are experimental applications requiring digital signal acquisition as well as data reduction and analysis. A prototype Signal Acquisition/Processing Station (SAPS) has been constructed and is currently undergoing tests. The system employs an LSI-11/23 computer with Data Translation analog-to-digital hardware. SAPS is housed in a roll-around cart which has been designed to withstand most subtle EMI/RFI environments. A user-friendly menu allows a user to access powerful data acquisition packages with a minimum of training. The software architecture of SAPS involves two operating systems, each being transparent to the user. Since this is a general purpose workstation with several units being utilized, an emphasis on low cost, reliability, and maintenance was stressed during conception and design. The system is targeted for mid-range frequency data acquisition; between a data logger and a transient digitizer.

  14. Signal processing and tracking of arrivals in ocean acoustic tomography.

    PubMed

    Dzieciuch, Matthew A

    2014-11-01

    The signal processing for ocean acoustic tomography experiments has been improved to account for the scattering of the individual arrivals. The scattering reduces signal coherence over time, bandwidth, and space. In the typical experiment, scattering is caused by the random internal-wave field and results in pulse spreading (over arrival-time and arrival-angle) and wander. The estimator-correlator is an effective procedure that improves the signal-to-noise ratio of travel-time estimates and also provides an estimate of signal coherence. The estimator-correlator smoothes the arrival pulse at the expense of resolution. After an arrival pulse has been measured, it must be associated with a model arrival, typically a ray arrival. For experiments with thousands of transmissions, this is a tedious task that is error-prone when done manually. An error metric that accounts for peak amplitude as well as travel-time and arrival-angle can be defined. The Viterbi algorithm can then be adapted to the task of automated peak tracking. Repeatable, consistent results are produced that are superior to a manual tracking procedure. The tracking can be adjusted by tuning the error metric in logical, quantifiable manner. PMID:25373953

  15. Hybrid integrated optic modules for real-time signal processing

    NASA Technical Reports Server (NTRS)

    Tsai, C. S.

    1984-01-01

    The most recent progress on four relatively new hybrid integrated optic device modules in LiNbO3 waveguides and one in YIG/GGG waveguide that are currently being studied are discussed. The five hybrid modules include a time-integrating acoustooptic correlator, a channel waveguide acoustooptic frequency shifter/modulator, an electrooptic channel waveguide total internal reflection moculator/switch, an electrooptic analog-to-digital converter using a Fabry-Perot modulator array, and a noncollinear magnetooptic modulator using magnetostatic surface waves. All of these devices possess the desirable characteristics of very large bandwidth (GHz or higher), very small substrate size along the optical path (typically 1.5 cm or less), single-mode optical propagation, and low drive power requirement. The devices utilize either acoustooptic, electrooptic or magnetooptic effects in planar or channel waveguides and, therefore, act as efficient interface devices between a light wave and temporal signals. Major areas of application lie in wideband multichannel optical real-time signal processing and communications. Some of the specific applications include spectral analysis and correlation of radio frequency (RF) signals, fiber-optic sensing, optical computing and multiport switching/routing, and analog-to-digital conversion of wide RF signals.

  16. Efficient audio signal processing for embedded systems

    NASA Astrophysics Data System (ADS)

    Chiu, Leung Kin

    As mobile platforms continue to pack on more computational power, electronics manufacturers start to differentiate their products by enhancing the audio features. However, consumers also demand smaller devices that could operate for longer time, hence imposing design constraints. In this research, we investigate two design strategies that would allow us to efficiently process audio signals on embedded systems such as mobile phones and portable electronics. In the first strategy, we exploit properties of the human auditory system to process audio signals. We designed a sound enhancement algorithm to make piezoelectric loudspeakers sound ”richer" and "fuller." Piezoelectric speakers have a small form factor but exhibit poor response in the low-frequency region. In the algorithm, we combine psychoacoustic bass extension and dynamic range compression to improve the perceived bass coming out from the tiny speakers. We also developed an audio energy reduction algorithm for loudspeaker power management. The perceptually transparent algorithm extends the battery life of mobile devices and prevents thermal damage in speakers. This method is similar to audio compression algorithms, which encode audio signals in such a ways that the compression artifacts are not easily perceivable. Instead of reducing the storage space, however, we suppress the audio contents that are below the hearing threshold, therefore reducing the signal energy. In the second strategy, we use low-power analog circuits to process the signal before digitizing it. We designed an analog front-end for sound detection and implemented it on a field programmable analog array (FPAA). The system is an example of an analog-to-information converter. The sound classifier front-end can be used in a wide range of applications because programmable floating-gate transistors are employed to store classifier weights. Moreover, we incorporated a feature selection algorithm to simplify the analog front-end. A machine learning algorithm AdaBoost is used to select the most relevant features for a particular sound detection application. In this classifier architecture, we combine simple "base" analog classifiers to form a strong one. We also designed the circuits to implement the AdaBoost-based analog classifier.

  17. Digital signal processing methods for biosequence comparison.

    PubMed Central

    Benson, D C

    1990-01-01

    A method is discussed for DNA or protein sequence comparison using a finite field fast Fourier transform, a digital signal processing technique; and statistical methods are discussed for analyzing the output of this algorithm. This method compares two sequences of length N in computing time proportional to N log N compared to N2 for methods currently used. This method makes it feasible to compare very long sequences. An example is given to show that the method correctly identifies sites of known homology. PMID:2349096

  18. Cellular defense processes regulated by pathogen-elicited receptor signaling

    NASA Astrophysics Data System (ADS)

    Wu, Rongcong; Goldsipe, Arthur; Schauer, David B.; Lauffenburger, Douglas A.

    2011-06-01

    Vertebrates are constantly threatened by the invasion of microorganisms and have evolved systems of immunity to eliminate infectious pathogens in the body. Initial sensing of microbial agents is mediated by the recognition of pathogens by means of molecular structures expressed uniquely by microbes of a given type. So-called 'Toll-like receptors' are expressed on host epithelial barrier cells play an essential role in the host defense against microbial pathogens by inducing cell responses (e.g., proliferation, death, cytokine secretion) via activation of intracellular signaling networks. As these networks, comprising multiple interconnecting dynamic pathways, represent highly complex multi-variate "information processing" systems, the signaling activities particularly critical for governing the host cell responses are poorly understood and not easily ascertained by a priori theoretical notions. We have developed over the past half-decade a "data-driven" computational modeling approach, on a 'cue-signal-response' combined experiment/computation paradigm, to elucidate key multi-variate signaling relationships governing the cell responses. In an example presented here, we study how a canonical set of six kinase pathways combine to effect microbial agent-induced apoptotic death of a macrophage cell line. One modeling technique, partial least-squares regression, yielded the following key insights: {a} signal combinations most strongly correlated to apoptotic death are orthogonal to those most strongly correlated with release of inflammatory cytokines; {b} the ratio of two key pathway activities is the most powerful predictor of microbe-induced macrophage apoptotic death; {c} the most influential time-window of this signaling activity ratio is surprisingly fast: less than one hour after microbe stimulation.

  19. Neural Correlates of Processing Passive Sentences

    PubMed Central

    Mack, Jennifer E.; Meltzer-Asscher, Aya; Barbieri, Elena; Thompson, Cynthia K.

    2013-01-01

    Previous research has shown that comprehension of complex sentences involving wh-movement (e.g., object-relative clauses) elicits activation in the left inferior frontal gyrus (IFG) and left posterior temporal cortex. However, relatively little is known about the neural correlates of processing passive sentences, which differ from other complex sentences in terms of representation (i.e., noun phrase (NP)-movement) and processing (i.e., the time course of syntactic reanalysis). In the present study, 27 adults (14 younger and 13 older) listened to passive and active sentences and performed a sentence-picture verification task using functional Magnetic Resonance Imaging (fMRI). Passive sentences, relative to active sentences, elicited greater activation in bilateral IFG and left temporo-occipital regions. Participant age did not significantly affect patterns of activation. Consistent with previous research, activation in left temporo-occipital cortex likely reflects thematic reanalysis processes, whereas, activation in the left IFG supports processing of complex syntax (i.e., NP-movement). Right IFG activation may reflect syntactic reanalysis processing demands associated with the sentence-picture verification task. PMID:24961525

  20. Inertial processing of vestibulo-ocular signals

    NASA Technical Reports Server (NTRS)

    Hess, B. J.; Angelaki, D. E.

    1999-01-01

    New evidence for a central resolution of gravito-inertial signals has been recently obtained by analyzing the properties of the vestibulo-ocular reflex (VOR) in response to combined lateral translations and roll tilts of the head. It is found that the VOR generates robust compensatory horizontal eye movements independent of whether or not the interaural translatory acceleration component is canceled out by a gravitational acceleration component due to simultaneous roll-tilt. This response property of the VOR depends on functional semicircular canals, suggesting that the brain uses both otolith and semicircular canal signals to estimate head motion relative to inertial space. Vestibular information about dynamic head attitude relative to gravity is the basis for computing head (and body) angular velocity relative to inertial space. Available evidence suggests that the inertial vestibular system controls both head attitude and velocity with respect to a gravity-centered reference frame. The basic computational principles underlying the inertial processing of otolith and semicircular canal afferent signals are outlined.

  1. An Introduction to Signal Processing in Chemical Analysis

    NSDL National Science Digital Library

    Professor Tom O'Haver

    This 26-page illustrated introduction to digital signal processing in chemical analysis covers signal arithmetic, signals and noise, smoothing, differentiation, resolution enhancement, harmonic analysis, convolution, deconvolution, Fourier filter, integration and peak area measurement, and curve fitting. It is accompanied by signal processing software for Macintosh with reference manual and tutorial (available for free download), video demonstrations, and Matlab signal processing modules for Mac, PC, and Unix.

  2. Processing, signaling, and physiological function of chemerin.

    PubMed

    Mattern, Andreas; Zellmann, Tristan; Beck-Sickinger, Annette G

    2014-01-01

    Chemerin is an immunomodulating factor secreted predominantly by adipose tissue and skin. Processed by a variety of proteases linked to inflammation, it activates the G-protein coupled receptor chemokine-like receptor 1 (CMKLR1) and induces chemotaxis in natural killer cells, macrophages, and immature dendritic cells. Recent developments revealed the role of the nonsignaling chemerin receptor C-C chemokine receptor-like 2 (CCRL2) in inflammation. Besides further research establishing its link to inflammatory skin conditions such as psoriasis, functions in healthy skin have also been reported. Here, the current understanding of chemerin processing, signaling and physiological function has been summarized, focusing on the regulation of its activity, its different receptors and its controversially discussed role in diseases. PMID:24446308

  3. Super-Nyquist signal transmission and digital signal processing

    NASA Astrophysics Data System (ADS)

    Zhang, Junwen; Yu, Jianjun; Chi, Nan

    2014-11-01

    Super-Nyquist, also known as Fast-than-Nyquist (FTN), signal generation based on optical or electrical spectrum shaping methods has been demonstrated to be an efficient scheme for future high-capacity transmission systems. Super- Nyquist signal demodulations based on maximum a posteriori (MAP) or maximum likelihood sequence estimation (MLSE) on receiver side have been demonstrated in 100G, 200G and 400G systems, which enables PDM-QPSK transmission with 4bit/s/Hz net spectral efficiency (SE) at lower OSNR requirement and longer transmission distance. Further studies also show the highly filtering-tolerant advantage of the super-Nyquist signal when using the 9-QAMbased multi-modulus equalization. This feature is quite useful for signals transmission under the aggressive optical filtering in multiple reconfigurable optical add-drop multiplexers (ROADMs) transmission link. In this paper, we review the newly reported super-Nyquist experiments using the optical super-Nyquist filtering 9-QAM like signals based on multi-modulus equalization (MMEQ). We directly recover the Nyquist filtered QPSK to a 9-QAM like signal. We first successfully transmitted 100-GHz-grid, 20 channels single-carrier 440-Gb/s super-Nyquist 9-QAM-like signal over 3600-km ultra-large effective-area fiber (ULAF) at record a net SE of 4b/s/Hz (after excluding the 7% hard-decision FEC overhead). The highly filtering-tolerant performance of the 9-QAM liked super-Nyquist signal is also experimentally demonstrated. Using this scheme, we then successfully transmit 10 channels 440-Gb/s signal over 3000- km ULAF and 10 cascaded ROADMs with 100-GHz-grid based on the single-carrier ETDM 110-GBaud QPSK. It is the highest baud rate of all-ETDM signal reported with the highest net SE at this baud rate for PDM-QPSK signal.

  4. GLAST Burst Monitor Signal Processing System

    SciTech Connect

    Bhat, P. Narayana; Briggs, Michael; Connaughton, Valerie; Paciesas, William; Preece, Robert [University of Alabama, NSSTC, 320 Sparkman Drive, Huntsville, AL 35805 (United States); Diehl, Roland; Greiner, Jochen; Kienlin, Andreas von; Lichti, Giselher; Steinle, Helmut [Max-Planck-Institute for Extraterrestrial Physics, Giessenbachstrasse 85748, Garching (Germany); Fishman, Gerald; Kouveliotou, Chryssa; Meegan, Charles; Wilson-Hodge, Colleen [Marshall Space Flight Center, VP62, Huntsville, AL 35812 (United States); Kippen, R. Marc [Los Alamos National Laboratory, ISR-1, MS B244, Los Alamos, NM 87545 (United States); Persyn, Steven [Southwest Research Institute, Dept. of Space Systems, 6220 Culebra Road, San Antonio, TX 78238 (United States)

    2007-07-12

    The onboard Data Processing Unit (DPU), designed and built by Southwest Research Institute, performs the high-speed data acquisition for GBM. The analog signals from each of the 14 detectors are digitized by high-speed multichannel analog data acquisition architecture. The streaming digital values resulting from a periodic (period of 104.2 ns) sampling of the analog signal by the individual ADCs are fed to a Field-Programmable Gate Array (FPGA). Real-time Digital Signal Processing (DSP) algorithms within the FPGA implement functions like filtering, thresholding, time delay and pulse height measurement. The spectral data with a 12-bit resolution are formatted according to the commandable look-up-table (LUT) and then sent to the High-Speed Science-Date Bus (HSSDB, speed=1.5 MB/s) to be telemetered to ground. The DSP offers a novel feature of a commandable and constant event deadtime. The ADC non-linearities have been calibrated so that the spectral data can be corrected during analysis. The best temporal resolution is 2 {mu}s for the pre-burst and post-trigger time-tagged events (TTE) data. The time resolution of the binned data types is commandable from 64 msec to 1.024 s for the CTIME data (8 channel spectral resolution) and 1.024 to 32.768 s for the CSPEC data (128 channel spectral resolution). The pulse pile-up effects have been studied by Monte Carlo simulations. For a typical GRB, the possible shift in the Epeak value at high-count rates ({approx}100 kHz) is {approx}1% while the change in the single power-law index could be up to 5%.

  5. GLAST Burst Monitor Signal Processing System

    NASA Astrophysics Data System (ADS)

    Bhat, P. Narayana; Briggs, Michael; Connaughton, Valerie; Diehl, Roland; Fishman, Gerald; Greiner, Jochen; Kippen, R. Marc; von Kienlin, Andreas; Kouveliotou, Chryssa; Lichti, Giselher; Meegan, Charles; Paciesas, William; Persyn, Steven; Preece, Robert; Steinle, Helmut; Wilson-Hodge, Colleen

    2007-07-01

    The onboard Data Processing Unit (DPU), designed and built by Southwest Research Institute, performs the high-speed data acquisition for GBM. The analog signals from each of the 14 detectors are digitized by high-speed multichannel analog data acquisition architecture. The streaming digital values resulting from a periodic (period of 104.2 ns) sampling of the analog signal by the individual ADCs are fed to a Field-Programmable Gate Array (FPGA). Real-time Digital Signal Processing (DSP) algorithms within the FPGA implement functions like filtering, thresholding, time delay and pulse height measurement. The spectral data with a 12-bit resolution are formatted according to the commandable look-up-table (LUT) and then sent to the High-Speed Science-Date Bus (HSSDB, speed=1.5 MB/s) to be telemetered to ground. The DSP offers a novel feature of a commandable & constant event deadtime. The ADC non-linearities have been calibrated so that the spectral data can be corrected during analysis. The best temporal resolution is 2 ?s for the pre-burst & post-trigger time-tagged events (TTE) data. The time resolution of the binned data types is commandable from 64 msec to 1.024 s for the CTIME data (8 channel spectral resolution) and 1.024 to 32.768 s for the CSPEC data (128 channel spectral resolution). The pulse pile-up effects have been studied by Monte Carlo simulations. For a typical GRB, the possible shift in the Epeak value at high-count rates (~100 kHz) is ~1% while the change in the single power-law index could be up to 5%.

  6. Active voltammetric microsensors with neural signal processing.

    SciTech Connect

    Vogt, M. C.

    1998-12-11

    Many industrial and environmental processes, including bioremediation, would benefit from the feedback and control information provided by a local multi-analyte chemical sensor. For most processes, such a sensor would need to be rugged enough to be placed in situ for long-term remote monitoring, and inexpensive enough to be fielded in useful numbers. The multi-analyte capability is difficult to obtain from common passive sensors, but can be provided by an active device that produces a spectrum-type response. Such new active gas microsensor technology has been developed at Argonne National Laboratory. The technology couples an electrocatalytic ceramic-metallic (cermet) microsensor with a voltammetric measurement technique and advanced neural signal processing. It has been demonstrated to be flexible, rugged, and very economical to produce and deploy. Both narrow interest detectors and wide spectrum instruments have been developed around this technology. Much of this technology's strength lies in the active measurement technique employed. The technique involves applying voltammetry to a miniature electrocatalytic cell to produce unique chemical ''signatures'' from the analytes. These signatures are processed with neural pattern recognition algorithms to identify and quantify the components in the analyte. The neural signal processing allows for innovative sampling and analysis strategies to be employed with the microsensor. In most situations, the whole response signature from the voltammogram can be used to identify, classify, and quantify an analyte, without dissecting it into component parts. This allows an instrument to be calibrated once for a specific gas or mixture of gases by simple exposure to a multi-component standard rather than by a series of individual gases. The sampled unknown analytes can vary in composition or in concentration, the calibration, sensing, and processing methods of these active voltammetric microsensors can detect, recognize, and quantify different signatures and support subsequent analyses. The instrument can be trained to recognize and report expected analyte components (within some tolerance), but also can alarm when unexpected components are detected. Unknowns can be repeat-sampled to build a reference library for later post processing and verification.

  7. Correlation of GPS signal fades due to ionospheric scintillation for aviation applications

    NASA Astrophysics Data System (ADS)

    Seo, Jiwon; Walter, Todd; Enge, Per

    2011-05-01

    Deep and frequent Global Positioning System (GPS) signal fading due to strong ionospheric scintillation is a major concern for GPS-guided aviation in equatorial areas during high solar activity. A GPS aviation receiver may lose carrier tracking lock under deep fading, and a lost channel cannot be used for position calculation until lock is reestablished. Hence, frequent loss of lock due to frequent fading can significantly reduce the availability of GPS aviation. However, the geometric diversity of the satellites can mitigate scintillation impact on GPS aviation depending on the correlation level of deep fades between satellites. This paper proposes a metric to measure the correlation level of two fading channels from the perspective of GPS aviation. Using this metric, the satellite-to-satellite correlation is studied based on real scintillation data. The low satellite-to-satellite correlation shown in this paper envisions notable availability benefit from the geometric diversity of satellites under strong scintillation. In addition, this paper proposes a way to generate correlated fading processes with arbitrary correlation coefficients. Using this correlated fading process model, the availability of Localizer Performance with Vertical guidance (LPV)-200 under severe scintillation scenarios is analyzed. The result emphasizes the importance of a fast reacquisition capability of an aviation receiver after a brief outage, which is not currently mandated by the aviation receiver performance standards.

  8. Signal Processing on Graphs: Recent Results, Challenges and Applications 1

    E-print Network

    Ortega, Antonio

    Signal Processing on Graphs: Recent Results, Challenges and Applications 1 Antonio Ortega Signal Processing on Graphs Sept. 2013 1 / 81 #12;Acknowledgements Collaborators - Dr. Sunil Narang (Microsoft) - Dr-1018977 A. Ortega (USC) Signal Processing on Graphs Sept. 2013 2 / 81 #12;Introduction Next Section 1

  9. The Factor Graph Approach to Model-Based Signal Processing

    E-print Network

    Loeliger, Hans-Andrea

    INVITED P A P E R The Factor Graph Approach to Model-Based Signal Processing Factor graphs can; factor graphs; graphical models; Kalman filtering; message passing; signal processing I. INTRODUCTION with an emphasis on signal processing. We hope to convey that factor graphs continue to grow more useful

  10. Signal processing issues in reflection tomography

    NASA Astrophysics Data System (ADS)

    Cadalli, Nail

    2001-12-01

    This dissertation focuses on signal modeling and processing issues of the following problems in reflection tomography: synthetic aperture radar (SAR) imaging of a runway and surroundings from an aircraft approaching for landing, acoustic imaging of objects buried in soil, and lidar imaging of underwater objects. The highly squinted geometry of runway imaging necessitates the incorporation of wavefront curvature into the signal model. We investigate the feasibility of using the wavenumber-domain (? - k) SAR inversion algorithm, which models the actual curvature of the wavefront, for runway imaging. We demonstrate the aberrations that the algorithm can produce when the squint angle is close to 90° and show that high-quality reconstruction is still possible provided that the interpolation is performed accurately enough, which can be achieved by increasing the temporal sampling rate. We compare the performance with that of a more general inversion method (GIM) that solves the measurement equation directly. The performances of both methods are comparable in the noise- free case. Being inherently robust to noise, GIM produces superior results in the noisy case. We also present a solution to the left-right ambiguity of runway imaging using interferometric processing. In imaging of objects buried in soil, we pursue an acoustic approach primarily for detection and imaging of cultural artifacts. We have developed a mathematical model and associated computer software in order to simulate the signals acquired by the actual experimental system, and a bistatic SAR-type algorithm for reconstruction. In the reconstructions from simulated data, objects were detectable, but near-field objects suffered from shifts and smears. To account for wavefront curvature, we formulated processing of the simulated data using the 3-D version of the monostatic ? - k algorithm. In lidar imaging of underwater objects, we formulate the problem as a 3-D tomographic reconstruction problem. We have developed software to simulate lidar returns at airborne receivers using the bistatic lidar return equations. Our simulator can model multiple scattering and absorption for various water types and system parameters. Our simulated data fits the characteristics of real data very well. We present our reconstruction results from the simulated and real data, and comparatively discuss the reconstructions.

  11. Ultrasonic signal processing and tissue characterization

    NASA Astrophysics Data System (ADS)

    Mu, Zhiping

    Ultrasound imaging has become one of the most widely used diagnostic tools in medicine. While it has advantages, compared with other modalities, in terms of safety, low-cost, accessibility, portability and capability of real-time imaging, it has limitations. One of the major disadvantages of ultrasound imaging is the relatively low image quality, especially the low signal-to-noise ratio (SNR) and the low spatial resolution. Part of this dissertation is dedicated to the development of digital ultrasound signal and image processing methods to improve ultrasound image quality. Conventional B-mode ultrasound systems display the demodulated signals, i.e., the envelopes, in the images. In this dissertation, I introduce the envelope matched quadrature filtering (EMQF) technique, which is a novel demodulation technique generating optimal performance in envelope detection. In ultrasonography, the echo signals are the results of the convolution of the pulses and the medium responses, and the finite pulse length is a major source of the degradation of the image resolution. Based on the more appropriate complex-valued medium response assumption rather than the real-valued assumption used by many researchers, a nonparametric iterative deconvolution method, the Least Squares method with Point Count regularization (LSPC), is proposed. This method was tested using simulated and experimental data, and has produced excellent results showing significant improvements in resolution. During the past two decades, ultrasound tissue characterization (UTC) has emerged as an active research field and shown potentials of applications in a variety of clinical areas. Particularly interesting to me is a group of methods characterizing the scatterer spatial distribution. For resolvable regular structures, a deconvolution based method is proposed to estimate parameters characterizing such structures, including mean scatterer spacing, and has demonstrated superior performance when compared to conventional methods in situations of small data segments and highly randomized scatterer distribution. For non-resolvable structures, based on the idea of analyzing the distribution of large-valued signal points, several features, referred to as the DLP features, are extracted from the signals and used to characterize the scatterer number density (SND) of the tissues. The idea is further extended to characterize inhomogeneous tissues that are better represented by composite scatterer models and found successful as well. A variety of physiological, histo-chemical, and morphological changes take place in skeletal muscles while aging. To apply the UTC techniques to study aging effects in skeletal muscles, in vitro experiments were made using extensor digitorum longus (primarily type II fibers), soleus (primarily type I), and quadriceps (mixed) muscles dissected from rats of three age groups (young, middle-aged, and old). Ultrasound RF signals were collected, and the attenuation coefficients and the DLP features were computed. Statistical analysis finds some significant differences between the features of different muscles in the same age group and between the features of the same muscles in different age groups. These findings are presented in chapter 5 and are consistent with the age-related changes previously observed and the behavior of the UTC features, showing the potential to develop UTC techniques as economical, easily accessible, and noninvasive tools for muscle condition evaluation.

  12. Method and apparatus for improving resolution in spectrometers processing output steps from non-ideal signal sources

    DOEpatents

    Warburton, William K.; Momayezi, Michael

    2006-06-20

    A method and apparatus for processing step-like output signals (primary signals) generated by non-ideal, for example, nominally single-pole ("N-1P ") devices. An exemplary method includes creating a set of secondary signals by directing the primary signal along a plurality of signal paths to a signal summation point, summing the secondary signals reaching the signal summation point after propagating along the signal paths to provide a summed signal, performing a filtering or delaying operation in at least one of said signal paths so that the secondary signals reaching said summing point have a defined time correlation with respect to one another, applying a set of weighting coefficients to the secondary signals propagating along said signal paths, and performing a capturing operation after any filtering or delaying operations so as to provide a weighted signal sum value as a measure of the integrated area QgT of the input signal.

  13. Nonlinear biochemical signal processing via noise propagation

    NASA Astrophysics Data System (ADS)

    Kim, Kyung Hyuk; Qian, Hong; Sauro, Herbert M.

    2013-10-01

    Single-cell studies often show significant phenotypic variability due to the stochastic nature of intra-cellular biochemical reactions. When the numbers of molecules, e.g., transcription factors and regulatory enzymes, are in low abundance, fluctuations in biochemical activities become significant and such "noise" can propagate through regulatory cascades in terms of biochemical reaction networks. Here we develop an intuitive, yet fully quantitative method for analyzing how noise affects cellular phenotypes based on identifying a system's nonlinearities and noise propagations. We observe that such noise can simultaneously enhance sensitivities in one behavioral region while reducing sensitivities in another. Employing this novel phenomenon we designed three biochemical signal processing modules: (a) A gene regulatory network that acts as a concentration detector with both enhanced amplitude and sensitivity. (b) A non-cooperative positive feedback system, with a graded dose-response in the deterministic case, that serves as a bistable switch due to noise-induced ultra-sensitivity. (c) A noise-induced linear amplifier for gene regulation that requires no feedback. The methods developed in the present work allow one to understand and engineer nonlinear biochemical signal processors based on fluctuation-induced phenotypes.

  14. A Novel Approach for Adaptive Signal Processing

    NASA Technical Reports Server (NTRS)

    Chen, Ya-Chin; Juang, Jer-Nan

    1998-01-01

    Adaptive linear predictors have been used extensively in practice in a wide variety of forms. In the main, their theoretical development is based upon the assumption of stationarity of the signals involved, particularly with respect to the second order statistics. On this basis, the well-known normal equations can be formulated. If high- order statistical stationarity is assumed, then the equivalent normal equations involve high-order signal moments. In either case, the cross moments (second or higher) are needed. This renders the adaptive prediction procedure non-blind. A novel procedure for blind adaptive prediction has been proposed and considerable implementation has been made in our contributions in the past year. The approach is based upon a suitable interpretation of blind equalization methods that satisfy the constant modulus property and offers significant deviations from the standard prediction methods. These blind adaptive algorithms are derived by formulating Lagrange equivalents from mechanisms of constrained optimization. In this report, other new update algorithms are derived from the fundamental concepts of advanced system identification to carry out the proposed blind adaptive prediction. The results of the work can be extended to a number of control-related problems, such as disturbance identification. The basic principles are outlined in this report and differences from other existing methods are discussed. The applications implemented are speech processing, such as coding and synthesis. Simulations are included to verify the novel modelling method.

  15. Phase correlation processing for DPIV measurements

    Microsoft Academic Search

    Adric C. Eckstein; John Charonko; Pavlos Vlachos

    2008-01-01

    A novel digital particle image velocimetry (DPIV) correlation method is presented, the Gaussian transformed phase correlation\\u000a (GTPC) estimator, using nonlinear filtering techniques coupled with the phase-transform (PHAT) generalized cross-correlation\\u000a filter. The use of spatial windowing is shown to be ideally suited for the use of phase correlation estimators, due to their\\u000a invariance to the loss of correlation effects. Error analysis

  16. Monte Carlo methods for signal processing: a review in the statistical signal processing context

    Microsoft Academic Search

    A. Doucet; Xiaodong Wang

    2005-01-01

    In this article, MCMC (Markov chain Monte Carlo methods) and SMC (sequential Monte Carlo methods) are introduced to sample and\\/or maximize high-dimensional probability distributions. These methods enable to perform likelihood or Bayesian inference for complex non-Gaussian signal processing problems.

  17. Signal processing of aircraft flyover noise

    NASA Technical Reports Server (NTRS)

    Kelly, Jeffrey J.

    1991-01-01

    A detailed analysis of signal processing concerns for measuring aircraft flyover noise is presented. Development of a de-Dopplerization scheme for both corrected time history and spectral data is discussed along with an analysis of motion effects on measured spectra. A computer code was written to implement the de-Dopplerization scheme. Input to the code is the aircraft position data and the pressure time histories. To facilitate ensemble averaging, a uniform level flyover is considered but the code can accept more general flight profiles. The effects of spectral smearing and its removal is discussed. Using data acquired from XV-15 tilt rotor flyover test comparisons are made showing the measured and corrected spectra. Frequency shifts are accurately accounted for by the method. It is shown that correcting for spherical spreading, Doppler amplitude, and frequency can give some idea about source directivity. The analysis indicated that smearing increases with frequency and is more severe on approach than recession.

  18. Signal Processing Issues in Fourier Transform Spectrometers

    NASA Astrophysics Data System (ADS)

    Hayes, Monson H.

    2002-12-01

    There are a number of interesting and challenging signal processing problems related to the design of a Fourier Transform Spectrometer (FTS). In this project, we look at a few of these problems in two different types of spectrometers-the Geostationary Imaging Fourier Transform Spectrometer (GIFTS), and a Far Infrared (FIR) FTS. One of the si nal processing challenges in GIFTS is the reduction of the massive data rate (2.4 x 109 bps) to an affordable telemetry rate of less than 60 Mbps. Since the GIFTS interferograms are heavily over-sampled, the first step is to decimate (down-sample) the interferograms with minimal distortion while keeping the signal processing algorithms simple enough to be implemented in the GIFTS hardware. Therefore, the first problem we looked at was the design of the decimation filters. Specifically, we performed a detailed analysis of two competing approaches that were being considered. The first, proposed by the Space Dynamics Lab (SDL), was to use a double sideband (real) band-pass filter. The second, proposed by Lincoln Laboratories (LL), was to use a single sideband (complex) band-pass filter. What the study showed was that a complex filter (LL approach) results in a savings of about 25% in the filtering requirements for the long-wave band, while in the mid-wave band the savings are approximately 50%. As a result, the decision was made to use a complex filter. Once the decision to use a complex filter had been made, we looked at some of the consequences of this decision. The most significant of these was the discovery that, with a complex filter, it is possible to extend the long-wave IR band beyond the folding frequency of 1174/cm and recover the SO2 line at 1176.5/cm. What this requires is the design of a band-pass decimation filter with a wider passband, and consequently of higher order. Specifically, it was shown that with about 25% more filter operations, the elusive SO2 line, believed to be irretrievable, could in fact be recovered. While working on the decimation filtering requirements, an issue arose with respect to how the 16-bit long-wave interferogram data should be processed by a 15-bit USES chip. There were two approaches being considered, and each one had at least one serious drawback. Therefore, given the nature of the data that is to be processed by the USES chip, we developed an efficient loss-less encoder that is robust to errors, and is easily decoded. Since the encoder eliminates the drawbacks of the other two approaches, and greatly simplifies the signal processing requirements, the downlink board is currently being redesigned to include this encoder. The last problem that was looked at involved an investigation into the optimum sampling strategy in the design of a far infrared FTS. The problem was to minimize the amount of spectral noise that is induced by non-uniform mirror velocity.

  19. Neural correlates of abstract verb processing.

    PubMed

    Rodríguez-Ferreiro, Javier; Gennari, Silvia P; Davies, Robert; Cuetos, Fernando

    2011-01-01

    The present study investigated the neural correlates of the processing of abstract (low imageability) verbs. An extensive body of literature has investigated concrete versus abstract nouns but little is known about how abstract verbs are processed. Spanish abstract verbs including emotion verbs (e.g., amar, "to love"; molestar, "to annoy") were compared to concrete verbs (e.g., llevar, "to carry"; arrastrar, "to drag"). Results indicated that abstract verbs elicited stronger activity in regions previously associated with semantic retrieval such as inferior frontal, anterior temporal, and posterior temporal regions, and that concrete and abstract activation networks (compared to that of pseudoverbs) were partially distinct, with concrete verbs eliciting more posterior activity in these regions. In contrast to previous studies investigating nouns, verbs strongly engage both left and right inferior frontal gyri, suggesting, as previously found, that right prefrontal cortex aids difficult semantic retrieval. Together with previous evidence demonstrating nonverbal conceptual roles for the active regions as well as experiential content for abstract word meanings, our results suggest that abstract verbs impose greater demands on semantic retrieval or property integration, and are less consistent with the view that abstract words recruit left-lateralized regions because they activate verbal codes or context, as claimed by proponents of the dual-code theory. Moreover, our results are consistent with distributed accounts of semantic memory because distributed networks may coexist with varying retrieval demands. PMID:20044889

  20. Neural correlates of implicit and explicit combinatorial semantic processing

    PubMed Central

    Graves, William W.; Binder, Jeffrey R.; Desai, Rutvik H.; Conant, Lisa L.; Seidenberg, Mark S.

    2010-01-01

    Language consists of sequences of words, but comprehending phrases involves more than concatenating meanings: A boat house is a shelter for boats, whereas a summer house is a house used during summer, and a ghost house is typically uninhabited. Little is known about the brain bases of combinatorial semantic processes. We performed two fMRI experiments using familiar, highly meaningful phrases (LAKE HOUSE) and unfamiliar phrases with minimal meaning created by reversing the word order of the familiar items (HOUSE LAKE). The first experiment used a 1-back matching task to assess implicit semantic processing, and the second used a classification task to engage explicit semantic processing. These conditions required processing of the same words, but with more effective combinatorial processing in the meaningful condition. The contrast of meaningful versus reversed phrases revealed activation primarily during the classification task, to a greater extent in the right hemisphere, including right angular gyrus, dorsomedial prefrontal cortex, and bilateral posterior cingulate/precuneus, areas previously implicated in semantic processing. Positive correlations of fMRI signal with lexical (word-level) frequency occurred exclusively with the 1-back task and to a greater spatial extent on the left, including left posterior middle temporal gyrus and bilateral parahippocampus. These results reveal strong effects of task demands on engagement of lexical versus combinatorial processing and suggest a hemispheric dissociation between these levels of semantic representation. PMID:20600969

  1. Biologically-based signal processing system applied to noise removal for signal extraction

    DOEpatents

    Fu, Chi Yung; Petrich, Loren I.

    2004-07-13

    The method and system described herein use a biologically-based signal processing system for noise removal for signal extraction. A wavelet transform may be used in conjunction with a neural network to imitate a biological system. The neural network may be trained using ideal data derived from physical principles or noiseless signals to determine to remove noise from the signal.

  2. Optimization of signal processing software for control system implementation

    Microsoft Academic Search

    Shuvra S. Bhattacharyya; William S. Levine

    2006-01-01

    Signal processing plays a fundamental role in the design of control systems — the portion of a digitally-implemented control system between the sensor outputs and the actuator inputs is precisely a digital signal processor (DSP). Consequently, effective techniques for design and optimization of signal processing software are important in achieving efficient controller implementations. Motivated by these relationships, this paper reviews

  3. Pedagogical reforms of digital signal processing education

    NASA Astrophysics Data System (ADS)

    Christensen, Michael

    The future of the engineering discipline is arguably predicated heavily upon appealing to the future generation, in all its sensibilities. The greatest burden in doing so, one might rightly believe, lies on the shoulders of the educators. In examining the causal means by which the profession arrived at such a state, one finds that the technical revolution, precipitated by global war, had, as its catalyst, institutions as expansive as the government itself to satisfy the demand for engineers, who, as a result of such an existential crisis, were taught predominantly theoretical underpinnings to address a finite purpose. By contrast, the modern engineer, having expanded upon this vision and adapted to an evolving society, is increasingly placed in the proverbial role of the worker who must don many hats: not solely a scientist, yet often an artist; not a businessperson alone, but neither financially naive; not always a representative, though frequently a collaborator. Inasmuch as change then serves as the only constancy in a global climate, therefore, the educational system - if it is to mimic the demands of the industry - is left with an inherent need for perpetual revitalization to remain relevant. This work aims to serve that end. Motivated by existing research in engineering education, an epistemological challenge is molded into the framework of the electrical engineer with emphasis on digital signal processing. In particular, it is investigated whether students are better served by a learning paradigm that tolerates and, when feasible, encourages error via a medium free of traditional adjudication. Through the creation of learning modules using the Adobe Captivate environment, a wide range of fundamental knowledge in signal processing is challenged within the confines of existing undergraduate courses. It is found that such an approach not only conforms to the research agenda outlined for the engineering educator, but also reflects an often neglected reality: that the student who is free to be creative, free to err, and free to self-correct is emblematic of the profession -- past, present, and future -- to which he or she unwittingly aspires.

  4. Coherent signal processing in optical coherence tomography

    NASA Astrophysics Data System (ADS)

    Kulkarni, Manish Dinkarrao

    1999-09-01

    Optical coherence tomography (OCT) is a novel method for non-invasive sub-surface imaging of biological tissue micro-structures. OCT achieves high spatial resolution ( ~ 15 m m in three dimensions) using a fiber-optically integrated system which is suitable for application in minimally invasive diagnostics, including endoscopy. OCT uses an optical heterodyne detection technique based on white light interferometry. Therefore extremely faint reflections ( ~ 10 fW) are routinely detected with high spatial localization. The goal of this thesis is twofold. The first is to present a theoretical model for describing image formation in OCT, and attempt to enhance the current level of understanding of this new modality. The second objective is to present signal processing methods for improving OCT image quality. We present deconvolution algorithms to obtain improved longitudinal resolution in OCT. This technique may be implemented without increasing system complexity as compared to current clinical OCT systems. Since the spectrum of the light backscattered from bio-scatterers is closely associated with ultrastructural variations in tissue, we propose a new technique for measuring spectra as a function of depth. This advance may assist OCT in differentiating various tissue types and detecting abnormalities within a tissue. In addition to depth resolved spectroscopy, Doppler processing of OCT signals can also improve OCT image contrast. We present a new technique, termed color Doppler OCT (CDOCT). It is an innovative extension of OCT for performing spatially localized optical Doppler velocimetry. Micron-resolution imaging of blood flow in sub-surface vessels in living tissue using CDOCT is demonstrated. The fundamental issues regarding the trade- off between the velocity estimation precision and image acquisition rate are presented. We also present novel algorithms for high accuracy velocity estimation. In many blood vessels velocities tend to be on the order of a few cm/s. In many cardiologic applications, it would be useful to measure shear rates in medium and large blood vessels. Therefore new algorithms for velocity imaging in blood vessels with very high flow rates are described.

  5. Overview of seismic signal processing equipment and procedures

    SciTech Connect

    Igusa, T.; Lum, P.K.W.

    1986-01-01

    The report provides a brief overview of the automatic data processing equipment (ADPE) and procedures used for processing seismic signals. The discussion includes basic information on the seismic recording systems and stations; a brief description of hardware, hardware configurations, and software; data formats; processing techniques used to convert seismic signals to computer-compatible format; and basic procedures for analysis of the processed signals. 8 refs., 8 figs., 2 tabs.

  6. Signal-to-noise ratio limitations for intensity correlation imaging.

    PubMed

    Fried, David L; Riker, Jim; Agrawal, Brij

    2014-07-01

    Intensity correlation imaging (ICI) is a concept which has been considered for the task of providing images of satellites in geosynchronous orbit using ground-based equipment. This concept is based on the intensity interferometer principle first developed by Hanbury Brown and Twiss. It is the objective of this paper to establish that a sun-lit geosynchronous satellite is too faint a target object to allow intensity interferometry to be used in developing image information about it-at least not in a reasonable time and with a reasonable amount of equipment. An analytic treatment of the basic phenomena is presented. This is an analysis of one aspect of the statistics of the very high frequency random variations of a very narrow portion of the optical spectra of the incoherent (black-body like-actually reflected sunlight) radiation from the satellite, an analysis showing that the covariance of this radiation as measured by a pair of ground-based telescopes is directly proportional to the square of the magnitude of one component of the Fourier transform of the image of the satellite-the component being the one for a spatial frequency whose value is determined by the separation of the two telescopes. This analysis establishes the magnitude of the covariance. A second portion of the analysis considers shot-noise effects. It is shown that even with much less than one photodetection event (pde) per signal integration time an unbiased estimate of the covariance of the optical field's random variations can be developed. Also, a result is developed for the standard deviation to be associated with the estimated value of the covariance. From these results an expression is developed for what may be called the signal-to-noise ratio to be associated with an estimate of the covariance. This signal-to-noise ratio, it turns out, does not depend on the measurement's integration time, ?t (in seconds), or on the optical spectral bandwidth, ?? (in Hertz), utilized-so long as ?t???1, which condition it would be hard to violate. It is estimated that for a D=3.16 m diameter satellite, with a pair of D=1.0 m diameter telescopes (which value of D probably represents an upper limit on allowable aperture diameter since the telescope aperture must be much too small to even resolve the size of the satellite) at least N=2.55×10(16) separate pairs of (one integration time, pde count) measurement values must be collected to achieve just a 10 dB signal-to-noise ratio. Working with 10 pairs of telescopes (all with the same separation), and with 10 nearly adjacent and each very narrow spectral bands extracted from the light collected by each of the telescope-so that for each measurement integration time there would be 100 pairs of measurement values available-and with an integration time as short as ?t=1 ns, it would take T=2.55×10(5) s or about 71 h to collect the data for just a single spatial frequency component of the image of the satellite. It is on this basis that it is concluded that the ICI concept does not seem likely to be able to provide a timely responsive capability for the imaging of geosynchronous satellites. PMID:25121442

  7. Spatial acoustic signal processing for immersive communication

    NASA Astrophysics Data System (ADS)

    Atkins, Joshua

    Computing is rapidly becoming ubiquitous as users expect devices that can augment and interact naturally with the world around them. In these systems it is necessary to have an acoustic front-end that is able to capture and reproduce natural human communication. Whether the end point is a speech recognizer or another human listener, the reduction of noise, reverberation, and acoustic echoes are all necessary and complex challenges. The focus of this dissertation is to provide a general method for approaching these problems using spherical microphone and loudspeaker arrays.. In this work, a theory of capturing and reproducing three-dimensional acoustic fields is introduced from a signal processing perspective. In particular, the decomposition of the spatial part of the acoustic field into an orthogonal basis of spherical harmonics provides not only a general framework for analysis, but also many processing advantages. The spatial sampling error limits the upper frequency range with which a sound field can be accurately captured or reproduced. In broadband arrays, the cost and complexity of using multiple transducers is an issue. This work provides a flexible optimization method for determining the location of array elements to minimize the spatial aliasing error. The low frequency array processing ability is also limited by the SNR, mismatch, and placement error of transducers. To address this, a robust processing method is introduced and used to design a reproduction system for rendering over arbitrary loudspeaker arrays or binaurally over headphones. In addition to the beamforming problem, the multichannel acoustic echo cancellation (MCAEC) issue is also addressed. A MCAEC must adaptively estimate and track the constantly changing loudspeaker-room-microphone response to remove the sound field presented over the loudspeakers from that captured by the microphones. In the multichannel case, the system is overdetermined and many adaptive schemes fail to converge to the true impulse response. This forces the need to track both the near and far end room responses. A transform domain method that mitigates this problem is derived and implemented. Results with a real system using a 16-channel loudspeaker array and 32-channel microphone array are presented.

  8. Optimal signal processing for continuous qubit readout

    NASA Astrophysics Data System (ADS)

    Ng, Shilin; Tsang, Mankei

    2014-08-01

    The measurement of a quantum two-level system, or a qubit in modern terminology, often involves an electromagnetic field that interacts with the qubit, before the field is measured continuously and the qubit state is inferred from the noisy field measurement. During the measurement, the qubit may undergo spontaneous transitions, further obscuring the initial qubit state from the observer. Taking advantage of some well-known techniques in stochastic detection theory, here we propose a signal processing protocol that can infer the initial qubit state optimally from the measurement in the presence of noise and qubit dynamics. Assuming continuous quantum-nondemolition measurements with Gaussian or Poissonian noise and a classical Markov model for the qubit, we derive analytic solutions to the protocol in some special cases of interest using It? calculus. Our method is applicable to multihypothesis testing for robust qubit readout and relevant to experiments on qubits in superconducting microwave circuits, trapped ions, nitrogen-vacancy centers in diamond, semiconductor quantum dots, or phosphorus donors in silicon.

  9. Integrated optical signal processing with magnetostatic waves

    NASA Technical Reports Server (NTRS)

    Fisher, A. D.; Lee, J. N.

    1984-01-01

    Magneto-optical devices based on Bragg diffraction of light by magnetostatic waves (MSW's) offer the potential of large time-bandwidth optical signal processing at microwave frequencies of 1 to 20 GHz and higher. A thin-film integrated-optical configuration, with the interacting MSW and guided-optical wave both propagating in a common ferrite layer, is necessary to avoid shape-factor demagnetization effects. The underlying theory of the MSW-optical interaction is outlined, including the development of expressions for optical diffraction efficiency as a function of MSW power and other relevant parameters. Bradd diffraction of guided-optical waves by transversely-propagating magnetostatic waves and collinear TE/TM mode conversion included by MSW's have been demonstrated in yttrium iron garnet (YIG) thin films. Diffraction levels as large as 4% (7 mm interaction length) and a modulation dynamic range of approx 30 dB have been observed. Advantages of these MSW-based devices over the analogous acousto-optical devices include: much greater operating frequencies, tunability of the MSW dispersion relation by varying either the RF frequency or the applied bias magnetic field, simple broad-band MSW transducer structures (e.g., a single stripline), and the potential for very high diffraction efficiencies.

  10. Optimal signal processing for continuous qubit readout

    E-print Network

    Shilin Ng; Mankei Tsang

    2014-08-06

    The measurement of a quantum two-level system, or a qubit in modern terminology, often involves an electromagnetic field that interacts with the qubit, before the field is measured continuously and the qubit state is inferred from the noisy field measurement. During the measurement, the qubit may undergo spontaneous transitions, further obscuring the initial qubit state from the observer. Taking advantage of some well known techniques in stochastic detection theory, here we propose a novel signal processing protocol that can infer the initial qubit state optimally from the measurement in the presence of noise and qubit dynamics. Assuming continuous quantum-nondemolition measurements with Gaussian or Poissonian noise and a classical Markov model for the qubit, we derive analytic solutions to the protocol in some special cases of interest using It\\={o} calculus. Our method is applicable to multi-hypothesis testing for robust qubit readout and relevant to experiments on qubits in superconducting microwave circuits, trapped ions, nitrogen-vacancy centers in diamond, semiconductor quantum dots, or phosphorus donors in silicon.

  11. Wavelet-based statistical signal processing using hidden Markov models

    Microsoft Academic Search

    Matthew S. Crouse; Robert D. Nowak; Richard G. Baraniuk

    1998-01-01

    Wavelet-based statistical signal processing techniques such as denoising and detection typically model the wavelet coefficients as independent or jointly Gaussian. These models are unrealistic for many real-world signals. We develop a new framework for statistical signal processing based on wavelet-domain hidden Markov models (HMMs) that concisely models the statistical dependencies and non-Gaussian statistics encountered in real-world signals. Wavelet-domain HMMs are

  12. Processing Motion Signals in Complex Environments

    NASA Technical Reports Server (NTRS)

    Verghese, Preeti

    2000-01-01

    Motion information is critical for human locomotion and scene segmentation. Currently we have excellent neurophysiological models that are able to predict human detection and discrimination of local signals. Local motion signals are insufficient by themselves to guide human locomotion and to provide information about depth, object boundaries and surface structure. My research is aimed at understanding the mechanisms underlying the combination of motion signals across space and time. A target moving on an extended trajectory amidst noise dots in Brownian motion is much more detectable than the sum of signals generated by independent motion energy units responding to the trajectory segments. This result suggests that facilitation occurs between motion units tuned to similar directions, lying along the trajectory path. We investigated whether the interaction between local motion units along the motion direction is mediated by contrast. One possibility is that contrast-driven signals from motion units early in the trajectory sequence are added to signals in subsequent units. If this were the case, then units later in the sequence would have a larger signal than those earlier in the sequence. To test this possibility, we compared contrast discrimination thresholds for the first and third patches of a triplet of sequentially presented Gabor patches, aligned along the motion direction. According to this simple additive model, contrast increment thresholds for the third patch should be higher than thresholds for the first patch.The lack of a measurable effect on contrast thresholds for these various manipulations suggests that the pooling of signals along a trajectory is not mediated by contrast-driven signals. Instead, these results are consistent with models that propose that the facilitation of trajectory signals is achieved by a second-level network that chooses the strongest local motion signals and combines them if they occur in a spatio-temporal sequence consistent with a trajectory. These results parallel the lack of increased apparent contrast along a static contour made up of similarly oriented elements.

  13. The use of digital signal processors (DSPs) in real-time processing of multi-parametric bioelectronic signals.

    PubMed

    Ressler, Johann; Dirscherl, Andreas; Grothe, Helmut; Wolf, Bernhard

    2007-02-01

    In many cases of bioanalytical measurement, calculation of large amounts of data, analysis of complex signal waveforms or signal speed can overwhelm the performance of microcontrollers, analog electronic circuits or even PCs. One method to obtain results in real time is to apply a digital signal processor (DSP) for the analysis or processing of measurement data. In this paper we show how DSP-supported multiplying and accumulating (MAC) operations, such as time/frequency transformation, pattern recognition by correlation, convolution or filter algorithms, can optimize the processing of bioanalytical data. Discrete integral calculations are applied to the acquisition of impedance values as part of multi-parametric sensor chips, to pH monitoring using light-addressable potentiometric sensors (LAPS) and to the analysis of rapidly changing signal shapes, such as action potentials of cultured neuronal networks, as examples of DSP capability. PMID:17313351

  14. International Scholarly Research Network ISRN Signal Processing

    E-print Network

    Boyer, Edmond

    1 Laboratoire Images, Signaux et Syst´emes Intelligents (LISSI-E.A.3956), Universit´e Paris Est Cr reconstruction or denoising aim, in some examples using artificial and pathological signals. 1. Introduction of signals have like pursuit methods [3], the Poper Orthogonal Decomposition (POD) [4], or Singular Value

  15. Accelerating radio astronomy cross-correlation with graphics processing units

    NASA Astrophysics Data System (ADS)

    Clark, M. A.; LaPlante, P. C.; Greenhill, L. J.

    2013-05-01

    We present a highly parallel implementation of the cross-correlation of time-series data using graphics processing units (GPUs), which is scalable to hundreds of independent inputs and suitable for the processing of signals from 'large-Formula' arrays of many radio antennas. The computational part of the algorithm, the X-engine, is implemented efficiently on NVIDIA's Fermi architecture, sustaining up to 79% of the peak single-precision floating-point throughput. We compare performance obtained for hardware- and software-managed caches, observing significantly better performance for the latter. The high performance reported involves use of a multi-level data tiling strategy in memory and use of a pipelined algorithm with simultaneous computation and transfer of data from host to device memory. The speed of code development, flexibility, and low cost of the GPU implementations compared with application-specific integrated circuit (ASIC) and field programmable gate array (FPGA) implementations have the potential to greatly shorten the cycle of correlator development and deployment, for cases where some power-consumption penalty can be tolerated.

  16. Acoustic signal detection through the cross-correlation method in experiments with different signal to noise ratio and reverberation conditions

    E-print Network

    Adrián-Martínez, S; Bou-Cabo, M; Felis, I; Llorens, C; Martínez-Mora, J A; Saldaña, M

    2015-01-01

    The study and application of signal detection techniques based on cross-correlation method for acoustic transient signals in noisy and reverberant environments are presented. These techniques are shown to provide high signal to noise ratio, good signal discernment from very close echoes and accurate detection of signal arrival time. The proposed methodology has been tested on real data collected in environments and conditions where its benefits can be shown. This work focuses on the acoustic detection applied to tasks of positioning in underwater structures and calibration such those as ANTARES and KM3NeT deep-sea neutrino telescopes, as well as, in particle detection through acoustic events for the COUPP/PICO detectors. Moreover, a method for obtaining the real amplitude of the signal in time (voltage) by using cross correlation has been developed and tested and is described in this work.

  17. Signal Processing for DNA Sequencing Petros T. Boufounos

    E-print Network

    Boufounos, Petros T.

    Signal Processing for DNA Sequencing by Petros T. Boufounos Submitted to the Department and Computer Science #12;2 #12;3 Signal Processing for DNA Sequencing by Petros T. Boufounos Submitted of Engineering in Electrical Engineering and Computer Science Abstract DNA sequencing is the process

  18. Abrogation of TGF-? signaling enhances chemokine production and correlates with prognosis in human breast cancer

    PubMed Central

    Bierie, Brian; Chung, Christine H.; Parker, Joel S.; Stover, Daniel G.; Cheng, Nikki; Chytil, Anna; Aakre, Mary; Shyr, Yu; Moses, Harold L.

    2009-01-01

    In human breast cancer, loss of carcinoma cell–specific response to TGF-? signaling has been linked to poor patient prognosis. However, the mechanisms through which TGF-? regulates these processes remain largely unknown. In an effort to address this issue, we have now identified gene expression signatures associated with the TGF-? signaling pathway in human mammary carcinoma cells. The results strongly suggest that TGF-? signaling mediates intrinsic, stromal-epithelial, and host-tumor interactions during breast cancer progression, at least in part, by regulating basal and oncostatin M–induced CXCL1, CXCL5, and CCL20 chemokine expression. To determine the clinical relevance of our results, we queried our TGF-?–associated gene expression signatures in 4 human breast cancer data sets containing a total of 1,319 gene expression profiles and associated clinical outcome data. The signature representing complete abrogation of TGF-? signaling correlated with reduced relapse-free survival in all patients; however, the strongest association was observed in patients with estrogen receptor–positive (ER-positive) tumors, specifically within the luminal A subtype. Together, the results suggest that assessment of TGF-? signaling pathway status may further stratify the prognosis of ER-positive patients and provide novel therapeutic approaches in the management of breast cancer. PMID:19451693

  19. Neural mechanisms of spatiotemporal signal processing

    NASA Astrophysics Data System (ADS)

    Khanbabaie Shoub, Shaban (Reza)

    We have studied the synaptic, dendritic, and network mechanisms of spatiotemporal signal processing underlying the computation of visual motion in the avian tectum. Such mechanisms are critical for information processing in all vertebrates, but have been difficult to elucidate in mammals because of anatomical limitations. We have therefore developed a chick tectal slice preparation, which has features that help us circumvent these limitations. Using single-electrode multi-pulse synaptic stimulation experiments we found that the SGC-I cell responds to synaptic stimulation in a binary manner and its response is phasic in a time dependent probabilistic manner over large time scales. Synaptic inputs at two locations typically interact in a mutually exclusive manner when delivered within the "interaction time" of approximately 30 ms. Then we constructed a model of SGC-I cell and the retinal inputs to examine the role of the observed non-linear cellular properties in shaping the response of SGC-I neurons to assumed retinal representations of dynamic spatiotemporal visual stimuli. We found that by these properties, SGC-I cells can classify different stimuli. Especially without the phasic synaptic signal transfer the model SGC-I cell fails to distinguish between the static stationary stimuli and dynamic spatiotemporal stimuli. Based on one-site synaptic response probability and the assumption of independent neighboring dendritic endings we predicted the response probability of SGC-I cells to multiple synaptic inputs. We tested this independence-based model prediction and found that the independency assumption is not valid. The measured SGC-I response probability to multiple synaptic inputs does not increase with the number of synaptic inputs. The presence of GABAergic horizontal cells in layer 5 suggest an inhibitory effect of these cells on the SGC-I retino-tectal synaptic responses. In our experiment we found that the measured SGC-I response probability to multiple synaptic inputs is reduced when inhibitory tectal circuits are blocked. By predicting the SGC-I response to multiple synaptic inputs based on blocked inhibitory circuitry we found that the response probability is closer to independent situation but not exactly. So there is more than just inhibitory mechanism involved. To characterize the dependency between two neighboring synapses we used 2-site stimulation experiments and measured the effect of one stimulation on a spatially separate synapse. To determine whether this inhibitory mechanism is pre-synaptic or post-synaptic we used chloride channel blocker intracellularly. We saw an increase in response probability when post-synaptic chloride channels are blocked. Finally we found a good agreement between our prediction and experimental results for Poisson spike trains which may be considered more natural stimuli. Only the early stage of SGC-I response is carrying most of the information. Analyzing the SGC-I spike timing and the accuracy of latency is the last part of the thesis.

  20. Optimizing signal and image processing applications using Intel libraries

    NASA Astrophysics Data System (ADS)

    Landré, Jérôme; Truchetet, Frédéric

    2007-01-01

    This paper presents optimized signal and image processing libraries from Intel Corporation. Intel Performance Primitives (IPP) is a low-level signal and image processing library developed by Intel Corporation to optimize code on Intel processors. Open Computer Vision library (OpenCV) is a high-level library dedicated to computer vision tasks. This article describes the use of both libraries to build flexible and efficient signal and image processing applications.

  1. Signal processing and display for electrochemical data

    NASA Technical Reports Server (NTRS)

    Young, R. N.; Wilkins, J. R.

    1977-01-01

    Two electrochemical electrodes provide signals; apparatus automatically determines reaction end point and displays lag period in time or cell concentration. Apparatus can be used with standard pH reference anode and platinum anode or with redox electrodes.

  2. PASSIVE SENSOR IMAGING USING CROSS CORRELATIONS OF NOISY SIGNALS IN A SCATTERING MEDIUM

    E-print Network

    Garnier, Josselin

    PASSIVE SENSOR IMAGING USING CROSS CORRELATIONS OF NOISY SIGNALS IN A SCATTERING MEDIUM JOSSELIN's function between two passive sensors can be estimated from the cross correlation of recorded signal that the travel time can be effectively estimated when the ray joining the two sensors continues into the noise

  3. Improved Hilbert transform to process the ultrasonic TOFD signal

    Microsoft Academic Search

    Yang Chenlong; Wang Liqiu; Xu Zhinong

    2010-01-01

    The difficulty in the TOFD is to identify the arrival time of every echo in the overlap waves, an improved Hilbert transform is proposed in this paper. Firstly, calculating the energy of the noise in the original signal, then processing the original signal and the pure noise that have the same energy as original signal with the EMD method. Comparing

  4. An overview of synthetic aperture radar signal processing techniques

    Microsoft Academic Search

    M. R. vant

    1991-01-01

    The principles of synthetic aperture radar and its significance in a military and remote sensing context are reviewed. The signal processing operations required to convert the signal data into an image are described. These operations must accomplish two things: correction of the range migration, both walk and curvature; and compression or focusing of the cross-range portion of the signal. These

  5. Algebraic Signal Processing Theory: 1-D Nearest-Neighbor Models

    E-print Network

    Kova?evi?, Jelena

    -transform, convolution, spectrum, and Fourier transform. The presented results extend the algebraic signal processing including time shift, signals, filters, z-transform, convolution, spectrum, and Fourier trans- form. These concepts come in two variants: one for infinite signals and one for finite (usually periodically extended

  6. Development of an Ontology-Directed Signal Processing Toolbox

    SciTech Connect

    Stephen W. Lang

    2011-05-27

    This project was focused on the development of tools for the automatic configuration of signal processing systems. The goal is to develop tools that will be useful in a variety of Government and commercial areas and useable by people who are not signal processing experts. In order to get the most benefit from signal processing techniques, deep technical expertise is often required in order to select appropriate algorithms, combine them into a processing chain, and tune algorithm parameters for best performance on a specific problem. Therefore a significant benefit would result from the assembly of a toolbox of processing algorithms that has been selected for their effectiveness in a group of related problem areas, along with the means to allow people who are not signal processing experts to reliably select, combine, and tune these algorithms to solve specific problems. Defining a vocabulary for problem domain experts that is sufficiently expressive to drive the configuration of signal processing functions will allow the expertise of signal processing experts to be captured in rules for automated configuration. In order to test the feasibility of this approach, we addressed a lightning classification problem, which was proposed by DOE as a surrogate for problems encountered in nuclear nonproliferation data processing. We coded a toolbox of low-level signal processing algorithms for extracting features of RF waveforms, and demonstrated a prototype tool for screening data. We showed examples of using the tool for expediting the generation of ground-truth metadata, for training a signal recognizer, and for searching for signals with particular characteristics. The public benefits of this approach, if successful, will accrue to Government and commercial activities that face the same general problem - the development of sensor systems for complex environments. It will enable problem domain experts (e.g. analysts) to construct signal and image processing chains without the aid of signal processing experts. Thus enabled, problem domain experts will be able to work more quickly and produce better quality work.

  7. Signal processing experiments with the LEGO MINDSTORMS NXT kit for use in signals and systems courses

    Microsoft Academic Search

    Bonnie Heck Ferri; Safayet Ahmed; Jennifer E. Michaels; Eric Dean; Chris Garyet; Sam Shearman

    2009-01-01

    This paper presents a set of inexpensive signal processing experiments that can be used as projects or hands-on demos to supplement signals and systems courses. Signals and systems concepts tend to be very mathematical and abstract, and students who prefer more practical material are at a disadvantage in these courses. The experiments are performed on the LEGO MINDSTORMS NXT platform,

  8. Techniques of EMG signal analysis: detection, processing, classification and applications

    Microsoft Academic Search

    M. B. I. Reaz; M. S. Hussain; F. Mohd-Yasin

    2006-01-01

    Electromyography (EMG) signals can be used for clinical\\/biomedical applications, Evolvable Hardware Chip (EHW) development,\\u000a and modern human computer interaction. EMG signals acquired from muscles require advanced methods for detection, decomposition,\\u000a processing, and classification. The purpose of this paper is to illustrate the various methodologies and algorithms for EMG\\u000a signal analysis to provide efficient and effective ways of understanding the signal

  9. Correlation algorithm and sampling techniques for estimating the signal-to-noise ratio of the electrocardiogram.

    PubMed

    Charayaphan, C; Marble, A E; Nugent, S T; Swingler, D

    1992-11-01

    An algorithm, based on correlation techniques, is proposed for estimating the signal-to-noise ratio of very low frequency signals contaminated by white and flicker noise. Sampling techniques based on converting a single continuous signal into two time series that satisfy the requirements of cross-correlation functions are proposed. The algorithm has been tested on simulated data and the electrocardiogram transduced from ten patients. PMID:1434576

  10. On the Long Range Correlation in Fbm-Based Signals with Mixed Statistics

    NASA Astrophysics Data System (ADS)

    Scipioni, A.; Rischette, P.

    2012-07-01

    The understanding of energy transfer mechanisms in a tokamak edge plasma is a major challenge for controlled fusion test reactors. High values of the Hurst exponent (H > 0.5) encountered in experimental probe data acquired in the scrape-off-layer (SOL) suggest the presence of long-range correlations favoring the hypothesis of an avalanche-type of radial transport. This communication aims at showing that this high value of Hurst coefficient does not necessarily imply the existence of long-time range correlations but it can be the witness of the presence of a particular behavior at small-time scales. Indeed, the development of a wavelet-based observer on synthetic signals, relying on fractional Brownian motions, has allowed the realization of a study model with mixed statistics. The associated time series, for which the H value is controlled, have been broken into blocks of variable length. Then, these different blocks have been scrambled randomly. Although potential long-range correlations have been thus destroyed, the wavelet-based estimator applied to these new synthetic signals is able to measure the original value of the Hurst parameter on a variable scale range. This approach highlights the persistence level on the scale range for several H and block size values. This technique reveals the reminiscent character of the synthetic process behavior appearing from small-time scales to long-time scales.

  11. Signal processing on graphs: Transforms and tomograms

    E-print Network

    Mendes, R Vilela; Araújo, Tanya

    2014-01-01

    Using projections on the (generalized) eigenvectors associated to matrices that characterize the topological structure, several authors have constructed generalizations of the Fourier transform on graphs. By exploring mappings of the spectrum of these matrices we show how to construct more general transforms, in particular wavelet-like transforms on graphs. For time-series, tomograms, a generalization of the Radon transforms to arbitrary pairs of non-commuting operators, are positive bilinear transforms with a rigorous probabilistic interpretation which provide a full characterization of the signals and are robust in the presence of noise. Here the notion of tomogram transform is also extended to signals on arbitrary graphs

  12. Digital signal processing in the radio science stability analyzer

    NASA Technical Reports Server (NTRS)

    Greenhall, C. A.

    1995-01-01

    The Telecommunications Division has built a stability analyzer for testing Deep Space Network installations during flight radio science experiments. The low-frequency part of the analyzer operates by digitizing wave signals with bandwidths between 80 Hz and 45 kHz. Processed outputs include spectra of signal, phase, amplitude, and differential phase; time series of the same quantities; and Allan deviation of phase and differential phase. This article documents the digital signal-processing methods programmed into the analyzer.

  13. Signal and Image Processing for Crime Control and Crime Prevention

    Microsoft Academic Search

    Susan Hackwood; P. Aaron Potter

    1999-01-01

    In this paper we will take a critical look at the research and development of signal and image processing technologies and new applications of existing technologies to improve crime control and crime prevention. Signal and image processing techniques are used in many aspects of sensing the environment both during a crime and in the post-crime analysis of the scene. Common

  14. Nonlinear Coch 3. Nonlinear Cochlear Signal Processing and Masking

    E-print Network

    Allen, Jont

    36 #12;1 Nonlinear Coch 3. Nonlinear Cochlear Signal Processing and Masking in Speech Perception of the auditory signal, a form of loudness noise. Dynamic masking is strictly cochlear, and is associated with cochlear outer-hair-cell process- ing. This form is responsible for dynamic nonlinear cochlear gain changes

  15. Mobile social signal processing: vision and research issues

    Microsoft Academic Search

    Alessandro Vinciarelli; Roderick Murray-Smith; Hervé Bourlard

    2010-01-01

    This paper introduces the First International Workshop on Mobile Social Signal Processing (SSP). The Workshop aims at bringing together the Mobile HCI and Social Signal Processing research communities. The former investigates approaches for effective interaction with mobile and wearable devices, while the latter focuses on modeling, analysis and synthesis of nonverbal behavior in human{human and human-machine interactions. While dealing with

  16. Image processing on ECG chart for ECG signal recovery

    Microsoft Academic Search

    T. W. Shen; T. F. Laio

    2009-01-01

    Medical imaging plays an indispensable role on medical informatics. Most of imaging processing technologies is focused on the identification of the locations of diseases on MRI, CT, PET, and SPECT images. However, only a few researches focused on one dimension signal recovery or reconstruction of electronic signals. Spatial and frequency methods were provided to process on colour or gray-level electrocardiogram

  17. Nonlinear signal processing using neural networks: Prediction and system modelling

    Microsoft Academic Search

    A. Lapedes; R. Farber

    1987-01-01

    The backpropagation learning algorithm for neural networks is developed into a formalism for nonlinear signal processing. We illustrate the method by selecting two common topics in signal processing, prediction and system modelling, and show that nonlinear applications can be handled extremely well by using neural networks. The formalism is a natural, nonlinear extension of the linear Least Mean Squares algorithm

  18. Low power signal processing architectures for network microsensors

    Microsoft Academic Search

    Michael J. Dong; K. Geoffrey Yung; William J. Kaiser

    1997-01-01

    Low power signal processing systems are required for distributed network microsensor techn- ology. Network microsensors now provide a new monitoring and control capability for civil and military applications in transportation, manufacturing, biomed- ical technology, environmental management, and safety and security systems. Signal processing methods for event detection have been developed with low power, parallel architectures that optimize performance for unique

  19. Certain aspects of adaptive array signal processing

    SciTech Connect

    Hong, Y.J.

    1985-01-01

    The effect of a finite distance signal source on an Applebaum type adaptive array for which the steering vector has random errors is examined. An imperfect steering vector includes the vector that steers the far field although the source is at a finite distance. Expressions are derived for the output signal-to-noise ratio (SNR) in terms of the signal direction, array element position, signal distance and element input SNR. The allowable de-focus range corresponding to a given degradation of the output SNR is determined. It is shown that the de-focus range of a conventional beam forming array cannot be directly applied to that of an adaptive array. An adaptive array is much more sensitive to the de-focusing than a conventional array. A linearly combined array is also examined. It combines the features of the Applebaum and the LMS arrays and is shown to be less sensitive to imperfect steering than a typical Applebaum array. This dissertation also involves the explanation of the suppression of multiple interferers by using a tapped delay-line scheme although the available degree of freedom is less than the number of the interferers. Results are demonstrated using computer simulations for all cases.

  20. Contrastive analysis of correlation dimension of EEG signals between normal and pathological groups

    Microsoft Academic Search

    Jiafu Zhu; Wei He; Hao Yang

    2008-01-01

    EEG signal is a typical nonlinear time series and its correlation dimension can be calculated to measure the series. In this paper, the correlation dimensions of 30 healthy samples and 30 patient samples are calculated. By the statistic result, an important conclusion is represented that the values of correlation dimension of different groups exist great difference. Based on more clinical

  1. Multifractal detrended cross-correlation analysis for two nonstationary signals.

    PubMed

    Zhou, Wei-Xing

    2008-06-01

    We propose a method called multifractal detrended cross-correlation analysis to investigate the multifractal behaviors in the power-law cross-correlations between two time series or higher-dimensional quantities recorded simultaneously, which can be applied to diverse complex systems such as turbulence, finance, ecology, physiology, geophysics, and so on. The method is validated with cross-correlated one- and two-dimensional binomial measures and multifractal random walks. As an example, we illustrate the method by analyzing two financial time series. PMID:18643354

  2. Multifractal detrended cross-correlation analysis for two nonstationary signals

    NASA Astrophysics Data System (ADS)

    Zhou, Wei-Xing

    2008-06-01

    We propose a method called multifractal detrended cross-correlation analysis to investigate the multifractal behaviors in the power-law cross-correlations between two time series or higher-dimensional quantities recorded simultaneously, which can be applied to diverse complex systems such as turbulence, finance, ecology, physiology, geophysics, and so on. The method is validated with cross-correlated one- and two-dimensional binomial measures and multifractal random walks. As an example, we illustrate the method by analyzing two financial time series.

  3. Real time all optical correlator for serialized time encoded signals

    NASA Astrophysics Data System (ADS)

    Shoeiby, Mehrdad; Mitchell, Arnan; Bui, Lam

    2015-03-01

    A novel technique for correlation of spectrally encoded data is presented. Data encoded in the spectrum of ultrafast optical pulses is mapped into the time domain using dispersion and then mixed with a spectrally engineered broadband pump using four wave mixing to create a narrow bandwidth idler, which is isolated and electronically integrated. Unlike previous methods, this solution provides all-optical functionality at every stage of correlation. The demonstrated frame rate of 20 MHz is limited only by the laser repetition rate.

  4. Optical and analog electronic signal processing

    Microsoft Academic Search

    H. Whitehouse

    1977-01-01

    A two lens optical Fourier transformation is shown to be equivalent to an electronic chirp transform. For discrete time signals this transformation becomes the discrete chirp-z-transform. The chirp-z-transform can be implemented using either charge transfer devices or surface acoustic wave devices. Through the use of appropriate architectures, a long one-dimensional chirp-z-transform can be rewritten as a modular chirp-z transform using

  5. Classification of no-signaling correlation and the "guess your neighbor's input" game

    NASA Astrophysics Data System (ADS)

    Wang, He-Ming; Zhou, Heng-Yun; Mu, Liang-Zhu; Fan, Heng

    2014-09-01

    We formulate a series of nontrivial equalities which are satisfied by all no-signaling correlations, meaning that no faster-than-light communication is allowed with the resource of these correlations. All quantum and classical correlations satisfy these equalities since they are no-signaling. By applying these equalities, we provide a general framework for solving the multipartite "guess your neighbor's input" (GYNI) game, which is naturally no-signaling but shows conversely that general no-signaling correlations are actually more nonlocal than those allowed by quantum mechanics. We confirm the validity of our method for the number of players from 3 up to 19, thus providing convincing evidence that it works for the general case. In addition, we solve analytically the tripartite GYNI and obtain a computable measure of supraquantum correlations. This result simplifies the defined optimization procedure to an analytic formula, thus characterizing explicitly the boundary between quantum and supraquantum correlations. In addition, we show that the gap between quantum and no-signaling boundaries containing supraquantum correlations can be closed by local orthogonality conditions in the tripartite case. Our results provide a computable classification of no-signaling correlations.

  6. Moving source localization using seismic signal processing

    NASA Astrophysics Data System (ADS)

    Asgari, Shadnaz; Stafsudd, Jing Z.; Hudson, Ralph E.; Yao, Kung; Taciroglu, Ertugrul

    2015-01-01

    Accurate localization of a seismic source in a near-field scenario where the distances between sensors and the source are less than a few wavelengths of the generated signal has shown to be a challenging task. Conventional localization algorithms often prove to be ineffective, as near-field seismic signals exhibit characteristics different from the well-studied far-field signals. The current work is aimed at the employment of a seismic sensor array for the localization and tracking of a near-field wideband moving source. In this paper, the mathematical derivation of a novel DOA estimation algorithm-dubbed the Modified Kirlin Method-has been presented in details. The estimated DOAs are then combined using a least-squares optimization method for source localization. The performance of the proposed method has been evaluated in a field experiment to track a moving truck. We also compare the DOA estimation and source localization results of the proposed method with those of two other existing methods originally developed for localization of a stationary wideband source; Covariance Matrix Analysis and the Surface Wave Analysis. Our results indicate that both the Surface Wave Analysis and the Modified Kirlin Methods are effective in locating and tracking a moving truck.

  7. Neuromorphic opto-electronic integrated circuits for optical signal processing

    NASA Astrophysics Data System (ADS)

    Romeira, B.; Javaloyes, J.; Balle, S.; Piro, O.; Avó, R.; Figueiredo, J. M. L.

    2014-08-01

    The ability to produce narrow optical pulses has been extensively investigated in laser systems with promising applications in photonics such as clock recovery, pulse reshaping, and recently in photonics artificial neural networks using spiking signal processing. Here, we investigate a neuromorphic opto-electronic integrated circuit (NOEIC) comprising a semiconductor laser driven by a resonant tunneling diode (RTD) photo-detector operating at telecommunication (1550 nm) wavelengths capable of excitable spiking signal generation in response to optical and electrical control signals. The RTD-NOEIC mimics biologically inspired neuronal phenomena and possesses high-speed response and potential for monolithic integration for optical signal processing applications.

  8. New signal processing technique for density profile reconstruction using reflectometry.

    PubMed

    Clairet, F; Ricaud, B; Briolle, F; Heuraux, S; Bottereau, C

    2011-08-01

    Reflectometry profile measurement requires an accurate determination of the plasma reflected signal. Along with a good resolution and a high signal to noise ratio of the phase measurement, adequate data analysis is required. A new data processing based on time-frequency tomographic representation is used. It provides a clearer separation between multiple components and improves isolation of the relevant signals. In this paper, this data processing technique is applied to two sets of signals coming from two different reflectometer devices used on the Tore Supra tokamak. For the standard density profile reflectometry, it improves the initialization process and its reliability, providing a more accurate profile determination in the far scrape-off layer with density measurements as low as 10(16) m(-1). For a second reflectometer, which provides measurements in front of a lower hybrid launcher, this method improves the separation of the relevant plasma signal from multi-reflection processes due to the proximity of the plasma. PMID:21895243

  9. Signal Processing for Recognition of Human Frustration

    Microsoft Academic Search

    Raul Fernandez; Rosalind W. Picard

    1997-01-01

    In this work, inspired by the application ofhuman-machine interaction and the potential usethat human-computer interfaces can make ofknowledge regarding the affective state of a user,we investigate the problem of sensing and recognizingtypical affective experiences that arisewhen people communicate with computers. Inparticular, we address the problem of detecting"frustration" in human computer interfaces. Byfirst sensing human biophysiological correlates ofinternal affective states,...

  10. Correlates of linguistic rhythm in the speech signal

    Microsoft Academic Search

    Franck Ramus; Marina Nespor; Jacques Mehler

    1999-01-01

    Spoken languages have been classified by linguists according to their rhythmic properties, and psycholinguists have relied on this classification to account for infants’ capacity to discriminate languages. Although researchers have measured many speech signal properties, they have failed to identify reliable acoustic characteristics for language classes. This paper presents instrumental measurements based on a consonant\\/vowel segmentation for eight languages. The

  11. Signal processing techniques in genomic engineering

    Microsoft Academic Search

    Xin-Yun Zhang; Fei Chen; Yuan-Ting Zhang; SHANNON C. AGNER; METIN AKAY; Zu-Hong Lu; M. M. Y. Waye; S. K.-W. Tsui

    2002-01-01

    Now that the human genome has been sequenced, the measurement, processing, and analysis of specific genomic information in real time are gaining considerable interest because of their importance to better the understanding of the inherent genomic function, the early diagnosis of disease, and the discovery of new drugs. Traditional methods to process and analyze deoxyribonucleic acid (DNA) or ribonucleic acid

  12. [Detrended cross-correlation analysis: a new method for gait signal analysis].

    PubMed

    Wang, Pingping; Wang, Jun

    2012-12-01

    The cross-correlation of gait signal can mirror the health situations of different people. It is important to analyze the long-range cross correlations of the two signals of nonstationarity for medical research. In this paper, we propose a detrended cross-correlation analysis (DCCA) method for analyzing the different gait signal in physiological and pathological conditions. Our work dealt with three kinds of gait signals, including those of normal young people (23 to 29 years of age), those of healthy old people (71 to 77 years of age) and those of the old people (60 to 77 years of age) with Parkinson's disease from the MIT-BIH database. We carried out the DCCA for the three gait signals of nonstationarity. The results showed that the self-similarity of gait signal got more unstable with the age increasing and health status worsening. From the cross-correlation analysis, we found that the cross-correlation degree of gait signal of young people increased gradually, the healthy old people changed slowly and the Parkinson's disease patients showed unstable changes. We can make medical diagnosis and treatment according to the differences among different gait signals. PMID:23469555

  13. Electrophysiological Correlates of Stimulus Equivalence Processes

    ERIC Educational Resources Information Center

    Haimson, Barry; Wilkinson, Krista M.; Rosenquist, Celia; Ouimet, Carolyn; McIlvane, William J.

    2009-01-01

    Research reported here concerns neural processes relating to stimulus equivalence class formation. In Experiment 1, two types of word pairs were presented successively to normally capable adults. In one type, the words had related usage in English (e.g., uncle, aunt). In the other, the two words were not typically related in their usage (e.g.,…

  14. The Signal Processing and Communications (SPC) toolbox, release 2

    NASA Astrophysics Data System (ADS)

    Brown, Dennis W.; Fargues, Monique P.

    1995-09-01

    The SPC (Signal Processing & Communications) toolbox is a software package designed to provide the user with a series of data manipulation tools which use MATLAB v.4 graphical user interface controls SPC can be used in the classroom to illustrate and to reinforce basic concepts in digital signal processing and communications. It frees the user from having to write and debug his/her own code and gives him/her more time to understand the advantages and drawbacks of each technique included in the package. It can also be used as a basic analysis and modeling tool for research in Signal Processing.

  15. B-Spline Signal Processing: Part I-Theory

    Microsoft Academic Search

    Michael Unser; Akram Aldroubi; Murray Eden

    1993-01-01

    This paper describes a set of efficient filtering techniques for the processing and representation of signals in terms of continuous B-spline basis functions. We first consider the problem of determining the spline coefficients for an exact signal interpolation (direct B-spline transform). The reverse operation is the signal reconstruction from its spline coefficients with an optional zooming factor rn (indirect B-spline

  16. Adaptive correlation image processing by collinear optical heterodyning

    Microsoft Academic Search

    Eugeny R. Tsvetov

    1996-01-01

    An optical heterodyne correlator, in which the functions of overlapping and scanning by reference image relatively signal image are realized with the hologram lens scanner in the plane of joint FOurier transform is described. An adaptive filtration of spatial frequency signs of input images may be implemented by matrix of rf photodetectors with summarized rf outputs and tunable sensitivity or

  17. Time reversal signal processing for communication.

    SciTech Connect

    Young, Derek P.; Jacklin, Neil; Punnoose, Ratish J.; Counsil, David T.

    2011-09-01

    Time-reversal is a wave focusing technique that makes use of the reciprocity of wireless propagation channels. It works particularly well in a cluttered environment with associated multipath reflection. This technique uses the multipath in the environment to increase focusing ability. Time-reversal can also be used to null signals, either to reduce unintentional interference or to prevent eavesdropping. It does not require controlled geometric placement of the transmit antennas. Unlike existing techniques it can work without line-of-sight. We have explored the performance of time-reversal focusing in a variety of simulated environments. We have also developed new algorithms to simultaneously focus at a location while nulling at an eavesdropper location. We have experimentally verified these techniques in a realistic cluttered environment.

  18. Advanced signal processing for the Blu-ray Disc system

    Microsoft Academic Search

    B. Stek; R. Otte; T. Jansen; D. Modrie

    2002-01-01

    Advanced signal processing enables high capacities for the BD system. Measurements show that data detection with a conventional equalizer does not give sufficient system margins. Both a Viterbi decoder and the limit equalizer give a significant improvement of the signal-to-noise ratio and therefore sufficiently large margins. An adaptive equalizer is able to correct the distortions introduced by tangential tilt. The

  19. Adaptive parametric algorithms for processing coherent Doppler-lidar signal

    Microsoft Academic Search

    Jean-Luc Zarader; Alain Dabas; Pierre H. Flamant; Bruno Gas; Olivier Adam

    1999-01-01

    The authors study the autoregressive and moving average (ARMA) filter for lidar signal processing. After a short presentation of the atmospheric laser Doppler instrument project (ALADIN), they introduce the objective of this paper, which is to extract the Doppler frequency and to retrieve the spectral width of a noised lidar signal. A general presentation of ARMA filters and parametric adaptive

  20. Adaptive blind signal processing-neural network approaches

    Microsoft Academic Search

    SHUN-ICHI AMARI; ANDRZEJ CICHOCKI

    1998-01-01

    Learning algorithms and underlying basic mathematical ideas are presented for the problem of adaptive blind signal processing, especially instantaneous blind separation and multichannel blind deconvolution\\/equalization of independent source signals. We discuss developments of adaptive learning algorithms based on the natural gradient approach and their properties concerning convergence, stability, and efficiency. Several promising schemas are proposed and reviewed in the paper.

  1. Implantable multielectrode array with on-chip signal processing

    Microsoft Academic Search

    Khalil Najafi; Kensall D. Wise

    1986-01-01

    A 20-channel microelectrode array used to sense meural signals will be described. An implantable device, it incorporates on-chip signal processing, self-testing, and consumes 5mW from a single 5V supply. The chip, with a 1.3mm2area, has 6?m features.

  2. Social Signal Processing: Understanding Nonverbal Communication in Social Interactions

    E-print Network

    Vinciarelli, Alessandro

    in human sciences have shown that nonverbal communication is the main channel through which we express to automatically infer social signals from nonverbal behavioral cues detected through sensors? · Is it possiblSocial Signal Processing: Understanding Nonverbal Communication in Social Interactions Alessandro

  3. Biomedical signal acquisition, processing and transmission using smartphone

    Microsoft Academic Search

    Pablo Roncagliolo; Luis Arredondo; Agustín González

    2007-01-01

    This article describes technical aspects involved in the programming of a system of acquisition, processing and transmission of biomedical signals by using mobile devices. This task is aligned with the permanent development of new technologies for the diagnosis and sickness treatment, based on the feasibility of measuring continuously different variables as electrocardiographic signals, blood pressure, oxygen concentration, pulse or simply

  4. Analog Integrated Circuits Design for Processing Physiological Signals

    Microsoft Academic Search

    Yan Li; Carmen C. Y. Poon; Yuan-Ting Zhang

    2010-01-01

    Analog integrated circuits (ICs) designed for processing physiological signals are important building blocks of wearable and implantable medical devices used for health monitoring or restoring lost body functions. Due to the nature of physiological signals and the corresponding application scenarios, the ICs designed for these applications should have low power consumption, low cutoff frequency, and low input-referred noise. In this

  5. [State-dependent processing of serial signals].

    PubMed

    Schmitt, R

    1990-01-01

    The relation between EEG patterns and performance, which was found experimentally, gives evidence for a state dependent information processing. The power distribution of the EEG one second before the stimulus onset determines the state measured by the used data acquisition system. To solve the on-line identification of the state four different approaches are proposed and compared. The two modes of triggering the stimulus onset labeled by alpha wave state and non alpha wave state led to significantly different reaction times. The proposed stochastic recurrence equation can be used to model the scanning process performed by 17 subjects in solving the task of searching the first number in a string of characters. The model is based on the decomposition of the measured reaction times according to the assumed elementary processes. PMID:1982383

  6. 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.

  7. Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing

    E-print Network

    Rickard, Scott

    in Echoic Environments Using DESPRIT Thomas Melia and Scott Rickard Sparse Signal Processing Group experiments conducted on synthetic and real world mixtures. Copyright © 2007 T. Melia and S. Rickard

  8. Sensitivity of polynomial composition and decomposition for signal processing applications

    E-print Network

    Demirtas, Sefa

    Polynomial composition is well studied in mathematics but has only been exploited indirectly and informally in signal processing. Potential future application of polynomial composition for filter implementation and data ...

  9. Signal processing letters: Charting a new course [Society News

    Microsoft Academic Search

    Alex Gershman; Kostas Plataniotis; K. J. R. Liu

    2008-01-01

    SPL's primary goal is to provide rapid publication of highly original, significant contributions and timely cutting-edge ideas in all areas within the field of interest of the IEEE Signal Processing Society.

  10. Functional description of signal processing in the Rogue GPS receiver

    NASA Technical Reports Server (NTRS)

    Thomas, J. B.

    1988-01-01

    Over the past year, two Rogue GPS prototype receivers have been assembled and successfully subjected to a variety of laboratory and field tests. A functional description is presented of signal processing in the Rogue receiver, tracing the signal from RF input to the output values of group delay, phase, and data bits. The receiver can track up to eight satellites, without time multiplexing among satellites or channels, simultaneously measuring both group delay and phase for each of three channels (L1-C/A, L1-P, L2-P). The Rogue signal processing described requires generation of the code for all three channels. Receiver functional design, which emphasized accuracy, reliability, flexibility, and dynamic capability, is summarized. A detailed functional description of signal processing is presented, including C/A-channel and P-channel processing, carrier-aided averaging of group delays, checks for cycle slips, acquistion, and distinctive features.

  11. 28. Perimeter acquisition radar building room #302, signal process and ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    28. Perimeter acquisition radar building room #302, signal process and analog receiver room - Stanley R. Mickelsen Safeguard Complex, Perimeter Acquisition Radar Building, Limited Access Area, between Limited Access Patrol Road & Service Road A, Nekoma, Cavalier County, ND

  12. Signal processing in biological cells : proteins, networks, and models

    E-print Network

    Said, Maya Rida, 1976-

    2005-01-01

    This thesis introduces systematic engineering principles to model, at different levels of abstraction the information processing in biological cells in order to understand the algorithms implemented by the signaling pathways ...

  13. Optical Signal Processing: Poisson Image Restoration and Shearing Interferometry

    NASA Technical Reports Server (NTRS)

    Hong, Yie-Ming

    1973-01-01

    Optical signal processing can be performed in either digital or analog systems. Digital computers and coherent optical systems are discussed as they are used in optical signal processing. Topics include: image restoration; phase-object visualization; image contrast reversal; optical computation; image multiplexing; and fabrication of spatial filters. Digital optical data processing deals with restoration of images degraded by signal-dependent noise. When the input data of an image restoration system are the numbers of photoelectrons received from various areas of a photosensitive surface, the data are Poisson distributed with mean values proportional to the illuminance of the incoherently radiating object and background light. Optical signal processing using coherent optical systems is also discussed. Following a brief review of the pertinent details of Ronchi's diffraction grating interferometer, moire effect, carrier-frequency photography, and achromatic holography, two new shearing interferometers based on them are presented. Both interferometers can produce variable shear.

  14. Optimization of correlated multiple responses of ultrasonic machining (USM) process

    Microsoft Academic Search

    Susanta Kumar Gauri; Rina Chakravorty; Shankar Chakraborty

    2011-01-01

    Ultrasonic machining (USM) process has several important performance measures (responses), some of which are correlated. For\\u000a example, material removal rate and tool wear rate are highly correlated. Although in the recent past several methods have\\u000a been proposed in the literature to resolve the multi-response optimization problems, only a few of them take care of the possible\\u000a correlation between the responses.

  15. Correlation of Behavior Changes and BOLD Signal in Alzheimer-like Rat Model

    Microsoft Academic Search

    Zheng-Hui HU; Xiao-Chuan WANG; Li-Yun LI; Mai-Li LIU; Rong LIU; Zhiqun LING; Qing TIAN; Xiao-Wei TANG; Yi-Gen WU; Jian-Zhi WANG

    2004-01-01

    To explore a potential means for the early diagnosis of Alzheimer disease, we studied the relationship of resting T2* signal and tau hyperphosphorylation\\/spatial memory deficit. The rat model with tau hyperphosphorylation and spatial memory deficit was established by bilateral hippocampi injection of isoproterenol (IP). Then, the correlative alteration between resting T2* signal and spatial memory retention was assessed with blood

  16. Hardware implementation of surface electromyogram signal processing: A survey

    Microsoft Academic Search

    Ahmad Jamal Salim; Soo Yew Guan

    2011-01-01

    This paper surveys the previous and ongoing research on surface electromyogram (sEMG) signal processing implementation through various hardware platforms. The development of system that incorporates sEMG analysis capability is essential in rehabilitation devices, prosthesis arm\\/limb and pervasive healthcare in general. Most advanced EMG signal processing algorithms rely heavily on computational resource of a PC that negates the elements of portability,

  17. All-optical signal processing using dynamic Brillouin gratings

    PubMed Central

    Santagiustina, Marco; Chin, Sanghoon; Primerov, Nicolay; Ursini, Leonora; Thévenaz, Luc

    2013-01-01

    The manipulation of dynamic Brillouin gratings in optical fibers is demonstrated to be an extremely flexible technique to achieve, with a single experimental setup, several all-optical signal processing functions. In particular, all-optical time differentiation, time integration and true time reversal are theoretically predicted, and then numerically and experimentally demonstrated. The technique can be exploited to process both photonic and ultra-wide band microwave signals, so enabling many applications in photonics and in radio science. PMID:23549159

  18. Correlation Dimension Analysis of Doppler Signals in Children with Aortic Valve Disorders

    Microsoft Academic Search

    Derya Yilmaz; Nihal Fatma Güler

    2010-01-01

    In this study, the correlation dimension analysis has been applied to the aortic valve Doppler signals to investigate the\\u000a complexity of the Doppler signals which belong to aortic stenosis (AS) and aortic insufficiency (AI) diseases and healthy\\u000a case. The Doppler signals of 20 healthy subjects, ten AS and ten AI patients were acquired via the Doppler echocardiography\\u000a system that is

  19. Cortical auditory signal processing in poor readers

    PubMed Central

    Nagarajan, Srikantan; Mahncke, Henry; Salz, Talya; Tallal, Paula; Roberts, Timothy; Merzenich, Michael M.

    1999-01-01

    Magnetoencephalographic responses recorded from auditory cortex evoked by brief and rapidly successive stimuli differed between adults with poor vs. good reading abilities in four important ways. First, the response amplitude evoked by short-duration acoustic stimuli was stronger in the post-stimulus time range of 150–200 ms in poor readers than in normal readers. Second, response amplitude to rapidly successive and brief stimuli that were identical or that differed significantly in frequency were substantially weaker in poor readers compared with controls, for interstimulus intervals of 100 or 200 ms, but not for an interstimulus interval of 500 ms. Third, this neurological deficit closely paralleled subjects’ ability to distinguish between and to reconstruct the order of presentation of those stimulus sequences. Fourth, the average distributed response coherence evoked by rapidly successive stimuli was significantly weaker in the ?- and ?-band frequency ranges (20–60 Hz) in poor readers, compared with controls. These results provide direct electrophysiological evidence supporting the hypothesis that reading disabilities are correlated with the abnormal neural representation of brief and rapidly successive sensory inputs, manifested in this study at the entry level of the cortical auditory/aural speech representational system(s). PMID:10339614

  20. Unlike particle correlations and the strange quark matter distillation process

    E-print Network

    D. Ardouin; Sven Soff; C. Spieles; S. A. Bass; H. Stocker; D. Gourio; S. Schramm; C. Greiner; R. Lednicky; V. L. Lyuboshits; J. P. Coffin; C. Kuhn

    2002-03-14

    We present a new technique for observing the strange quark matter distillation process based on unlike particle correlations. A simulation is presented based on the scenario of a two-phase thermodynamical evolution model.

  1. Techniques of EMG signal analysis: detection, processing, classification and applications

    PubMed Central

    Hussain, M.S.; Mohd-Yasin, F.

    2006-01-01

    Electromyography (EMG) signals can be used for clinical/biomedical applications, Evolvable Hardware Chip (EHW) development, and modern human computer interaction. EMG signals acquired from muscles require advanced methods for detection, decomposition, processing, and classification. The purpose of this paper is to illustrate the various methodologies and algorithms for EMG signal analysis to provide efficient and effective ways of understanding the signal and its nature. We further point up some of the hardware implementations using EMG focusing on applications related to prosthetic hand control, grasp recognition, and human computer interaction. A comparison study is also given to show performance of various EMG signal analysis methods. This paper provides researchers a good understanding of EMG signal and its analysis procedures. This knowledge will help them develop more powerful, flexible, and efficient applications. PMID:16799694

  2. Signal-processing theory for the TurboRogue receiver

    NASA Technical Reports Server (NTRS)

    Thomas, J. B.

    1995-01-01

    Signal-processing theory for the TurboRogue receiver is presented. The signal form is traced from its formation at the GPS satellite, to the receiver antenna, and then through the various stages of the receiver, including extraction of phase and delay. The analysis treats the effects of ionosphere, troposphere, signal quantization, receiver components, and system noise, covering processing in both the 'code mode' when the P code is not encrypted and in the 'P-codeless mode' when the P code is encrypted. As a possible future improvement to the current analog front end, an example of a highly digital front end is analyzed.

  3. Feature Analysis Mechanical Fault Signals Based on Correlation Dimension and Complexity

    Microsoft Academic Search

    Bingcheng Wang; Zhaohui Ren

    2010-01-01

    In connection with the nonlinear dynamic characteristics shown from the performance of fault rotating mechanical system, based on the research and analysis, correlation dimension and complexity can be used to characterize the system state of motion. The authors propose the analysis method of correlation dimension and complexity to the signal feature of mechanical fault. Using theory of phase space reconstruction,

  4. Net analyte signal based two-dimensional (NAS 2D) correlation near infrared spectroscopy

    Microsoft Academic Search

    Ying Geng; Bingren Xiang

    2010-01-01

    A new method of analysis, based on the net analyte signal presented by Lorber is proposed for the two-dimensional correlation near infrared spectroscopy. A spectra data set under the static perturbation of concentration was collected. NAS is manipulated for removing the information that was unrelated to a certain analyte. To demonstrate the potential of NAS 2D correlation spectroscopy, a set

  5. System noise cancellation by digital signal processing for SQUID measurement

    NASA Astrophysics Data System (ADS)

    Sakuta, K.; Mizoguti, K.; Setoguchi, A.; Itozaki, H.

    2006-05-01

    It is important to suppress both environmental noise and system noise as much as possible when a weak magnetic signal is measured by a superconducting quantum interference device (SQUID). Environmental noise can be suppressed by using magnetic shielding or a gradiometer. However, we still have system noise produced by the electronics such as coils and amplifiers, even if we use perfect magnetic shielding or a gradiometer. This research has been aimed at reducing this system noise signal in measured data using digital signal processing. Two SQUIDs are placed close together, and the same magnetic field is detected with these two SQUIDs simultaneously. The outputs of these SQUID magnetometers, however, are different from each other, because the system noise included in the signal has random phase, amplitude and frequency for each respective SQUID. By extracting the in-phase components from these two SQUID output signals, the system noise signal can be reduced, and as a result, the signal from the measuring object in which we are interested can be obtained. An adaptive digital filter (ADF) algorithm was used for this extraction of the in-phase components. When the signal-to-noise ratio was 0.5, the noise signal was decreased by about 10 dB by this processing. In addition, the frequency division by the wavelet transform was used to raise the performance of the in-phase component extraction. The noise signal is reduced at each frequency band, and each of the band elements is reconstructed by an inverse wavelet transform to obtain the signal of the object. The noise removal performance was improved to about -20 dB when this method was used. In addition, the waveform distortion became lower than that processed without wavelet transform.

  6. Signal processing method and system for noise removal and signal extraction

    DOEpatents

    Fu, Chi Yung (San Francisco, CA); Petrich, Loren (Lebanon, OR)

    2009-04-14

    A signal processing method and system combining smooth level wavelet pre-processing together with artificial neural networks all in the wavelet domain for signal denoising and extraction. Upon receiving a signal corrupted with noise, an n-level decomposition of the signal is performed using a discrete wavelet transform to produce a smooth component and a rough component for each decomposition level. The n.sup.th level smooth component is then inputted into a corresponding neural network pre-trained to filter out noise in that component by pattern recognition in the wavelet domain. Additional rough components, beginning at the highest level, may also be retained and inputted into corresponding neural networks pre-trained to filter out noise in those components also by pattern recognition in the wavelet domain. In any case, an inverse discrete wavelet transform is performed on the combined output from all the neural networks to recover a clean signal back in the time domain.

  7. Simplified signal processing for impedance spectroscopy with spectrally sparse sequences

    NASA Astrophysics Data System (ADS)

    Annus, P.; Land, R.; Reidla, M.; Ojarand, J.; Mughal, Y.; Min, M.

    2013-04-01

    Classical method for measurement of the electrical bio-impedance involves excitation with sinusoidal waveform. Sinusoidal excitation at fixed frequency points enables wide variety of signal processing options, most general of them being Fourier transform. Multiplication with two quadrature waveforms at desired frequency could be easily accomplished both in analogue and in digital domains, even simplest quadrature square waves can be considered, which reduces signal processing task in analogue domain to synchronous switching followed by low pass filter, and in digital domain requires only additions. So called spectrally sparse excitation sequences (SSS), which have been recently introduced into bio-impedance measurement domain, are very reasonable choice when simultaneous multifrequency excitation is required. They have many good properties, such as ease of generation and good crest factor compared to similar multisinusoids. Typically, the usage of discrete or fast Fourier transform in signal processing step is considered so far. Usage of simplified methods nevertheless would reduce computational burden, and enable simpler, less costly and less energy hungry signal processing platforms. Accuracy of the measurement with SSS excitation when using different waveforms for quadrature demodulation will be compared in order to evaluate the feasibility of the simplified signal processing. Sigma delta modulated sinusoid (binary signal) is considered to be a good alternative for a synchronous demodulation.

  8. Genomic signal processing: from matrix algebra to genetic networks.

    PubMed

    Alter, Orly

    2007-01-01

    DNA microarrays make it possible, for the first time, to record the complete genomic signals that guide the progression of cellular processes. Future discovery in biology and medicine will come from the mathematical modeling of these data, which hold the key to fundamental understanding of life on the molecular level, as well as answers to questions regarding diagnosis, treatment, and drug development. This chapter reviews the first data-driven models that were created from these genome-scale data, through adaptations and generalizations of mathematical frameworks from matrix algebra that have proven successful in describing the physical world, in such diverse areas as mechanics and perception: the singular value decomposition model, the generalized singular value decomposition model comparative model, and the pseudoinverse projection integrative model. These models provide mathematical descriptions of the genetic networks that generate and sense the measured data, where the mathematical variables and operations represent biological reality. The variables, patterns uncovered in the data, correlate with activities of cellular elements such as regulators or transcription factors that drive the measured signals and cellular states where these elements are active. The operations, such as data reconstruction, rotation, and classification in subspaces of selected patterns, simulate experimental observation of only the cellular programs that these patterns represent. These models are illustrated in the analyses of RNA expression data from yeast and human during their cell cycle programs and DNA-binding data from yeast cell cycle transcription factors and replication initiation proteins. Two alternative pictures of RNA expression oscillations during the cell cycle that emerge from these analyses, which parallel well-known designs of physical oscillators, convey the capacity of the models to elucidate the design principles of cellular systems, as well as guide the design of synthetic ones. In these analyses, the power of the models to predict previously unknown biological principles is demonstrated with a prediction of a novel mechanism of regulation that correlates DNA replication initiation with cell cycle-regulated RNA transcription in yeast. These models may become the foundation of a future in which biological systems are modeled as physical systems are today. PMID:17634608

  9. IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 53, NO. 7, JULY 2005 2421 On Spectral Theory of Cyclostationary

    E-print Network

    Wang, Jiandong

    /or autocorrelation are periodically time-varying sequences [16], [17], [44]. Discrete-time cyclostationary signals spectrum was defined as the spectrum of a -periodically correlated1 sequence; the spec- tral relationshipIEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 53, NO. 7, JULY 2005 2421 On Spectral Theory

  10. Signal processing in local neuronal circuits based on activity-dependent noise and competition

    NASA Astrophysics Data System (ADS)

    Volman, Vladislav; Levine, Herbert

    2009-09-01

    We study the characteristics of weak signal detection by a recurrent neuronal network with plastic synaptic coupling. It is shown that in the presence of an asynchronous component in synaptic transmission, the network acquires selectivity with respect to the frequency of weak periodic stimuli. For nonperiodic frequency-modulated stimuli, the response is quantified by the mutual information between input (signal) and output (network's activity) and is optimized by synaptic depression. Introducing correlations in signal structure resulted in the decrease in input-output mutual information. Our results suggest that in neural systems with plastic connectivity, information is not merely carried passively by the signal; rather, the information content of the signal itself might determine the mode of its processing by a local neuronal circuit.

  11. Correlation Processing Of Local Seismic Data: Applications for Autonomous Sensor Deployments

    SciTech Connect

    Dodge, D A

    2010-11-16

    Excavation and operation of an underground facility is likely to produce an extensive suite of seismic signals observable at the surface for perhaps several km. Probably a large fraction of such signals will be correlated, so the design of a monitoring framework should include consideration of a correlation processing capability. Correlation detectors have been shown to be significantly more sensitive than beam-forming power detectors. Although correlation detectors have a limited detection footprint, they can be generalized into multi-rank subspace detectors which are sensitive over a much larger range of source mechanisms and positions. Production of subspace detectors can be automated, so their use in an autonomous framework may be contemplated. Waveform correlation also can be used to produce very high precision phase picks which may be jointly inverted to simultaneously relocate groups of events. The relative precision of the resulting hypocenters is sufficient to visualize structural detail at a scale of less than a few tens of meters. Three possible correlation processor systems are presented. All use a subspace signal detection framework. The simplest system uses a single-component sensor and is capable of detection and classification of signals. The most complicated system uses many sensors deployed around the facility, and is capable of detection, classification, and high-precision source location. Data from a deep underground mine are presented to demonstrate the applicability of correlation processing to monitoring an underground facility. Although the source region covers an area of about 600m by 580m, all but two of the events form clusters at a threshold of 0.7. All the events could have been detected and classified by the subspace detection framework, and high-precision picks can be computed for all cluster members.

  12. Subband-domain signal processing for radar array systems

    NASA Astrophysics Data System (ADS)

    Rabinkin, Daniel V.; Pulsone, Nicholas B.

    1999-11-01

    Subband-domain algorithms provide an attractive technique for wideband radar array processing. The subband-domain approach decomposes a received wideband signal into a set of narrowband signals. While the number of processing threads in the system increases, the narrowband signals within each subband can be sampled at a correspondingly slower rate. Therefore, the data rate at the input is similar to that at the output of the subband processor. There are several advantages to the subbanding method. It can simplify typical radar algorithms such as adaptive beamforming and equalization by the virtue of reducing subband signal bandwidth, thereby potentially reducing the computational complexity over an equivalent tapped-delay line approach. It also allows for a greater parallelization of the processing task, hence enabling the use of slower and less power consuming hardware. In order to evaluate the validity of the subbanding approach, it is compared with conventional processing methods. This paper focuses on adaptive beamforming and pulse compression performance for a wideband radar system. The performance of an adaptive beamformer is given for a polyphase filter based subband approach and is measured against narrowband processing. SINR loss curves and beampatterns for a subband system are presented. Design criteria for subband polyphase filter processing that minimizes signal distortion are provided and the distortion is characterized. Finally subband- domain pulse compression is demonstrated and compared with the conventional approach.

  13. Assess sleep stage by modern signal processing techniques.

    PubMed

    Wu, Hau-Tieng; Talmon, Ronen; Lo, Yu-Lun

    2015-04-01

    In this paper, two modern adaptive signal processing techniques, empirical intrinsic geometry and synchrosqueezing transform, are applied to quantify different dynamical features of the respiratory and electroencephalographic signals. We show that the proposed features are theoretically rigorously supported, as well as capture the sleep information hidden inside the signals. The features are used as input to multiclass support vector machines with the radial basis function to automatically classify sleep stages. The effectiveness of the classification based on the proposed features is shown to be comparable to human expert classification-the proposed classification of awake, REM, N1, N2, and N3 sleeping stages based on the respiratory signal (resp. respiratory and EEG signals) has the overall accuracy 81.7% (resp. 89.3%) in the relatively normal subject group. In addition, by examining the combination of the respiratory signal with the electroencephalographic signal, we conclude that the respiratory signal consists of ample sleep information, which supplements to the information stored in the electroencephalographic signal. PMID:25438301

  14. Low power, compact charge coupled device signal processing system

    NASA Technical Reports Server (NTRS)

    Bosshart, P. W.; Buss, D. D.; Eversole, W. L.; Hewes, C. R.; Mayer, D. J.

    1980-01-01

    A variety of charged coupled devices (CCDs) for performing programmable correlation for preprocessing environmental sensor data preparatory to its transmission to the ground were developed. A total of two separate ICs were developed and a third was evaluated. The first IC was a CCD chirp z transform IC capable of performing a 32 point DFT at frequencies to 1 MHz. All on chip circuitry operated as designed with the exception of the limited dynamic range caused by a fixed pattern noise due to interactions between the digital and analog circuits. The second IC developed was a 64 stage CCD analog/analog correlator for performing time domain correlation. Multiplier errors were found to be less than 1 percent at designed signal levels and less than 0.3 percent at the measured smaller levels. A prototype IC for performing time domain correlation was also evaluated.

  15. Signal processing aspects of computer music: A survey

    Microsoft Academic Search

    JAMES ANDERSON MOORER

    1977-01-01

    The application of modern signal processing techniques to the production and processing of musical sound gives the composer and musician a level of freedom and precision of control never before obtainable. This paper surveys the use of analyis of natural sounds for synthesis, the use of speech and vocoder techniques, methods of artificial reverberation, the use of discrete summation formulae

  16. 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.

  17. Inspection problem of composite materials using an ultrasonic signal processing

    E-print Network

    Paris-Sud XI, Université de

    techniques associated to ultrasonic instrumentation are tested for their ability to resolve echoes reflected processing. The ultrasonic testing is based on the detection and the interpretation of the ultrasonic wavesInspection problem of composite materials using an ultrasonic signal processing A. Benammara , R

  18. Genomic Signal Processing: Predicting Basic Molecular Biological Principles

    NASA Astrophysics Data System (ADS)

    Alter, Orly

    2005-03-01

    Advances in high-throughput technologies enable acquisition of different types of molecular biological data, monitoring the flow of biological information as DNA is transcribed to RNA, and RNA is translated to proteins, on a genomic scale. Future discovery in biology and medicine will come from the mathematical modeling of these data, which hold the key to fundamental understanding of life on the molecular level, as well as answers to questions regarding diagnosis, treatment and drug development. Recently we described data-driven models for genome-scale molecular biological data, which use singular value decomposition (SVD) and the comparative generalized SVD (GSVD). Now we describe an integrative data-driven model, which uses pseudoinverse projection (1). We also demonstrate the predictive power of these matrix algebra models (2). The integrative pseudoinverse projection model formulates any number of genome-scale molecular biological data sets in terms of one chosen set of data samples, or of profiles extracted mathematically from data samples, designated the ``basis'' set. The mathematical variables of this integrative model, the pseudoinverse correlation patterns that are uncovered in the data, represent independent processes and corresponding cellular states (such as observed genome-wide effects of known regulators or transcription factors, the biological components of the cellular machinery that generate the genomic signals, and measured samples in which these regulators or transcription factors are over- or underactive). Reconstruction of the data in the basis simulates experimental observation of only the cellular states manifest in the data that correspond to those of the basis. Classification of the data samples according to their reconstruction in the basis, rather than their overall measured profiles, maps the cellular states of the data onto those of the basis, and gives a global picture of the correlations and possibly also causal coordination of these two sets of states. Mapping genome-scale protein binding data using pseudoinverse projection onto patterns of RNA expression data that had been extracted by SVD and GSVD, a novel correlation between DNA replication initiation and RNA transcription during the cell cycle in yeast, that might be due to a previously unknown mechanism of regulation, is predicted. (1) Alter & Golub, Proc. Natl. Acad. Sci. USA 101, 16577 (2004). (2) Alter, Golub, Brown & Botstein, Miami Nat. Biotechnol. Winter Symp. 2004 (www.med.miami.edu/mnbws/alter-.pdf)

  19. 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.

  20. Electrophysiological correlates of processing faces of younger and older individuals

    E-print Network

    Johnson, Marcia K.

    ) for younger than older faces at occipito-temporal electrodes; and (iv) larger late positive potential peakingElectrophysiological correlates of processing faces of younger and older individuals Natalie C, West Haven, CT, USA The 'own-age bias' in face processing suggests that the age of a face constitutes

  1. The development of a cognitive process-oriented correlation model

    E-print Network

    Kneuven, Richard James

    1988-01-01

    Plan. . . . . . . . . . . . . American Literature Unit Plan. Cognitive Information-Processing Model. . CHAPTER V SUMMARY, LIMITATIONS) CONLCUSIONS, AND IMPLICATIONS. Summary. Limitations. Conclusions. Implications. REFERENCES, APPENDIX A...THE DEVELOPMENT OF A COGNITIVE PROCESS-ORIENTED CORRELATION MODEL A Thesis by RICHARD JAMES KNEUVEN Submitted to the Office of Graduate Studies of Texas AIIM University in partial fulfillment of the requirements for the degree of MASTER...

  2. Neural Correlates of Semantic Competition during Processing of Ambiguous Words

    ERIC Educational Resources Information Center

    Bilenko, Natalia Y.; Grindrod, Christopher M.; Myers, Emily B.; Blumstein, Sheila E.

    2009-01-01

    The current study investigated the neural correlates that underlie the processing of ambiguous words and the potential effects of semantic competition on that processing. Participants performed speeded lexical decisions on semantically related and unrelated prime-target pairs presented in the auditory modality. The primes were either ambiguous…

  3. Signal processing techniques for atrial fibrillation source detection.

    PubMed

    Ambadkar, Minal; Leonelli, Fabio M; Sankar, Ravi

    2014-01-01

    In clinical practice, Atrial Fibrillation (AF) is the most common and critical cardiac arrhythmia encountered. The treatment that can ensure permanent AF removal is catheter ablation, where cardiologists destroy the affected cardiac muscle cells with RF or Laser. In this procedure it is necessary to know exactly from which part of the heart AF triggers are originated. Various signal processing algorithms provide a strong tool to track AF sources. This study proposes, signal processing techniques that can be exploited for characterization, analysis and source detection of AF signals. These algorithms are implemented on Electrocardiogram (ECG) and intracardiac signals which contain important information that allows the analysis of anatomic and physiologic aspects of the whole cardiac muscle. PMID:25570578

  4. Advanced Signal Processing for the Blu-ray Disc System

    Microsoft Academic Search

    Bert Stek; Rob Otte; Theo Jansen; David Modrie

    2003-01-01

    Advanced signal processing techniques enable higher capacities for the Blu-ray Disc (BD) system. A signal-to-noise analysis of a Limit Equalizer circuit in the BD system is performed. Limit equalizer (LE) and adaptive controlled partial response maximum likelihood (PRML) bit detection schemes are compared on the basis of system margins. Measurements with an adaptive equaliser were also performed to improve tangential

  5. Visualizing confusion matrices for multidimensional signal detection correlational methods

    NASA Astrophysics Data System (ADS)

    Zhou, Yue; Wischgoll, Thomas; Blaha, Leslie M.; Smith, Ross; Vickery, Rhonda J.

    2013-12-01

    Advances in modeling and simulation for General Recognition Theory have produced more data than can be easily visualized using traditional techniques. In this area of psychological modeling, domain experts are struggling to find effective ways to compare large-scale simulation results. This paper describes methods that adapt the web-based D3 visualization framework combined with pre-processing tools to enable domain specialists to more easily interpret their data. The D3 framework utilizes Javascript and scalable vector graphics (SVG) to generate visualizations that can run readily within the web browser for domain specialists. Parallel coordinate plots and heat maps were developed for identification-confusion matrix data, and the results were shown to a GRT expert for an informal evaluation of their utility. There is a clear benefit to model interpretation from these visualizations when researchers need to interpret larger amounts of simulated data.

  6. Application of homomorphic signal processing to stress wave factor analysis

    NASA Technical Reports Server (NTRS)

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

    1985-01-01

    The stress wave factor (SWF) signal, which is the output of an ultrasonic testing system where the transmitting and receiving transducers are coupled to the same face of the test structure, is analyzed in the frequency domain. The SWF signal generated in an isotropic elastic plate is modelled as the superposition of successive reflections. The reflection which is generated by the stress waves which travel p times as a longitudinal (P) wave and s times as a shear (S) wave through the plate while reflecting back and forth between the bottom and top faces of the plate is designated as the reflection with p, s. Short-time portions of the SWF signal are considered for obtaining spectral information on individual reflections. If the significant reflections are not overlapped, the short-time Fourier analysis is used. A summary of the elevant points of homomorphic signal processing, which is also called cepstrum analysis, is given. Homomorphic signal processing is applied to short-time SWF signals to obtain estimates of the log spectra of individual reflections for cases in which the reflections are overlapped. Two typical SWF signals generated in aluminum plates (overlapping and non-overlapping reflections) are analyzed.

  7. P-code enhanced method for processing encrypted GPS signals without knowledge of the encryption code

    NASA Technical Reports Server (NTRS)

    Meehan, Thomas K. (Inventor); Thomas, Jr., Jess Brooks (Inventor); Young, Lawrence E. (Inventor)

    2000-01-01

    In the preferred embodiment, an encrypted GPS signal is down-converted from RF to baseband to generate two quadrature components for each RF signal (L1 and L2). Separately and independently for each RF signal and each quadrature component, the four down-converted signals are counter-rotated with a respective model phase, correlated with a respective model P code, and then successively summed and dumped over presum intervals substantially coincident with chips of the respective encryption code. Without knowledge of the encryption-code signs, the effect of encryption-code sign flips is then substantially reduced by selected combinations of the resulting presums between associated quadrature components for each RF signal, separately and independently for the L1 and L2 signals. The resulting combined presums are then summed and dumped over longer intervals and further processed to extract amplitude, phase and delay for each RF signal. Precision of the resulting phase and delay values is approximately four times better than that obtained from straight cross-correlation of L1 and L2. This improved method provides the following options: separate and independent tracking of the L1-Y and L2-Y channels; separate and independent measurement of amplitude, phase and delay L1-Y channel; and removal of the half-cycle ambiguity in L1-Y and L2-Y carrier phase.

  8. Synthesis and processing of pseudo noise signals by spin precession in Y3 Fe5O12 films

    NASA Astrophysics Data System (ADS)

    Kolokoltsev, Oleg V.; Ordóñez-Romero, César L.; Qureshi, Naser

    2011-07-01

    A simple method for synthesis of phase shift keying (PSK) signals in the microwave frequency range is presented. It is shown that the signal coding and processing can be efficiently realized by spin excitations in thin ferrite films. PSK signals are constructed through control of magnetization precession in a magnetic material by a pulsed magnetic field, and their compression is performed by a spin-wave based correlator, eliminating the need for semiconductor circuitry.

  9. Digital processing of RF signals from optical frequency combs

    NASA Astrophysics Data System (ADS)

    Cizek, Martin; Smid, Radek; Buchta, Zden?k.; Mikel, B?etislav; Lazar, Josef; Cip, Ond?ej

    2013-01-01

    The presented work is focused on digital processing of beat note signals from a femtosecond optical frequency comb. The levels of mixing products of single spectral components of the comb with CW laser sources are usually very low compared to products of mixing all the comb components together. RF counters are more likely to measure the frequency of the strongest spectral component rather than a weak beat note. Proposed experimental digital signal processing system solves this problem by analyzing the whole spectrum of the output RF signal and using software defined radio (SDR) algorithms. Our efforts concentrate in two main areas: Firstly, using digital servo-loop techniques for locking free running continuous laser sources on single components of the fs comb spectrum. Secondly, we are experimenting with digital signal processing of the RF beat note spectrum produced by f-2f 1 technique used for assessing the offset and repetition frequencies of the comb, resulting in digital servo-loop stabilization of the fs comb. Software capable of computing and analyzing the beat-note RF spectrums using FFT and peak detection was developed. A SDR algorithm performing phase demodulation on the f- 2f signal is used as a regulation error signal source for a digital phase-locked loop stabilizing the offset frequency of the fs comb.

  10. Reconfigurable high-speed optical signal processing and high-capacity optical transmitter

    NASA Astrophysics Data System (ADS)

    Chitgarha, Mohammad Reza

    The field of optics and photonics enables several technologies including communication, bioimaging, spectroscopy, Ladars, microwave photonics and data processing [1-139]. The ability to use and manipulate large amounts of data is transforming many vital areas of society. The high capacity that optics brought to communications might also bring advantages to increase performance in signal processing by using a novel all-optical implementation of a tapped-delay-line, a fundamental building block for digital signal processing. This all-optical alternative provides real-time processing of amplitude- and phase-encoded optical fields, such that the overall potential speed-up is 10-100 fold faster than individual electronic processors with 5 GHz clock speeds. It can also enhance the optical data generation and transmission techniques by using different optical nonlinear processes to achieve higher baud rate data with more complex modulation format. Here, we demonstrate a reconfigurable high- speed optical tapped-delay-line, enabling several fundamental real-time signal processing functions such as equalization, correlation and discrete Fourier transform. Using nonlinear optics and dispersive elements, continuous tunability in time, amplitude and phase of the tapped-delay-line can be achieved at high speed. We also demonstrate a reconfigurable optical generation of higher-order modulation formats including pulse-amplitude-modulation (PAM) signals and quadrature-amplitude-modulation (QAM) signals [140-195].

  11. Aperiodic signals processing via parameter-tuning stochastic resonance in a photorefractive ring cavity

    SciTech Connect

    Li, Xuefeng, E-mail: lixfpost@163.com [School of Science, Xi'an University of Post and Telecommunications, Xi'an, 710121 (China)] [School of Science, Xi'an University of Post and Telecommunications, Xi'an, 710121 (China); Cao, Guangzhan; Liu, Hongjun [Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, 710119 (China)] [Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, 710119 (China)

    2014-04-15

    Based on solving numerically the generalized nonlinear Langevin equation describing the nonlinear dynamics of stochastic resonance by Fourth-order Runge-Kutta method, an aperiodic stochastic resonance based on an optical bistable system is numerically investigated. The numerical results show that a parameter-tuning stochastic resonance system can be realized by choosing the appropriate optical bistable parameters, which performs well in reconstructing aperiodic signals from a very high level of noise background. The influences of optical bistable parameters on the stochastic resonance effect are numerically analyzed via cross-correlation, and a maximum cross-correlation gain of 8 is obtained by optimizing optical bistable parameters. This provides a prospective method for reconstructing noise-hidden weak signals in all-optical signal processing systems.

  12. Statistical signal processing for an implantable ethanol biosensor.

    PubMed

    Han, Jae-Joon; Doerschuk, Peter C; Gelfand, Saul B; O'Connor, Sean J

    2006-01-01

    The understanding of drinking patterns leading to alcoholism has been hindered by an inability to unobtrusively measure ethanol consumption over periods of weeks to months in the community environment. Signal processing for an implantable ethanol MEMS bio sensor under simultaneous development is described where the sensor-signal processing system will provide a novel approach to this need. For safety and user acceptability issues, the sensor will be implanted subcutaneously and therefore measure peripheral-tissue ethanol concentration. A statistical signal processing system based on detailed models of the physiology and using extended Kalman filtering and dynamic programming tools is described which determines ethanol consumption and kinetics in other compartments from the time course of peripheral-tissue ethanol concentration. PMID:17945790

  13. Detectors and signal processing for high-energy physics

    SciTech Connect

    Rehak, P.

    1981-01-01

    Basic principles of the particle detection and signal processing for high-energy physics experiments are presented. It is shown that the optimum performance of a properly designed detector system is not limited by incidental imperfections, but solely by more fundamental limitations imposed by the quantum nature and statistical behavior of matter. The noise sources connected with the detection and signal processing are studied. The concepts of optimal filtering and optimal detector/amplifying device matching are introduced. Signal processing for a liquid argon calorimeter is analyzed in some detail. The position detection in gas counters is studied. Resolution in drift chambers for the drift coordinate measurement as well as the second coordinate measurement is discussed.

  14. ISLE (Image and Signal Processing LISP Environment) reference manual

    SciTech Connect

    Sherwood, R.J.; Searfus, R.M.

    1990-01-01

    ISLE is a rapid prototyping system for performing image and signal processing. It is designed to meet the needs of a person doing development of image and signal processing algorithms in a research environment. The image and signal processing modules in ISLE form a very capable package in themselves. They also provide a rich environment for quickly and easily integrating user-written software modules into the package. ISLE is well suited to applications in which there is a need to develop a processing algorithm in an interactive manner. It is straightforward to develop the algorithms, load it into ISLE, apply the algorithm to an image or signal, display the results, then modify the algorithm and repeat the develop-load-apply-display cycle. ISLE consists of a collection of image and signal processing modules integrated into a cohesive package through a standard command interpreter. ISLE developer elected to concentrate their effort on developing image and signal processing software rather than developing a command interpreter. A COMMON LISP interpreter was selected for the command interpreter because it already has the features desired in a command interpreter, it supports dynamic loading of modules for customization purposes, it supports run-time parameter and argument type checking, it is very well documented, and it is a commercially supported product. This manual is intended to be a reference manual for the ISLE functions The functions are grouped into a number of categories and briefly discussed in the Function Summary chapter. The full descriptions of the functions and all their arguments are given in the Function Descriptions chapter. 6 refs.

  15. How to estimate the correlation dimension of high-dimensional signals?

    PubMed

    Michalak, Krzysztof Piotr

    2014-09-01

    The paper presents improvements to the Takens-Ellner (TE) algorithm estimating the correlation dimension (d) of high-dimensional signals. The signal being the sum of 4 Lorenz signals and possessing the correlation dimension d approximately equal to 8 was analyzed. The conversion of TE to the classic Grassberger-Proccacia (GP) algorithm is presented that shows the advantage of TE over the GP algorithm. The maximal d estimated for the given number of points in phase space is significantly higher for the TE algorithm than for the GP algorithm. The formula for the precision of individual d estimation is presented. The paper shows, how to estimate the distance corresponding to the end of the Linear Scaling Region in the correlation integral function, even before starting the procedure of d estimation. It makes it possible to reject the majority of longer distances from the analysis reducing the computation time considerably. PMID:25273198

  16. How to estimate the correlation dimension of high-dimensional signals?

    NASA Astrophysics Data System (ADS)

    Michalak, Krzysztof Piotr

    2014-09-01

    The paper presents improvements to the Takens-Ellner (TE) algorithm estimating the correlation dimension (d) of high-dimensional signals. The signal being the sum of 4 Lorenz signals and possessing the correlation dimension d approximately equal to 8 was analyzed. The conversion of TE to the classic Grassberger-Proccacia (GP) algorithm is presented that shows the advantage of TE over the GP algorithm. The maximal d estimated for the given number of points in phase space is significantly higher for the TE algorithm than for the GP algorithm. The formula for the precision of individual d estimation is presented. The paper shows, how to estimate the distance corresponding to the end of the Linear Scaling Region in the correlation integral function, even before starting the procedure of d estimation. It makes it possible to reject the majority of longer distances from the analysis reducing the computation time considerably.

  17. IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 55, NO. 8, AUGUST 2007 4151 On Probing Signal Design For MIMO Radar

    E-print Network

    Xie, Yao

    of the targets of interest, or more generally to approximate a given transmit beampattern, and also to minimize the cross-correlation of the signals reflected back to the radar by the targets of interest. In this paper the cross-correlation of the signals bounced from various targets of interest--an operation that, once again

  18. The Savant Hypothesis: is autism a signal-processing problem?

    PubMed

    Fabricius, Thomas

    2010-08-01

    Autism is being investigated through many different approaches. This paper suggests the genetic, perceptual, cognitive, and histological findings ultimately manifest themselves as variations of the same signal-processing problem of defective compression. The Savant Hypothesis is formulated from first principles of both mathematical signal-processing and primary neuroscience to reflect the failure of compression. The Savant Hypothesis is applied to the problem of autism in a surprisingly straightforward application. The enigma of the autistic savant becomes intuitive when observed from this approach. PMID:20347529

  19. Calcium Signals: The Lead Currency of Plant Information Processing

    PubMed Central

    Kudla, Jörg; Batisti?, Oliver; Hashimoto, Kenji

    2010-01-01

    Ca2+ signals are core transducers and regulators in many adaptation and developmental processes of plants. Ca2+ signals are represented by stimulus-specific signatures that result from the concerted action of channels, pumps, and carriers that shape temporally and spatially defined Ca2+ elevations. Cellular Ca2+ signals are decoded and transmitted by a toolkit of Ca2+ binding proteins that relay this information into downstream responses. Major transduction routes of Ca2+ signaling involve Ca2+-regulated kinases mediating phosphorylation events that orchestrate downstream responses or comprise regulation of gene expression via Ca2+-regulated transcription factors and Ca2+-responsive promoter elements. Here, we review some of the remarkable progress that has been made in recent years, especially in identifying critical components functioning in Ca2+ signal transduction, both at the single-cell and multicellular level. Despite impressive progress in our understanding of the processing of Ca2+ signals during the past years, the elucidation of the exact mechanistic principles that underlie the specific recognition and conversion of the cellular Ca2+ currency into defined changes in protein–protein interaction, protein phosphorylation, and gene expression and thereby establish the specificity in stimulus response coupling remain to be explored. PMID:20354197

  20. Diffraction tomographic signal processing algorithms for tunnel detection

    SciTech Connect

    Witten, A.J.

    1993-08-01

    Signal processing algorithms have been developed for wave based imaging using diffraction tomography. The basis for this image reconstruction procedure is the generalized projection slice theorem (GPST) which, for homogeneous waves, is an analytic relationship between the spatial Fourier transform of the acquired data and the spatial Fourier transform of the spatial profile (object function) of the object being imaged. Imaging within geophysical diffraction tomography when only homogeneous waves are considered can then be accomplished by inversion of the GPST using standard numerical techniques. In an attenuating background medium or when eddy currents or static fields are considered, a generalized GPST can be derived that involves both real and complex spatial frequencies. In this case, direct Fourier inversion is not possible because of the presence of the complex frequencies. Although direct inversion and, hence, complete imaging is not possible for such cases, the generalized CPST`S can be used to analytically shift the location of data templates matched to specified targets and these templates can, in turn, be correlated with acquired data to detect and estimate the location of the specified targets. Since GPST`s are used directly in the detection problem, there is no need to numerically invert the intergal transform of the object function. For this reason, target detection can be accomplished in a computationally efficient manner independent of the type of measurement or background geologic conditions. A number of GPST`s are derived and the use of GPST`s for both imaging and detection of subsurface voids is demonstrated in several recent applications.

  1. Wavelet-based correlations of impedance cardiography signals and heart rate variability

    NASA Astrophysics Data System (ADS)

    Podtaev, Sergey; Dumler, Andrew; Stepanov, Rodion; Frick, Peter; Tziberkin, Kirill

    2010-04-01

    The wavelet-based correlation analysis is employed to study impedance cardiography signals (variation in the impedance of the thorax z(t) and time derivative of the thoracic impedance (- dz/dt)) and heart rate variability (HRV). A method of computer thoracic tetrapolar polyrheocardiography is used for hemodynamic registrations. The modulus of wavelet-correlation function shows the level of correlation, and the phase indicates the mean phase shift of oscillations at the given scale (frequency). Significant correlations essentially exceeding the values obtained for noise signals are defined within two spectral ranges, which correspond to respiratory activity (0.14-0.5 Hz), endothelial related metabolic activity and neuroendocrine rhythms (0.0095-0.02 Hz). Probably, the phase shift of oscillations in all frequency ranges is related to the peculiarities of parasympathetic and neuro-humoral regulation of a cardiovascular system.

  2. Widespread correlation patterns of fMRI signal across visual cortex reflect eccentricity organization.

    PubMed

    Arcaro, Michael J; Honey, Christopher J; Mruczek, Ryan Eb; Kastner, Sabine; Hasson, Uri

    2015-01-01

    The human visual system can be divided into over two-dozen distinct areas, each of which contains a topographic map of the visual field. A fundamental question in vision neuroscience is how the visual system integrates information from the environment across different areas. Using neuroimaging, we investigated the spatial pattern of correlated BOLD signal across eight visual areas on data collected during rest conditions and during naturalistic movie viewing. The correlation pattern between areas reflected the underlying receptive field organization with higher correlations between cortical sites containing overlapping representations of visual space. In addition, the correlation pattern reflected the underlying widespread eccentricity organization of visual cortex, in which the highest correlations were observed for cortical sites with iso-eccentricity representations including regions with non-overlapping representations of visual space. This eccentricity-based correlation pattern appears to be part of an intrinsic functional architecture that supports the integration of information across functionally specialized visual areas. PMID:25695154

  3. Electrical Engineering Faculty Tulay Adali, Ph.D., North Carolina State University: Statistical signal processing, machine learning for signal

    E-print Network

    Adali, Tulay

    -scale integrated sensor systems, RF-photonic and optical switching devices Anthony Johnson, Ph.D., City College: Statistical signal processing, machine learning for signal processing, adaptive signal processing, biomedical: Optical communications, non-linear optics, lasers, bio-photonics Chein-I Chang, Ph.D., University

  4. Monitoring Signaling Processes in Living Cells Using Biosensors

    NSDL National Science Digital Library

    Klaus Hahn (Scripps Research Institute; Department of Cell Biology; REV)

    2003-10-21

    This collection of nine animations shows how different types of biosensors report changes in cellular processes through the production of a visually detectable signal. Biosensors can be created by attaching one or more fluorescent proteins (such as green fluorescent protein) to a target protein or peptide or by attaching a fluorescent dye that is sensitive to its environment to a protein or peptide. Conformational changes in proteins in response to ligand binding, changes in the concentration of cellular metabolites or signaling messengers, changes in protein localization, and changes in protein activity or covalent modification can all be detected with biosensors. These animations can be used separately or together to illustrate how molecular biology, chemistry, and microscopy have converged to allow cellular processes to be visualized in living cells. Several of the animations describe the production of a fluorescent resonance energy transfer (FRET) signal.

  5. Analysis of cross-correlations in electroencephalogram signals as an approach to proactive diagnosis of schizophrenia

    E-print Network

    Timashev, Serge F; Polyakov, Yuriy S; Demin, Sergey A; Kaplan, Alexander Ya

    2011-01-01

    We apply flicker-noise spectroscopy (FNS), a time series analysis method operating on structure functions and power spectrum estimates, to study the clinical electroencephalogram (EEG) signals recorded in children/adolescents (11 to 14 years of age) with diagnosed schizophrenia-spectrum symptoms at the National Center for Psychiatric Health (NCPH) of the Russian Academy of Medical Sciences. The EEG signals for these subjects were compared with the signals for a control sample of chronically depressed children/adolescents. The purpose of the study is to look for diagnostic signs of subjects' susceptibility to schizophrenia in the FNS parameters for specific electrodes and cross-correlations between the signals simultaneously measured at different points on the scalp. Our analysis of EEG signals from scalp-mounted electrodes at locations F3 and F4, which are symmetrically positioned in the left and right frontal areas of cerebral cortex, respectively, demonstrates an essential role of frequency-phase synchroniz...

  6. Signal processing of rotating pancake eddy current signal for steam generator tubes

    SciTech Connect

    Kumano, S.; Kawase, N.; Kawata, K. [Mitsubishi Heavy Industries, Ltd., Kobe (Japan); Kurokawa, A. [Japan Power Engineering Inspection Corp., Tokyo (Japan)

    1995-08-01

    For the accurate detection of flaws on the steam generator tubes by the eddy current inspection, it is important for the ECT signal processing to remove noise elements such as supporting objects around the tube, and metallic attachments, while saving the effect of flaws in the signal. In this paper, the technique to remove these noises out of the rotating pancake eddy current signals is discussed. Their method combines the image processing techniques with the multifrequency method. The two dimensional filter type is defined based on the heuristics, and the filter coefficients for signals with different scanning frequencies are statistically calculated so that the filtered output becomes similar to the desired signals. Their method was tested with the test pieces, which have EDM slits of 60% depth in the circular direction, metallic attachments of several thickness, and the tube sheet around the tube. The goal of the process was to remove the effects of noise elements, whereas the effect of the slit is stored. The result showed the efficiency of noise reduction power of their method. On the next step, this method is tested on the plant data and is evaluated its power in more detail.

  7. GRAPE: a CASE tool for digital signal parallel processing

    Microsoft Academic Search

    Rudy Lauwereins; Marc Engels; J. Peperstraete; E. Steegmans; J. Van Ginderdeuren

    1990-01-01

    The use of computer-aided software engineering (CASE) tools for stream-oriented real-time digital signal processing (DSP) applications is discussed. These applications are characterized by a continuous stream of data samples or a continuous stream of blocks of data samples arriving at the processing facility at time instances completely determined by the outside world. An overview of existing development tools for DSP

  8. Signal processing in an acousto-optical spectral colorimeter

    NASA Astrophysics Data System (ADS)

    Emeljanov, Sergey P.; Kludzin, Victor V.; Kochin, Leonid B.; Medvedev, Sergey V.; Polosin, Lev L.; Sokolov, Vladimir K.

    2002-02-01

    The algorithms of spectrometer signals processing in the acousto-optical spectral colorimeter, proposed earlier are discussed. This processing is directional on distortion elimination of an optical system spectral characteristics and photoelectric transformations, and also for calculation of tristimulus coefficients X,Y,Z in an international colorimetric system of a CIE - 31 and transformation them in coordinates of recommended CIE uniform contrast systems LUV and LAB.

  9. Functional Languages in Signal Processing Applied to Prosthetic Limb Control

    Microsoft Academic Search

    Alcimar Barbosa Soares; Antonio Claudio Paschoarelli Veiga; Adriano de Oliveira Andrade; Antonio Costa Pereira; Jamil Salem Barbar

    2002-01-01

    This article describes how one can use functional languages to develop a dedicated system for controlling a prosthetic arm. It shows the prototype artificial limb along with the development of the various algorithms and software used to process electromyographic (EMG) signals, to be used as inputs for the control mechanism. Great emphasis is also laid on the parametric modelling used

  10. Technology and Signal Processing for Brain-Machine Interfaces

    Microsoft Academic Search

    Justin C. Sanchez; Jose C. Principe; Toshikazu Nishida; Rizwan Bashirullah; John Harris; Jose Fortes

    2008-01-01

    Neural interfaces hold the promise to become one of the great technological advancements of the 21st century because they can provide new means of communication by directly accessing and interpreting brain intentional states. This article presents a set of grand challenges for brain-machine interfaces (BMI) and investigates recent advances in neurotechnology and signal processing methods to overcome them.

  11. Digital Signal Processing in the Analysis of Genomic Sequences

    Microsoft Academic Search

    Juan V. Lorenzo-Ginori; Aníbal Rodríguez-Fuentes; Ricardo Grau Ábalo; Robersy Sánchez

    2009-01-01

    Digital Signal Processing (DSP) applications in Bioinformatics have received great attention in recent years, where new effective methods for genomic sequence analysis, such as the detection of coding regions, have been devel- oped. The use of DSP principles to analyze genomic sequences requires defining an adequate representation of the nucleo- tide bases by numerical values, converting the nucleotide sequences into

  12. Metamaterials for threat reduction applications: imaging, signal processing, and cloaking

    E-print Network

    Metamaterials for threat reduction applications: imaging, signal processing, and cloaking R. D structured materials, termed metamaterials (MM), has dramati- cally expanded our view of electromagnetic with metamaterials provides a promising approach--from a device perspective--towards fill- ing this gap

  13. Time delay estimation for passive sonar signal processing

    Microsoft Academic Search

    G. Carter

    1981-01-01

    An overview of applied research in passive sonar signal processing estimation techniques for naval systems is presented. The naval problem that motivates time delay estimation is the source state estimation problem. A discussion of this problem in terms of estimating the position and velocity of a moving acoustic source is presented. Optimum bearing and range estimators are presented for the

  14. Signal processing for the TOPAZ Time Projection Chamber

    SciTech Connect

    Ikeda, H.; Iwasaki, H.; Iwata, S.; Kobayashi, M.; Matsuda, T.; Nakamura, K.; Yamauchi, M.; Aihara, H.; Enomoto, R.; Fujii, H.

    1987-02-01

    The signals from the TOPAZ Time Projection Chamber, after being processed by a low noise preamplifier and a shaper amplifier, are recorded by a CCD based digitizer system. The system achieved an integral operation in the environment of FASTBUS with Sector Sequencers and FPI.

  15. Model Based Signal Processing Algorithm for MIDP GPR

    E-print Network

    Kansas, University of

    Model Based Signal Processing Algorithm for MIDP GPR Visweswaran Srinivasamurthy, Dr. Muhammad to review this report. #12;iii Abstract The use of Ground-penetrating Radar (GPR) for geological exploration of the subsurface layers in terms of an equivalent electrical parameter called Permittivity. The GPR data

  16. International Symposium on Image and Signal Processing and Analysis,

    E-print Network

    Hurdal, Monica K.

    and Applications in Bayesian Signal Processing I C.6 Machine Vision 20:00 Gala Dinner ­ Bosphorus Cruise Ship #12 on Advances in Design and Implementation of Multirate Filters and Filter Banks 12:30- 13:30 Lunch Break 13: Energy-Aware DSP Algorithm Design Professor Lars Wanhammar Division of Electronics Systems, Department

  17. Computation-Efficient Image Signal Processing for CMOS Image Sensors

    Microsoft Academic Search

    Ki-Seok Kwon; Eun-Joo Bae; Seokho Lee; Jinook Song; In-Cheol Park

    This paper presents an efficient image signal processing method proposed for CMOS image sensors. In the proposed method, the color correction is moved to the front of the color demosaic to reduce the arithmetic complexity required in the color correction to one third, and a new color correction method is suggested to achieve good images with less data. In spite

  18. Low complexity digital signal processing system design techniques

    Microsoft Academic Search

    Jong-sun Park

    2005-01-01

    Complexity reduction in the Digital Signal Processing (DSP) system design has been of particular interest since lower computational complexity leads to high performance and low power design. In this work, we present low complexity DSP design techniques. The first part of this work is about low complexity finite impulse response (FIR) filter and discrete cosine transform (DCT) architectures based on

  19. Applets for Chromatography, Signal Processing and General Analytical Chemistry

    NSDL National Science Digital Library

    This site offers Java-based applets as organized in 4 categories: analytical and general chemistry, instrumental chemical analysis, instrumentation/signal processing, data analysis/chemometrics. Each applet includes a short introduction followed by a user controlled input of experimental conditions, such as seen for diffusion in electrochemistry.

  20. Acoustic Signal Processing for Pipe Condition Assessment, Report #4360

    EPA Science Inventory

    Unique to prestressed concrete cylinder pipe (PCCP), individual wire breaks create an excitation in the pipe wall that may vary in response to the remaining compression of the pipe core. This project was designed to improve acoustic signal processing for pipe condition assessment...

  1. Ultrafast optical signal processing based upon space-time dualities

    Microsoft Academic Search

    James van Howe; Chris Xu

    2006-01-01

    The last two decades have seen a wealth of optical instrumentation based upon the concepts of space-time duality. A historical overview of how this beautiful framework has been exploited to develop instruments for optical signal processing is presented. The power of this framework is then demonstrated by reviewing four devices in detail based upon space-time dualities that have been experimentally

  2. Applications of convex optimization in signal processing and digital communication

    Microsoft Academic Search

    Zhi-Quan Luo

    2003-01-01

    In the last two decades, the mathematical programming community has witnessed some spectacular advances in interior point methods and robust optimization. These advances have recently started to signifi- cantly impact various fields of applied sciences and engineering where computational efficiency is essential. This paper focuses on two such fields: digital signal processing and communication. In the past, the widely used

  3. Multimedia Signal Processing for Behavioral Quantification in Neuroscience

    E-print Network

    . The scientific study of animal behavior or Ethology is a discipline that was developed in the early and mid-twentieth century. What we are now witnessing is the growth of the field of Quantitative Ethology, aided examine four case studies of Quantitative Ethology using audio and video signal processing. The field

  4. Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing

    E-print Network

    Boyer, Edmond

    soundtrack is somehow robust against impairments. Optical sound recording has indeed an interesting and rich the last years. However, the restoration of the soundtrack has been mainly performed in the sound domain, using signal processing methods, despite the fact that it is recorded as a continuous image between

  5. Bioimaging: A new frontier area for signal processing research

    Microsoft Academic Search

    J.-C. Olivo-Marin

    2009-01-01

    It is now a common consensus that in-depth understanding of biological systems requires robust and systematic quantification of their spatiotemporal characteristics. This endeavour has been significantly enlightened over the past decades thanks to the numerous advances in fluorescent probes, labeling techniques and microscopy systems. It is likewise a consensus that more powerful and specific signal\\/image processing methods are henceforth required

  6. A Signal Processing System for Underwater Acoustic ROV Communication

    Microsoft Academic Search

    Lee E. Freitag; J. A. Catipovic

    1989-01-01

    A high performance system for communication with untethered underwater vehicles is presented. The system is centered around multiple digital processors which perform a variety of signal processing tasks. The processors are combined into an array using a flexible architecture designed for communication prcessing. A basic system has been tested at 5 kbit\\/sec over the Rayleigh-fading multipath channel in Woods Hole

  7. Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing

    E-print Network

    Boyer, Edmond

    implantable devices (CIDs), such as cardiac resynchronization therapy pacemaker (CRT-P) and car- diacHindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2008 December 2007; Accepted 7 July 2008 Recommended by Qi Tian Current cardiac implantable devices offer

  8. [book REVIEW] IEEE SIGNAL PROCESSING MAGAZINE [128] JULY 2008

    E-print Network

    Fowler, James E.

    , while more recent methods such as blind image deconvolution, anisotropic diffu- sion, and inpainting go[book REVIEW] IEEE SIGNAL PROCESSING MAGAZINE [128] JULY 2008 Mathematics of Digital Images@ece.msstate.edu), Mississippi State University. T he field of digital imag- ing is vast and diverse. At its foundations

  9. VOLUME 7, ISSUE 3 JULY 2011 Signal Processing in Acoustics

    E-print Network

    Jaffe, Jules

    VOLUME 7, ISSUE 3 JULY 2011 Signal Processing in Acoustics Acoustics Today A publication of the Acoustical Society of America Model-Based Ocean Acoustics Physical and Engineering Acoustics Speech have been applied to data with biological origins: ­ "Three-dimensional passive acoustic localization

  10. Signal Processing for Phased Array Feeds in Radio Astronomical Telescopes

    E-print Network

    Wirthlin, Michael J.

    Signal Processing for Phased Array Feeds in Radio Astronomical Telescopes Brian D. Jeffs, Senior (PAFs) for radio telescopes can increase the instrument field of view and sky survey speed. Unique numerical simulations and exper- imental data from a 19 element PAF on the Green Bank 20-Meter Telescope

  11. Genomic Signal Processing: From Matrix Algebra to Genetic Networks

    E-print Network

    Utah, University of

    harmonic and digital ring oscillators. 1. Introduction 1.1. DNA Microarray Technology and Genome the emergence of the DNA microarray hybridization technology in the past decade. This novel experimental high#12;2 Genomic Signal Processing: From Matrix Algebra to Genetic Networks Orly Alter Summary DNA

  12. STRUCTURAL HEALTH MONITORING INSTRUMENTATION, SIGNAL PROCESSING AND INTERPRETATION WITH PIEZOELECTRIC

    E-print Network

    Giurgiutiu, Victor

    STRUCTURAL HEALTH MONITORING INSTRUMENTATION, SIGNAL PROCESSING AND INTERPRETATION and understanding. #12;iii ABSTRACT Structural health monitoring (SHM) is a major concern in engineering community. SHM sets out to determine the health of a structure by reading an array of sensors that are embedded

  13. Advanced Turbulence Measurements and Signal Processing for Hydropower Flow Characterization

    E-print Network

    on turbine performance, structural loading, and fatigue. Signal Post-Processing Algorithms for Acoustic). Representative Projects · Effects of Large Scale Energetic Eddies on MHK Turbine Performance ­ ORNL measured (MHK) development sites and around scaled MHK turbine technologies in the laboratory

  14. Signal processing underlying extrinsic control of stem cell fate

    E-print Network

    Zandstra, Peter W.

    Signal processing underlying extrinsic control of stem cell fate Ryan E. Davey and Peter W. Zandstra Purpose of review Strategies to manipulate stem cells for therapeutic applications are limited by our inability to control or predict stem cell fate decisions in response to exogenous stimuli

  15. SPLINES : A PERFECT FIT FOR SIGNAL\\/IMAGE PROCESSING

    Microsoft Academic Search

    Michael Unser

    1999-01-01

    This paper attempts to fullfill three goals. The first one is to provide a tutorial on splinesthat is geared to a signal processing audience. The second one is to gather all their importantproperties, and to provide an overview of the mathematical and computational tools available;i.e., a road map for the practitioner with references to the appropriate literature. The third goalis

  16. Mobile Social Signal Processing: Vision and Research Alessandro Vinciarelli

    E-print Network

    Vinciarelli, Alessandro

    and behavior of their users (e.g., po- sition, movement, hand grip behavior, proximity to social network on Mobile Social Signal Processing (SSP). The Workshop aims at bringing together the Mobile HCI and Social behavior in human­human and human­ machine interactions. While dealing with similar problems, the two

  17. Signal processing in medical imaging and image-guided intervention

    Microsoft Academic Search

    Milan Sonka

    2011-01-01

    Thisis an introductionto a specialsession ofICASSP devoted to signalprocessing techniquesin medicalimagingand image analysis that consists of this introduction and 5 research presentations, each addressingone aspect of the medicalimaging field in which signal processing plays an irreplaceable role. The topics cover a broad spectrum of medical imaging problems from image acquisition to image analysis to populationbased anatomical modeling. The focus is

  18. Automatic Extraction of Physiological Features from Vibro-Acoustic Heart Signals: Correlation with Echo-Doppler

    E-print Network

    Intrator, Nathan

    with Echo-Doppler G Amit1 , N Gavriely2 , J Lessick2,3 , N Intrator1 1 School of Computer Science, Tel-acoustic signals carry valuable physiological information that can be potentially used for cardiac monitoring with electrocardiogram and echo-Doppler audio signals. Processing algorithms were developed to extract temporal

  19. Parallel-Processing Software for Correlating Stereo Images

    NASA Technical Reports Server (NTRS)

    Klimeck, Gerhard; Deen, Robert; Mcauley, Michael; DeJong, Eric

    2007-01-01

    A computer program implements parallel- processing algorithms for cor relating images of terrain acquired by stereoscopic pairs of digital stereo cameras on an exploratory robotic vehicle (e.g., a Mars rove r). Such correlations are used to create three-dimensional computatio nal models of the terrain for navigation. In this program, the scene viewed by the cameras is segmented into subimages. Each subimage is assigned to one of a number of central processing units (CPUs) opera ting simultaneously.

  20. Neural Correlates of Bridging Inferences and Coherence Processing

    ERIC Educational Resources Information Center

    Kim, Sung-il; Yoon, Misun; Kim, Wonsik; Lee, Sunyoung; Kang, Eunjoo

    2012-01-01

    We explored the neural correlates of bridging inferences and coherence processing during story comprehension using Positron Emission Tomography (PET). Ten healthy right-handed volunteers were visually presented three types of stories (Strong Coherence, Weak Coherence, and Control) consisted of three sentences. The causal connectedness among…

  1. DoA of gunshot signals in a spatial microphone array: Performance of the interpolated Generalized Cross-Correlation method

    Microsoft Academic Search

    Izabela L. Freire; Josea A. Apolinario

    2011-01-01

    The direction of arrival of impulsive, wide- band audio signals, specifically of gunshot signals, is the main interest of this work. The Generalized Cross- Correlation (GCC) method, typically employed for wide- band signals, is used in a tetrahedral microphone array to estimate horizontal and vertical angles. An investigation on the performance of the scheme is carried out based on signals

  2. A robust sinusoidal signal processing method for interferometers

    NASA Astrophysics Data System (ADS)

    Wu, Xiang-long; Zhang, Hui; Tseng, Yang-Yu; Fan, Kuang-Chao

    2013-10-01

    Laser interferometers are widely used as a reference for length measurement. Reliable bidirectional optical fringe counting is normally obtained by using two orthogonally sinusoidal signals derived from the two outputs of an interferometer with path difference. These signals are subject to be disturbed by the geometrical errors of the moving target that causes the separation and shift of two interfering light spots on the detector. It results in typical Heydemann errors, including DC drift, amplitude variation and out-of-orthogonality of two sinusoidal signals that will seriously reduce the accuracy of fringe counting. This paper presents a robust sinusoidal signal processing method to correct the distorted waveforms by hardware. A corresponding circuit board has been designed. A linear stage equipped with a laser displacement interferometer and a height gauge equipped with a linear grating interferometer are used as the test beds. Experimental results show that, even with a seriously disturbed input waveform, the output Lissajous circle can always be stabilized after signal correction. This robust method increases the stability and reliability of the sinusoidal signals for data acquisition device to deal with pulse count and phase subdivision.

  3. Activation of parallel fiber feedback by spatially diffuse stimuli reduces signal and noise correlations via independent mechanisms in a cerebellum-like structure.

    PubMed

    Simmonds, Benjamin; Chacron, Maurice J

    2015-01-01

    Correlations between the activities of neighboring neurons are observed ubiquitously across systems and species and are dynamically regulated by several factors such as the stimulus' spatiotemporal extent as well as by the brain's internal state. Using the electrosensory system of gymnotiform weakly electric fish, we recorded the activities of pyramidal cell pairs within the electrosensory lateral line lobe (ELL) under spatially localized and diffuse stimulation. We found that both signal and noise correlations were markedly reduced (>40%) under the latter stimulation. Through a network model incorporating key anatomical features of the ELL, we reveal how activation of diffuse parallel fiber feedback from granule cells by spatially diffuse stimulation can explain both the reduction in signal as well as the reduction in noise correlations seen experimentally through independent mechanisms. First, we show that burst-timing dependent plasticity, which leads to a negative image of the stimulus and thereby reduces single neuron responses, decreases signal but not noise correlations. Second, we show trial-to-trial variability in the responses of single granule cells to sensory input reduces noise but not signal correlations. Thus, our model predicts that the same feedback pathway can simultaneously reduce both signal and noise correlations through independent mechanisms. To test this prediction experimentally, we pharmacologically inactivated parallel fiber feedback onto ELL pyramidal cells. In agreement with modeling predictions, we found that inactivation increased both signal and noise correlations but that there was no significant relationship between magnitude of the increase in signal correlations and the magnitude of the increase in noise correlations. The mechanisms reported in this study are expected to be generally applicable to the cerebellum as well as other cerebellum-like structures. We further discuss the implications of such decorrelation on the neural coding strategies used by the electrosensory and by other systems to process natural stimuli. PMID:25569283

  4. Activation of Parallel Fiber Feedback by Spatially Diffuse Stimuli Reduces Signal and Noise Correlations via Independent Mechanisms in a Cerebellum-Like Structure

    PubMed Central

    Simmonds, Benjamin; Chacron, Maurice J.

    2015-01-01

    Correlations between the activities of neighboring neurons are observed ubiquitously across systems and species and are dynamically regulated by several factors such as the stimulus' spatiotemporal extent as well as by the brain's internal state. Using the electrosensory system of gymnotiform weakly electric fish, we recorded the activities of pyramidal cell pairs within the electrosensory lateral line lobe (ELL) under spatially localized and diffuse stimulation. We found that both signal and noise correlations were markedly reduced (>40%) under the latter stimulation. Through a network model incorporating key anatomical features of the ELL, we reveal how activation of diffuse parallel fiber feedback from granule cells by spatially diffuse stimulation can explain both the reduction in signal as well as the reduction in noise correlations seen experimentally through independent mechanisms. First, we show that burst-timing dependent plasticity, which leads to a negative image of the stimulus and thereby reduces single neuron responses, decreases signal but not noise correlations. Second, we show trial-to-trial variability in the responses of single granule cells to sensory input reduces noise but not signal correlations. Thus, our model predicts that the same feedback pathway can simultaneously reduce both signal and noise correlations through independent mechanisms. To test this prediction experimentally, we pharmacologically inactivated parallel fiber feedback onto ELL pyramidal cells. In agreement with modeling predictions, we found that inactivation increased both signal and noise correlations but that there was no significant relationship between magnitude of the increase in signal correlations and the magnitude of the increase in noise correlations. The mechanisms reported in this study are expected to be generally applicable to the cerebellum as well as other cerebellum-like structures. We further discuss the implications of such decorrelation on the neural coding strategies used by the electrosensory and by other systems to process natural stimuli. PMID:25569283

  5. Biomechanical Correlates of Surface Electromyography Signals Obtained during Swallowing by Healthy Adults

    ERIC Educational Resources Information Center

    Crary, Michael A.; Carnaby (Mann), Giselle D.; Groher, Michael E.

    2006-01-01

    Purpose: The purpose of this study was to describe biomechanical correlates of the surface electromyographic signal obtained during swallowing by healthy adult volunteers. Method: Seventeen healthy adults were evaluated with simultaneous videofluoroscopy and surface electromyography (sEMG) while swallowing 5 mL of liquid barium sulfate. Three…

  6. Passive Sensor Imaging Using Cross Correlations of Noisy Signals in a Scattering Medium

    Microsoft Academic Search

    G. Papanicolaou; J. Garnier

    2008-01-01

    It is well known that the travel time or even the full Green's function between two passive sensors can be estimated from the cross correlation of recorded signal amplitudes generated by ambient noise sources. It is also known that the direction of the energy flux from the noise sources affects the estimation of the travel time. Using the stationary phase

  7. Study on Correlative Dimension of HRV Signals and Its Clinical Applications

    Microsoft Academic Search

    Dongping Xiao; Wei He; Hao Yang; Chuanxiang Yu

    2005-01-01

    In this paper an advanced algorithm based on G-P algorithm is introduced to calculate the correlative dimension (CD) of HRV signals. Moreover, Theiler's correction is considered to avoid the autocorrelation effect of the time serials. It will reduce the possibility to get spurious dimension. The algorithm is applied to clinical HRV data which are collected from twelve young healthy subjects

  8. Training Signal Design for Estimation of Correlated MIMO Channels with Colored

    E-print Network

    Hager, William

    Training Signal Design for Estimation of Correlated MIMO Channels with Colored Interference Yong error (MMSE) channel estimator is derived and the optimal training sequences are designed based in the construction of the optimal training sequences. We also design an efficient scheme to feed back the required

  9. RECEIVED SIGNAL STRENGTH-BASED SENSOR LOCALIZATION IN SPATIALLY CORRELATED SHADOWING

    E-print Network

    Buehrer, R. Michael

    strength (RSS) measurements is investigated in this paper. Most studies for RSS lo- calization assume. Index Terms-- received signal strength (RSS), sensor localiza- tion, correlated shadowing, semidefinite (RSS) [3, 4, 5], and time-difference-of-arrival (TDOA) [6]. In this paper, RSS localiza- tion

  10. Advanced algorithms and architectures for signal processing III; Proceedings of the Meeting, San Diego, CA, Aug. 15-17, 1988

    NASA Astrophysics Data System (ADS)

    Luk, Franklin T.

    Various papers on advanced algorithms and architectures for signal processing are presented. The general topics addressed include: matrix computations, signal processing techniques, time-frequency analysis and the Wigner-Ville distribution, fault tolerance and processor implementation techniques, and high resolution beamforming and estimation. Individual subjects discussed include: experimental evaluation of multifrequency angle-of-arrival estimation, adaptive cancellation of correlated signals in a multiple beam antenna system, error effects on the processing of adaptive array data using the bimodal optical computer, new criterion for the determination of the number of signals in high-resolution array processing, reduced dimension beam space broadband source localization, self-calibration techniques for high-resolution array processing, efficient minimum variance distortionless response processing using a systolic array.

  11. Method and apparatus for a single channel digital communications system. [synchronization of received PCM signal by digital correlation with reference signal

    NASA Technical Reports Server (NTRS)

    Couvillon, L. A., Jr.; Carl, C.; Goldstein, R. M.; Posner, E. C.; Green, R. R. (inventors)

    1973-01-01

    A method and apparatus are described for synchronizing a received PCM communications signal without requiring a separate synchronizing channel. The technique provides digital correlation of the received signal with a reference signal, first with its unmodulated subcarrier and then with a bit sync code modulated subcarrier, where the code sequence length is equal in duration to each data bit.

  12. Mass Spectral Peak Distortion Due to Fourier Transform Signal Processing

    NASA Astrophysics Data System (ADS)

    Rockwood, Alan L.; Erve, John C. L.

    2014-12-01

    Distortions of peaks can occur when one uses the standard method of signal processing of data from the Orbitrap and other FT-based methods of mass spectrometry. These distortions arise because the standard method of signal processing is not a linear process. If one adds two or more functions, such as time-dependent signals from a Fourier transform mass spectrometer and performs a linear operation on the sum, the result is the same as if the operation was performed on separate functions and the results added. If this relationship is not valid, the operation is non-linear and can produce unexpected and/or distorted results. Although the Fourier transform itself is a linear operator, the standard algorithm for processing spectra in Fourier transform-based methods include non-linear mathematical operators such that spectra processed by the standard algorithm may become distorted. The most serious consequence is that apparent abundances of the peaks in the spectrum may be incorrect. In light of these considerations, we performed theoretical modeling studies to illustrate several distortion effects that can be observed, including abundance distortions. In addition, we discuss experimental systems where these effects may manifest, including suggested systems for study that should demonstrate these peak distortions. Finally, we point to several examples in the literature where peak distortions may be rationalized by the phenomena presented here.

  13. Modern Techniques in Acoustical Signal and Image Processing

    SciTech Connect

    Candy, J V

    2002-04-04

    Acoustical signal processing problems can lead to some complex and intricate techniques to extract the desired information from noisy, sometimes inadequate, measurements. The challenge is to formulate a meaningful strategy that is aimed at performing the processing required even in the face of uncertainties. This strategy can be as simple as a transformation of the measured data to another domain for analysis or as complex as embedding a full-scale propagation model into the processor. The aims of both approaches are the same--to extract the desired information and reject the extraneous, that is, develop a signal processing scheme to achieve this goal. In this paper, we briefly discuss this underlying philosophy from a ''bottom-up'' approach enabling the problem to dictate the solution rather than visa-versa.

  14. Snore related signals processing in a private cloud computing system.

    PubMed

    Qian, Kun; Guo, Jian; Xu, Huijie; Zhu, Zhaomeng; Zhang, Gongxuan

    2014-09-01

    Snore related signals (SRS) have been demonstrated to carry important information about the obstruction site and degree in the upper airway of Obstructive Sleep Apnea-Hypopnea Syndrome (OSAHS) patients in recent years. To make this acoustic signal analysis method more accurate and robust, big SRS data processing is inevitable. As an emerging concept and technology, cloud computing has motivated numerous researchers and engineers to exploit applications both in academic and industry field, which could have an ability to implement a huge blue print in biomedical engineering. Considering the security and transferring requirement of biomedical data, we designed a system based on private cloud computing to process SRS. Then we set the comparable experiments of processing a 5-hour audio recording of an OSAHS patient by a personal computer, a server and a private cloud computing system to demonstrate the efficiency of the infrastructure we proposed. PMID:25205499

  15. The Scientist and Engineer's Guide to Digital Signal Processing

    NSDL National Science Digital Library

    Smith, Steven W.

    2002-01-01

    Dr. Steve Smith offers his book about digital signal processing (DSP) free, in its entirety, on this site. The DSP guide introduces the reader to the fundamentals, and then delves into digital filters, applications, and complex techniques. All 33 chapters can be downloaded individually or as a whole. The book is quite well written, with plenty of figures, graphs, and illustrations that accompany the text. Smith derives equations for topics such as Fourier and Laplace transforms, and he clearly defines the terms and how to use them. This book is excellent for college students in a DSP or signals communications course.

  16. Data fusion and correlation techniques testbed development audio processing study

    NASA Astrophysics Data System (ADS)

    1990-09-01

    A study was performed as part of the development of the Data Fusion and Correlation Testbed (DFACT) prototype to investigate the audio processing requirements of the DFACT system. The DFACT system was conceived to provide a testbed for design and implementation of software architectures and communications sensor information, and analysis and correlation algorithms, for land electronic warfare. The base system consists of a number of analyst workstations and intercept operator workstations interconnected through Ethernet. A number of computer controlled intercept receivers along with a communications emitter locating system provide data to DFACT for reduction, correlation, and fusion activities. Intercepted messages are transcribed by the intercept operators and stored in a database for further processing by the analysts. The study examines the basic audio processing capabilities required by DFACT both from a functional and processing perspective. Issues related to throughput, storage capacity, and data retrieval are examined, and a suitable system architecture for a DFACT audio processor is described that satisfies all DFACT system audio processing requirements.

  17. INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING Int. J. Adapt. Control Signal Process. 2006; 20:447474

    E-print Network

    Tsiotras, Panagiotis

    -phase permanent-magnet synchronous brushless DC motor. Copyright # 2006 John Wiley & Sons, Ltd. Received 11 April 2005; Revised 27 April 2006; Accepted 22 May 2006 KEY WORDS: wavelets; reaction wheel; DC brushless motor; denoising 1. INTRODUCTION Wavelets have become very popular in signal processing during the last

  18. A latent process regression model for spatially correlated count data.

    PubMed

    McShane, L M; Albert, P S; Palmatier, M A

    1997-06-01

    This paper proposes a regression model for spatially correlated count data that generalizes the work of Zeger (1988, Biometrika 75, 621-629) developed in a time-series setting. In this approach, spatial correlation is introduced through a latent process, and the marginal mean function may contain spatial trends and covariates. Generalized estimating equations are used to estimate and perform marginal inference on the spatial trend and covariate effects. The feasibility of this approach is demonstrated using an example of the distribution of neuronal cell counts in a laboratory culture dish. PMID:9192458

  19. 516 IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 57, NO. 2, FEBRUARY 2009 Reversible Resampling of Integer Signals

    E-print Network

    Hao, Pengwei

    sample data for the transformation during the process or for "undo" recovery after the process. Some and by the NKBRPC of China by Grant 2004CB318005. The associate editor coordinating the review of this manuscript for the transformation during the process or for "undo" recovery after the process. For signal interpolation, a signal

  20. Synthetic aperture radar signal processing on the MPP

    NASA Technical Reports Server (NTRS)

    Ramapriyan, H. K.; Seiler, E. J.

    1987-01-01

    Satellite-borne Synthetic Aperture Radars (SAR) sense areas of several thousand square kilometers in seconds and transmit phase history signal data several tens of megabits per second. The Shuttle Imaging Radar-B (SIR-B) has a variable swath of 20 to 50 km and acquired data over 100 kms along track in about 13 seconds. With the simplification of separability of the reference function, the processing still requires considerable resources; high speed I/O, large memory and fast computation. Processing systems with regular hardware take hours to process one Seasat image and about one hour for a SIR-B image. Bringing this processing time closer to acquisition times requires an end-to-end system solution. For the purpose of demonstration, software was implemented on the present Massively Parallel Processor (MPP) configuration for processing Seasat and SIR-B data. The software takes advantage of the high processing speed offered by the MPP, the large Staging Buffer, and the high speed I/O between the MPP array unit and the Staging Buffer. It was found that with unoptimized Parallel Pascal code, the processing time on the MPP for a 4096 x 4096 sample subset of signal data ranges between 18 and 30.2 seconds depending on options.

  1. An Observational Signal of the Void Shape Correlation and its Link to the Cosmic Web

    NASA Astrophysics Data System (ADS)

    Lee, Jounghun; Hoyle, Fiona

    2015-04-01

    The shapes of cosmic voids are prone to distortions caused by external tidal forces since their low densities imply a lower internal resistance. This susceptibility of the void shapes to tidal distortions makes them useful as indicators of large-scale tidal and density fields, despite the practical difficulty in defining them. Using the void catalog constructed by Pan et al. from the Seventh Data Release of the Sloan Digital Sky Survey (SDSS DR7), we detect a clear 4? signal of spatial correlations of the void shapes on a scale of 20 {{h}-1} Mpc and show that the signal is robust against the projection of the void shapes onto the plane of sky. By constructing a simple analytic model for the void shape correlation, within the framework of tidal torque theory, we demonstrate that the void shape correlation function scales linearly with the two-point correlation function of the linear density field. We also find direct observational evidence for the cross-correlation of the void shapes with the large-scale velocity shear field that was linearly reconstructed by Lee et al. from SDSS DR7. We discuss the possibility of using the void shape correlation function to break the degeneracy between the density parameter and the power spectrum amplitude and to independently constrain the neutrino mass as well.

  2. Tracking the dehydration process of raw honey by synchronous two-dimensional near infrared correlation spectroscopy

    NASA Astrophysics Data System (ADS)

    Chen, Guiyun; Sun, Xin; Huang, Yuping; Chen, Kunjie

    2014-11-01

    Though much attention is paid to honey quality assessment, few reports on characteristic of manually dehydrated honey have been found. The aim of this investigation is to track the dehydration process of raw honey using synchronous two-dimensional (2D) near infrared correlation spectroscopy. To minimize the impact of dehydration to honey quality, seventy-two honey samples from six different dehydration stages were obtained using drum wind drying method with temperature controlled at 40 °C. Their dynamic short-wave NIR spectra from 600 to 1100 nm were collected in the transmission mode from 10 to 50 °C with an increment of 5 °C and were analyzed using synchronous two-dimensional correlation method. Short-wave NIR spectral data has been exploited less than other NIR region for its weaker signal especially for water absorption's interference with useful information. The investigation enlarged the signal at this band using synchronous 2D correlation analysis, revealing the fingerprinting feature of rape honey and chaste honey during the artificial dehydration process. The results have shown that, with the help of 2D correlation analysis, this band can detect the variation of the second overtone of O-H and N-H groups vibration upon their H-bonds forming or collapsing resulted from the interactions between water and solute. The results have also shown that 2D-NIRS method is able to convert the tiny changes in honey constituents into the detectable fingerprinting difference, which provides a new method for assessing honey quality.

  3. Two-point correlation properties of stochastic "cloud processes''

    E-print Network

    Gabrielli, Andrea

    2007-01-01

    We study how the two-point density correlation properties of a point particle distribution are modified when each particle is divided, by a stochastic process, into an equal number of identical "daughter" particles. We consider generically that there may be non-trivial correlations in the displacement fields describing the positions of the different daughters of the same "mother" particle, and then treat separately the cases in which there are, or are not, correlations also between the displacements of daughters belonging to different mothers. For both cases exact formulae are derived relating the structure factor (power spectrum) of the daughter distribution to that of the mother. These results can be considered as a generalization of the analogous equations obtained in ref. [1] (cond-mat/0409594) for the case of stochastic displacement fields applied to particle distributions. An application of the present results is that they give explicit algorithms for generating, starting from regular lattice arrays, st...

  4. Two-point correlation properties of stochastic splitting processes

    NASA Astrophysics Data System (ADS)

    Gabrielli, Andrea; Joyce, Michael

    2008-03-01

    We study how the two-point density correlation properties of a point particle distribution are modified when each particle is divided, by a stochastic process, into an equal number of identical “daughter” particles. We consider generically that there may be nontrivial correlations in the displacement fields describing the positions of the different daughters of the same “mother” particle and then treat separately the cases in which there are, or are not, correlations also between the displacements of daughters belonging to different mothers. For both cases exact formulas are derived relating the structure factor (power spectrum) of the daughter distribution to that of the mothers. An application of these results is that they give explicit algorithms for generating, starting from regular lattice arrays, stochastic particle distributions with an arbitrarily high degree of large-scale uniformity. Such distributions are of interest, in particular, in the context of studies of self-gravitating systems in cosmology.

  5. Nonlinear signal processing of electroencephalograms for automated sleep monitoring

    NASA Astrophysics Data System (ADS)

    Wilson, D.; Rowlands, D. D.; James, Daniel A.; Cutmore, T.

    2005-02-01

    An automated classification technique is desirable to identify the different stages of sleep. In this paper a technique for differentiating the characteristics of each sleep phase has been developed. This is an ideal pre-processor stage for classifying systems such as neural networks. A wavelet based continuous Morlet transform was developed to analyse the EEG signal in both the time and frequency domain. Test results using two 100 epoch EEG test data sets from pre-recorded EEG data are presented. Key rhythms in the EEG signal were identified and classified using the continuous wavelet transform. The wavelet results indicated each sleep phase contained different rhythms and artefacts (noise from muscle movement in the EEG); providing proof that an EEG can be classified accordingly. The coefficients founded by the wavelet transform have been emphasised by statistical techniques. Hypothesis testing was used to highlight major differences between adjacent sleep stages. Various signal processing methods such as power spectrum density and the discrete wavelet transform have been used to emphasise particular characteristics in an EEG. By implementing signal processing methods on an EEG data set specific rules for each sleep stage have been developed suitable for a neural network classification solution.

  6. Deterring watermark collusion attacks using signal processing techniques

    NASA Astrophysics Data System (ADS)

    Lemma, Aweke N.; van der Veen, Michiel

    2007-02-01

    Collusion attack is a malicious watermark removal attack in which the hacker has access to multiple copies of the same content with different watermarks and tries to remove the watermark using averaging. In the literature, several solutions to collusion attacks have been reported. The main stream solutions aim at designing watermark codes that are inherently resistant to collusion attacks. The other approaches propose signal processing based solutions that aim at modifying the watermarked signals in such a way that averaging multiple copies of the content leads to a significant degradation of the content quality. In this paper, we present signal processing based technique that may be deployed for deterring collusion attacks. We formulate the problem in the context of electronic music distribution where the content is generally available in the compressed domain. Thus, we first extend the collusion resistance principles to bit stream signals and secondly present experimental based analysis to estimate a bound on the maximum number of modified versions of a content that satisfy good perceptibility requirement on one hand and destructive averaging property on the other hand.

  7. 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.

  8. Fetal QRS extraction from abdominal recordings via model-based signal processing and intelligent signal merging.

    PubMed

    Haghpanahi, Masoumeh; Borkholder, David A

    2014-08-01

    Noninvasive fetal ECG (fECG) monitoring has potential applications in diagnosing congenital heart diseases in a timely manner and assisting clinicians to make more appropriate decisions during labor. However, despite advances in signal processing and machine learning techniques, the analysis of fECG signals has still remained in its preliminary stages. In this work, we describe an algorithm to automatically locate QRS complexes in noninvasive fECG signals obtained from a set of four electrodes placed on the mother's abdomen. The algorithm is based on an iterative decomposition of the maternal and fetal subspaces and filtering of the maternal ECG (mECG) components from the fECG recordings. Once the maternal components are removed, a novel merging technique is applied to merge the signals and detect the fetal QRS (fQRS) complexes. The algorithm was trained and tested on the fECG datasets provided by the PhysioNet/CinC challenge 2013. The final results indicate that the algorithm is able to detect fetal peaks for a variety of signals with different morphologies and strength levels encountered in clinical practice. PMID:25069479

  9. Signal Processing for Young Child Speech Language Development

    Microsoft Academic Search

    Dongxin Xu; Umit Yapanel; Sharmi Gray; Jill Gilkerson; Jeff Richards; John Hansen

    Speech signal processing and other man-machine interaction technologies have been developed for improved child-computer interaction for education, entertainment, as well as other applications (1, 2). However, for very young children (in the age range of 0 to 4 years old, and especially 0 to 2), such interaction is not encouraged (3, 4). Instead, parent-child interaction is highly recommended (3, 4)

  10. Cathedral-II: A Silicon Compiler for Digital Signal Processing

    Microsoft Academic Search

    H. De Man; J. Rabaey; L. Claesen

    1986-01-01

    The article describes the status of work at IMEC on the Cathedral-II silicon compiler. The compiler was developed to synthesize synchronous multiprocessor system chips for digital signal processing. It is a continuation of work on the Cathedral-I operational silicon compiler for bit-serial digital filters. Cathedral-II is based on a ¿meet in the middle¿ design method that encourages a total separation

  11. REMOTE CARDIAC SURVEILLANCE UTILIZING ADVANCED SIGNAL PROCESSING AND TELECOMMUNICATION TECHNOLOGY

    Microsoft Academic Search

    H. Hutten

    2001-01-01

    Aim: Computer-assisted processing of intramyocardial electrograms employing internet-based transmission to specialized service centers. Materials and methods: Implantable pacemakers provided with broad-bandwidth electrogram telemetry and using fractally coated electrodes render possible the acquisition of intramyocardial electrograms from the spontaneously beating as well as from the paced heart. These signals are transmitted via the Internet to the service center in Graz where

  12. Contributors to a multivariate statistical process control chart signal

    Microsoft Academic Search

    George C. Runger; Frank B. Alt; Douglas C. Montgomery

    1996-01-01

    A significant practical disadvantage of multivariate statistical process control is that it is difficult to determine which of the monitored variables is responsible for the out-of-control signal. While there have been several proposed techniques and diagnostics, most of these have disadvantages. Rather than an ad hoc selection, we use three approaches to develop a diagnostic for a chi-square chart and

  13. Superconductive tapped delay lines for microwave analog signal processing

    Microsoft Academic Search

    R. Withers; A. Anderson; P. Wright; S. Reible

    1983-01-01

    Passive superconducting tapped delay lines have been fabricated for use as matched filters for multigigahertz bandwidth analog signal processing. Specifically, linear frequency-modulated dispersive delay lines, also known as chirp filters, having a bandwidth of 2.6 GHz centered at 4 GHz and a dispersion time of 35 ns have been constructed. The stripline structure consists of a 4000-A-thick patterned niobium film

  14. Universal signal processing method for multimode reflective sensors

    E-print Network

    Larson, Robert Eugene

    1988-01-01

    Chair of Advisory Committee: Dr. Henry F. Taylor An experimental investigation was conducted to determine if the development of a universal signal processing method for multimode fiber optic reflective sensors was possible. A sensor system... was constructed for the measurement of distance as a function of the percentage of light reflectively coupled into an optical fiber from a flat mirror. An internal mirror made from splicing a bare fiber to a fiber coated with a dielectric film, was used as a...

  15. Flash Signal Processing and NAND/ReRAM SSD

    NASA Astrophysics Data System (ADS)

    Takeuchi, K.

    The widespread use of NAND Flash memories in SSDs has unleashed new avenues of innovation for the enterprise and client computing. System-wide architectural changes are required to make full use of the advantages of SSDs in terms of performance, reliability and power. Signal processing technologies are becoming more and more popular to countermeasure all the parasitic effects of a Flash NAND array: the first part of this chapter deals with such techniques.

  16. Lab Exercises: Digital Signal Processing with Field Programmable Gate Arrays

    NSDL National Science Digital Library

    Dr. Uwe Meyer-Baese

    This website features a collection of eight laboratory experiments in the use of Field Programmable Gate Arrays (FPGAs), user-configurable semiconductor devices, for digital signal processing (DSP). The labs cover both leading FPGA vendors (Xilinx and Altera), provide a MatLab/Simulink-based design flow and are intended for use in university-level classes in electrical and computer engineering. Site materials include downloadable files in two versions compatible with each vendor's devices, and student worksheets.

  17. Optoelectronic signal processing using finite impulse response neural networks

    NASA Astrophysics Data System (ADS)

    H. B. Xavier da Silveira, Paulo Eduardo

    2001-08-01

    This thesis investigates the use of finite impulse response neural network as the computational algorithm for efficient optoelectronic signal processing. The study begins with the analysis and development of different suitable algorithms, followed by the optoelectronic design of single-layer and multi-layer architectures, and it is concluded with the presentation of the results of a successful experimental implementation. First, finite impulse response adaptive filters and neural networks-the algorithmic building blocks-are introduced, followed by a description of finite impulse response neural networks. This introduction is followed by a historical background, describing early optoelectronic implementations of these algorithms. Next, different algorithms capable of temporal back-propagation are derived in detail, including a novel modification to the conventional algorithm, called delayed-feedback back- propagation. Based on these algorithms, different optoelectronic processors making use of adaptive volume holograms and three-dimensional optical processing are developed. Two single-layer architectures are presented: the input delay plane architecture and the output delay plane architecture. By combining them it is possible to implement both forward and backward propagation in two complementary multi-layer architectures: the first making use of the conventional temporal back-propagation and the second making use of delayed feedback back-propagation. Next, emphasis is given to a specific application: the processing of signals from adaptive antenna arrays. This research is initiated by computer simulations of different scenarios with multiple broadband signals and jammers, in planar and circular arrays, studying issues such as the effect of modulator non-linearities to the performance of the array, and the relation between the number of jammers and the final nulling depth. Two sets of simulations are presented: the first set applied to RF antenna arrays and the second set applied to an experimental implementation of a sonar adaptive array. Experimental results are presented for a single-layer optical processor making use of a scrolling spatial light modulator for representing the input signal and its delayed versions, photorefractive dynamic gratings for implementing the adaptive weights, differential heterodyning for bipolar signal representation, a phase- locked loop for controlling the optical path length, providing long term interferometric stabilization, and acousto-optic modulators for modulating the feedback error signal. Results for multiple beam-forming and jammer nulling are presented for planar and circular adaptive arrays. Finally, it is also shown how one can determine the position of the signal source from the images diffracted from the photorefractive hologram used to store the dynamic weights.

  18. Noise-benefit forbidden-interval theorems for threshold signal detectors based on cross correlations

    NASA Astrophysics Data System (ADS)

    Mitaim, Sanya; Kosko, Bart

    2014-11-01

    We show that the main forbidden interval theorems of stochastic resonance hold for a correlation performance measure. Earlier theorems held only for performance measures based on mutual information or the probability of error detection. Forbidden interval theorems ensure that a threshold signal detector benefits from deliberately added noise if the average noise does not lie in an interval that depends on the threshold value. We first show that this result holds for correlation for all finite-variance noise and for all forms of infinite-variance stable noise. A second forbidden-interval theorem gives necessary and sufficient conditions for a local noise benefit in a bipolar signal system when the noise comes from a location-scale family. A third theorem gives a general condition for a local noise benefit for arbitrary signals with finite second moments and for location-scale noise. This result also extends forbidden intervals to forbidden bands of parameters. A fourth theorem gives necessary and sufficient conditions for a local noise benefit when both the independent signal and noise are normal. A final theorem derives necessary and sufficient conditions for forbidden bands when using arrays of threshold detectors for arbitrary signals and location-scale noise.

  19. Noise-benefit forbidden-interval theorems for threshold signal detectors based on cross correlations.

    PubMed

    Mitaim, Sanya; Kosko, Bart

    2014-11-01

    We show that the main forbidden interval theorems of stochastic resonance hold for a correlation performance measure. Earlier theorems held only for performance measures based on mutual information or the probability of error detection. Forbidden interval theorems ensure that a threshold signal detector benefits from deliberately added noise if the average noise does not lie in an interval that depends on the threshold value. We first show that this result holds for correlation for all finite-variance noise and for all forms of infinite-variance stable noise. A second forbidden-interval theorem gives necessary and sufficient conditions for a local noise benefit in a bipolar signal system when the noise comes from a location-scale family. A third theorem gives a general condition for a local noise benefit for arbitrary signals with finite second moments and for location-scale noise. This result also extends forbidden intervals to forbidden bands of parameters. A fourth theorem gives necessary and sufficient conditions for a local noise benefit when both the independent signal and noise are normal. A final theorem derives necessary and sufficient conditions for forbidden bands when using arrays of threshold detectors for arbitrary signals and location-scale noise. PMID:25493756

  20. Analysis of cross-correlations in electroencephalogram signals as an approach to proactive diagnosis of schizophrenia

    NASA Astrophysics Data System (ADS)

    Timashev, Serge F.; Panischev, Oleg Yu.; Polyakov, Yuriy S.; Demin, Sergey A.; Kaplan, Alexander Ya.

    2012-02-01

    We apply flicker-noise spectroscopy (FNS), a time series analysis method operating on structure functions and power spectrum estimates, to study the clinical electroencephalogram (EEG) signals recorded in children/adolescents (11 to 14 years of age) with diagnosed schizophrenia-spectrum symptoms at the National Center for Psychiatric Health (NCPH) of the Russian Academy of Medical Sciences. The EEG signals for these subjects were compared with the signals for a control sample of chronically depressed children/adolescents. The purpose of the study is to look for diagnostic signs of subjects' susceptibility to schizophrenia in the FNS parameters for specific electrodes and cross-correlations between the signals simultaneously measured at different points on the scalp. Our analysis of EEG signals from scalp-mounted electrodes at locations F3 and F4, which are symmetrically positioned in the left and right frontal areas of cerebral cortex, respectively, demonstrates an essential role of frequency-phase synchronization, a phenomenon representing specific correlations between the characteristic frequencies and phases of excitations in the brain. We introduce quantitative measures of frequency-phase synchronization and systematize the values of FNS parameters for the EEG data. The comparison of our results with the medical diagnoses for 84 subjects performed at NCPH makes it possible to group the EEG signals into 4 categories corresponding to different risk levels of subjects' susceptibility to schizophrenia. We suggest that the introduced quantitative characteristics and classification of cross-correlations may be used for the diagnosis of schizophrenia at the early stages of its development.

  1. Signal Processing Consideration For A Millimeter Wave Seeker

    NASA Astrophysics Data System (ADS)

    Mahmoodi, A. B.; Kaveh, M.

    1983-10-01

    Since the reflectivity characteristics from target and clutter are considerably different at millimeter wave frequencies, one should not consider the same signal processing philosophies as it's used at lower frequencies. To derive the full advantage of improved resolution capability at such high frequencies the target and clutter signature and their statistical properties should be considered in the design of the operation millimeter wave radar seekers. We are proposing a statistical signal processing approach which can be incorporated in the design of constant false alarm processor of an airborne millimeter wave seeker. This scheme consists of three distinct functional units, (I) An adaptive filter for noise elimination and decorrelation of signal and clutter, (II) A pattern classifier for identifying the type of clutter statistical distribution and (III) A CFAR processor. This scheme enables an airborne millimeter wave radar to process more information during every scan while maintaining a constant false alarm rate by fixing a threshold adaptive to the type of clutter that is encountered.

  2. Signal processing of microbolometer infrared focal-plane arrays

    NASA Astrophysics Data System (ADS)

    Zhang, Junju; Qian, Yunsheng; Chang, Benkang; Xing, Suxia; Sun, Lianjun

    2005-01-01

    A 320×240-uncooled-microbolometer-based signal processing circuit for infrared focal-plane arrays is presented, and the software designs of this circuit system are also discussed in details. This signal processing circuit comprises such devices as FPGA, D/A, A/D, SRAM, Flash, DSP, etc., among which, FPGA is the crucial part, which realizing the generation of drive signals for infrared focal-plane, nonuniformity correction, image enhancement and video composition. The device of DSP, mainly offering auxiliary functions, carries out communication with PC and loads data when power-up. The phase locked loops (PLL) is used to generate high-quality clocks with low phase dithering and multiple clocks are to used satisfy the demands of focal-plane arrays, A/D, D/A and FPGA. The alternate structure is used to read or write SRAM in order to avoid the contradiction between different modules. FIFO embedded in FPGA not only makes full use of the resources of FPGA but acts as the channel between different modules which have different-speed clocks. What's more, working conditions, working process, physical design and management of the circuit are discussed. In software designing, all the function modules realized by FPGA and DSP devices, which are mentioned in the previous part, are discussed explicitly. Particularly to the nonuniformity correction module, the pipeline structure is designed to improve the working frequency and the ability to realize more complex algorithm.

  3. Nonlinear signal processing using neural networks: Prediction and system modelling

    SciTech Connect

    Lapedes, A.; Farber, R.

    1987-06-01

    The backpropagation learning algorithm for neural networks is developed into a formalism for nonlinear signal processing. We illustrate the method by selecting two common topics in signal processing, prediction and system modelling, and show that nonlinear applications can be handled extremely well by using neural networks. The formalism is a natural, nonlinear extension of the linear Least Mean Squares algorithm commonly used in adaptive signal processing. Simulations are presented that document the additional performance achieved by using nonlinear neural networks. First, we demonstrate that the formalism may be used to predict points in a highly chaotic time series with orders of magnitude increase in accuracy over conventional methods including the Linear Predictive Method and the Gabor-Volterra-Weiner Polynomial Method. Deterministic chaos is thought to be involved in many physical situations including the onset of turbulence in fluids, chemical reactions and plasma physics. Secondly, we demonstrate the use of the formalism in nonlinear system modelling by providing a graphic example in which it is clear that the neural network has accurately modelled the nonlinear transfer function. It is interesting to note that the formalism provides explicit, analytic, global, approximations to the nonlinear maps underlying the various time series. Furthermore, the neural net seems to be extremely parsimonious in its requirements for data points from the time series. We show that the neural net is able to perform well because it globally approximates the relevant maps by performing a kind of generalized mode decomposition of the maps. 24 refs., 13 figs.

  4. Signal shredding by autogenic processes in sedimentary systems

    NASA Astrophysics Data System (ADS)

    Jerolmack, D. J.; Paola, C.; Martin, R.

    2009-12-01

    Erosional and depositional landscapes evolve in response to changes in external drivers such as climate, tectonic motion, and eustatic sea level. These changes are typically imposed via time-varying boundary conditions with a wide range of time scales, and are transmitted to the landscape via changes in sediment flux. The response of landscapes is then mediated by the mechanics of sediment transport. Understanding how signals of environmental forcing are transmitted and preserved in sedimentary systems is crucial for predicting landscape response to environmental change, and for the inverse problem of interpreting Earth history from landforms and the depositional record. It is generally understood that climatic or tectonic signals can be modified - for example, damped and/or phase-shifted - as they propagate through sedimentary systems. Here we examine a much stronger effect: sediment transport can act as a noisy, nonlinear filter that destroys (“shreds”) signals of environmental forcing so that they are not merely masked but entirely lost. Signal shredding is analogous to modulated turbulence in fluid flows. We demonstrate that autogenic variations in sediment transport associated with sediment storage and release act as a kind of “morphodynamic turbulence”, with a temporal spectrum and finite-size cutoff similar to fluid turbulence. External signals are destroyed when their time and magnitude scales fall within the range of autogenic fluctuations. Sufficiently high-amplitide and/or long-period signals survive, albeit with superimposed noise. We show using several landscape models that autogenic sediment storage and release, and hence signal shredding, result from the ubiquitous presence of thresholds in sediment transport systems - for example, avalanching, landsliding, bed load transport, and river avulsion. We confirm the signal-shredding effect experimentally by imposing cyclical variations in sediment supply on a table-top rice pile. We suggest that Earth's sedimentary archives could be dominated by transport “noise” on time scales up to tens of thousands of years. This time scale range overlaps in particular with known climatic time scales, meaning that in many systems the physical signature of these signals may be lost. On the other hand, depositional patterns associated with autogenic dynamics may be relatively uninfluenced by high-frequency external processes, and hence statistically predictable.

  5. [A modified speech enhancement algorithm for electronic cochlear implant and its digital signal processing realization].

    PubMed

    Wang, Yulin; Tian, Xuelong

    2014-08-01

    In order to improve the speech quality and auditory perceptiveness of electronic cochlear implant under strong noise background, a speech enhancement system used for electronic cochlear implant front-end was constructed. Taking digital signal processing (DSP) as the core, the system combines its multi-channel buffered serial port (McBSP) data transmission channel with extended audio interface chip TLV320AIC10, so speech signal acquisition and output with high speed are realized. Meanwhile, due to the traditional speech enhancement method which has the problems as bad adaptability, slow convergence speed and big steady-state error, versiera function and de-correlation principle were used to improve the existing adaptive filtering algorithm, which effectively enhanced the quality of voice communications. Test results verified the stability of the system and the de-noising performance of the algorithm, and it also proved that they could provide clearer speech signals for the deaf or tinnitus patients. PMID:25464779

  6. [A modified speech enhancement algorithm for electronic cochlear implant and its digital signal processing realization].

    PubMed

    Wang, Yulin; Tian, Xuelong

    2014-08-01

    In order to improve the speech quality and auditory perceptiveness of electronic cochlear implant under strong noise background, a speech enhancement system used for electronic cochlear implant front-end was constructed. Taking digital signal processing (DSP) as the core, the system combines its multi-channel buffered serial port (McBSP) data transmission channel with extended audio interface chip TLV320AIC10, so speech signal acquisition and output with high speed are realized. Meanwhile, due to the traditional speech enhancement method which has the problems as bad adaptability, slow convergence speed and big steady-state error, versiera function and de-correlation principle were used to improve the existing adaptive filtering algorithm, which effectively enhanced the quality of voice communications. Test results verified the stability of the system and the de-noising performance of the algorithm, and it also proved that they could provide clearer speech signals for the deaf or tinnitus patients. PMID:25508410

  7. Particle image velocimetry correlation signal-to-noise ratio metrics and measurement uncertainty quantification

    NASA Astrophysics Data System (ADS)

    Xue, Zhenyu; Charonko, John J.; Vlachos, Pavlos P.

    2014-11-01

    In particle image velocimetry (PIV) the measurement signal is contained in the recorded intensity of the particle image pattern superimposed on a variety of noise sources. The signal-to-noise-ratio (SNR) strength governs the resulting PIV cross correlation and ultimately the accuracy and uncertainty of the resulting PIV measurement. Hence we posit that correlation SNR metrics calculated from the correlation plane can be used to quantify the quality of the correlation and the resulting uncertainty of an individual measurement. In this paper we extend the original work by Charonko and Vlachos and present a framework for evaluating the correlation SNR using a set of different metrics, which in turn are used to develop models for uncertainty estimation. Several corrections have been applied in this work. The SNR metrics and corresponding models presented herein are expanded to be applicable to both standard and filtered correlations by applying a subtraction of the minimum correlation value to remove the effect of the background image noise. In addition, the notion of a ‘valid’ measurement is redefined with respect to the correlation peak width in order to be consistent with uncertainty quantification principles and distinct from an ‘outlier’ measurement. Finally the type and significance of the error distribution function is investigated. These advancements lead to more robust and reliable uncertainty estimation models compared with the original work by Charonko and Vlachos. The models are tested against both synthetic benchmark data as well as experimental measurements. In this work, {{U}68.5} uncertainties are estimated at the 68.5% confidence level while {{U}95} uncertainties are estimated at 95% confidence level. For all cases the resulting calculated coverage factors approximate the expected theoretical confidence intervals, thus demonstrating the applicability of these new models for estimation of uncertainty for individual PIV measurements.

  8. DSPSR: Digital Signal Processing Software for Pulsar Astronomy

    NASA Astrophysics Data System (ADS)

    van Straten, W.; Bailes, M.

    2011-01-01

    dspsr is a high-performance, open-source, object-oriented, digital signal processing software library and application suite for use in radio pulsar astronomy. Written primarily in C++, the library implements an extensive range of modular algorithms that can optionally exploit both multiple-core processors and general-purpose graphics processing units. After over a decade of research and development, dspsr is now stable and in widespread use in the community. This paper presents a detailed description of its functionality, justification of major design decisions, analysis of phase-coherent dispersion removal algorithms, and demonstration of performance on some contemporary microprocessor architectures.

  9. Digital signal processing in AFM topography and recognition imaging

    NASA Astrophysics Data System (ADS)

    Adamsmair, Stefan; Ebner, Andreas; Hinterdorfer, Peter; Zagar, Bernhard

    2005-10-01

    Atomic force microscopy (AFM) has proven to be a powerful tool to observe topographical details at the nano- and subnanometer scale. Since this is a rather new technique, new enhancements with faster scanning rates, more accurate measurements and more detailed information were developed. This requires also a higher demand on the signal processing and the controlling software. Operating an AFM with analog driven hardware is often limited by drift and noise problems. Here we overcome this problem by introducing digital signal processing capable of accurately stabilizing the piezo control in the newly developed TREC (topography and recognition imaging) mode. In this mode topographical information and molecular recognition between tip bound ligand and surface bound receptors is simultaneously acquired. The sought information is conveyed by slight variations of the minima and maxima of the signal amplitudes. These variations are very small compared to the maximum possible DC deflection. Furthermore, the DC offset exhibits a rather large drift mostly attributed to temperature changes. To obtain reliable tracking results the oscillating photodiode signal needs to be nonlinearly filtered and efficiently separated into four major components: the maxima, the minima, the spatial average of the maxima, and the spatial average of the minima. The recognition image is then obtained by a nonlinear combination of these four components evaluated at spatial locations derived from the zero-crossings of the differentiated signal resulting from a modified differentiator FIR filter. Furthermore, to reliably estimate the DC drift an exponential tracking of the extrema by a first-order IIR filter is performed. The applicability of the proposed algorithms is demonstrated for biotin and avidin.

  10. Knowledge-based signal processing for radar ESM systems

    NASA Astrophysics Data System (ADS)

    Roe, J.; Cussons, S.; Feltham, A.

    1990-10-01

    Radar electronic support measures (ESM) systems perform the functions of threat detection and area surveillance to determine the identity and bearing of surrounding radar emitters. Automatic ESM systems incorporate a passive receiver to measure the parameters of detected radar pulses and an automatic processor to rapidly sort pulses and identify the emitters. Current processors use algorithmic processing methods which are inflexible and do not fully utilize available sources of a priori information. The paper discusses the role of knowledge-based processing methods and how they may be applied to the key ESM signal-processing functions of deinterleaving, merge and emitter identification. ESM processors are required to sort input pulse data streams exceeding one million pulses per second and minimize the reporting latency of new emitters. The paper further discusses the requirements to achieve real-time operation of knowledge-based ESM processing techniques.

  11. Correlation between laser-induced breakdown spectroscopy signal and moisture content

    NASA Astrophysics Data System (ADS)

    Liu, Yuan; Gigant, Lionel; Baudelet, Matthieu; Richardson, Martin

    2012-07-01

    The possibility of using Laser-Induced Breakdown Spectroscopy (LIBS) for measuring the moisture content of fresh food samples is studied. The normalized line emission of oxygen is highly correlated with the moisture content of the sample, cheese in our case, and can be used as a moisture marker in situations where oxygen interference from the matrix is not a critical issue. The linear correlation between the oxygen signal and the moisture content in the sample shows great potential for using LIBS as an alternative spectroscopic method for moisture monitoring.

  12. Net analyte signal based two-dimensional (NAS 2D) correlation near infrared spectroscopy

    NASA Astrophysics Data System (ADS)

    Geng, Ying; Xiang, Bingren

    2010-06-01

    A new method of analysis, based on the net analyte signal presented by Lorber is proposed for the two-dimensional correlation near infrared spectroscopy. A spectra data set under the static perturbation of concentration was collected. NAS is manipulated for removing the information that was unrelated to a certain analyte. To demonstrate the potential of NAS 2D correlation spectroscopy, a set of concentration-dependent near infrared spectra of Sinomenine Hydrochloride in methanol was used as an example. The results show that NAS 2D, reconstructed from a series of principal factors can extract more subtle and useful spectra features, and make the band assignment explicable for structure analysis.

  13. High-Speed Digital Signal Processing Method for Detection of Repeating Earthquakes Using GPGPU-Acceleration

    NASA Astrophysics Data System (ADS)

    Kawakami, Taiki; Okubo, Kan; Uchida, Naoki; Takeuchi, Nobunao; Matsuzawa, Toru

    2013-04-01

    Repeating earthquakes are occurring on the similar asperity at the plate boundary. These earthquakes have an important property; the seismic waveforms observed at the identical observation site are very similar regardless of their occurrence time. The slip histories of repeating earthquakes could reveal the existence of asperities: The Analysis of repeating earthquakes can detect the characteristics of the asperities and realize the temporal and spatial monitoring of the slip in the plate boundary. Moreover, we are expecting the medium-term predictions of earthquake at the plate boundary by means of analysis of repeating earthquakes. Although the previous works mostly clarified the existence of asperity and repeating earthquake, and relationship between asperity and quasi-static slip area, the stable and robust method for automatic detection of repeating earthquakes has not been established yet. Furthermore, in order to process the enormous data (so-called big data) the speedup of the signal processing is an important issue. Recently, GPU (Graphic Processing Unit) is used as an acceleration tool for the signal processing in various study fields. This movement is called GPGPU (General Purpose computing on GPUs). In the last few years the performance of GPU keeps on improving rapidly. That is, a PC (personal computer) with GPUs might be a personal supercomputer. GPU computing gives us the high-performance computing environment at a lower cost than before. Therefore, the use of GPUs contributes to a significant reduction of the execution time in signal processing of the huge seismic data. In this study, first, we applied the band-limited Fourier phase correlation as a fast method of detecting repeating earthquake. This method utilizes only band-limited phase information and yields the correlation values between two seismic signals. Secondly, we employ coherence function using three orthogonal components (East-West, North-South, and Up-Down) of seismic data as a detailed analysis of repeating earthquakes. This method gives us the correlation between two seismic data at each frequency. Then, we evaluate the effectiveness of these methods. Moreover, we also examined the GPGPU acceleration technique for these methods. We compare the execution time between GPU (NVIDIA GeForce GTX 580) and CPU (Intel Core i7 960) processing. The parameters of both analyses are on equal terms. In case of band limited phase only correlation, the obtained results indicate that single GPU is ca. 8.0 times faster than 4-core CPU (auto-optimization with OpenMP). On the other hand, GPU is times as fast as CPU. And in case of coherence function using three components, GPU is 12.7 times as fast as CPU. This study examines the high-speed signal processing of huge seismic data using the GPU architecture. It was found that both band-limited Fourier phase correlation and coherence function using three orthogonal components are effective, and that the GPGPU-based acceleration for the temporal signal processing is very useful. We will employ the multi-GPU computing, and expand the GPGPU-based high-speed signal processing framework for the detection of repeating earthquakes in the future.

  14. Signal processing techniques for stepped frequency ultra-wideband radar

    NASA Astrophysics Data System (ADS)

    Nguyen, Lam

    2014-05-01

    The U.S. Army Research Laboratory (ARL) has developed the impulse-based, ground vehicle-based, forward-looking ultra-wideband (UWB), synthetic aperture radar (SAR) to detect concealed targets. Although the impulse-based architecture offers its own advantages, one of the important challenges is that when using this architecture it is very difficult to transmit a radar signal with an arbitrary bandwidth and shape. This feature is crucial for the radar to be compliant with the local frequency authority. In addition, being able to transmit signals with an arbitrary spectral shape is an important step in creating the next generation of smart (cognitive) radars. Therefore, we have designed a next-generation prototype radar to take advantage of the stepped frequency architecture. The design and building of the radar hardware is underway. In this paper, we study the radar transmit and acquisition scheme; the trade-offs between SAR image performance and various key radar parameters; and data reconstruction techniques for radar signals with an arbitrary spectrum. This study demonstrates performance, provides some guidelines for the radar design, and serves as a foundation for the signal and image processing stage.

  15. Influence of probe pressure on the diffuse correlation spectroscopy blood flow signal: extra-cerebral contributions

    PubMed Central

    Mesquita, Rickson C.; Schenkel, Steven S.; Minkoff, David L.; Lu, Xiangping; Favilla, Christopher G.; Vora, Patrick M.; Busch, David R.; Chandra, Malavika; Greenberg, Joel H.; Detre, John A.; Yodh, A. G.

    2013-01-01

    A pilot study explores relative contributions of extra-cerebral (scalp/skull) versus brain (cerebral) tissues to the blood flow index determined by diffuse correlation spectroscopy (DCS). Microvascular DCS flow measurements were made on the head during baseline and breath-holding/hyperventilation tasks, both with and without pressure. Baseline (resting) data enabled estimation of extra-cerebral flow signals and their pressure dependencies. A simple two-component model was used to derive baseline and activated cerebral blood flow (CBF) signals, and the DCS flow indices were also cross-correlated with concurrent Transcranial Doppler Ultrasound (TCD) blood velocity measurements. The study suggests new pressure-dependent experimental paradigms for elucidation of blood flow contributions from extra-cerebral and cerebral tissues. PMID:23847725

  16. Biophoton signal transmission and processing in the brain.

    PubMed

    Tang, Rendong; Dai, Jiapei

    2014-10-01

    The transmission and processing of neural information in the nervous system plays a key role in neural functions. It is well accepted that neural communication is mediated by bioelectricity and chemical molecules via the processes called bioelectrical and chemical transmission, respectively. Indeed, the traditional theories seem to give valuable explanations for the basic functions of the nervous system, but difficult to construct general accepted concepts or principles to provide reasonable explanations of higher brain functions and mental activities, such as perception, learning and memory, emotion and consciousness. Therefore, many unanswered questions and debates over the neural encoding and mechanisms of neuronal networks remain. Cell to cell communication by biophotons, also called ultra-weak photon emissions, has been demonstrated in several plants, bacteria and certain animal cells. Recently, both experimental evidence and theoretical speculation have suggested that biophotons may play a potential role in neural signal transmission and processing, contributing to the understanding of the high functions of nervous system. In this paper, we review the relevant experimental findings and discuss the possible underlying mechanisms of biophoton signal transmission and processing in the nervous system. PMID:24461927

  17. Overview of frequency bandwidth determination techniques of useful signal in case of leaks detection by correlation method

    NASA Astrophysics Data System (ADS)

    Faerman, V. A.; Avramchuk, V. S.; Luneva, E. E.

    2014-10-01

    In this paper an overview of useful signal detection methods on the background of intense noise and limits determination methods of useful signal is presented. The following features are considered: peculiarities of usage of correlation analysis, cross-amplitude spectrum, coherence function, cross-phase spectrum, time-frequency correlation function in case of frequency limits determination as well as leaks detection in pipelines. The possibility of using time-frequency correlation function for solving above named issues is described. Time- frequency correlation function provides information about the signals correlation for each of the investigated frequency bands. Data about location of peaks on the surface plot of a time- frequency correlation function allows making an assumption about the spectral composition of useful signal and its frequency boundaries.

  18. Correlation dynamics and enhanced signals for the identification of serial biomolecules and DNA bases

    NASA Astrophysics Data System (ADS)

    Ahmed, Towfiq; Haraldsen, Jason T.; Rehr, John J.; Di Ventra, Massimiliano; Schuller, Ivan; Balatsky, Alexander V.

    2014-03-01

    Nanopore-based sequencing has demonstrated a significant potential for the development of fast, accurate, and cost-efficient fingerprinting techniques for next generation molecular detection and sequencing. We propose a specific multilayered graphene-based nanopore device architecture for the recognition of single biomolecules. Molecular detection and analysis can be accomplished through the detection of transverse currents as the molecule or DNA base translocates through the nanopore. To increase the overall signal-to-noise ratio and the accuracy, we implement a new ‘multi-point cross-correlation’ technique for identification of DNA bases or other molecules on the single molecular level. We demonstrate that the cross-correlations between each nanopore will greatly enhance the transverse current signal for each molecule. We implement first-principles transport calculations for DNA bases surveyed across a multilayered graphene nanopore system to illustrate the advantages of the proposed geometry. A time-series analysis of the cross-correlation functions illustrates the potential of this method for enhancing the signal-to-noise ratio. This work constitutes a significant step forward in facilitating fingerprinting of single biomolecules using solid state technology.

  19. Two-dimensional compression of surface electromyographic signals using column-correlation sorting and image encoders.

    PubMed

    Costa, Marcus V C; Carvalho, Joao L A; Berger, Pedro A; Zaghetto, Alexandre; da Rocha, Adson F; Nascimento, Francisco A O

    2009-01-01

    We present a new preprocessing technique for two-dimensional compression of surface electromyographic (S-EMG) signals, based on correlation sorting. We show that the JPEG2000 coding system (originally designed for compression of still images) and the H.264/AVC encoder (video compression algorithm operating in intraframe mode) can be used for compression of S-EMG signals. We compare the performance of these two off-the-shelf image compression algorithms for S-EMG compression, with and without the proposed preprocessing step. Compression of both isotonic and isometric contraction S-EMG signals is evaluated. The proposed methods were compared with other S-EMG compression algorithms from the literature. PMID:19963967

  20. Signal Correlation with Phase-Conjugate Holographic Reconstruction Using a BaTiO3 Crystal

    NASA Astrophysics Data System (ADS)

    Brody, Philip S.

    1986-06-01

    An experimental demonstration is presented of a new optically implemented analog method which generates the correlation function of a reference rf signal and a continuous signal input. A reference signal input into an acousto-optic cell produces an index-of-refraction pattern. A coherent pulse input into the cell is modulated by the index pattern. This optical pulse, phase modulated by the index pattern, is directed into a BaTiO3 crystal and recorded there as a volume phase hologram. At this point a second input into the cell produces a second, moving, index-of-refraction pattern in the cell. A second optical input passing through the cell generates a phase-conjugate reconstruction of the original optical field, that of the pulse diffracted by the reference index pattern. The conjugate field propagates back through the cell, where it is diffracted by the moving pattern. The back-propagating cell output is collected by a spherical lens. There is a variation in intensity at the focus, as the moving index pattern shifts with respect to the stationary reconstruction. This variation, a function of the shift, is the correlation function of the two signals.

  1. Long-range vibration sensor based on correlation analysis of optical frequency-domain reflectometry signals.

    PubMed

    Ding, Zhenyang; Yao, X Steve; Liu, Tiegen; Du, Yang; Liu, Kun; Han, Qun; Meng, Zhuo; Chen, Hongxin

    2012-12-17

    We present a novel method to achieve a space-resolved long- range vibration detection system based on the correlation analysis of the optical frequency-domain reflectometry (OFDR) signals. By performing two separate measurements of the vibrated and non-vibrated states on a test fiber, the vibration frequency and position of a vibration event can be obtained by analyzing the cross-correlation between beat signals of the vibrated and non-vibrated states in a spatial domain, where the beat signals are generated from interferences between local Rayleigh backscattering signals of the test fiber and local light oscillator. Using the proposed technique, we constructed a standard single-mode fiber based vibration sensor that can have a dynamic range of 12 km and a measurable vibration frequency up to 2 kHz with a spatial resolution of 5 m. Moreover, preliminarily investigation results of two vibration events located at different positions along the test fiber are also reported. PMID:23263066

  2. Ramanujan sums for signal processing of low-frequency noise.

    PubMed

    Planat, Michel; Rosu, Haret; Perrine, Serge

    2002-11-01

    An aperiodic (low-frequency) spectrum may originate from the error term in the mean value of an arithmetical function such as Möbius function or Mangoldt function, which are coding sequences for prime numbers. In the discrete Fourier transform the analyzing wave is periodic and not well suited to represent the low-frequency regime. In place we introduce a different signal processing tool based on the Ramanujan sums c(q)(n), well adapted to the analysis of arithmetical sequences with many resonances p/q. The sums are quasiperiodic versus the time n and aperiodic versus the order q of the resonance. Different results arise from the use of this Ramanujan-Fourier transform in the context of arithmetical and experimental signals. PMID:12513577

  3. Multidimensional optical signal processing using optical coherent transient spatial-spectral holography

    NASA Astrophysics Data System (ADS)

    Anderson, Kenneth Edward

    This thesis presents analysis and experimental demonstrations of several new optical signal processing architectures that are based on optical coherent transient (OCT) technology and investigates many system design issues that must be taken into account when building such systems. OCT materials have the potential to optically process both high bandwidth (>10 GHz) and high time-bandwidth (>106) signals with the ability to potentially store huge amounts of data (up to 1000's of TB/cm3 using spatial-temporal holography. Several OCT system architectures are proposed and discussed including: raster image correlators, scanners, RF spectrum analyzers, time integrating correlators, image sequence correlators, and dynamic optical switches. In addition, some of the first experimental demonstrations of multiple channel spatial-temporal signal processing using OCT materials are shown. Novel system architectures for performing chromatic, polarization mode, and modal dispersion compensation are discussed, analyzed, and initial experimental results are shown demonstrating chromatic dispersion compensation of up to 5 mus of dispersion. A new approach for multiplexing 100's of individual DWDM channels of information down one multimode fiber is proposed and analyzed. In addition, a high bandwidth adaptive phased array beam steering system is also proposed and investigated along with experimental results showing the first demonstration of simultaneous time delay and processing of information with OCT materials. Lastly, results are presented for several stabilized lasers systems that have been built throughout the course of this research. The techniques used for stabilizing these lasers systems included optical feedback from gratings and Fabry-Perot cavities and electronic feedback techniques using Pound-Drever-Hall frequency locking.

  4. A fast microcomputer language for signal acquisition, processing and display.

    PubMed

    Patek, D R; Tompkins, W J

    1980-12-01

    Data Acquisition and Display (DAD) language was designed to facilitate the application of 8080- and Z80-based microcomputers to problems involving signal acquisition, processing and display. DAD supports instructions that are similar to those BASIC but also has instructions found in the structured programming languages. Implemented as an interactive compiler and designed around a hardware arithmetic processing unit interfaced to the S100 bus, DAD executes its instructions considerably faster than most high-level languages. DAD supports floating point, double-precision integer and an additional single-byte-integer data structure for the acquisition and processing of 8-bit resolution data. DAD interfaces with peripherals that use the unsigned-magnitude or 2'-s-complement data format. A hardware programmable interval timer supplies accurate timing for many of DAD's instructions. DAD operates under and relies upon the CP/M operating system for its console and disk file input/output. PMID:7249601

  5. Cramer-Rao Bound for Gaussian Random Processes and Applications to Radar Processing of Atmospheric Signals

    NASA Technical Reports Server (NTRS)

    Frehlich, Rod

    1993-01-01

    Calculations of the exact Cramer-Rao Bound (CRB) for unbiased estimates of the mean frequency, signal power, and spectral width of Doppler radar/lidar signals (a Gaussian random process) are presented. Approximate CRB's are derived using the Discrete Fourier Transform (DFT). These approximate results are equal to the exact CRB when the DFT coefficients are mutually uncorrelated. Previous high SNR limits for CRB's are shown to be inaccurate because the discrete summations cannot be approximated with integration. The performance of an approximate maximum likelihood estimator for mean frequency approaches the exact CRB for moderate signal to noise ratio and moderate spectral width.

  6. Referential processing: reciprocity and correlates of naming and imaging.

    PubMed

    Paivio, A; Clark, J M; Digdon, N; Bons, T

    1989-03-01

    To shed light on the referential processes that underlie mental translation between representations of objects and words, we studied the reciprocity and determinants of naming and imaging reaction times (RT). Ninety-six subjects pressed a key when they had covertly named 248 pictures or imaged to their names. Mean naming and imagery RTs for each item were correlated with one another, and with properties of names, images, and their interconnections suggested by prior research and dual coding theory. Imagery RTs correlated .56 (df = 246) with manual naming RTs and .58 with voicekey naming RTs from prior studies. A factor analysis of the RTs and of 31 item characteristics revealed 7 dimensions. Imagery and naming RTs loaded on a common referential factor that included variables related to both directions of processing (e.g., missing names and missing images). Naming RTs also loaded on a nonverbal-to-verbal factor that included such variables as number of different names, whereas imagery RTs loaded on a verbal-to-nonverbal factor that included such variables as rated consistency of imagery. The other factors were verbal familiarity, verbal complexity, nonverbal familiarity, and nonverbal complexity. The findings confirm the reciprocity of imaging and naming, and their relation to constructs associated with distinct phases of referential processing. PMID:2927314

  7. Enhancement of MS Signal Processing For Improved Cancer Biomarker Discovery

    NASA Astrophysics Data System (ADS)

    Si, Qian

    Technological advances in proteomics have shown great potential in detecting cancer at the earliest stages. One way is to use the time of flight mass spectroscopy to identify biomarkers, or early disease indicators related to the cancer. Pattern analysis of time of flight mass spectra data from blood and tissue samples gives great hope for the identification of potential biomarkers among the complex mixture of biological and chemical samples for the early cancer detection. One of the keys issues is the pre-processing of raw mass spectra data. A lot of challenges need to be addressed: unknown noise character associated with the large volume of data, high variability in the mass spectroscopy measurements, and poorly understood signal background and so on. This dissertation focuses on developing statistical algorithms and creating data mining tools for computationally improved signal processing for mass spectrometry data. I have introduced an advanced accurate estimate of the noise model and a half-supervised method of mass spectrum data processing which requires little knowledge about the data.

  8. Automatic signal processing of front monitor radar for tunneling machines

    SciTech Connect

    Sato, Toru [Kyoto Univ. (Japan). Dept. of Electronics and Communication] [Kyoto Univ. (Japan). Dept. of Electronics and Communication; Takeda, Kenya [NTT Co. Ltd., Chiba (Japan)] [NTT Co. Ltd., Chiba (Japan); Nagamatsu, Takashi [Mitsubishi Heavy Industries, Ltd., Tokyo (Japan)] [Mitsubishi Heavy Industries, Ltd., Tokyo (Japan); Wakayama, Toshio [Mitsubishi Electric Corp., Kamakura, Kanagawa (Japan)] [Mitsubishi Electric Corp., Kamakura, Kanagawa (Japan); Kimura, Iwane [Osaka Inst. of Tech., Hirakata, Osaka (Japan)] [Osaka Inst. of Tech., Hirakata, Osaka (Japan); Shinbo, Tetsuya [Komatsu Co. Ltd., Kanagawa (Japan)] [Komatsu Co. Ltd., Kanagawa (Japan)

    1997-03-01

    It is planned to install a front monitoring impulse radar on the surface of the rotating drill of tunneling machines in order to detect obstacles such as casing pipes of vertical borings. The conventional aperture synthesis technique can no more be applied to such cases because the radar image of a pipe dies not constituent a hyperbola as is the case for linear scanning radars. The authors have developed a special purpose signal processing algorithm with the aid of the discrete model fitting method, which can be used for any pattern of scanning. The details of the algorithm are presented together with the results of numerical simulations and test site experiments.

  9. 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.

  10. Music Perception with Current Signal Processing Strategies for Cochlear Implants

    E-print Network

    This work presents a brief review on hearing with cochlear implants with emphasis on music perception. Although speech perception in noise with cochlear implants is still the major challenge, music perception is becoming more and more important. Music can modulate emotions and stimulate the brain in different ways than speech, for this reason, music can impact in quality of life for cochlear implant users. In this paper we present traditional and new trends to improve the perception of pitch with cochlear implants as well as some signal processing methods that have been designed with the aim to improve music perception. Finally, a review of music evaluation methods will be presented.

  11. 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.

  12. DSPSR: Digital Signal Processing Software for Pulsar Astronomy

    NASA Astrophysics Data System (ADS)

    van Straten, W.; Bailes, M.

    2010-10-01

    DSPSR, written primarily in C++, is an open-source, object-oriented, digital signal processing software library and application suite for use in radio pulsar astronomy. The library implements an extensive range of modular algorithms for use in coherent dedispersion, filterbank formation, pulse folding, and other tasks. The software is installed and compiled using the standard GNU configure and make system, and is able to read astronomical data in 18 different file formats, including FITS, S2, CPSR, CPSR2, PuMa, PuMa2, WAPP, ASP, and Mark5.

  13. Frequency of spontaneous BOLD signal shifts during infancy and correlates with cognitive performance.

    PubMed

    Alcauter, Sarael; Lin, Weili; Smith, J Keith; Goldman, Barbara D; Reznick, J Steven; Gilmore, John H; Gao, Wei

    2015-04-01

    Numerous studies have been conducted to delineate the early development of different functional networks, based on measuring the temporal synchronization of spontaneous blood oxygenation level-dependent (BOLD) signals acquired using resting state functional MRI (rsfMRI). However, little attention has been paid to the change of the frequency properties of these signals during early brain development. Such frequency properties may reflect important physiological changes and potentially have significant cognitive consequences. In this study, leveraging a large (N=86 subjects), longitudinal sample of human infants scanned during the first two years of life, we aimed to specifically delineate the developmental changes of the frequency characteristics of spontaneous BOLD signals. Both whole-brain and network-level examinations were carried out and the frequency-behavior relationship was explored. Our results revealed a clear right-ward shift of BOLD signal frequency during the first year of life. Moreover, the power at the peak-frequency for sensorimotor and lateral visual networks correlates with domain-specific Mullen Scales in 1-year-olds, suggesting the behavioral significance of the BOLD signal frequency during infancy. Findings from this study shed light into early functional brain development and provide a new perspective for future searches for functional developmental abnormalities. PMID:25459875

  14. AN ONLINE SYSTEM FOR SYNCHRONIZED PROCESSING OF VIDEO AND AUDIO SIGNALS

    E-print Network

    Amer, Aishy

    and processed sepa- rately. The signals are buffered and integrated and synchro- nized using a time-stamping technique. Time-stamps pro- vide the timing information for each of the audio and video processes processing, audio processing, signals integration, synchronized audio and video signals; time- stamping. 1

  15. Characteristic Cutting Signals for Machined Surface Condition Monitoring in Micro milling Processes

    NASA Astrophysics Data System (ADS)

    Jang, Su-Hoon; Jang, Ik-Soo; Kim, Jeong-Suk; Choi, Tae-Ku; Gu, Min-Su

    2011-01-01

    The demands of mechanical precision micro machining technology have increased due to the need for micro scale precision shapes and parts in biotechnology, optics, and machinery. In the micro-machining process, the machining parameters must be controlled in order to improve the precision and quality of machined parts. Improvements must be made in exclusive precision machining and extensive study of machining technology must be conducted in order to overcome current challenges in the micro machining process. This paper investigates the correlation between the machined surface condition and acoustic emission(AE) signals characterized according to the cutting conditions in the miro-machining process. Micro end mills (200 ?m diameter) and an air turbine spindle (120,000rpm) were used machine aluminum 6061-T6. The characteristics of the AE parameters were extracted in order to monitor the condition of the machined surface texture in micro milling process.

  16. Social signal processing for studying parent–infant interaction

    PubMed Central

    Avril, Marie; Leclère, Chloë; Viaux, Sylvie; Michelet, Stéphane; Achard, Catherine; Missonnier, Sylvain; Keren, Miri; Cohen, David; Chetouani, Mohamed

    2014-01-01

    Studying early interactions is a core issue of infant development and psychopathology. Automatic social signal processing theoretically offers the possibility to extract and analyze communication by taking an integrative perspective, considering the multimodal nature and dynamics of behaviors (including synchrony). This paper proposes an explorative method to acquire and extract relevant social signals from a naturalistic early parent–infant interaction. An experimental setup is proposed based on both clinical and technical requirements. We extracted various cues from body postures and speech productions of partners using the IMI2S (Interaction, Multimodal Integration, and Social Signal) Framework. Preliminary clinical and computational results are reported for two dyads (one pathological in a situation of severe emotional neglect and one normal control) as an illustration of our cross-disciplinary protocol. The results from both clinical and computational analyzes highlight similar differences: the pathological dyad shows dyssynchronic interaction led by the infant whereas the control dyad shows synchronic interaction and a smooth interactive dialog. The results suggest that the current method might be promising for future studies. PMID:25540633

  17. Signal transduction and information processing in mammalian taste buds

    PubMed Central

    2013-01-01

    The molecular machinery for chemosensory transduction in taste buds has received considerable attention within the last decade. Consequently, we now know a great deal about sweet, bitter, and umami taste mechanisms and are gaining ground rapidly on salty and sour transduction. Sweet, bitter, and umami tastes are transduced by G-protein-coupled receptors. Salty taste may be transduced by epithelial Na channels similar to those found in renal tissues. Sour transduction appears to be initiated by intracellular acidification acting on acid-sensitive membrane proteins. Once a taste signal is generated in a taste cell, the subsequent steps involve secretion of neurotransmitters, including ATP and serotonin. It is now recognized that the cells responding to sweet, bitter, and umami taste stimuli do not possess synapses and instead secrete the neurotransmitter ATP via a novel mechanism not involving conventional vesicular exocytosis. ATP is believed to excite primary sensory afferent fibers that convey gustatory signals to the brain. In contrast, taste cells that do have synapses release serotonin in response to gustatory stimulation. The postsynaptic targets of serotonin have not yet been identified. Finally, ATP secreted from receptor cells also acts on neighboring taste cells to stimulate their release of serotonin. This suggests that there is important information processing and signal coding taking place in the mammalian taste bud after gustatory stimulation. PMID:17468883

  18. Two-point correlation properties of stochastic "cloud processes''

    E-print Network

    Andrea Gabrielli; Michael Joyce

    2007-11-02

    We study how the two-point density correlation properties of a point particle distribution are modified when each particle is divided, by a stochastic process, into an equal number of identical "daughter" particles. We consider generically that there may be non-trivial correlations in the displacement fields describing the positions of the different daughters of the same "mother" particle, and then treat separately the cases in which there are, or are not, correlations also between the displacements of daughters belonging to different mothers. For both cases exact formulae are derived relating the structure factor (power spectrum) of the daughter distribution to that of the mother. These results can be considered as a generalization of the analogous equations obtained in ref. [1] (cond-mat/0409594) for the case of stochastic displacement fields applied to particle distributions. An application of the present results is that they give explicit algorithms for generating, starting from regular lattice arrays, stochastic particle distributions with an arbitrarily high degree of large-scale uniformity.

  19. Gravity influences top-down signals in visual processing.

    PubMed

    Cheron, Guy; Leroy, Axelle; Palmero-Soler, Ernesto; De Saedeleer, Caty; Bengoetxea, Ana; Cebolla, Ana-Maria; Vidal, Manuel; Dan, Bernard; Berthoz, Alain; McIntyre, Joseph

    2014-01-01

    Visual perception is not only based on incoming visual signals but also on information about a multimodal reference frame that incorporates vestibulo-proprioceptive input and motor signals. In addition, top-down modulation of visual processing has previously been demonstrated during cognitive operations including selective attention and working memory tasks. In the absence of a stable gravitational reference, the updating of salient stimuli becomes crucial for successful visuo-spatial behavior by humans in weightlessness. Here we found that visually-evoked potentials triggered by the image of a tunnel just prior to an impending 3D movement in a virtual navigation task were altered in weightlessness aboard the International Space Station, while those evoked by a classical 2D-checkerboard were not. Specifically, the analysis of event-related spectral perturbations and inter-trial phase coherency of these EEG signals recorded in the frontal and occipital areas showed that phase-locking of theta-alpha oscillations was suppressed in weightlessness, but only for the 3D tunnel image. Moreover, analysis of the phase of the coherency demonstrated the existence on Earth of a directional flux in the EEG signals from the frontal to the occipital areas mediating a top-down modulation during the presentation of the image of the 3D tunnel. In weightlessness, this fronto-occipital, top-down control was transformed into a diverging flux from the central areas toward the frontal and occipital areas. These results demonstrate that gravity-related sensory inputs modulate primary visual areas depending on the affordances of the visual scene. PMID:24400069

  20. Optimal processing and the statistics of visual input signals

    NASA Astrophysics Data System (ADS)

    de Ruyter van Steveninck, Rob

    2008-03-01

    Sensory information processing can be seen as a statistical estimation problem, where relevant features are extracted from a raw stream of sensory input containing an imperfect representation of those features. Broadly speaking, the optimal solution to the feature extraction problem depends on the statistical structure of those input signals. Here we study the statistics of natural visual input signals, and the optimal solution to the problem of visual motion detection. Motion detection is a biologically important feature estimation problem, as many animals use vision to estimate their motion through space. Many years ago, Reichardt and Poggio drew attention to two important aspects of this problem: First, computing motion from an array of photosensors is an irreducibly nonlinear operation, and second, biological versions of this operation seem mathematically tractable. To paraphrase, the problem is interesting but not hopelessly complicated. In this spirit I will discuss motion estimation in the visual system of the blowfly, with an emphasis on performance under natural conditions. As noted above, the array of photoreceptors in the retina implicitly contains data on self motion, but this relation is noisy, indirect and ambiguous due to photon shot noise and optical blurring, and also as a result of the structure of the natural environment. Further, natural variations in the visual signal to noise ratio are enormous, and nonlinear operations are especially susceptible to noise. One can therefore reasonably hope that animals have evolved interesting optimization strategies to deal with large variations in signal quality. I will present experimental data, both from sampling natural probability distributions, and from motion sensitive neurons in the fly brain, that illustrate some of these solutions and that suggest that the fly indeed approaches optimality. The implications of these findings and their possible generalizations will be discussed.

  1. Quantum process tomography: the role of initial correlations

    E-print Network

    Mario Ziman

    2006-09-01

    We address the problem of quantum process tomography with the preparators producing states correlated with the environmental degrees of freedom that play role in the system-environment interactions. We discuss the physical situations, in which the dynamics is described by nonlinear, or noncompletely positive transformations. In particular, we show that arbitrary mapping $\\varrho_{\\rm in}\\to\\varrho_{\\rm out}$ can be realized by using appropriate set of preparators and applying the unitary operation SWAP. The experimental ``realization'' of perfect NOT operation is presented. We address the problem of the verification of the compatibility of the preparator devices with the estimating process. The evolution map describing the dynamics in arbitrary time interval is known not to be completely positive, but still linear. The tomography and general properties of these maps are discussed.

  2. A Novel Technique for Preventing Signal Cancellation in Space-Time Adaptive Processing

    Microsoft Academic Search

    Youming Li; Rangding Wang

    2008-01-01

    This paper addresses the issue of space-time adaptive processing (STAP) when the target signal is present in the training data. Target cancellation will occur in the STAP processing when the target signal leaks into the neighbouring range-gates for estimating clutter covariance matrix. In this paper, some linear constraints are added both on target signal and clutter to prevent target signal

  3. Tunable photonic filters: a digital signal processing design approach.

    PubMed

    Binh, Le Nguyen

    2009-05-20

    Digital signal processing techniques are used for synthesizing tunable optical filters with variable bandwidth and centered reference frequency including the tunability of the low-pass, high-pass, bandpass, and bandstop optical filters. Potential applications of such filters are discussed, and the design techniques and properties of recursive digital filters are outlined. The basic filter structures, namely, the first-order all-pole optical filter (FOAPOF) and the first-order all-zero optical filter (FOAZOF), are described, and finally the design process of tunable optical filters and the designs of the second-order Butterworth low-pass, high-pass, bandpass, and bandstop tunable optical filters are presented. Indeed, we identify that the all-zero and all-pole networks are equivalent with well known principles of optics of interference and resonance, respectively. It is thus very straightforward to implement tunable optical filters, which is a unique feature. PMID:19458728

  4. Nonlinear signal-processing model for signal generation in multilevel two-dimensional optical storage.

    PubMed

    Fagoonee, Lina; Coene, Wim M J; Moinian, Abdolhosein; Honary, Bahram

    2004-02-15

    A two-dimensional optical storage (TwoDOS) format with binary modulation is being developed in which channel bits are arranged on a two-dimensional hexagonal lattice [W. M. J. Coene, in Optical Data Storage, Vol. 88 of OSA Trends in Optics and Photonics Series (Optical Society of America, Washington, D.C., 2003), pp. 90-92]. The aim is to increase the capacity by a factor of 2 and the data rate by a factor of 10 over third-generation Blu-ray Disc technology. Following a route similar to that used in one-dimensional conventional optical storage [Jpn. J. Appl. Phys. 42, 1074 (2003)] could lead to a further increase in capacity by the addition of another dimension to writing data, such as the use of multiple levels instead of the two levels (pit and land) used in the binary TwoDOS disk format. We present a nonlinear signal-processing model for signal waveform generation as a function of the M-ary channel symbols, as well as simulated signal readouts for multilevel TwoDOS. PMID:14971761

  5. Tomography of the Fermi-LAT ?-Ray Diffuse Extragalactic Signal via Cross Correlations with Galaxy Catalogs

    NASA Astrophysics Data System (ADS)

    Xia, Jun-Qing; Cuoco, Alessandro; Branchini, Enzo; Viel, Matteo

    2015-03-01

    Building on our previous cross-correlation analysis (Xia et al. 2011) between the isotropic ?-ray background (IGRB) and different tracers of the large-scale structure of the universe, we update our results using 60 months of data from the Large Area Telescope (LAT) on board the Fermi Gamma-ray Space Telescope (Fermi). We perform a cross-correlation analysis both in configuration and spherical harmonics space between the IGRB and objects that may trace the astrophysical sources of the IGRB: QSOs in the Sloan Digital Sky Survey (SDSS) DR6, the SDSS DR8 Main Galaxy Sample, luminous red galaxies (LRGs) in the SDSS catalog, infrared-selected galaxies in the Two Micron All Sky Survey (2MASS), and radio galaxies in the NRAO VLA Sky Survey (NVSS). The benefit of correlating the Fermi-LAT signal with catalogs of objects at various redshifts is to provide tomographic information on the IGRB, which is crucial in separating the various contributions and clarifying its origin. The main result is that, unlike in our previous analysis, we now observe a significant (>3.5?) cross-correlation signal on angular scales smaller than 1° in the NVSS, 2MASS, and QSO cases and, at lower statistical significance (?3.0?), with SDSS galaxies. The signal is stronger in two energy bands, E > 0.5 GeV and E > 1 GeV, but it is also seen at E > 10 GeV. No cross-correlation signal is detected between Fermi data and the LRGs. These results are robust against the choice of the statistical estimator, estimate of errors, map cleaning procedure, and instrumental effects. Finally, we test the hypothesis that the IGRB observed by Fermi-LAT originates from the summed contributions of three types of unresolved extragalactic sources: BL Lacertae objects (BL Lacs), flat spectrum radio quasars (FSRQs), and star-forming galaxies (SFGs). We find that a model in which the IGRB is mainly produced by SFGs (72-37+23% with 2? errors), with BL Lacs and FSRQs giving a minor contribution, provides a good fit to the data. We also consider a possible contribution from misaligned active galactic nuclei, and we find that, depending on the details of the model and its uncertainty, they can also provide a substantial contribution, partly degenerate with the SFG one.

  6. Phase resolved digital signal processing in optical coherence tomography

    NASA Astrophysics Data System (ADS)

    de Boer, Johannes F.; Tripathi, Renu; Park, Boris H.; Nassif, Nader

    2002-06-01

    We present phase resolved digital signal processing techniques for Optical Coherence Tomography to correct for the non Gaussian shape of source spectra and for Group Delay Dispersion (GDD). A broadband source centered at 820 nm was synthesized by combining the spectra of two superluminescent diodes to improve axial image resolution in an optical coherence tomography (OCT) system. Spectral shaping was used to reduce the side lobes (ringing) in the axial point spread function due to the non-Gaussian shape of the spectra. Images of onion cells taken with each individual source and the combined sources, respectively, show the improved resolution and quality enhancement in a turbid biological sample. An OCT system operating at 1310 nm was used to demonstrate that the broadening effect of group delay dispersion (GDD) on the coherence function could be eliminated completely by introducing a quadratic phase shift in the Fourier domain of the interferometric signal. The technique is demonstrated by images of human skin grafts with group delay dispersion mismatch between sample and reference arm before and after digital processing.

  7. Regulation of TGF? and related signals by precursor processing.

    PubMed

    Constam, Daniel B

    2014-08-01

    Secreted cytokines of the TGF? family are found in all multicellular organisms and implicated in regulating fundamental cell behaviors such as proliferation, differentiation, migration and survival. Signal transduction involves complexes of specific type I and II receptor kinases that induce the nuclear translocation of Smad transcription factors to regulate target genes. Ligands of the BMP and Nodal subgroups act at a distance to specify distinct cell fates in a concentration-dependent manner. These signaling gradients are shaped by multiple factors, including proteases of the proprotein convertase (PC) family that hydrolyze one or several peptide bonds between an N-terminal prodomain and the C-terminal domain that forms the mature ligand. This review summarizes information on the proteolytic processing of TGF? and related precursors, and its spatiotemporal regulation by PCs during development and various diseases, including cancer. Available evidence suggests that the unmasking of receptor binding epitopes of TGF? is only one (and in some cases a non-essential) function of precursor processing. Future studies should consider the impact of proteolytic maturation on protein localization, trafficking and turnover in cells and in the extracellular space. PMID:24508081

  8. Wavelet-Based Signal and Image Processing for Target Recognition

    NASA Astrophysics Data System (ADS)

    Sherlock, Barry G.

    2002-11-01

    The PI visited NSWC Dahlgren, VA, for six weeks in May-June 2002 and collaborated with scientists in the G33 TEAMS facility, and with Marilyn Rudzinsky of T44 Technology and Photonic Systems Branch. During this visit the PI also presented six educational seminars to NSWC scientists on various aspects of signal processing. Several items from the grant proposal were completed, including (1) wavelet-based algorithms for interpolation of 1-d signals and 2-d images; (2) Discrete Wavelet Transform domain based algorithms for filtering of image data; (3) wavelet-based smoothing of image sequence data originally obtained for the CRITTIR (Clutter Rejection Involving Temporal Techniques in the Infra-Red) project. The PI visited the University of Stellenbosch, South Africa to collaborate with colleagues Prof. B.M. Herbst and Prof. J. du Preez on the use of wavelet image processing in conjunction with pattern recognition techniques. The University of Stellenbosch has offered the PI partial funding to support a sabbatical visit in Fall 2003, the primary purpose of which is to enable the PI to develop and enhance his expertise in Pattern Recognition. During the first year, the grant supported publication of 3 referred papers, presentation of 9 seminars and an intensive two-day course on wavelet theory. The grant supported the work of two students who functioned as research assistants.

  9. A nonlinear optoelectronic filter for electronic signal processing

    E-print Network

    Loh, William

    The conversion of electrical signals into modulated optical waves and back into electrical signals provides the capacity for low-loss radio-frequency (RF) signal transfer over optical fiber. Here, we show that the unique ...

  10. ISCCSP 2004 SIGNAL PROCESSING WITH FACTOR GRAPHS: EXAMPLES

    E-print Network

    Loeliger, Hans-Andrea

    and ana- lyzing such signals is called electromyography (EMG). A discrete-time model of such signals may = 1 is shown in Fig. 3. A basic task in electromyography is to estimate the source signals Xi from

  11. Increasing signal processing sophistication in the calculation of the respiratory modulation of the photoplethysmogram (DPOP).

    PubMed

    Addison, Paul S; Wang, Rui; Uribe, Alberto A; Bergese, Sergio D

    2014-09-11

    DPOP (?POP or Delta-POP) is a non-invasive parameter which measures the strength of respiratory modulations present in the pulse oximetry photoplethysmogram (pleth) waveform. It has been proposed as a non-invasive surrogate parameter for pulse pressure variation (PPV) used in the prediction of the response to volume expansion in hypovolemic patients. Many groups have reported on the DPOP parameter and its correlation with PPV using various semi-automated algorithmic implementations. The study reported here demonstrates the performance gains made by adding increasingly sophisticated signal processing components to a fully automated DPOP algorithm. A DPOP algorithm was coded and its performance systematically enhanced through a series of code module alterations and additions. Each algorithm iteration was tested on data from 20 mechanically ventilated OR patients. Correlation coefficients and ROC curve statistics were computed at each stage. For the purposes of the analysis we split the data into a manually selected 'stable' region subset of the data containing relatively noise free segments and a 'global' set incorporating the whole data record. Performance gains were measured in terms of correlation against PPV measurements in OR patients undergoing controlled mechanical ventilation. Through increasingly advanced pre-processing and post-processing enhancements to the algorithm, the correlation coefficient between DPOP and PPV improved from a baseline value of R = 0.347 to R = 0.852 for the stable data set, and, correspondingly, R = 0.225 to R = 0.728 for the more challenging global data set. Marked gains in algorithm performance are achievable for manually selected stable regions of the signals using relatively simple algorithm enhancements. Significant additional algorithm enhancements, including a correction for low perfusion values, were required before similar gains were realised for the more challenging global data set. PMID:25209132

  12. Peta-Flop Real Time Radio Astronomy Signal Processing Instrumentation and the CASPER Collaboration

    NASA Astrophysics Data System (ADS)

    Werthimer, Dan

    2014-04-01

    I will briefly describe next generation radio telescopes, such as HERA and the Square Kilometer Array (SKA), which will require 1E15 to 1E17 operations per second of real time processing. I'll present some of the new architectures we've used to develop a variety of heterogeneous FPGA-GPU-CPU based signal processing systems for such telescopes, including spectrometers, correlators, and beam formers. I will also describe the CASPER collaboration, which has developed architectures, open source programming tools, libraries and reference designs that make it relatively easy to develop a variety of scalable, upgradeable, fault tolerant, low power, real time digital signal processing instrumentation. CASPER utilizes commercial 10Gbit and 40 Gbit ethernet switches to interconnect open source general purpose field programmable gate array (FPGA) boards with GPUs and software modules. CASPER collaborators at hundreds of universities, government labs and observatories have used these techniques to rapidly develop and deploy a variety of correlators, beamformers, spectrometers, pulsar/transient machines, and VLBI instrumentation. CASPER instrumentation is also utilized in physics, medicine, genomics and engineering. Open source source hardware, software, libraries, tools, tutorials, reference designs, information about workshops, and how to join the collaboration are available at http://casper.berkeley.edu

  13. ENG BE/EC 519. Speech Signal Processing Oded Ghitza, Biomedical Engineering

    E-print Network

    Vajda, Sandor

    Methods 13 Automatic Speech Recognition and Natural Language Understanding 14 Finale Topics1 ENG BE/EC 519. Speech Signal Processing Oded Ghitza, Biomedical Engineering The goal signal processing, and their applications to contemporary speech technology. The course is organized

  14. From Bursts to Back-Projection: Signal Processing Techniques for Earth and Planetary Observing Radars

    NASA Technical Reports Server (NTRS)

    Rosen, Paul A.

    2012-01-01

    Discusses: (1) JPL Radar Overview and Historical Perspective (2) Signal Processing Needs in Earth and Planetary Radars (3) Examples of Current Systems and techniques (4) Future Perspectives in signal processing for radar missions

  15. Correlation between a loss of auxin signaling and a loss of proliferation in maize antipodal cells

    PubMed Central

    Chettoor, Antony M.; Evans, Matthew M. S.

    2015-01-01

    The plant life cycle alternates between two genetically active generations: the diploid sporophyte and the haploid gametophyte. In angiosperms the gametophytes are sexually dimorphic and consist of only a few cells. The female gametophyte, or embryo sac, is comprised of four cell types: two synergids, an egg cell, a central cell, and a variable number of antipodal cells. In some species the antipodal cells are indistinct and fail to proliferate, so many aspects of antipodal cell function and development have been unclear. In maize and many other grasses, the antipodal cells proliferate to produce a highly distinct cluster at the chalazal end of the embryo sac that persists at the apex of the endosperm after fertilization. The antipodal cells are a site of auxin accumulation in the maize embryo sac. Analysis of different families of genes involved in auxin biosynthesis, distribution, and signaling for expression in the embryo sac demonstrates that all steps are expressed within the embryo sac. In contrast to auxin signaling, cytokinin signaling is absent in the embryo sac and instead occurs adjacent to but outside of the antipodal cells. Mutant analysis shows a correlation between a loss of auxin signaling and a loss of proliferation of the antipodal cells. The leaf polarity mutant Laxmidrib1 causes a lack of antipodal cell proliferation coupled with a loss of DR5 and PIN1a expression in the antipodal cells. PMID:25859254

  16. High resolution signal-processing method for extrinsic Fabry-Perot interferometric sensors

    NASA Astrophysics Data System (ADS)

    Xie, Jiehui; Wang, Fuyin; Pan, Yao; Wang, Junjie; Hu, Zhengliang; Hu, Yongming

    2015-03-01

    In this paper, a signal-processing method for optical fiber extrinsic Fabry-Perot interferometric sensors is presented. It achieves both high resolution and absolute measurement of the dynamic change of cavity length with low sampling points in wavelength domain. In order to improve the demodulation accuracy, the reflected interference spectrum is cleared by Discrete Wavelet Transform and adjusted by the Hilbert transform. Then the cavity length is interrogated by the cross correlation algorithm. The continuous tests show the resolution of cavity length is only 36.7 pm. Moreover, the corresponding resolution of cavity length is only 1 pm on the low frequency range below 420 Hz, and the corresponding power spectrum shows the possibility of detecting the ultra-low frequency signals based on spectra detection.

  17. Disrupted muscarinic M1 receptor signaling correlates with loss of protein kinase C activity and glutamatergic deficit in Alzheimer's disease.

    PubMed

    Tsang, Shirley W Y; Pomakian, Justine; Marshall, Gad A; Vinters, Harry V; Cummings, Jeffrey L; Chen, Christopher P L-H; Wong, Peter T-H; Lai, Mitchell K P

    2007-09-01

    There are few studies on the clinical and neurochemical correlates of postsynaptic cholinergic dysfunction in Alzheimer's disease (AD). We have previously found that attenuation of guanine nucleotide-binding (G-) protein coupling to muscarinic M(1) receptors in the neocortex was associated with dementia severity. The present study aims to study whether this loss of M(1)/G-protein coupling is related to alterations in signaling kinases and NMDA receptors. Postmortem frontal cortices of 22 AD subjects and 12 elderly controls were obtained to measure M(1) receptors, M(1)/G-protein coupling, NMDA receptors as well as protein kinase C (PKC) and Src kinase activities. We found that the extent of M(1)/G-protein coupling loss was correlated with reductions in PKC activity and NMDA receptor density. In contrast, Src kinase activity was neither altered nor associated with M(1)/G-protein coupling. Given the well established roles of neuronal PKC signaling and NMDA receptor function in cognitive processes, our results lend further insight into the mechanisms by which postsynaptic cholinergic dysfunction may underlie the cognitive features of AD, and suggest alternative therapeutic targets to cholinergic replacement. PMID:16828202

  18. Improved Statistical Signal Processing of Nonstationary Random Processes Using Time-Warping

    NASA Astrophysics Data System (ADS)

    Wisdom, Scott Thomas

    A common assumption used in statistical signal processing of nonstationary random signals is that the signals are locally stationary. Using this assumption, data is segmented into short analysis frames, and processing is performed using these short frames. Short frames limit the amount of data available, which in turn limits the performance of statistical estimators. In this thesis, we propose a novel method that promises improved performance for a variety of statistical signal processing algorithms. This method proposes to estimate certain time-varying parameters of nonstationary signals and then use this estimated information to perform a time-warping of the data that compensates for the time-varying parameters. Since the time-warped data is more stationary, longer analysis frames may be used, which improves the performance of statistical estimators. We first examine the spectral statistics of two particular types of nonstationary random processes that are useful for modeling ship propeller noise and voiced speech. We examine the effect of time-varying frequency content on these spectral statistics, and in addition show that the cross-frequency spectral statistics of these signals contain significant additional information that is not usually exploited using a stationary assumption. This information, combined with our proposed method, promises improvements for a wide variety of applications in the future. We then describe and test an implementation of our time-warping method, the fan-chirp transform. We apply our method to two applications, detection of ship noise in a passive sonar application and joint denoising and dereverberation of speech. Our method yields improved results for both applications compared to conventional methods.

  19. Error reduction in laser remote sensing: combined effects of cross correlation and signal averaging.

    PubMed

    Menyuk, N; Killinger, D K; Menyuk, C R

    1985-01-01

    A systematic analysis is presented of the extent to which the accuracy of a differential-absorption lidar (DIAL) measurement may be improved by using the combined effects of signal averaging and temporal cross correlation. Previous studies which considered these effects separately are extended by incorporating both effects into a single analytical framework. In addition, experimental results involving lidar returns from a diffusely reflecting target using a dual-CO2 laser DIAL system with both heterodyne and direct detection are presented. These results are shown to be in good agreement with the theoretical analysis and help establish the limits of accuracy achievable under various experimental conditions. PMID:18216912

  20. DESIGN OF A REAL-TIME DIGITAL SIGNAL PROCESSING AUDIO PROCESSING TECHNIQUE

    E-print Network

    Jagielski, Christopher

    2012-04-24

    This thesis outlines the design of a real-time digital signal processing technique for pitch detection and analysis via spectral analysis. A sound’s musical pitch can be determined from its fundamental frequency, and a note that is said to be “out...

  1. An Enhanced Signal Processing Strategy For Fetal Heart Rate Detection Charles Brewton

    E-print Network

    Zahorian, Stephen A.

    ABSTRACT An Enhanced Signal Processing Strategy For Fetal Heart Rate Detection Charles Brewton Old the signal processing strategy for an acoustic fetal heart rate monitor. The theory, implementation, and testing of several possible signal processing strategies for fetal heart rate detection are presented

  2. PHOTOCREDIT 1053-5888/08/$25.002008IEEE IEEE SIGNAL PROCESSING MAGAZINE [29] JANUARY 2008

    E-print Network

    Slatton, Clint

    ©PHOTOCREDIT 1053-5888/08/$25.00©2008IEEE IEEE SIGNAL PROCESSING MAGAZINE [29] JANUARY 2008 Digital Object Identifier 10.1109/MSP.2007.909525 1053-5888/08/$25.00©2008IEEE IEEE SIGNAL PROCESSING MAGAZINE MAGAZINE [30] JANUARY 2008IEEE SIGNAL PROCESSING MAGAZINE [30] JANUARY 2008 system, muscles) using

  3. New Solutions for Substation Sensing, Signal Processing and Decision Making M. Kezunovic, Fellow IEEE

    E-print Network

    New Solutions for Substation Sensing, Signal Processing and Decision Making M. Kezunovic, Fellow describes a new solution for integrating substation sensing, signal processing and decision making for more. Introduction The existing substation designs for sensing, signal processing and decision-making have been

  4. VSIPL: an object-based open standard API for vector, signal, and image processing

    Microsoft Academic Search

    Randall Janka; Randall Judd; James Lebak; Mark Richards; Dan Campbell

    2001-01-01

    VSIPL, the Vector, Signal, and Image Processing Library, is an open standard application programmer's interface (API) for signal and image processing. Defined by a consortium of industry, government, and academic representatives, VSIPL is gaining widespread acceptance as a de facto standard in the embedded signal processing world. The primary goal of the API is to increase the portability of vector

  5. Strong Monogamies of No-Signaling Violations for Bipartite Correlation Bell Inequalities

    NASA Astrophysics Data System (ADS)

    Ramanathan, Ravishankar; Horodecki, Pawe?

    2014-11-01

    The phenomenon of monogamy of Bell inequality violations is interesting both from the fundamental perspective as well as in cryptographic applications such as the extraction of randomness and secret bits. In this article, we derive new and stronger monogamy relations for violations of Bell inequalities in general no-signaling theories. These relations are applicable to the class of binary output correlation inequalities known as xor games, and to free unique games. In many instances of interest, we show that the derived relation provides a significant strengthening over previously known results. Our result connects, for the first time, the property of monogamy with that crucial part of the Bell expression that is necessary for revealing a contradiction with local realistic predictions, thus shifting the paradigm in the field of monogamy of correlations.

  6. Signal Processing Methods for Liquid Rocket Engine Combustion Stability Assessments

    NASA Technical Reports Server (NTRS)

    Kenny, R. Jeremy; Lee, Erik; Hulka, James R.; Casiano, Matthew

    2011-01-01

    The J2X Gas Generator engine design specifications include dynamic, spontaneous, and broadband combustion stability requirements. These requirements are verified empirically based high frequency chamber pressure measurements and analyses. Dynamic stability is determined with the dynamic pressure response due to an artificial perturbation of the combustion chamber pressure (bomb testing), and spontaneous and broadband stability are determined from the dynamic pressure responses during steady operation starting at specified power levels. J2X Workhorse Gas Generator testing included bomb tests with multiple hardware configurations and operating conditions, including a configuration used explicitly for engine verification test series. This work covers signal processing techniques developed at Marshall Space Flight Center (MSFC) to help assess engine design stability requirements. Dynamic stability assessments were performed following both the CPIA 655 guidelines and a MSFC in-house developed statistical-based approach. The statistical approach was developed to better verify when the dynamic pressure amplitudes corresponding to a particular frequency returned back to pre-bomb characteristics. This was accomplished by first determining the statistical characteristics of the pre-bomb dynamic levels. The pre-bomb statistical characterization provided 95% coverage bounds; these bounds were used as a quantitative measure to determine when the post-bomb signal returned to pre-bomb conditions. The time for post-bomb levels to acceptably return to pre-bomb levels was compared to the dominant frequency-dependent time recommended by CPIA 655. Results for multiple test configurations, including stable and unstable configurations, were reviewed. Spontaneous stability was assessed using two processes: 1) characterization of the ratio of the peak response amplitudes to the excited chamber acoustic mode amplitudes and 2) characterization of the variability of the peak response's frequency over the test duration. This characterization process assists in evaluating the discreteness of a signal as well as the stability of the chamber response. Broadband stability was assessed using a running root-mean-square evaluation. These techniques were also employed, in a comparative analysis, on available Fastrac data, and these results are presented here.

  7. Identification and utilization of arbitrary correlations in models of recombination signal sequences

    PubMed Central

    Cowell, Lindsay G; Davila, Marco; Kepler, Thomas B; Kelsoe, Garnett

    2002-01-01

    Background A significant challenge in bioinformatics is to develop methods for detecting and modeling patterns in variable DNA sequence sites, such as protein-binding sites in regulatory DNA. Current approaches sometimes perform poorly when positions in the site do not independently affect protein binding. We developed a statistical technique for modeling the correlation structure in variable DNA sequence sites. The method places no restrictions on the number of correlated positions or on their spatial relationship within the site. No prior empirical evidence for the correlation structure is necessary. Results We applied our method to the recombination signal sequences (RSS) that direct assembly of B-cell and T-cell antigen-receptor genes via V(D)J recombination. The technique is based on model selection by cross-validation and produces models that allow computation of an information score for any signal-length sequence. We also modeled RSS using order zero and order one Markov chains. The scores from all models are highly correlated with measured recombination efficiencies, but the models arising from our technique are better than the Markov models at discriminating RSS from non-RSS. Conclusions Our model-development procedure produces models that estimate well the recombinogenic potential of RSS and are better at RSS recognition than the order zero and order one Markov models. Our models are, therefore, valuable for studying the regulation of both physiologic and aberrant V(D)J recombination. The approach could be equally powerful for the study of promoter and enhancer elements, splice sites, and other DNA regulatory sites that are highly variable at the level of individual nucleotide positions. PMID:12537561

  8. Electrophysiological correlates of the BOLD signal for EEG-informed fMRI

    PubMed Central

    Murta, Teresa; Leite, Marco; Carmichael, David W; Figueiredo, Patrícia; Lemieux, Louis

    2015-01-01

    Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are important tools in cognitive and clinical neuroscience. Combined EEG–fMRI has been shown to help to characterise brain networks involved in epileptic activity, as well as in different sensory, motor and cognitive functions. A good understanding of the electrophysiological correlates of the blood oxygen level-dependent (BOLD) signal is necessary to interpret fMRI maps, particularly when obtained in combination with EEG. We review the current understanding of electrophysiological–haemodynamic correlates, during different types of brain activity. We start by describing the basic mechanisms underlying EEG and BOLD signals and proceed by reviewing EEG-informed fMRI studies using fMRI to map specific EEG phenomena over the entire brain (EEG–fMRI mapping), or exploring a range of EEG-derived quantities to determine which best explain colocalised BOLD fluctuations (local EEG–fMRI coupling). While reviewing studies of different forms of brain activity (epileptic and nonepileptic spontaneous activity; cognitive, sensory and motor functions), a significant attention is given to epilepsy because the investigation of its haemodynamic correlates is the most common application of EEG-informed fMRI. Our review is focused on EEG-informed fMRI, an asymmetric approach of data integration. We give special attention to the invasiveness of electrophysiological measurements and the simultaneity of multimodal acquisitions because these methodological aspects determine the nature of the conclusions that can be drawn from EEG-informed fMRI studies. We emphasise the advantages of, and need for, simultaneous intracranial EEG–fMRI studies in humans, which recently became available and hold great potential to improve our understanding of the electrophysiological correlates of BOLD fluctuations. PMID:25277370

  9. Single sensor processing to obtain high resolution color component signals

    NASA Technical Reports Server (NTRS)

    Glenn, William E. (Inventor)

    2010-01-01

    A method for generating color video signals representative of color images of a scene includes the following steps: focusing light from the scene on an electronic image sensor via a filter having a tri-color filter pattern; producing, from outputs of the sensor, first and second relatively low resolution luminance signals; producing, from outputs of the sensor, a relatively high resolution luminance signal; producing, from a ratio of the relatively high resolution luminance signal to the first relatively low resolution luminance signal, a high band luminance component signal; producing, from outputs of the sensor, relatively low resolution color component signals; and combining each of the relatively low resolution color component signals with the high band luminance component signal to obtain relatively high resolution color component signals.

  10. Optical hybrid analog-digital signal processing based on spike processing in neurons

    NASA Astrophysics Data System (ADS)

    Fok, Mable P.; Tian, Yue; Rosenbluth, David; Deng, Yanhua; Prucnal, Paul R.

    2011-09-01

    Spike processing is one kind of hybrid analog-digital signal processing, which has the efficiency of analog processing and the robustness to noise of digital processing. When instantiated with optics, a hybrid analog-digital processing primitive has the potential to be scalable, computationally powerful, and have high operation bandwidth. These devices open up a range of processing applications for which electronic processing is too slow. Our approach is based on a hybrid analog/digital computational primitive that elegantly implements the functionality of an integrate-and-fire neuron using a Ge-doped non-linear optical fiber and off-the-shelf semiconductor devices. In this paper, we introduce our photonic neuron architecture and demonstrate the feasibility of implementing simple photonic neuromorphic circuits, including the auditory localization algorithm of the barn owl, which is useful for LIDAR localization, and the crayfish tail-flip escape response.

  11. Temporally selective processing of communication signals by auditory midbrain neurons

    PubMed Central

    Christensen-Dalsgaard, Jakob; Kelley, Darcy B.

    2011-01-01

    Perception of the temporal structure of acoustic signals contributes critically to vocal signaling. In the aquatic clawed frog Xenopus laevis, calls differ primarily in the temporal parameter of click rate, which conveys sexual identity and reproductive state. We show here that an ensemble of auditory neurons in the laminar nucleus of the torus semicircularis (TS) of X. laevis specializes in encoding vocalization click rates. We recorded single TS units while pure tones, natural calls, and synthetic clicks were presented directly to the tympanum via a vibration-stimulation probe. Synthesized click rates ranged from 4 to 50 Hz, the rate at which the clicks begin to overlap. Frequency selectivity and temporal processing were characterized using response-intensity curves, temporal-discharge patterns, and autocorrelations of reduplicated responses to click trains. Characteristic frequencies ranged from 140 to 3,250 Hz, with minimum thresholds of ?90 dB re 1 mm/s at 500 Hz and ?76 dB at 1,100 Hz near the dominant frequency of female clicks. Unlike units in the auditory nerve and dorsal medullary nucleus, most toral units respond selectively to the behaviorally relevant temporal feature of the rate of clicks in calls. The majority of neurons (85%) were selective for click rates, and this selectivity remained unchanged over sound levels 10 to 20 dB above threshold. Selective neurons give phasic, tonic, or adapting responses to tone bursts and click trains. Some algorithms that could compute temporally selective receptive fields are described. PMID:21289132

  12. Sensometrics: identifying pen digitizers by statistical multimedia signal processing

    NASA Astrophysics Data System (ADS)

    Oermann, Andrea; Vielhauer, Claus; Dittmann, Jana

    2007-02-01

    In this paper a new approach will be introduced to identify pen-based digitizer devices based on handwritten samples used for biometric user authentication. This new method of digitizer identification based on their signal properties can also be seen as an influencing part in the new research area of so-called sensometrics. The goal of the work presented in this paper is to identify statistical features, derived from signals provided by pen-based digitizer tablets during the writing process, which allow identification, or at least group discrimination of different device types. Based on a database of a total of approximately 40,000 writing samples taken on 23 different pen digitizers, specific features for class discrimination will be chosen and a novel feature vector based classification system will be implemented and experimentally validated. The goal of our experimental validation is to study the class space that can be obtained, given a specific feature set, i.e. to which degree single tablets and/or groups of pen digitizers can be identified using our developed classification by a decision tree model. The results confirm that a group discrimination of devices can be achieved. By applying this new approach, the 23 different tablets from our database can be discriminated in 19 output groups.

  13. Regulation of Amyloid Precursor Protein Processing by Serotonin Signaling

    PubMed Central

    Pimenova, Anna A.; Thathiah, Amantha; De Strooper, Bart; Tesseur, Ina

    2014-01-01

    Proteolytic processing of the amyloid precursor protein (APP) by the ?- and ?-secretases releases the amyloid-? peptide (A?), which deposits in senile plaques and contributes to the etiology of Alzheimer's disease (AD). The ?-secretase cleaves APP in the A? peptide sequence to generate soluble APP? (sAPP?). Upregulation of ?-secretase activity through the 5-hydroxytryptamine 4 (5-HT4) receptor has been shown to reduce A? production, amyloid plaque load and to improve cognitive impairment in transgenic mouse models of AD. Consequently, activation of 5-HT4 receptors following agonist stimulation is considered to be a therapeutic strategy for AD treatment; however, the signaling cascade involved in 5-HT4 receptor-stimulated proteolysis of APP remains to be determined. Here we used chemical and siRNA inhibition to identify the proteins which mediate 5-HT4d receptor-stimulated ?-secretase activity in the SH-SY5Y human neuronal cell line. We show that G protein and Src dependent activation of phospholipase C are required for ?-secretase activity, while, unexpectedly, adenylyl cyclase and cAMP are not involved. Further elucidation of the signaling pathway indicates that inositol triphosphate phosphorylation and casein kinase 2 activation is also a prerequisite for ?-secretase activity. Our findings provide a novel route to explore the treatment of AD through 5-HT4 receptor-induced ?-secretase activation. PMID:24466315

  14. Attosecond metrology: from electron capture to future signal processing

    NASA Astrophysics Data System (ADS)

    Krausz, Ferenc; Stockman, Mark I.

    2014-03-01

    The accurate measurement of time lies at the heart of experimental science, and is relevant to everyday life. Extending chronoscopy to ever shorter timescales has been the key to gaining real-time insights into microscopic phenomena, ranging from vital biological processes to the dynamics underlying high technologies. The generation of isolated attosecond pulses in 2001 allowed the fastest of all motions outside the nucleus -- electron dynamics in atomic systems -- to be captured. Attosecond metrology has provided access to several hitherto immeasurably fast electron phenomena in atoms, molecules and solids. The fundamental importance of electron processes for the physical and life sciences, technology and medicine has rendered the young field of attosecond science one of the most dynamically expanding research fields of the new millennium. Here, we review the basic concepts underlying attosecond measurement and control techniques. Among their many potential applications, we focus on the exploration of the fundamental speed limit of electronic signal processing. This endeavour relies on ultimate-speed electron metrology, as provided by attosecond technology.

  15. REVIEW ARTICLE: Spectrophotometric applications of digital signal processing

    NASA Astrophysics Data System (ADS)

    Morawski, Roman Z.

    2006-09-01

    Spectrophotometry is more and more often the method of choice not only in analysis of (bio)chemical substances, but also in the identification of physical properties of various objects and their classification. The applications of spectrophotometry include such diversified tasks as monitoring of optical telecommunications links, assessment of eating quality of food, forensic classification of papers, biometric identification of individuals, detection of insect infestation of seeds and classification of textiles. In all those applications, large numbers of data, generated by spectrophotometers, are processed by various digital means in order to extract measurement information. The main objective of this paper is to review the state-of-the-art methodology for digital signal processing (DSP) when applied to data provided by spectrophotometric transducers and spectrophotometers. First, a general methodology of DSP applications in spectrophotometry, based on DSP-oriented models of spectrophotometric data, is outlined. Then, the most important classes of DSP methods for processing spectrophotometric data—the methods for DSP-aided calibration of spectrophotometric instrumentation, the methods for the estimation of spectra on the basis of spectrophotometric data, the methods for the estimation of spectrum-related measurands on the basis of spectrophotometric data—are presented. Finally, the methods for preprocessing and postprocessing of spectrophotometric data are overviewed. Throughout the review, the applications of DSP are illustrated with numerous examples related to broadly understood spectrophotometry.

  16. On adaptive robustness approach to Anti-Jam signal processing

    NASA Astrophysics Data System (ADS)

    Poberezhskiy, Y. S.; Poberezhskiy, G. Y.

    An effective approach to exploiting statistical differences between desired and jamming signals named adaptive robustness is proposed and analyzed in this paper. It combines conventional Bayesian, adaptive, and robust approaches that are complementary to each other. This combining strengthens the advantages and mitigates the drawbacks of the conventional approaches. Adaptive robustness is equally applicable to both jammers and their victim systems. The capabilities required for realization of adaptive robustness in jammers and victim systems are determined. The employment of a specific nonlinear robust algorithm for anti-jam (AJ) processing is described and analyzed. Its effectiveness in practical situations has been proven analytically and confirmed by simulation. Since adaptive robustness can be used by both sides in electronic warfare, it is more advantageous for the fastest and most intelligent side. Many results obtained and discussed in this paper are also applicable to commercial applications such as communications in unregulated or poorly regulated frequency ranges and systems with cognitive capabilities.

  17. Information processing by tree fellers: signal detection analysis.

    PubMed

    Henderson, M; Over, R

    1993-01-01

    Eighteen experienced tree fellers and eighteen forestry students watched video recordings of mature eucalypts being felled by a man using a chain saw, and then rated whether each tree had fallen normally or abnormally. Signal-detection analysis showed that the tree fellers were more accurate than the forestry students in predicting eventual outcome. Further, the tree fellers achieved peak accuracy in discrimination by the time the logger had completed cutting the scarf (typically several minutes before the tree hit the ground), whereas the forestry students predicted outcome most accurately only when a tree was falling (and about 1 s from hitting the ground). Study of the bases for information processing and decision making by tree fellers has implications for personnel selection and training, as well as for formulation of effective work practices. PMID:8041591

  18. Frequency division multiplexing OTDR with fast signal processing

    NASA Astrophysics Data System (ADS)

    Lu, Lidong; Song, Yuejiang; Zhang, Xuping; Zhu, Fan

    2012-10-01

    A frequency division multiplexing optical time domain reflectometry (FDM-OTDR) is proposed and experimentally demonstrated. A phase modulator is employed to convert single frequency laser to multiple frequencies where four frequencies are adopted as the probe. Coherent detection between the backscattered Rayleigh signals of the four-frequency probe light pulses propagating in fiber under test (FUT) and original single frequency local oscillator (LO) only generates two intermediate frequencies (IFs) as the result of direct synthesizing of the same IFs. The two dominant IFs are processed by parallel computing method. Experimental results show that compared with conventional C-OTDR the FDM-OTDR is four times faster in fading noise reduction and can also bring a 1.9 dB single way dynamic range (SWDR) enhancement.

  19. Digital Signal Processing System for Active Noise Reduction

    NASA Astrophysics Data System (ADS)

    Edmonson, William W.; Tucker, Jerry

    2002-12-01

    Over the years there has been a need to improve the comfort of passengers in flight. One avenue for increasing comfort is to reduce cabin noise that is attributed to the engine and the vibration of fuselage panels that radiate sound. High frequency noise can be abated using sound absorbing material. Though, for low frequency noise the sound absorption material would have to very thick, thereby reducing the cabin size. To reduce these low frequency disturbances, active noise control systems (ANC) is being developed that utilizes feedback for cancellation of the disturbance. The active noise control system must be small in size, be a low power device, and operate in real-time. It must also be numerically stable i.e. insensitive to temperature and pressure variations. The ANC system will be a module that consists of digital signal processor (DSP), analog-digital and digital-analog converters, power converters, an actuator and sensors. The DSP will implement the feedback control algorithm that controls the actuators. This module will be attached to panels on the inside of the fuselage for actively eliminating resonant modes of the structure caused by turbulent flow across the fuselage Skin. A hardware prototype of the ANC system must be able to eliminate broadband noise consisting of a bandwidth between 100 Hz and 1500 Hz, which requires a sample rate of 5000 Hz. The analog/digital converters output accuracy is 16 bits with a 2's-compliment format and a very short acquisition time. This will also yield the appropriate dynamic range. Similar specifications are required of the digital/analog converter. The processor section of the system integrates a digital signal processor (TI TMS320C33) with analog/digital (Burr-Brown ADS8320) and digital/analog signal (DAC853 1) converters. The converters with associated power conditioning circuitry and test points reside on a daughter board that sits on top of a Spectrum Digital evaluation module. This will have the ability to test different adaptive noise cancellation algorithms and provide an operational prototype to understand the behavior of the system under test. DSP software was required to interface the processor with the data converters using interrupt routines. The goal is to build a complete ANC system that can be placed on a flexible circuit with added memory circuitry that also contains the power supply, sensors and actuators. This work on the digital signal processing system for active noise reduction was completed in collaboration with another ASEE Fellow, Dr. Jerry Tucker from Virginia Commonwealth University, Richmond, VA.

  20. Correlation study between contamination and signal degradation in single-mode APC connectors

    NASA Astrophysics Data System (ADS)

    Lytle, Steve; Brown, Matt; Berdinskikh, Tatiana; Wilson, Douglas H.; Fisher, David; Huang, Sun-Yuan; Hughes, Mike; Mitcheltree, Tom; Roche, Brian J.

    2009-06-01

    This paper summarizes the correlation study between contamination and scratches on singlemode APC connectors and signal degradation; leading to an Acceptance Criteria Matrix. The study is a continuation of International Electronics Manufacturing Initiative (iNEMI) research on development of cleanliness specification for singlemode angled physical contact (SM-APC) connectors. Twenty-five APC SC connectors on one-meter patch cords were used for this study. The Design of the Experiment (DoE) was a multi-step process that involved: (1) inspecting, cleaning and inspecting connectors being tested (devices under test, or DUTs) and launch connectors; (2) making multiple matings and dematings of each DUT, in a pristine state, with a reference connector, and recording Return Loss (RL) data after each cycle; (3) manually applying dust to the cleaned end-faces of the DUTs; then (4) mating contaminated DUTs with clean reference connectors at least five times, taking RL measurements after each mating and saving fiber end-face images for both connectors. It was shown that connectors with the contamination at the core (9um diameter) demonstrated a dramatic decrease in average RL of 14.2 dB. In comparison, the samples with contamination on the cladding and clear core demonstrated a negligible change in RL of 0.15 dB. For highly contaminated samples in the cladding layer, we found the changes of RL to be about 5-6 dB. Further investigation established that particle migration during successive matings also occurs on the ferrule within the contact zone (approximately <250 ?m in diameter). Polishing scratches had no impact on RL of APC connectors. Based on the experimental data described in this paper, an inspection criteria matrix is proposed for SM-APC connectors including the zone definitions and number of allowable defects (contamination and scratches) for each zone. The recommendations on pass/fail criteria have been provided to the IEC (International Electrotechnical Committee). It is expected IEC-61300-3-25, which contains these criteria, will publish in 2009.

  1. Neural Correlates of Affect Processing and Aggression in Methamphetamine Dependence

    PubMed Central

    Payer, Doris E.; Lieberman, Matthew D.; London, Edythe D.

    2012-01-01

    Context Methamphetamine abuse is associated with high rates of aggression, but few studies have addressed the contributing neurobiological factors. Objective To quantify aggression, investigate function of the amygdala and prefrontal cortex, and assess relationships between brain function and behavior in methamphetamine-dependent individuals. Design In a case-control study, aggression and brain activation were compared between methamphetamine-dependent and control participants. Setting Participants were recruited from the general community to an academic research center. Participants Thirty-nine methamphetamine-dependent volunteers (16 women) who were abstinent for 7 to 10 days and 37 drug-free control volunteers (18 women) participated in the study; subsets completed self-report and behavioral measures. Functional magnetic resonance imaging (fMRI) was performed on 25 methamphetamine-dependent and 23 control participants. Main outcome measures We measured self-reported and perpetrated aggression, and self-reported alexithymia. Brain activation was assessed using fMRI during visual processing of facial affect (affect matching), and symbolic processing (affect labeling), the latter representing an incidental form of emotion regulation. Results Methamphetamine-dependent participants self-reported more aggression and alexithymia than control participants and escalated perpetrated aggression more following provocation. Alexithymia scores correlated with measures of aggression. During affect matching, fMRI showed no differences between groups in amygdala activation, but found lower activation in methamphetamine-dependent than control participants in bilateral ventral inferior frontal gyrus. During affect labeling, participants recruited dorsal inferior frontal gyrus and exhibited decreased amygdala activity, consistent with successful emotion regulation; there was no group difference in this effect. The magnitude of decrease in amygdala activity during affect labeling correlated inversely with self-reported aggression in control participants, and perpetrated aggression in all participants. Ventral inferior frontal gyrus activation correlated inversely with alexithymia in control participants. Conclusions Contrary to the hypotheses, methamphetamine-dependent individuals may successfully regulate emotions through incidental means (affect labeling). Instead, low ventral inferior frontal gyrus activity may contribute to heightened aggression by limiting emotional insight. PMID:21041607

  2. A nonlinear optoelectronic filter for electronic signal processing

    PubMed Central

    Loh, William; Yegnanarayanan, Siva; Ram, Rajeev J.; Juodawlkis, Paul W.

    2014-01-01

    The conversion of electrical signals into modulated optical waves and back into electrical signals provides the capacity for low-loss radio-frequency (RF) signal transfer over optical fiber. Here, we show that the unique properties of this microwave-photonic link also enable the manipulation of RF signals beyond what is possible in conventional systems. We achieve these capabilities by realizing a novel nonlinear filter, which acts to suppress a stronger RF signal in the presence of a weaker signal independent of their separation in frequency. Using this filter, we demonstrate a relative suppression of 56?dB for a stronger signal having a 1-GHz center frequency, uncovering the presence of otherwise undetectable weaker signals located as close as 3.5?Hz away. The capabilities of the optoelectronic filter break the conventional limits of signal detection, opening up new possibilities for radar and communication systems, and for the field of precision frequency metrology. PMID:24402418

  3. Quantum correlation dynamics in photosynthetic processes assisted by molecular vibrations

    E-print Network

    G. L. Giorgi; M. Roncaglia; F. A. Raffa; M. Genovese

    2015-01-30

    During the long course of evolution, nature has learnt how to exploit quantum effects. In fact, recent experiments reveal the existence of quantum processes whose coherence extends over unexpectedly long time and space ranges. In particular, photosynthetic processes in light-harvesting complexes display a typical oscillatory dynamics ascribed to quantum coherence. Here, we consider the simple model where a dimer made of two chromophores is strongly coupled with a quasi-resonant vibrational mode. We observe the occurrence of wide oscillations of genuine quantum correlations, between electronic excitations and the environment, represented by vibrational bosonic modes. Such a quantum dynamics has been unveiled through the calculation of the negativity of entanglement and the discord, indicators widely used in quantum information for quantifying the resources needed to realize quantum technologies. We also discuss the possibility of approximating additional weakly-coupled off-resonant vibrational modes, simulating the disturbances induced by the rest of the environment, by a single vibrational mode. Within this approximation, one can show that the off-resonant bath behaves like a classical source of noise.

  4. Neural correlates of impaired emotion processing in manifest Huntington's disease.

    PubMed

    Dogan, Imis; Saß, Christian; Mirzazade, Shahram; Kleiman, Alexandra; Werner, Cornelius J; Pohl, Anna; Schiefer, Johannes; Binkofski, Ferdinand; Schulz, Jörg B; Shah, N Jon; Reetz, Kathrin

    2014-05-01

    The complex phenotype of Huntington's disease (HD) encompasses motor, psychiatric and cognitive dysfunctions, including early impairments in emotion recognition. In this first functional magnetic resonance imaging study, we investigated emotion-processing deficits in 14 manifest HD patients and matched controls. An emotion recognition task comprised short video clips displaying one of six basic facial expressions (sadness, happiness, disgust, fear, anger and neutral). Structural changes between patients and controls were assessed by means of voxel-based morphometry. Along with deficient recognition of negative emotions, patients exhibited predominantly lower neural response to stimuli of negative valences in the amygdala, hippocampus, striatum, insula, cingulate and prefrontal cortices, as well as in sensorimotor, temporal and visual areas. Most of the observed reduced activity patterns could not be explained merely by regional volume loss. Reduced activity in the thalamus during fear correlated with lower thalamic volumes. During the processing of sadness, patients exhibited enhanced amygdala and hippocampal activity along with reduced recruitment of the medial prefrontal cortex. Higher amygdala activity was related to more pronounced amygdala atrophy and disease burden. Overall, the observed emotion-related dysfunctions in the context of structural neurodegeneration suggest both disruptions of striatal-thalamo-cortical loops and potential compensation mechanism with greater disease severity in manifest HD. PMID:23482620

  5. A common neuronal code for perceptual processes in visual cortex? Comparing choice and attentional correlates in V5/MT.

    PubMed Central

    Krug, Kristine

    2004-01-01

    In the past two decades, sensory neuroscience has moved from describing response properties to external stimuli in cerebral cortex to establishing connections between neuronal activity and sensory perception. The seminal studies by Newsome, Movshon and colleagues in the awake behaving macaque firmly link single cells in extrastriate area V5/MT and perception of motion. A decade later, extrastriate visual cortex appears awash with neuronal correlates for many different perceptual tasks. Examples are attentional signals, choice signals for ambiguous images, correlates for binocular rivalry, stereo and shape perception, and so on. These diverse paradigms are aimed at elucidating the neuronal code for perceptual processes, but it has been little studied how they directly compare or even interact. In this paper, I explore to what degree the measured neuronal signals in V5/MT for choice and attentional paradigms might reflect a common neuronal mechanism for visual perception. PMID:15306408

  6. Correlation between light scattering signal and tissue reversibility in rat brain exposed to hypoxia

    NASA Astrophysics Data System (ADS)

    Kawauchi, Satoko; Sato, Shunichi; Uozumi, Yoichi; Nawashiro, Hiroshi; Ishihara, Miya; Kikuchi, Makoto

    2010-02-01

    Light scattering signal is a potential indicator of tissue viability in brain because cellular and subcellular structural integrity should be associated with cell viability in brain tissue. We previously performed multiwavelength diffuse reflectance measurement for a rat global ischemic brain model and observed a unique triphasic change in light scattering at a certain time after oxygen and glucose deprivation. This triphasic scattering change (TSC) was shown to precede cerebral ATP exhaustion, suggesting that loss of brain tissue viability can be predicted by detecting scattering signal. In the present study, we examined correlation between light scattering signal and tissue reversibility in rat brain in vivo. We performed transcranial diffuse reflectance measurement for rat brain; under spontaneous respiration, hypoxia was induced for the rat by nitrogen gas inhalation and reoxygenation was started at various time points. We observed a TSC, which started at 140 +/- 15 s after starting nitrogen gas inhalation (mean +/- SD, n=8). When reoxygenation was started before the TSC, all rats survived (n=7), while no rats survived when reoxygenation was started after the TSC (n=8). When reoxygenation was started during the TSC, rats survived probabilistically (n=31). Disability of motor function was not observed for the survived rats. These results indicate that TSC can be used as an indicator of loss of tissue reversibility in brains, providing useful information on the critical time zone for treatment to rescue the brain.

  7. Chatter, process damping, and chip segmentation in turning: A signal processing approach

    NASA Astrophysics Data System (ADS)

    Taylor, Christopher M.; Turner, Sam; Sims, Neil D.

    2010-11-01

    An increasing number of aerospace components are manufactured from titanium and nickel alloys that are difficult to machine due to their thermal and mechanical properties. This limits the metal removal rates that can be achieved from the production process. However, under these machining conditions the phenomenon of process damping can be exploited to help avoid self-excited vibrations known as regenerative chatter. This means that greater widths of cut can be taken so as to increase the metal removal rate, and hence offset the cutting speed restrictions that are imposed by the thermo-mechanical properties of the material. However, there is little or no consensus as to the underlying mechanisms that cause process damping. The present study investigates two process damping mechanisms that have previously been proposed in the machining literature: the tool flank/workpiece interference effect, and the short regenerative effect. A signal processing procedure is employed to identify flank/workpiece interference from experimental data. Meanwhile, the short regenerative model is solved using a new frequency domain approach that yields additional insight into its stabilising effect. However, analysis and signal processing of the experimentally obtained data reveals that neither of these models can fully explain the increases in stability that are observed in practice. Meanwhile, chip segmentation effects were observed in a number of measurements, and it is suggested that segmentation could play an important role in the process-damped chatter stability of these materials.

  8. Exploration, processing and visualization of physiological signals from the ICU

    E-print Network

    Renjifo, Carlos A

    2005-01-01

    This report studies physiological signals measured from patients in the Intensive Care Unit (ICU). The signals explored include heart rate, arterial blood pressure, pulmonary artery pressure, and central venous pressure ...

  9. Adaptive Signal Processing Laboratory (ASPL) Electrical and Computer Engineering Department

    E-print Network

    Slatton, Clint

    and Computer Engineering Dept. Gainesville, FL 32611 Abstract ­ Extremely Low Frequency (ELF) electromagnetic interference Introduction #12;Extremely low frequency (ELF) electromagnetic signals ( University of Florida Clustering Methods for Extremely Low Frequency Subsurface Signals ASPL Report No. Rep

  10. Polygaussian Approximation and Adaptive Processing of an Electrocardiographic Signal Against Interference Background

    NASA Astrophysics Data System (ADS)

    Ivlev, D. N.; Orlov, I. Ya.

    2004-07-01

    We present the results of a study and substantiation of the method of polygaussian approximation of an electrocardiographic (ECG) signal against interference background during computer analysis of that signal. It is proposed to use adaptive processing of ECG signals, which allows one to increase the signal-to-interference ratio by over 7 dB.

  11. LOW POWER GLOBAL NAVIGATION SATELLITE SYSTEM (GNSS) SIGNAL DETECTION AND PROCESSING

    Microsoft Academic Search

    Dennis M. Akos; Per-Ludvig Normark; Jeong-Taek Lee; Konstantin G. Gromov; James B. Y. Tsui; John Schamus; Wright-Patterson AFB

    2000-01-01

    The ability to detect and process weak Global Navigation Satellite System (GNSS) signals is extremely valuable as the specified received power levels of such signals are already quite low. For example, the GPS-SPS signal specification indicates the signal power at the antenna will be -130 dBm. Such weak detection techniques would be of importance for a number of applications. This

  12. Signal Processing 80 (2000) 2597}2608 Minimum variance "lters and mixed spectrum estimation

    E-print Network

    Paris-Sud XI, Université de

    Signal Processing 80 (2000) 2597}2608 Minimum variance "lters and mixed spectrum estimation M that highlights this amplitude lost. Two signal types are taken into account: periodic deterministic signals (narrow-band spectral structures) and stationary random signals (broad-band spectral structures). Without

  13. Differential auditory signal processing in an animal model

    NASA Astrophysics Data System (ADS)

    Lim, Dukhwan; Kim, Chongsun; Chang, Sun O.

    2002-05-01

    Auditory evoked responses were collected in male zebra finches (Poephila guttata) to objectively determine differential frequency selectivity. First, the mating call of the animal was recorded and analyzed for its frequency components through the customized program. Then, auditory brainstem responses and cortical responses of each anesthetized animal were routinely recorded in response to tone bursts of 1-8 kHz derived from the corresponding mating call spectrum. From the results, most mating calls showed relatively consistent spectral structures. The upper limit of the spectrum was well under 10 kHz. The peak energy bands were concentrated in the region less than 5 kHz. The assessment of auditory brainstem responses and cortical evoked potentials showed differential selectivity with a series of characteristic scales. This system appears to be an excellent model to investigate complex sound processing and related language behaviors. These data could also be used in designing effective signal processing strategies in auditory rehabilitation devices such as hearing aids and cochlear implants. [Work supported by Brain Science & Engineering Program from Korean Ministry of Science and Technology.

  14. Optimal Signal Processing of Frequency-Stepped CW Radar Data

    NASA Technical Reports Server (NTRS)

    Ybarra, Gary A.; Wu, Shawkang M.; Bilbro, Griff L.; Ardalan, Sasan H.; Hearn, Chase P.; Neece, Robert T.

    1995-01-01

    An optimal signal processing algorithm is derived for estimating the time delay and amplitude of each scatterer reflection using a frequency-stepped CW system. The channel is assumed to be composed of abrupt changes in the reflection coefficient profile. The optimization technique is intended to maximize the target range resolution achievable from any set of frequency-stepped CW radar measurements made in such an environment. The algorithm is composed of an iterative two-step procedure. First, the amplitudes of the echoes are optimized by solving an overdetermined least squares set of equations. Then, a nonlinear objective function is scanned in an organized fashion to find its global minimum. The result is a set of echo strengths and time delay estimates. Although this paper addresses the specific problem of resolving the time delay between the two echoes, the derivation is general in the number of echoes. Performance of the optimization approach is illustrated using measured data obtained from an HP-851O network analyzer. It is demonstrated that the optimization approach offers a significant resolution enhancement over the standard processing approach that employs an IFFT. Degradation in the performance of the algorithm due to suboptimal model order selection and the effects of additive white Gaussion noise are addressed.

  15. Optimal Signal Processing of Frequency-Stepped CW Radar Data

    NASA Technical Reports Server (NTRS)

    Ybarra, Gary A.; Wu, Shawkang M.; Bilbro, Griff L.; Ardalan, Sasan H.; Hearn, Chase P.; Neece, Robert T.

    1995-01-01

    An optimal signal processing algorithm is derived for estimating the time delay and amplitude of each scatterer reflection using a frequency-stepped CW system. The channel is assumed to be composed of abrupt changes in the reflection coefficient profile. The optimization technique is intended to maximize the target range resolution achievable from any set of frequency-stepped CW radar measurements made in such an environment. The algorithm is composed of an iterative two-step procedure. First, the amplitudes of the echoes are optimized by solving an overdetermined least squares set of equations. Then, a nonlinear objective function is scanned in an organized fashion to find its global minimum. The result is a set of echo strengths and time delay estimates. Although this paper addresses the specific problem of resolving the time delay between the first two echoes, the derivation is general in the number of echoes. Performance of the optimization approach is illustrated using measured data obtained from an HP-X510 network analyzer. It is demonstrated that the optimization approach offers a significant resolution enhancement over the standard processing approach that employs an IFFT. Degradation in the performance of the algorithm due to suboptimal model order selection and the effects of additive white Gaussion noise are addressed.

  16. Tensor Decompositions for Signal Processing Applications: From two-way to multiway component analysis

    NASA Astrophysics Data System (ADS)

    Cichocki, Andrzej; Mandic, Danilo; De Lathauwer, Lieven; Zhou, Guoxu; Zhao, Qibin; Caiafa, Cesar; PHAN, HUY ANH

    2015-03-01

    The widespread use of multi-sensor technology and the emergence of big datasets has highlighted the limitations of standard flat-view matrix models and the necessity to move towards more versatile data analysis tools. We show that higher-order tensors (i.e., multiway arrays) enable such a fundamental paradigm shift towards models that are essentially polynomial and whose uniqueness, unlike the matrix methods, is guaranteed under verymild and natural conditions. Benefiting fromthe power ofmultilinear algebra as theirmathematical backbone, data analysis techniques using tensor decompositions are shown to have great flexibility in the choice of constraints that match data properties, and to find more general latent components in the data than matrix-based methods. A comprehensive introduction to tensor decompositions is provided from a signal processing perspective, starting from the algebraic foundations, via basic Canonical Polyadic and Tucker models, through to advanced cause-effect and multi-view data analysis schemes. We show that tensor decompositions enable natural generalizations of some commonly used signal processing paradigms, such as canonical correlation and subspace techniques, signal separation, linear regression, feature extraction and classification. We also cover computational aspects, and point out how ideas from compressed sensing and scientific computing may be used for addressing the otherwise unmanageable storage and manipulation problems associated with big datasets. The concepts are supported by illustrative real world case studies illuminating the benefits of the tensor framework, as efficient and promising tools for modern signal processing, data analysis and machine learning applications; these benefits also extend to vector/matrix data through tensorization. Keywords: ICA, NMF, CPD, Tucker decomposition, HOSVD, tensor networks, Tensor Train.

  17. Clay content evaluation in soils through GPR signal processing

    NASA Astrophysics Data System (ADS)

    Tosti, Fabio; Patriarca, Claudio; Slob, Evert; Benedetto, Andrea; Lambot, Sébastien

    2013-10-01

    The mechanical behavior of soils is partly affected by their clay content, which arises some important issues in many fields of employment, such as civil and environmental engineering, geology, and agriculture. This work focuses on pavement engineering, although the method applies to other fields of interest. Clay content in bearing courses of road pavement frequently causes damages and defects (e.g., cracks, deformations, and ruts). Therefore, the road safety and operability decreases, directly affecting the increase of expected accidents. In this study, different ground-penetrating radar (GPR) methods and techniques were used to non-destructively investigate the clay content in sub-asphalt compacted soils. Experimental layout provided the use of typical road materials, employed for road bearing courses construction. Three types of soils classified by the American Association of State Highway and Transportation Officials (AASHTO) as A1, A2, and A3 were used and adequately compacted in electrically and hydraulically isolated test boxes. Percentages of bentonite clay were gradually added, ranging from 2% to 25% by weight. Analyses were carried out for each clay content using two different GPR instruments. A pulse radar with ground-coupled antennae at 500 MHz centre frequency and a vector network analyzer spanning the 1-3 GHz frequency range were used. Signals were processed in both time and frequency domains, and the consistency of results was validated by the Rayleigh scattering method, the full-waveform inversion, and the signal picking techniques. Promising results were obtained for the detection of clay content affecting the bearing capacity of sub-asphalt layers.

  18. Playback of beyond high definition video signal in holographic data storage system with wavefront compensation and parallel signal processing

    NASA Astrophysics Data System (ADS)

    Muroi, Tetsuhiko; Kinoshita, Nobuhiro; Ishii, Norihiko; Kamijo, Koji; Kikuchi, Hiroshi

    2014-09-01

    We have developed a holographic data storage system that can demonstrate real-time playback of beyond high definition video signals. In the proposed system, to increase the data-transfer rate of the reproduced data, we focused on improving the SNR of the reproduced data and on improving the signal processing speed, which the SNR of the reproduced data has a significant effect on. One of the factors that deteriorate the SNR is shrinkage in the medium. This shrinkage distorts recorded holograms and degrades the quality of the reproduced data. We investigated wavefront compensation as a means to improve the SNR of reproduced data degraded by hologram distortion and found that controlling the defocus component of the reference beam is effective. We have also been developing parallel signal processing to increase the data-transfer rate. We placed three GPUs in the signal processing unit: one for the reproduced data detection from the reconstructed image and two for the LDPC decoding for error correction of the reproduced data. The LDPC decoding required a lot more time than the data detection, so we designed a signal processing in which detected data in the GPU for the data detection were sent to the two GPUs for the LDPC decoding alternatively. We implemented wavefront compensation for the defocus component and developed parallel signal processing with three GPUs for our holographic data storage system. Using this system, we demonstrated real-time playback of beyond high definition video signals with 50 Mbps.

  19. Correlative intravital imaging of cGMP signals and vasodilation in mice

    PubMed Central

    Thunemann, Martin; Schmidt, Kjestine; de Wit, Cor; Han, Xiaoxing; Jain, Rakesh K.; Fukumura, Dai; Feil, Robert

    2014-01-01

    Cyclic guanosine monophosphate (cGMP) is an important signaling molecule and drug target in the cardiovascular system. It is well known that stimulation of the vascular nitric oxide (NO)-cGMP pathway results in vasodilation. However, the spatiotemporal dynamics of cGMP signals themselves and the cGMP concentrations within specific cardiovascular cell types in health, disease, and during pharmacotherapy with cGMP-elevating drugs are largely unknown. To facilitate the analysis of cGMP signaling in vivo, we have generated transgenic mice that express fluorescence resonance energy transfer (FRET)-based cGMP sensor proteins. Here, we describe two models of intravital FRET/cGMP imaging in the vasculature of cGMP sensor mice: (1) epifluorescence-based ratio imaging in resistance-type vessels of the cremaster muscle and (2) ratio imaging by multiphoton microscopy within the walls of subcutaneous blood vessels accessed through a dorsal skinfold chamber. Both methods allow simultaneous monitoring of NO-induced cGMP transients and vasodilation in living mice. Detailed protocols of all steps necessary to perform and evaluate intravital imaging experiments of the vasculature of anesthetized mice including surgery, imaging, and data evaluation are provided. An image segmentation approach is described to estimate FRET/cGMP changes within moving structures such as the vessel wall during vasodilation. The methods presented herein should be useful to visualize cGMP or other biochemical signals that are detectable with FRET-based biosensors, such as cyclic adenosine monophosphate or Ca2+, and to correlate them with respective vascular responses. With further refinement and combination of transgenic mouse models and intravital imaging technologies, we envision an exciting future, in which we are able to “watch” biochemistry, (patho-)physiology, and pharmacotherapy in the context of a living mammalian organism. PMID:25352809

  20. SCOPE: IEEE Signal Processing Magazine publishes tutorial-style articles on signal processing research and applications, as well as columns and forums of interest to the signal processing community. Coverage ranges from fundamental principles to practical

    E-print Network

    Nehorai, Arye

    [CONTENTS] SCOPE: IEEE Signal Processing Magazine publishes tutorial-style articles on signal MAGAZINE (ISSN 1053-5888) (ISPREG) is published bimonthly by the Institute of Electrical and Electronics of U.S. Copyright Law for private use of patrons: (1) those post-1977 articles that carry a code

  1. PROCESSING OF SONAR SIGNALS USING NEURAL NETWORKS FOR ROBUST TARGET DIFFERENTIATION

    E-print Network

    Barshan, Billur

    PROCESSING OF SONAR SIGNALS USING NEURAL NETWORKS FOR ROBUST TARGET DIFFERENTIATION Birsel Ayrulu ABSTRACT This study investigates the processing of sonar signals using neural networks for robust di is of interest for intel- ligent systems. Amplitude and time-of- ight TOF patterns of sonar signals acquired from

  2. A realistic coupled nonlinear artificial ECG, BP, and respiratory signal generator for assessing noise performance of biomedical signal processing algorithms

    NASA Astrophysics Data System (ADS)

    Clifford, Gari D.; McSharry, Patrick E.

    2004-05-01

    Extensions to a previously published nonlinear model for generating realistic artificial electrocardiograms to include blood pressure and respiratory signals are presented. The model accurately reproduces many of the important clinical qualities of these signals such as QT dispersion, realistic beat to beat variability in timing and morphology and pulse transit time. The advantage of this artificial model is that the signal is completely known (and therefore its clinical descriptors can be specified exactly) and contains no noise. Artifact and noise can therefore be added in a quantifiable and controlled manner in order to test relevant biomedical signal processing algorithms. Application examples using Independent Component Analysis to remove artifacts are presented.

  3. All-Optical Signal Processing of Periodic Signals Using a Brillouin Gain Comb

    Microsoft Academic Search

    CÉsar Jauregui Misas; Periklis Petropoulos; David J. Richardson

    2008-01-01

    The amplification of periodic signals using a Brillouin gain comb provides the opportunity to manipulate the amplitude and phase of a signal's individual spectral harmonics and, therefore, its temporal characteristics. In addition to obvious applications in pulse shaping, the approach offers new opportunities in the context of slow-light generation which include power-efficient Brillouin amplification of broadband periodic signals without delay,

  4. Memory processes in the response of plants to environmental signals.

    PubMed

    Tafforeau, M; Verdus, M C; Norris, V; Ripoll, C; Thellier, M

    2006-01-01

    Plants are sensitive to stimuli from the environment (e.g., wind, rain, contact, pricking, wounding). They usually respond to such stimuli by metabolic or morphogenetic changes. Sometimes the information corresponding to a stimulus may be "stored" in the plant where it remains inactive until a second stimulus "recalls" this information and finally allows it to take effect. Two experimental systems have proved especially useful in unravelling the main features of these memory-like processes.In the system based on Bidens seedlings, an asymmetrical treatment (e.g., pricking, or gently rubbing one of the seedling cotyledons) causes the cotyledonary buds to grow asymmetrically after release of apical dominance by decapitation of the seedlings. This information may be stored within the seedlings, without taking effect, for at least two weeks; then the information may be recalled by subjecting the seedlings to a second, appropriate, treatment that permits transduction of the signal into the final response (differential growth of the buds). Whilst storage is an irreversible, all-or-nothing process, recall is sensitive to a number of factors, including the intensity of these factors, and can readily be enabled or disabled. In consequence, it is possible to recall the stored message several times successively.In the system based on flax seedlings, stimulation such as manipulation stimulus, drought, wind, cold shock and radiation from a GSM telephone or from a 105 GHz Gunn oscillator, has no apparent effect. If, however, the seedlings are subjected at the same time to transient calcium depletion, numerous epidermal meristems form in their hypocotyls. When the calcium depletion treatment is applied a few days after the mechanical treatment, the time taken for the meristems to appear is increased by a number of days exactly equal to that between the application of the mechanical treatment and the beginning of the calcium depletion treatment. This means that a meristem-production information corresponding to the stimulation treatment has been stored in the plants, without any apparent effect, until the calcium depletion treatment recalls this information to allow it to take effect. Gel electrophoresis has shown that a few protein spots are changed (pI shift, appearance or disappearance of a spot) as a consequence of the application of the treatments that store or recall a meristem-production signal in flax seedlings. A SIMS investigation has revealed that the pI shift of one of these spots is probably due to protein phosphorylation. Modifications of the proteome have also been observed in Arabidopsis seedlings subjected to stimuli such as cold shock or radiation from a GSM telephone. PMID:19521470

  5. Electrophysiological correlates of melodic processing in congenital amusia.

    PubMed

    Omigie, Diana; Pearce, Marcus T; Williamson, Victoria J; Stewart, Lauren

    2013-08-01

    Music listening involves using previously internalized regularities to process incoming musical structures. A condition known as congenital amusia is characterized by musical difficulties, notably in the detection of gross musical violations. However, there has been increasing evidence that individuals with the disorder show preserved musical ability when probed using implicit methods. To further characterize the degree to which amusic individuals show evidence of latent sensitivity to musical structure, particularly in the context of stimuli that are ecologically valid, electrophysiological recordings were taken from a sample of amusic and control participants as they listened to real melodies. To encourage them to pay attention to the music, participants were asked to detect occasional notes in a different timbre. Using a computational model of auditory expectation to identify points of varying levels of expectedness in these melodies (in units of information content (IC), a measure which has an inverse relationship with probability), ERP analysis investigated the extent to which the amusic brain differs from that of controls when processing notes of high IC (low probability) as compared to low IC ones (high probability). The data revealed a novel effect that was highly comparable in both groups: Notes with high IC reliably elicited a delayed P2 component relative to notes with low IC, suggesting that amusic individuals, like controls, found these notes more difficult to evaluate. However, notes with high IC were also characterized by an early frontal negativity in controls that was attenuated in amusic individuals. A correlation of this early negative effect with the ability to make accurate note expectedness judgments (previous data collected from a subset of the current sample) was shown to be present in typical individuals but compromised in individuals with amusia: a finding in line with evidence of a close relationship between the amplitude of such a response and explicit knowledge of musical deviance. PMID:23707539

  6. Correlations between the Signal Complexity of Cerebral and Cardiac Electrical Activity: A Multiscale Entropy Analysis

    PubMed Central

    Lin, Pei-Feng; Lo, Men-Tzung; Tsao, Jenho; Chang, Yi-Chung; Lin, Chen; Ho, Yi-Lwun

    2014-01-01

    The heart begins to beat before the brain is formed. Whether conventional hierarchical central commands sent by the brain to the heart alone explain all the interplay between these two organs should be reconsidered. Here, we demonstrate correlations between the signal complexity of brain and cardiac activity. Eighty-seven geriatric outpatients with healthy hearts and varied cognitive abilities each provided a 24-hour electrocardiography (ECG) and a 19-channel eye-closed routine electroencephalography (EEG). Multiscale entropy (MSE) analysis was applied to three epochs (resting-awake state, photic stimulation of fast frequencies (fast-PS), and photic stimulation of slow frequencies (slow-PS)) of EEG in the 1–58 Hz frequency range, and three RR interval (RRI) time series (awake-state, sleep and that concomitant with the EEG) for each subject. The low-to-high frequency power (LF/HF) ratio of RRI was calculated to represent sympatho-vagal balance. With statistics after Bonferroni corrections, we found that: (a) the summed MSE value on coarse scales of the awake RRI (scales 11–20, RRI-MSE-coarse) were inversely correlated with the summed MSE value on coarse scales of the resting-awake EEG (scales 6–20, EEG-MSE-coarse) at Fp2, C4, T6 and T4; (b) the awake RRI-MSE-coarse was inversely correlated with the fast-PS EEG-MSE-coarse at O1, O2 and C4; (c) the sleep RRI-MSE-coarse was inversely correlated with the slow-PS EEG-MSE-coarse at Fp2; (d) the RRI-MSE-coarse and LF/HF ratio of the awake RRI were correlated positively to each other; (e) the EEG-MSE-coarse at F8 was proportional to the cognitive test score; (f) the results conform to the cholinergic hypothesis which states that cognitive impairment causes reduction in vagal cardiac modulation; (g) fast-PS significantly lowered the EEG-MSE-coarse globally. Whether these heart-brain correlations could be fully explained by the central autonomic network is unknown and needs further exploration. PMID:24498375

  7. In-Band OSNR monitoring by polarization diversity and electronic signal processing

    Microsoft Academic Search

    Qi Sui; Chao Lu; A. Lau

    2009-01-01

    A cost-effective optical signal-to-noise ratio (OSNR) monitoring technique by electronically processing the received signals from both polarization is proposed. This method enable in-band OSNR monitoring without the need for polarization control.

  8. Monitoring and predicting cognitive state and performance via physiological correlates of neuronal signals.

    PubMed

    Russo, Michael B; Stetz, Melba C; Thomas, Maria L

    2005-07-01

    Judgment, decision making, and situational awareness are higher-order mental abilities critically important to operational cognitive performance. Higher-order mental abilities rely on intact functioning of multiple brain regions, including the prefrontal, thalamus, and parietal areas. Real-time monitoring of individuals for cognitive performance capacity via an approach based on sampling multiple neurophysiologic signals and integrating those signals with performance prediction models potentially provides a method of supporting warfighters' and commanders' decision making and other operationally relevant mental processes and is consistent with the goals of augmented cognition. Cognitive neurophysiological assessments that directly measure brain function and subsequent cognition include positron emission tomography, functional magnetic resonance imaging, mass spectroscopy, near-infrared spectroscopy, magnetoencephalography, and electroencephalography (EEG); however, most direct measures are not practical to use in operational environments. More practical, albeit indirect measures that are generated by, but removed from the actual neural sources, are movement activity, oculometrics, heart rate, and voice stress signals. The goal of the papers in this section is to describe advances in selected direct and indirect cognitive neurophysiologic monitoring techniques as applied for the ultimate purpose of preventing operational performance failures. These papers present data acquired in a wide variety of environments, including laboratory, simulator, and clinical arenas. The papers discuss cognitive neurophysiologic measures such as digital signal processing wrist-mounted actigraphy; oculometrics including blinks, saccadic eye movements, pupillary movements, the pupil light reflex; and high-frequency EEG. These neurophysiological indices are related to cognitive performance as measured through standard test batteries and simulators with conditions including sleep loss, time on task, and aviation flight-induced fatigue. PMID:16018331

  9. Probing two-field open inflation by resonant signals in correlation functions

    SciTech Connect

    Battefeld, Thorsten; Niemeyer, Jens C.; Vlaykov, Dimitar, E-mail: tbattefe@astro.physik.uni-goettingen.de, E-mail: niemeyer@astro.physik.uni-goettingen.de, E-mail: vlaykov@astro.physik.uni-goettingen.de [Institute for Astrophysics, University of Goettingen, Friedrich Hund Platz 1, D-37077 Goettingen (Germany)

    2013-05-01

    We derive oscillatory signals in correlation functions in two-field open inflation by means of the in-in formalism; such signatures are caused by resonances between oscillations in the tunnelling field and fluctuations in the inflaton during the curvature dominated, intermediate and subsequent inflationary regime. While amplitudes are model-dependent, we find distinct oscillations in the power and bi-spectrum that can act as a direct probe of the curvature dominated phase and thus, indirectly, strengthen the claim of the string landscape if they were observed. We comment on the prospects of detecting these tell-tale signs in current experiments, which is challenging, but not impossible. At the technical level, we pay special attention to the applicability conditions for truncating fluctuations to the light (inflaton) field and derive upper limits on the oscillation amplitude of the heavy field. A violation of these bounds requires a multi-field analysis at the perturbed level.

  10. [Analysis of sleep electroencephalograph signal based on detrended cross-correlation].

    PubMed

    Wang, Yulan; Wang, Jun

    2014-02-01

    The quality of sleep has a great relationship with health and working efficiency. The result of sleep stage classification is an important indicator to measure the quality of sleep, and it is also an important way to diagnose and treat sleep disorders. In this paper, the method of detrended cross-correlation analysis (DCCA) was used to analyze sleep stage classification, sleep electroencephalograph signals, which were extracted from the MIT-BIH Polysomno graphic Database randomly. The results showed that the average DCCA exponent of the awake period is smaller than that of the first stage of non-rapid eye movement (NREM) sleeps. It is well concluded that the method of studying the sleep electroencephalograph with this method is of great significance to improve the quality of sleep, to diagnose and to treat sleep disorders. PMID:24804482

  11. Research on the signal processing technology of laser fuze

    NASA Astrophysics Data System (ADS)

    Gao, Jing; Deng, Jiahao; Cai, Kerong

    2011-06-01

    Laser fuze has been widely used in a variety of large-caliber ammunitions, such as missile, aerial bomb and rocket bomb, due to its typical advantages of proactivity in target detection, sharp directivity of probe field and strong antielectromagnetic interference ability. Recently a new kind of small laser fuze adapted to small-caliber ammunitions is being actively developed. Designed the mathematic model of the laser echo waveform based on Gauss beam and deduced time domain of echo impulse power with varied sharps of target (such as plane target, circle target and mutant target). Echo impulse waveform of laser fuse with the noise interference, such as sunlight and raindrop, also has been studied based on the modeling. The test experiments show that the system can detect weak laser echoed wave, distinguish target and interferences signal by amplifying, modulating and processing the echoed waveform, and detect vertical test board (gray iron) at 5m far away with no more than 90mA current. The test results in High overload conditions indicates that the prototyping can work normally and steadily in the whole trajectory.

  12. Protein import into plant mitochondria: signals, machinery, processing, and regulation.

    PubMed

    Murcha, Monika W; Kmiec, Beata; Kubiszewski-Jakubiak, Szymon; Teixeira, Pedro F; Glaser, Elzbieta; Whelan, James

    2014-12-01

    The majority of more than 1000 proteins present in mitochondria are imported from nuclear-encoded, cytosolically synthesized precursor proteins. This impressive feat of transport and sorting is achieved by the combined action of targeting signals on mitochondrial proteins and the mitochondrial protein import apparatus. The mitochondrial protein import apparatus is composed of a number of multi-subunit protein complexes that recognize, translocate, and assemble mitochondrial proteins into functional complexes. While the core subunits involved in mitochondrial protein import are well conserved across wide phylogenetic gaps, the accessory subunits of these complexes differ in identity and/or function when plants are compared with Saccharomyces cerevisiae (yeast), the model system for mitochondrial protein import. These differences include distinct protein import receptors in plants, different mechanistic operation of the intermembrane protein import system, the location and activity of peptidases, the function of inner-membrane translocases in linking the outer and inner membrane, and the association/regulation of mitochondrial protein import complexes with components of the respiratory chain. Additionally, plant mitochondria share proteins with plastids, i.e. dual-targeted proteins. Also, the developmental and cell-specific nature of mitochondrial biogenesis is an aspect not observed in single-celled systems that is readily apparent in studies in plants. This means that plants provide a valuable model system to study the various regulatory processes associated with protein import and mitochondrial biogenesis. PMID:25324401

  13. Cryogenic loss monitors with FPGA TDC signal processing

    SciTech Connect

    Warner, A.; Wu, J.; /Fermilab

    2011-09-01

    Radiation hard helium gas ionization chambers capable of operating in vacuum at temperatures ranging from 5K to 350K have been designed, fabricated and tested and will be used inside the cryostats at Fermilab's Superconducting Radiofrequency beam test facility. The chamber vessels are made of stainless steel and all materials used including seals are known to be radiation hard and suitable for operation at 5K. The chambers are designed to measure radiation up to 30 kRad/hr with sensitivity of approximately 1.9 pA/(Rad/hr). The signal current is measured with a recycling integrator current-to-frequency converter to achieve a required measurement capability for low current and a wide dynamic range. A novel scheme of using an FPGA-based time-to-digital converter (TDC) to measure time intervals between pulses output from the recycling integrator is employed to ensure a fast beam loss response along with a current measurement resolution better than 10-bit. This paper will describe the results obtained and highlight the processing techniques used.

  14. A new signal processing technique for fiber optic interferometric sensors

    NASA Astrophysics Data System (ADS)

    Fang, Jianxun

    A new signal processing technique for fiber optic interferometric sensors is presented. This technique provides a way to monitor interferometric sensors such that high accuracy is maintained even using relatively inexpensive Fabry-Perot (FP) lasers, as a basis for implementing low-cost, high performance fiber optic sensor systems. Application of this technique in temperature measurement has been demonstrated with a fiber optic Fabry-Perot Interferometer (FFPI) as a sensing head. Good performance of temperature sensor is obtained using a low-quality multimode FP laser, and even better performance is observed with a distributed feedback (DFB) laser diode. The accuracies are measured to be 4.58% for a FP laser and 2.32% for a DFB laser, respectively. However, the unambiguous measurement range is limited to 7°C using a laser diode as a light source emitting at a wavelength of 1.3-?m. Dual wavelength technique is employed to overcome this limitation. The unambiguous dynamic range is extended to 43°C using one 1.3-?m laser diode and one 1.55- ?m laser diode. Further improvement in dynamic range using lasers with a smaller wavelength separation is possible.

  15. Digital signal processing in bio-implantable systems: Design challenges and emerging solutions

    Microsoft Academic Search

    Seetharam Narasimhan; Swarup Bhunia

    2010-01-01

    Implantable systems that monitor biological signals require increasingly complex digital signal processing (DSP) electronics for real-time in-situ analysis and compression of the recorded signals. While it is well-known that such signal processing hardware needs to be implemented under tight area and power constraints for small footprint and increased battery-life, new design requirements emerge with their increasing complexity. Use of nanoscale

  16. Signal Processing and Machine Learning for Intelligent Patient Monitoring

    E-print Network

    Wang, Xiaorui "Ray"

    to predict, estimate, and diagnose, ... #12;Problem Statement: Mind the Gap in Medical Signals Constant Mortality Prediction · Patient specific mortality prediction using physiological measurements · Application

  17. Detection and Processing Techniques of FECG Signal for Fetal Monitoring

    PubMed Central

    2009-01-01

    Fetal electrocardiogram (FECG) signal contains potentially precise information that could assist clinicians in making more appropriate and timely decisions during labor. The ultimate reason for the interest in FECG signal analysis is in clinical diagnosis and biomedical applications. The extraction and detection of the FECG signal from composite abdominal signals with powerful and advance methodologies are becoming very important requirements in fetal monitoring. The purpose of this review paper is to illustrate the various methodologies and developed algorithms on FECG signal detection and analysis to provide efficient and effective ways of understanding the FECG signal and its nature for fetal monitoring. A comparative study has been carried out to show the performance and accuracy of various methods of FECG signal analysis for fetal monitoring. Finally, this paper further focused some of the hardware implementations using electrical signals for monitoring the fetal heart rate. This paper opens up a passage for researchers, physicians, and end users to advocate an excellent understanding of FECG signal and its analysis procedures for fetal heart rate monitoring system. PMID:19495912

  18. Correlation of laser ablation plasma emission with ICP-AES signal intensity

    SciTech Connect

    Fernandez, A.J.; Mao, X.L.; Shannon, M.A. [Lawrence Berkeley Lab., CA (United States)] [and others

    1994-12-31

    Laser ablation offers many favorable characteristics for direct solid sample chemical analysis. However, the technique usually provides poor precision in comparison to solution nebulization. The primary contributor to this imprecision is the irreproducibility of the laser material interaction. This paper describes a technique for monitoring changes in the laser material interaction directly, and using these data to improve inductively coupled atomic emission spectroscopy (ICP-AES). Simultaneous measurements of the spectral emission intensity in the laser-induced plasma (LIP) and the ICP-AES were made under different power density conditions. The LIP spatial profile and excitation temperature was measured. The data from the LIP show a strong correlation with ICP-AES signal intensity. Both emission signals increase linearly with the laser power density (log-log) and show a change in the slope for different spot sizes and laser powers. These results support the occurrence of two different ablation mechanisms, a less efficient interaction dominating at the higher power densities (> 1 GW/cm2) and a more efficient interaction in the lower power density regimes. The benefits of using simultaneous monitoring of the laser induced plasma for chemical analysis by ICP-AES will be discussed.

  19. Analyzing the Homeostasis of Signaling Proteins by a Combination of Western Blot and Fluorescence Correlation Spectroscopy

    PubMed Central

    Chung, Yi-Da; Sinzinger, Michael D.; Bovee-Geurts, Petra; Krause, Marina; Dinkla, Sip; Joosten, Irma; Koopman, Werner J.; Adjobo-Hermans, Merel J.W.; Brock, Roland

    2011-01-01

    The determination of intracellular protein concentrations is a prerequisite for understanding protein interaction networks in systems biology. Today, protein quantification is based either on mass spectrometry, which requires large cell numbers and sophisticated measurement protocols, or on quantitative Western blotting, which requires the expression and purification of a recombinant protein as a reference. Here, we present a method that uses a transiently expressed fluorescent fusion protein of the protein-of-interest as an easily accessible reference in small volumes of crude cell lysates. The concentration of the fusion protein is determined by fluorescence correlation spectroscopy, and this concentration is used to calibrate the intensity of bands on a Western blot. We applied this method to address cellular protein homeostasis by determining the concentrations of the plasma membrane-located transmembrane scaffolding protein LAT and soluble signaling proteins in naïve T cells and transformed T-cell lymphoma (Jurkat) cells (with the latter having nine times the volume of the former). Strikingly, the protein numbers of soluble proteins scaled with the cell volume, whereas that of the transmembrane protein LAT scaled with the membrane surface. This leads to significantly different stoichiometries of signaling proteins in transformed and naïve cells in concentration ranges that may translate directly into differences in complex formation. PMID:22261070

  20. Signal processing and statistical descriptive reanalysis of steady state chute-flow experiments

    NASA Astrophysics Data System (ADS)

    truong, hoan; eckert, nicolas; keylock, chris; naaim, mohamed; bellot, hervé

    2014-05-01

    An accurate knowledge of snow rheology is needed for the mitigation against avalanche hazard. Indeed snow avalanches have a significant impact on the livelihoods and economies of alpine communities. To do so, 60 small-scale in-situ flow experiments were performed with various slopes, temperatures and flow depths. The investigation of these data previously seemed to show the dense flow of dry snow may be composed of two layers; a sheared basal layer made of single snow grains and a less sheared upper layer made of large aggregates. These outcomes were mainly based on the mean velocity profile of the flow and on interpretation in terms of rheological behavior of granular materials and snow microstructure [Pierre G. Rognon et al., 2007]. Here, the main objective remains the same, but the rheological and physical viewpoints are put aside to extract as much information contained in the data as possible various using signal processing methods and descriptive statistics methods as the maximum overlap discrete wavelet transform (MODWT), transfer entropy (TE) and maximum cross-correlation (MCC). Specifically, we aim at the improving the velocity estimations as function of the depth particularly the velocity fluctuations around the mean profile to better document the behavior of dense dry snow flows during a steady and uniform chute regime. The data are composed of pairs of voltage signals (right and left), which makes that the velocity is known indirectly only. The MCC method is classically used to determine the time lag between both signals. Previously, the MCC method that showed the mean velocity profile may be fitted by a simple bilinear function [Pierre G. Rognon et al., 2007], but no interesting temporal dynamics could be highlighted. Hence, a new process method was developed to provide velocity series with much better temporal resolution. The process is mainly made of a MODWT-based denoising method and the choice of window size for correlation. The results prove to be good enough in term of reasonable variability and measurement numbers. A statistical descriptive analysis of the velocity results shows a disagreement with the previous outcomes. Indeed, the clustering method and the empirical probability distribution functions show that the vertical velocity profile may reflect three different behaviors, possibly corresponding to three layers and/or to transient flow layers. These flow layers are located at different heights depending on initial conditions of flow experiments (temperature, slope and depth). Keywords: Maximum cross correlation, MODWT, probability distribution function