Science.gov

Sample records for signal processing correlation

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

    DOEpatents

    Erskine, David J.

    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.

  2. 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.

  3. The EVLA Correlator - Signal Processing for Ultra-Sensitive Astronomy

    NASA Astrophysics Data System (ADS)

    Dewdney, P. E.; Carlson, B. R.

    2000-05-01

    Companion papers by the EVLA team illustrate the power of the EVLA, which can be enabled only by the most powerful, flexible correlator conceived to date. Moreover, since the correlator will be expected to process signals containing interference, it must be robust to radio frequency interference. We propose to build a correlator to process signals from up to 40 antennas in eight independently tunable, 2 GHz wide IF-bands (typically four left and four right polarizations). This will provide the basic continuum sensitivity needed to explore the high red-shift objects of the ``Evolving Universe'' or the weak polarized signals of the ``Magnetic Universe''. High spectral resolution confers the ability to observe very narrow spectral lines or to carry out esoteric planetary radar observations. Large numbers of channels permit searches for highly red-shifted spectral lines over large volumes of the universe at once or simultaneous observations of multiple spectral lines in the ``Obscured Universe''. We expect to be able to provide 16384 channels per baseline that can be flexibly distributed over all the IF-bands or concentrated in very narrow sub-bands. Objects in the ``Transient Universe'', from pulsars to solar bursts can be accomodated by 10 ms integration periods, asynchronous triggering of short observation ``bursts'', and up to 1024 pulsar ``phase bins'' per baseline. Strong signals from astronomical masers, the sun, and interference require spectral dynamic range of >105, which combined with high spectral resolution, will permit the expurgation of interference. These are the most important specifications needed to realize the potential of the EVLA. We expect to be able to meet them, using an innovative correlator architecture.

  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

    SciTech Connect

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

    2006-08-30

    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{approx}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.

  6. The S2 VLBI Correlator: A Correlator for Space VLBI and Geodetic Signal Processing

    NASA Astrophysics Data System (ADS)

    Carlson, B. R.; Dewdney, P. E.; Burgess, T. A.; Casorso, R. V.; Petrachenko, W. T.; Cannon, W. H.

    1999-08-01

    A unique lag-based VLBI correlator system has been developed for the purpose of supporting S2-based space VLBI observations in both the Japanese-led VSOP mission and the Canadian Geodetic VLBI program. The system architecture has been designed so that replication of a small number of modules can be used to construct systems with a wide range of sizes. Optimized for a large correlator, the design is ``station based'' in the sense that as many hardware and software functions as possible are performed before data are replicated and transmitted for baseline (station pair) processing. As well as delay compensation and generation of phase rotation coefficients, station-based functions include autocorrelation, tone extraction, pulsar gating, signal-statistics accumulation, and digital filtering. Doppler-shift correction (fringe stopping) is performed on a baseline basis at each correlator lag so that there are no smearing effects (lag-dependent loss of coherence) or frequency shifts that must otherwise be corrected after correlation. This is a key element that simplifies the baseline processing architecture when high accelerations associated with an orbiting antenna must be considered. Flexible, efficient distribution of data from station-based hardware to baseline-based hardware is accomplished by serializing the wide data paths to 1 Gbit s^-1 signals and using high-speed switches to route the signals to their final destinations where they are deserialized before cross-correlation. This greatly reduces the size, wiring complexity, and cost of the system. The interval between updates of the delay models, integration times, and other important events is typically 10 ms but can be as short as 1 ms. Within this period, delay and fringe model generation is performed using linear hardware synthesizers. The correlator also contains a number of unique signal processing functions that extend its capability beyond a basic VLBI correlator: flexible Local Oscillator frequency switching for bandwidth synthesis; rapid (1 ms) correlator dump intervals (allowing, for example, the study of some single-pulse pulsar characteristics on VLBI baselines) simple but powerful multirate digital signal-processing techniques to allow correlation of signals at different but related sample rates; and a digital ``zoom'' filter for producing very high resolution cross-power spectra. The correlator software, written almost entirely in C, is highly integrated into the system, supports all of the functions mentioned above, and is reconfigurable to support expansion of the correlator. The software schedules the use of hardware resources to enable correlation of multiple observations concurrently and automatically schedules the correlation of observations that require more than the available number of physical playback terminals. There is also substantial precorrelation consistency checking. The delay model is based on CALC for ground-based antennas and NAIF for space-based antennas. Output data are stored in the UVFITS format. The paper describes the design rationale, architecture, and function of the correlator and also provides specifications for the implemented system.

  7. 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

  8. Applications of acousto-optical correlation devices in radar signal processing

    NASA Astrophysics Data System (ADS)

    Xu, Jieping; Yu, Kuanxin

    1989-09-01

    The actual efficiency of acousto-optical correlation devices in radar signal processing was investigated experimentally. As far as centimeter wave band (3GHz) single carrier frequency square pulse radar signals and unmodulated random wave interference is concerned, it measured different pulse widths, different signal-to-noise ratios and, for these periods of time, the height of correlation peaks as well as the size of the correlation gain when there were different pulse widths. When the pulse width was 2.5 micro s, the correlation gain was 30dB. When the pulse width was 0.5 micro s, the correlation gain was 23dB. As far as the correlation peaks of acousto-optical correlation device outputs are concerned, they were all several score mV or higher. It was not necessary to go through any amplification. Rather, it was possible to make use of an oscillascope to directly carry out observations and measurements.

  9. Study of photon correlation techniques for processing of laser velocimeter signals

    NASA Technical Reports Server (NTRS)

    Mayo, W. T., Jr.

    1977-01-01

    The objective was to provide the theory and a system design for a new type of photon counting processor for low level dual scatter laser velocimeter (LV) signals which would be capable of both the first order measurements of mean flow and turbulence intensity and also the second order time statistics: cross correlation auto correlation, and related spectra. A general Poisson process model for low level LV signals and noise which is valid from the photon-resolved regime all the way to the limiting case of nonstationary Gaussian noise was used. Computer simulation algorithms and higher order statistical moment analysis of Poisson processes were derived and applied to the analysis of photon correlation techniques. A system design using a unique dual correlate and subtract frequency discriminator technique is postulated and analyzed. Expectation analysis indicates that the objective measurements are feasible.

  10. The triple correlation - Applications in astronomical speckle interferometry and in signal processing

    NASA Astrophysics Data System (ADS)

    Wirnitzer, B.

    The concept of the triple correlation in image and signal processing is presented. Its advantages are illustrated using the example of imaging through the earth's turbulent atmosphere. Problem-oriented formulas for this example are given. Various other applications of the triple correlation and the bispectral Fourier analog are discussed, including the Gamos triple intensity interferometer, bispectral Satos velocity measurements, bispectral holography, bispectral detection of nonlinearities, shift-invariant imaging in extremely weak light intensity, and higher-order spectrograms of musical tones.

  11. Lee filtered burst selecting in the photon correlation LDA signal processing

    NASA Astrophysics Data System (ADS)

    Vámos, Lénárd; Jani, Péter

    2008-04-01

    The photon correlation Laser Doppler Anemometers were developed to measure the flow velocity also in the nanometer particle range. An LDA signal processing method has been developed for dividing the raw data line of photon correlation LDA into shorter parts corresponding to single particle transit (burst). The commonly used Lee filter was applied with some modification and an intelligent burst finding algorithm was developed. By this way the LDA system was adapted for single particle counting. The complete simulation algorithm gives an opportunity for discussing the burst selecting and so the particle counting efficiency as a function of the SNR. Size estimation from the burst size was discussed and compared to the model-based signal processing technique. The minimum detectable particle size was estimated.

  12. Modified Multilook Cross Correlation technique for Doppler centroid estimation in SAR image signal processing

    NASA Astrophysics Data System (ADS)

    Bee Cheng, Sew

    Synthetic Aperture Radar (SAR) is one of the widely used remote sensing sensors which produces high resolution image by using advance signal processing technique. SAR managed to operate in all sorts of weather and cover wide range of area. To produce a high-quality image, accurate parameters such as Doppler centroid are required for precise SAR signal processing. In the azimuth matched filtering of SAR signal processing, Doppler centroid is an important azimuth parameter that helps to focus the image pixels. Doppler centroid has always been overlooked during SAR signal processing. It is due to the fact that estimation of Doppler centroid involved complicated calculation and increased computational load. Therefore, researcher used to apply only the approximate Doppler value which is not precise and cause defocus effort in the generated SAR image. In this study, several conventional Doppler centroid estimation algorithms are reviewed and developed using Matlab software program to extract the Doppler parameter from received SAR data, namely Spectrum Fit Algorithm, Wavelength Diversity Algorithm (WDA), Multilook Cross Correlation Algorithm (MLCC), and Multilook Beat Frequency Algorithm (MLBF). Two sets of SAR data are employed to evaluate the performance of each estimator, i.e. simulated point target data and RADARSAT-1 Vancouver scene raw data. These experiments gave a sense of accuracy for the estimated results together with computational time consumption. Point target is simulated to generate ideal case SAR data with pre-defined SAR system parameters.

  13. 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.

  14. Cross-Correlation: An fMRI Signal-Processing Strategy

    PubMed Central

    Hyde, James S.; Jesmanowicz, Andrzej

    2011-01-01

    The discovery of functional MRI (fMRI), with the first papers appearing in 1992, gave rise to new categories of data that drove the development of new signal-processing strategies. Workers in the field were confronted with image time courses, which could be reshuffled to form pixel time courses. The waveform in an active pixel time-course was determined not only by the task sequence but also by the hemodynamic response function. Reference waveforms could be cross-correlated with pixel time courses to form an array of cross-correlation coefficients. From this array of numbers, colorized images could be created and overlaid on anatomical images. An early paper from the authors’ laboratory is extensively reviewed here (Bandettini et al. 1993. Magn. Reson. Med. 30:161–173). That work was carried out using the vocabulary of vector algebra. Cross-correlation methodology was central to the discovery of functional connectivity MRI (fcMRI) by Biswal et al. (1995. Magn. Reson. Med. 34:537–541). In this method, a whole volume time course of images is collected while the brain is nominally at rest and connectivity is studied by cross-correlation of pixel time courses. PMID:22051223

  15. Non-contact strip speed measurement using electrostatic sensing and correlation signal-processing techniques

    NASA Astrophysics Data System (ADS)

    Yan, Yong; Rodrigues, Shaun J.; Xie, Zizhuo

    2011-07-01

    Accurate and reliable strip speed measurement is desirable in many manufacturing industries for both monitoring and control purposes. This paper presents the recent development in non-contact measurement of strip speed using electrostatic sensors in combination with correlation signal-processing techniques. A pair of metal electrodes is used to obtain signals from the moving strip. The speed of the strip is then determined from the known fixed spacing between the electrodes and the time delay between the two signals. Experimental tests were conducted on a motorized strip speed test rig under a range of conditions. An optical tachometer was used as a reference instrument to gauge the accuracy of the strip speed measurement system. The system design considerations, advantages and limitations are addressed. Results demonstrate that the system is capable of measuring strip speed robustly with a relative error not greater than ±1.8% and a repeatability of 2.5% over the speed range of 0.8 to 10 m s-1.

  16. Signal processing

    NASA Astrophysics Data System (ADS)

    Easton, Roger L., Jr.

    1990-01-01

    Space-variant coordinate transformations may be profitably applied to many signal processing problems; for example, image convolutions are often computed by multiplying the Fourier transforms of the images rather than by direct methods (i.e., shift, multiply, and add). Some signal processing algorithms are presently under study that operate on projection-based representations of the function. The best known projection representation is the Radon transform (Radon, 1917) (Easton, 1986), which is the mathematical basis for several medical imaging techniques, e.g., medical computed tomography (CT or CAT) and nuclear magnetic resonance imaging (MRI). The Radon transform reduces the 2-D data set to a series of 1-D line integral projections at each azimuth.

  17. Signal processing

    NASA Astrophysics Data System (ADS)

    Norman, David M.

    The application of signal processing technology to conventional weapons systems can lower operator workloads and enhance kill probabilities, while automating wide-area surveillance, target search and classification, target tracking, and aimpoint selection. Immediate opportunities exist for automatic target cueing in underwater and over-the-horizon targeting, as well as for airborne multiple-target fire control. By embedding the transit/receive electronics into conformal aircraft sensor arrays, a 'smart' skin can be created. Electronically scanned phased arrays can be used to yield accurate azimuthal and elevation positions while nullifying EW threats. Attention is given to major development thrusts in algorithm design.

  18. Software Radar signal processing

    NASA Astrophysics Data System (ADS)

    Grydeland, T.; Lind, F. D.; Erickson, P. J.; Holt, J. M.

    2005-01-01

    Software infrastructure is a growing part of modern radio science systems. As part of developing a generic infrastructure for implementing Software Radar systems, we have developed a set of reusable signal processing components. These components are generic software-based implementations for use on general purpose computing systems. The components allow for the implementation of signal processing chains for radio frequency signal reception, correlation-based data processing, and cross-correlation-based interferometry. The components have been used to implement the signal processing necessary for incoherent scatter radar signal reception and processing as part of the latest version of the Millstone Hill Data Acquisition System (MIDAS-W). Several hardware realizations with varying capabilities have been created, and these have been used successfully with different radars. We discuss the signal processing components in detail, describe the software patterns in which they are used, and show example data from the Millstone Hill, EISCAT Svalbard, and SOUSY Svalbard radars.

  19. Improved sensitivity of intensity-modulated spectroscopy using correlative signal processing.

    PubMed

    Ataie, Vahid; Papen, George

    2011-02-01

    Frequency-modulation (FM) spectroscopy is known to be a sensitive spectroscopic technique capable of accurately measuring the frequency dependence of the absorption and index of refraction of narrow spectral features. The absorption and index of refraction are coupled by a form of the Kramers-Kronig (K-K) relations, and both components provide information about the spectral feature. In this Letter, we propose a processing technique based on fitting the data to a complex signal model derived from the K-K relation. By using this complex constraint and only processing a single quadrature, our model predicts significant improvement in the minimum detectable absorption compared with conventional FM spectroscopy. PMID:21283185

  20. Advanced signal processing

    NASA Astrophysics Data System (ADS)

    Creasey, D. J.

    1985-12-01

    A collection of papers on advanced signal processing in radar, sonar, and communications is presented. The topics addressed include: transmitter aerials, high-power amplifier design for active sonar, radar transmitters, receiver array technology for sonar, new underwater acoustic detectors, diversity techniques in communications receivers, GaAs IC amplifiers for radar and communication receivers, integrated optical techniques for acoustooptic receivers, logarithmic receivers, CCD processors for sonar, acoustooptic correlators, designing in silicon, very high performance integrated circuits, and digital filters. Also discussed are: display types, scan converters in sonar, display ergonomics, simulators, high throughput sonar processors, optical fiber systems for signal processing, satellite communications, VLSI array processor for image and signal processing, ADA, future of cryogenic devices for signal processing applications, advanced image understanding, and VLSI architectures for real-time image processing.

  1. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2006-06-01

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

  3. Optical signal processing

    NASA Astrophysics Data System (ADS)

    Dorey, J.

    The theoretical principles, design, and application of optical signal-processing devices are examined in a general review and illustrated with diagrams, with an emphasis on their use in radar, sonar, and lidar systems. Topics discussed include Fourier and Fresnel transforms, coherent-light computer techniques (film, electrooptical acoustooptical, and hybrid recording methods; processing of SLAR data; the convolution theorem in coherent optics; and the use of spatial or temporal integration in acoustooptic components), and incoherent-light techniques (the Mertz setup, mask correlation, elimination of spurious components, localization and imaging of EM or IR sources by a mobile-mask technique, and processing of vectors and matrices). The need to compress the output data of high-speed optical processors by detection, thresholding, or (possibly nonlinear) block-recognition functions related to extraction and decision-making processes is stressed, since otherwise digital processing of the output causes a bottleneck effect which negates the speed advantages of optical systems over all-digital solutions.

  4. Signal Processing, Analysis, & Display

    SciTech Connect

    Lager, Darrell; Azevado, Stephen

    1986-06-01

    SIG is a general-purpose signal processing, analysis, and display program. Its main purpose is to perform manipulations on time- and frequency-domain signals. However, it has been designed to ultimately accommodate other representations for data such as multiplexed signals and complex matrices. Two user interfaces are provided in SIG - a menu mode for the unfamiliar user and a command mode for more experienced users. In both modes errors are detected as early as possible and are indicated by friendly, meaningful messages. An on-line HELP package is also included. A variety of operations can be performed on time- and frequency-domain signals including operations on the samples of a signal, operations on the entire signal, and operations on two or more signals. Signal processing operations that can be performed are digital filtering (median, Bessel, Butterworth, and Chebychev), ensemble average, resample, auto and cross spectral density, transfer function and impulse response, trend removal, convolution, Fourier transform and inverse window functions (Hamming, Kaiser-Bessel), simulation (ramp, sine, pulsetrain, random), and read/write signals. User definable signal processing algorithms are also featured. SIG has many options including multiple commands per line, command files with arguments,commenting lines, defining commands, and automatic execution for each item in a repeat sequence. Graphical operations on signals and spectra include: x-y plots of time signals; real, imaginary, magnitude, and phase plots of spectra; scaling of spectra for continuous or discrete domain; cursor zoom; families of curves; and multiple viewports.

  5. Signal Processing, Analysis, & Display

    Energy Science and Technology Software Center (ESTSC)

    1986-06-01

    SIG is a general-purpose signal processing, analysis, and display program. Its main purpose is to perform manipulations on time- and frequency-domain signals. However, it has been designed to ultimately accommodate other representations for data such as multiplexed signals and complex matrices. Two user interfaces are provided in SIG - a menu mode for the unfamiliar user and a command mode for more experienced users. In both modes errors are detected as early as possible andmore » are indicated by friendly, meaningful messages. An on-line HELP package is also included. A variety of operations can be performed on time- and frequency-domain signals including operations on the samples of a signal, operations on the entire signal, and operations on two or more signals. Signal processing operations that can be performed are digital filtering (median, Bessel, Butterworth, and Chebychev), ensemble average, resample, auto and cross spectral density, transfer function and impulse response, trend removal, convolution, Fourier transform and inverse window functions (Hamming, Kaiser-Bessel), simulation (ramp, sine, pulsetrain, random), and read/write signals. User definable signal processing algorithms are also featured. SIG has many options including multiple commands per line, command files with arguments,commenting lines, defining commands, and automatic execution for each item in a repeat sequence. Graphical operations on signals and spectra include: x-y plots of time signals; real, imaginary, magnitude, and phase plots of spectra; scaling of spectra for continuous or discrete domain; cursor zoom; families of curves; and multiple viewports.« less

  6. High-resolution optical refractometer based on a long-period grating Michelson interferometer using a cross-correlation signal-processing method

    NASA Astrophysics Data System (ADS)

    Zhou, Xinlei; Chen, Ke; Mao, Xuefeng; Peng, Wei; Yu, Qingxu

    2015-12-01

    We report a high-resolution optical refractometer based on the long-period grating Michelson interferometer. The interferometer phase shift depends on the refractive index that surrounds the fiber probe. A cross-correlation signal-processing method is used to demodulate the interferometer phase shift. Experimental results show that a resolution of 310-6 refractive index unit (RIU) can be obtained using this cross-correlation signal processing method. In addition, a measurement sensitivity up to 3103 deg/RIU is showed as the surrounding refractive index changing from 1.33 to 1.42. Such high-resolution and low-cost optical refractometers would find more applications in chemical or biochemical sensing fields.

  7. 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.

  8. Microwave photonic signal processing.

    PubMed

    Minasian, R A; Chan, E H W; Yi, X

    2013-09-23

    Photonic signal processing offers the advantages of large time-bandwidth capabilities to overcome inherent electronic limitations. In-fibre signal processors are inherently compatible with fibre optic microwave systems that can integrate with wireless antennas, and can provide connectivity with in-built signal conditioning and electromagnetic interference immunity. Recent methods in wideband and adaptive signal processing, which address the challenge of realising programmable microwave photonic phase shifters and true-time delay elements for phased array beamforming; ultra-wideband Hilbert transformers; single passband, widely tunable, and switchable microwave photonic filters; and ultra-wideband microwave photonic mixers, are described. In addition, a new microwave photonic mixer structure is presented, which is based on using the inherent frequency selectivity of the stimulated Brillouin scattering loss spectrum to suppress the carrier of a dual-phase modulated optical signal. Results for the new microwave photonic mixer demonstrate an extremely wide bandwidth operation of 0.2 to 20 GHz and a large conversion efficiency improvement compared to the conventional microwave photonic mixer. PMID:24104178

  9. 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.

  10. Telemetry Ranging: Signal Processing

    NASA Astrophysics Data System (ADS)

    Hamkins, J.; Kinman, P.; Xie, H.; Vilnrotter, V.; Dolinar, S.

    2016-02-01

    This article describes the details of the signal processing used in a telemetry ranging system in which timing information is extracted from the downlink telemetry signal in order to compute spacecraft range. A previous article describes telemetry ranging concepts and architecture, which are a slight variation of a scheme published earlier. As in that earlier work, the telemetry ranging concept eliminates the need for a dedicated downlink ranging signal to communicate the necessary timing information. The present article describes the operation and performance of the major receiver functions on the spacecraft and the ground --- many of which are standard tracking loops already in use in JPL's flight and ground radios --- and how they can be used to provide the relevant information for making a range measurement. It also describes the implementation of these functions in software, and performance of an end-to-end software simulation of the telemetry ranging system.

  11. Digital signal processing

    NASA Astrophysics Data System (ADS)

    Meyer, G.

    The theory, realization techniques, and applications of digital filtering are surveyed, with an emphasis on the development of software, in a handbook for advanced students of electrical and electronic engineering and practicing development engineers. The foundations of the theory of discrete signals and systems are introduced. The design of one-dimensional linear systems is discussed, and the techniques are expanded to the treatment of two-dimensional discrete and multidimensional analog systems. Numerical systems, quantification and limitation, and the characteristics of particular signal-processing devices are considered in a section on design realization. An appendix contains definitions of the basic mathematical concepts, derivations and proofs, and tables of integration and differentiation formulas.

  12. Signal and Image Processing Operations

    Energy Science and Technology Software Center (ESTSC)

    1995-05-10

    VIEW is a software system for processing arbitrary multidimensional signals. It provides facilities for numerical operations, signal displays, and signal databasing. The major emphasis of the system is on the processing of time-sequences and multidimensional images. The system is designed to be both portable and extensible. It runs currently on UNIX systems, primarily SUN workstations.

  13. Signal processing in SETI

    NASA Technical Reports Server (NTRS)

    Cullers, D. K.; Linscott, I. R.; Oliver, B. M.

    1985-01-01

    It is believed that the Galaxy might contain ten billion potential life sites. In view of the physical inaccessibility of extraterrestrial life on account of the vast distances involved, a logical first step in a search for extraterrestrial intelligence (SETI) appears to be an attempt to detect signals already being radiated. The characteristics of the signals to be expected are discussed together with the search strategy of a NASA program. It is pointed out that all presently planned searches will use existing radio-astronomy antennas. If no extraterrestrial intelligence signals are discovered, society will have to decide whether SETI justifies a dedicated facility of much greater collecting area. Attention is given to a multichannel spectrum analyzer, CW signal detection, pulse detection, the pattern detector, and details of SETI system operation.

  14. 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.

  15. Digital signal processing the Tevatron BPM signals

    SciTech Connect

    Cancelo, G.; James, E.; Wolbers, S.; /Fermilab

    2005-05-01

    The Beam Position Monitor (TeV BPM) readout system at Fermilab's Tevatron has been updated and is currently being commissioned. The new BPMs use new analog and digital hardware to achieve better beam position measurement resolution. The new system reads signals from both ends of the existing directional stripline pickups to provide simultaneous proton and antiproton measurements. The signals provided by the two ends of the BPM pickups are processed by analog band-pass filters and sampled by 14-bit ADCs at 74.3MHz. A crucial part of this work has been the design of digital filters that process the signal. This paper describes the digital processing and estimation techniques used to optimize the beam position measurement. The BPM electronics must operate in narrow-band and wide-band modes to enable measurements of closed-orbit and turn-by-turn positions. The filtering and timing conditions of the signals are tuned accordingly for the operational modes. The analysis and the optimized result for each mode are presented.

  16. SIG. Signal Processing, Analysis, & Display

    SciTech Connect

    Hernandez, J.; Lager, D.; Azevedo, S.

    1992-01-22

    SIG is a general-purpose signal processing, analysis, and display program. Its main purpose is to perform manipulations on time and frequency-domain signals. However, it has been designed to ultimately accommodate other representations for data such as multiplexed signals and complex matrices. Two user interfaces are provided in SIG; a menu mode for the unfamiliar user and a command mode for more experienced users. In both modes errors are detected as early as possible and are indicated by friendly, meaningful messages. An on-line HELP package is also included. A variety of operations can be performed on time and frequency-domain signals including operations on the samples of a signal, operations on the entire signal, and operations on two or more signals. Signal processing operations that can be performed are digital filtering (median, Bessel, Butterworth, and Chebychev), ensemble average, resample, auto and cross spectral density, transfer function and impulse response, trend removal, convolution, Fourier transform and inverse window functions (Hamming, Kaiser-Bessel), simulation (ramp, sine, pulsetrain, random), and read/write signals. User definable signal processing algorithms are also featured. SIG has many options including multiple commands per line, command files with arguments, commenting lines, defining commands, and automatic execution for each item in a `repeat` sequence. Graphical operations on signals and spectra include: x-y plots of time signals; real, imaginary, magnitude, and phase plots of spectra; scaling of spectra for continuous or discrete domain; cursor zoom; families of curves; and multiple viewports.

  17. SIG. Signal Processing, Analysis, & Display

    SciTech Connect

    Hernandez, J.; Lager, D.; Azevedo, S.

    1992-01-22

    SIG is a general-purpose signal processing, analysis, and display program. Its main purpose is to perform manipulations on time- and frequency-domain signals. However, it has been designed to ultimately accommodate other representations for data such as multiplexed signals and complex matrices. Two user interfaces are provided in SIG - a menu mode for the unfamiliar user and a command mode for more experienced users. In both modes errors are detected as early as possible and are indicated by friendly, meaningful messages. An on-line HELP package is also included. A variety of operations can be performed on time- and frequency-domain signals including operations on the samples of a signal, operations on the entire signal, and operations on two or more signals. Signal processing operations that can be performed are digital filtering (median, Bessel, Butterworth, and Chebychev), ensemble average, resample, auto and cross spectral density, transfer function and impulse response, trend removal, convolution, Fourier transform and inverse window functions (Hamming, Kaiser-Bessel), simulation (ramp, sine, pulsetrain, random), and read/write signals. User definable signal processing algorithms are also featured. SIG has many options including multiple commands per line, command files with arguments,commenting lines, defining commands, and automatic execution for each item in a repeat sequence. Graphical operations on signals and spectra include: x-y plots of time signals; real, imaginary, magnitude, and phase plots of spectra; scaling of spectra for continuous or discrete domain; cursor zoom; families of curves; and multiple viewports.

  18. SIG. Signal Processing, Analysis, & Display

    SciTech Connect

    Hernandez, J.; Lager, D.; Azevedo, S.

    1992-01-22

    SIG is a general-purpose signal processing, analysis, and display program. Its main purpose is to perform manipulations on time-and frequency-domain signals. However, it has been designed to ultimately accommodate other representations for data such as multiplexed signals and complex matrices. Two user interfaces are provided in SIG - a menu mode for the unfamiliar user and a command mode for more experienced users. In both modes errors are detected as early as possible and are indicated by friendly, meaningful messages. An on-line HELP package is also included. A variety of operations can be performed on time and frequency-domain signals including operations on the samples of a signal, operations on the entire signal, and operations on two or more signals. Signal processing operations that can be performed are digital filtering (median, Bessel, Butterworth, and Chebychev), ensemble average, resample, auto and cross spectral density, transfer function and impulse response, trend removal, convolution, Fourier transform and inverse window functions (Hamming, Kaiser-Bessel), simulation (ramp, sine, pulsetrain, random), and read/write signals. User definable signal processing algorithms are also featured. SIG has many options including multiple commands per line, command files with arguments, commenting lines, defining commands, and automatic execution for each item in a repeat sequence. Graphical operations on signals and spectra include: x-y plots of time signals; real, imaginary, magnitude, and phase plots of spectra; scaling of spectra for continuous or discrete domain; cursor zoom; families of curves; and multiple viewports.

  19. Nonlinear Transfer of Signal and Noise Correlations in Cortical Networks

    PubMed Central

    Lyamzin, Dmitry R.; Barnes, Samuel J.; Donato, Roberta; Garcia-Lazaro, Jose A.; Keck, Tara

    2015-01-01

    Signal and noise correlations, a prominent feature of cortical activity, reflect the structure and function of networks during sensory processing. However, in addition to reflecting network properties, correlations are also shaped by intrinsic neuronal mechanisms. Here we show that spike threshold transforms correlations by creating nonlinear interactions between signal and noise inputs; even when input noise correlation is constant, spiking noise correlation varies with both the strength and correlation of signal inputs. We characterize these effects systematically in vitro in mice and demonstrate their impact on sensory processing in vivo in gerbils. We also find that the effects of nonlinear correlation transfer on cortical responses are stronger in the synchronized state than in the desynchronized state, and show that they can be reproduced and understood in a model with a simple threshold nonlinearity. Since these effects arise from an intrinsic neuronal property, they are likely to be present across sensory systems and, thus, our results are a critical step toward a general understanding of how correlated spiking relates to the structure and function of cortical networks. PMID:26019325

  20. 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.

  1. Signal processing for semiconductor detectors

    SciTech Connect

    Goulding, F.S.; Landis, D.A.

    1982-02-01

    A balanced perspective is provided on the processing of signals produced by semiconductor detectors. The general problems of pulse shaping to optimize resolution with constraints imposed by noise, counting rate and rise time fluctuations are discussed.

  2. [Signal processing in contour implants].

    PubMed

    Ormezzano, Y; Deleurme, C; Vormès, E; Frachet, B

    1990-01-01

    Signal processing by cochlear implants is aimed at transmitting all the acoustic information carried by the human voice, whether in its semantic, esthetic or affective aspects, as an electrical signal. The "translating" approach, which encodes the signal according to the characteristics of the sounds, can only be ideally used in multiple-canal implants. On the contrary, our experience with various single-canal prostheses shows that our patients choose one of these according to the comfort of the signal and to its reliability rather than to the complexity of signal processing: all prostheses produce approximately the same results, whatever the method implemented. The contour implant allows an easy, effective and well-tolerated fitting at low costs. PMID:2256623

  3. Signal processor for processing ultrasonic receiver signals

    DOEpatents

    Fasching, George E.

    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.

  4. Signal processing in photoacoustic detection of phase transitions by means of the autospectra correlation-based method: Evaluation with ceramic BaTiO3

    NASA Astrophysics Data System (ADS)

    Meja-Uriarte, E. V.; Navarrete, M.; Villagrn-Muniz, M.

    2004-09-01

    This work describes a simple numerical procedure which, when applied to digitally recorded photoacoustic (PA) signals, allows the construction of thermal profiles (rS,drS/dT) to determine: the transition order, the phase transition temperature (Tc), and the phase transformation temperature range (?T), on samples, which undergo low-high transitions. During continuous heating of the sample, the ultrasonic signal was generated using a pulsed laser beam incident on a surface and detected on the opposite surface of the sample using a long quartz bar attached to a piezoelectric sensor. The thermal profile, rS, is built from a sequence of the ordinary correlation coefficients ri associated with an interval of temperature. The ri coefficients are calculated from amplitude spectra pairs. The amplitude spectra are obtained via fast Fourier transforms from original PA records. This procedure is applied on samples of bulk ceramic BaTiO3 to obtain their thermal behavior. The PA signal and temperature sample were registered every 0.2. The samples were heated from room temperature to 137 C at a rate of 0.1 C min-1. The thermal profile rS shows the entire thermal history including the structural phase transition from tetragonal to cubic (T-C), which appears as a jump on the graph within an uncertainty of 2%. The drS/dT profile shows that the T-C phase transformation occurs over a range of temperatures. The results are in agreement with those reported in the literature.

  5. VLSI mixed signal processing system

    NASA Technical Reports Server (NTRS)

    Alvarez, A.; Premkumar, A. B.

    1993-01-01

    An economical and efficient VLSI implementation of a mixed signal processing system (MSP) is presented in this paper. The MSP concept is investigated and the functional blocks of the proposed MSP are described. The requirements of each of the blocks are discussed in detail. A sample application using active acoustic cancellation technique is described to demonstrate the power of the MSP approach.

  6. Signal processing of anthropometric data

    NASA Astrophysics Data System (ADS)

    Zimmermann, W. J.

    1983-09-01

    The Anthropometric Measurements Laboratory has accumulated a large body of data from a number of previous experiments. The data is very noisy, therefore it requires the application of some signal processing schemes. Moreover, it was not regarded as time series measurements but as positional information; hence, the data is stored as coordinate points as defined by the motion of the human body. The accumulated data defines two groups or classes. Some of the data was collected from an experiment designed to measure the flexibility of the limbs, referred to as radial movement. The remaining data was collected from experiments designed to determine the surface of the reach envelope. An interactive signal processing package was designed and implemented. Since the data does not include time this package does not include a time series element. Presently the results is restricted to processing data obtained from those experiments designed to measure flexibility.

  7. System for monitoring non-coincident, nonstationary process signals

    DOEpatents

    Gross, Kenneth C.; Wegerich, Stephan W.

    2005-01-04

    An improved system for monitoring non-coincident, non-stationary, process signals. The mean, variance, and length of a reference signal is defined by an automated system, followed by the identification of the leading and falling edges of a monitored signal and the length of the monitored signal. The monitored signal is compared to the reference signal, and the monitored signal is resampled in accordance with the reference signal. The reference signal is then correlated with the resampled monitored signal such that the reference signal and the resampled monitored signal are coincident in time with each other. The resampled monitored signal is then compared to the reference signal to determine whether the resampled monitored signal is within a set of predesignated operating conditions.

  8. Acoustic Signal Processing in Photorefractive Optical Systems.

    NASA Astrophysics Data System (ADS)

    Zhou, Gan

    This thesis discusses applications of the photorefractive effect in the context of acoustic signal processing. The devices and systems presented here illustrate the ideas and optical principles involved in holographic processing of acoustic information. The interest in optical processing stems from the similarities between holographic optical systems and contemporary models for massively parallel computation, in particular, neural networks. An initial step in acoustic processing is the transformation of acoustic signals into relevant optical forms. A fiber-optic transducer with photorefractive readout transforms acoustic signals into optical images corresponding to their short-time spectrum. The device analyzes complex sound signals and interfaces them with conventional optical correlators. The transducer consists of 130 multimode optical fibers sampling the spectral range of 100 Hz to 5 kHz logarithmically. A physical model of the human cochlea can help us understand some characteristics of human acoustic transduction and signal representation. We construct a life-sized cochlear model using elastic membranes coupled with two fluid-filled chambers, and use a photorefractive novelty filter to investigate its response. The detection sensitivity is determined to be 0.3 angstroms per root Hz at 2 kHz. Qualitative agreement is found between the model response and physiological data. Delay lines map time-domain signals into space -domain and permit holographic processing of temporal information. A parallel optical delay line using dynamic beam coupling in a rotating photorefractive crystal is presented. We experimentally demonstrate a 64 channel device with 0.5 seconds of time-delay and 167 Hz bandwidth. Acoustic signal recognition is described in a photorefractive system implementing the time-delay neural network model. The system consists of a photorefractive optical delay-line and a holographic correlator programmed in a LiNbO_3 crystal. We demonstrate the recognition of synthesized chirps as well as spoken words. A photorefractive ring resonator containing an optical delay line can learn temporal information through self-organization. We experimentally investigate a system that learns by itself and picks out the most-frequently -presented signals from the input. We also give results demonstrating the separation of two orthogonal temporal signals into two competing ring resonators.

  9. Signal processing in eukaryotic chemotaxis

    NASA Astrophysics Data System (ADS)

    Segota, Igor; Rachakonda, Archana; Franck, Carl

    2013-03-01

    Unlike inanimate condensed matter, living cells depend upon the detection of chemical signals for their existence. First, we experimentally determined the chemotaxis response of eukaryotic Dictyostelium cells to static folic acid gradients and show that they can respond to gradients as shallow as 0.2% across the cell body. Second, using Shannon's information theory, we showed that the information cells receive about the gradient exceeds the theoretically predicted information at the receptor-ligand binding step, resulting in the violation of the data processing inequality. Finally, we analyzed how eukaryotic cells can affect the gradient signals by secreting enzymes that degrade the signal. We analyzed this effect with a focus on a well described Dictyostelium cAMP chemotaxis system where cAMP signals are affected by an extracellular cAMP phosphodiesterase (PDE) and its inhibitor (PDI). Using a reaction-diffusion model of this set of interactions in the extracellular space, we show that cells can effectively sense much steeper chemical gradients than naively expected (up to a factor of 12). We also found that the rough estimates of experimental PDE and PDI secretion rates are close to the optimal values for gradient sensing as predicted by our model.

  10. Nuclear sensor signal processing circuit

    DOEpatents

    Kallenbach, Gene A.; Noda, Frank T.; Mitchell, Dean J.; Etzkin, Joshua L.

    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.

  11. Adaptive techniques for signal processing in communications

    NASA Astrophysics Data System (ADS)

    Claasen, T. A. C. M.; Mecklenbraeuker, W. F. G.

    1985-11-01

    The basic characteristics of adaptive signal processing techniques are described. Consideration is given to adaptive equalization; adaptive echo cancellation; adaptive noise cancellation; and linear predictive coding. The principle classes of signal processing systems are discussed, including: adaptive systems identification systems; signal estimation systems; and signal correction systems. The main components of adaptive processing routines are also described, with attention given to a priori knowledge; quality criteria; adaptive signal processing algorithms; and gradients methods. Block diagrams of the different adaptive processing systems are provided.

  12. 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.

  13. Signal Processing Expert Code (SPEC)

    SciTech Connect

    Ames, H.S.

    1985-12-01

    The purpose of this paper is to describe a prototype expert system called SPEC which was developed to demonstrate the utility of providing an intelligent interface for users of SIG, a general purpose signal processing code. The expert system is written in NIL, runs on a VAX 11/750 and consists of a backward chaining inference engine and an English-like parser. The inference engine uses knowledge encoded as rules about the formats of SIG commands and about how to perform frequency analyses using SIG. The system demonstrated that expert system can be used to control existing codes.

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

    SciTech Connect

    Seevinck, M. P.

    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.

  15. Signal processing for distributed sensor concept: DISCO

    NASA Astrophysics Data System (ADS)

    Rafailov, Michael K.

    2007-04-01

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

  16. VLSI systems design for digital signal processing. Volume 1 - Signal processing and signal processors

    NASA Astrophysics Data System (ADS)

    Bowen, B. A.; Brown, W. R.

    This book is concerned with the design of digital signal processing systems which utilize VLSI (Very Large Scale Integration) components. The presented material is intended for use by electrical engineers at the senior undergraduate or introductory graduate level. It is the purpose of this volume to present an overview of the important elements of background theory, processing techniques, and hardware evolution. Digital signals are considered along with linear systems and digital filters, taking into account the transform analysis of deterministic signals, a statistical signal model, time domain representations of discrete-time linear systems, and digital filter design techniques and implementation issues. Attention is given to aspects of detection and estimation, digital signal processing algorithms and techniques, issues which must be resolved in a processor design methodology, the fundamental concepts of high performance processing in terms of two early super computers, and the extension of these concepts to more recent processors.

  17. A correlated empirical mode decomposition method for partial discharge signal denoising

    NASA Astrophysics Data System (ADS)

    Tang, Ya-Wen; Tai, Cheng-Chi; Su, Ching-Chau; Chen, Chien-Yi; Chen, Jiann-Fuh

    2010-08-01

    Empirical mode decomposition (EMD) is a signal processing method used to extract intrinsic mode functions (IMFs) from a complicated signal. For a measurement with two or more correlated inputs, finding and capturing the correlated IMFs is a critical challenge that must be confronted. In this paper, a new correlated EMD method is proposed. The cross-correlation method was employed to determine dependence between the IMFs. To verify feasibility, an analysis was performed on simulated test signals and practically measured partial discharge (PD) signals collected from several acoustic emission sensors. At the surface of the gas-insulated transmission line, the PD signal arrived at the AE sensors with varying time delays and unique mechanism vibrations. Following an abnormal detection using the standard-deviation variation, the PD signal and the background signal of each sensor were applied using the correlated-EMD method. A twice correlated-EMD calculation was applied to the signals for the purpose of noise elimination. In addition, the unwanted low-frequency IMFs induced from the EMD calculations were excluded. The experimental results reveal that the correlated-EMD method performs well on both selecting and denoising the correlated IMFs. The results further provide analysis on correlated-input applications with a precise signal completely induced from the disturbance.

  18. Seismic signal processing on heterogeneous supercomputers

    NASA Astrophysics Data System (ADS)

    Gokhberg, Alexey; Ermert, Laura; Fichtner, Andreas

    2015-04-01

    The processing of seismic signals - including the correlation of massive ambient noise data sets - represents an important part of a wide range of seismological applications. It is characterized by large data volumes as well as high computational input/output intensity. Development of efficient approaches towards seismic signal processing on emerging high performance computing systems is therefore essential. Heterogeneous supercomputing systems introduced in the recent years provide numerous computing nodes interconnected via high throughput networks, every node containing a mix of processing elements of different architectures, like several sequential processor cores and one or a few graphical processing units (GPU) serving as accelerators. A typical representative of such computing systems is "Piz Daint", a supercomputer of the Cray XC 30 family operated by the Swiss National Supercomputing Center (CSCS), which we used in this research. Heterogeneous supercomputers provide an opportunity for manifold application performance increase and are more energy-efficient, however they have much higher hardware complexity and are therefore much more difficult to program. The programming effort may be substantially reduced by the introduction of modular libraries of software components that can be reused for a wide class of seismology applications. The ultimate goal of this research is design of a prototype for such library suitable for implementing various seismic signal processing applications on heterogeneous systems. As a representative use case we have chosen an ambient noise correlation application. Ambient noise interferometry has developed into one of the most powerful tools to image and monitor the Earth's interior. Future applications will require the extraction of increasingly small details from noise recordings. To meet this demand, more advanced correlation techniques combined with very large data volumes are needed. This poses new computational problems that require dedicated HPC solutions. The chosen application is using a wide range of common signal processing methods, which include various IIR filter designs, amplitude and phase correlation, computing the analytic signal, and discrete Fourier transforms. Furthermore, various processing methods specific for seismology, like rotation of seismic traces, are used. Efficient implementation of all these methods on the GPU-accelerated systems represents several challenges. In particular, it requires a careful distribution of work between the sequential processors and accelerators. Furthermore, since the application is designed to process very large volumes of data, special attention had to be paid to the efficient use of the available memory and networking hardware resources in order to reduce intensity of data input and output. In our contribution we will explain the software architecture as well as principal engineering decisions used to address these challenges. We will also describe the programming model based on C++ and CUDA that we used to develop the software. Finally, we will demonstrate performance improvements achieved by using the heterogeneous computing architecture. This work was supported by a grant from the Swiss National Supercomputing Centre (CSCS) under project ID d26.

  19. 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.

  20. Optimal Correlation Filters for Images with Signal-Dependent Noise

    NASA Technical Reports Server (NTRS)

    Downie, John D.; Walkup, John F.

    1994-01-01

    We address the design of optimal correlation filters for pattern detection and recognition in the presence of signal-dependent image noise sources. The particular examples considered are film-grain noise and speckle. Two basic approaches are investigated: (1) deriving the optimal matched filters for the signal-dependent noise models and comparing their performances with those derived for traditional signal-independent noise models and (2) first nonlinearly transforming the signal-dependent noise to signal-independent noise followed by the use of a classical filter matched to the transformed signal. We present both theoretical and computer simulation results that demonstrate the generally superior performance of the second approach in terms of the correlation peak signal-to-noise ratio.

  1. Variation in signal-preference genetic correlations in Enchenopa treehoppers (Hemiptera: Membracidae).

    PubMed

    Fowler-Finn, Kasey D; Kilmer, Joseph T; Hallett, Allysa C; Rodríguez, Rafael L

    2015-07-01

    Fisherian selection is a within-population process that promotes signal-preference coevolution and speciation due to signal-preference genetic correlations. The importance of the contribution of Fisherian selection to speciation depends in part on the answer to two outstanding questions: What explains differences in the strength of signal-preference genetic correlations? And, how does the magnitude of within-species signal-preference covariation compare to species differences in signals and preferences? To address these questions, we tested for signal-preference genetic correlations in two members of the Enchenopa binotata complex, a clade of plant-feeding insects wherein speciation involves the colonization of novel host plants and signal-preference divergence. We used a full-sibling, split-family rearing experiment to estimate genetic correlations and to analyze the underlying patterns of variation in signals and preferences. Genetic correlations were weak or zero, but exploration of the underlying patterns of variation in signals and preferences revealed some full-sib families that varied by as much as 50% of the distance between similar species in the E. binotata complex. This result was stronger in the species that showed greater amounts of genetic variation in signals and preferences. We argue that some forms of weak signal-preference genetic correlation may have important evolutionary consequences. PMID:26306166

  2. Processing Aftershock Sequences Using Waveform Correlation

    NASA Astrophysics Data System (ADS)

    Resor, M. E.; Procopio, M. J.; Young, C. J.; Carr, D. B.

    2008-12-01

    For most event monitoring systems, the objective is to keep up with the flow of incoming data, producing a bulletin with some modest, relatively constant, time delay after present time, often a period of a few hours or less. Because the association problem scales exponentially and not linearly with the number of detections, a dramatic increase in seismicity due to an aftershock sequence can easily cause the bulletin delay time to increase dramatically. In some cases, the production of a bulletin may cease altogether, until the automatic system can catch up. For a nuclear monitoring system, the implications of such a delay could be dire. Given the expected similarity between a mainshock and aftershocks, it has been proposed that waveform correlation may provide a powerful means to simultaneously increase the efficiency of processing aftershock sequences, while also lowering the detection threshold and improving the quality of the event solutions. However, many questions remain unanswered. What are the key parameters for achieving the best correlations between waveforms (window length, filtering, etc.), and are they sequence-dependent? What is the overall percentage of similar events in an aftershock sequence, i.e. what is the maximum level of efficiency that a waveform correlation could be expected to achieve? Finally, how does this percentage of events vary among sequences? Using data from the aftershock sequence for the December 26, 2004 Mw 9.1 Sumatra event, we investigate these issues by building and testing a prototype waveform correlation event detection system that automatically expands its library of known events as new signatures are indentified in the aftershock sequence (by traditional signal detection and event processing). Our system tests all incoming data against this dynamic library, thereby identify any similar events before traditional processing takes place. In the region surrounding the Sumatra event, the NEIC EDR contains 4997 events in the 9 months following the mainshock, and only 265 events during the same period for the previous year, so this sequence represents a formidable challenge for any automatic processing system. Preliminary results suggest that a waveform correlation-based system can detect on the order of 10% or more of the aftershocks for this event. Results published in the recent literature suggest that significantly larger proportions may be achievable for other aftershock sequences with smaller fault ruptures; we investigate and report encouraging results from one such sequence. Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy's National Nuclear Security Administration under Contract DE-AC04- 94AL85000.

  3. 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.

  4. 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.

  5. On the Relationship between Signal Bandwidth and Frequency Correlation for Surface Forward Scattered Signals

    NASA Astrophysics Data System (ADS)

    Culver, Lee; Bradley, David

    2004-11-01

    The relationship between the signal bandwidth and the correlation of a single surface reflected arrival with the transmitted signal has been investigated experimentally and compared with two theories. The dependence of correlation on signal bandwidth is termed frequency correlation. Decorrelation of surface scattered signals is a direct consequence of time spread. Thus the acoustic measurement utilized two pure tone signals, from which time spread has been estimated, and four broadband signals with different bandwidths, from which correlation with the transmitted signal has been calculated. A model developed by Dahl for the ocean surface bistatic scattering cross section was used to predict time spread, which agreed very well with the measured time spread. Next, scattering cross section prediction was employed in two theories that predict frequency correlation. The first, published by Reeves in 1974, compared well with the measurements for bandwidths up to 2 kHz, but under predicted correlation for signal bandwidth between 7 and 22 kHz. In the second, linear systems theory was used to develop a mathematical relationship between time spread and frequency correlation. Predictions made using the linear systems theory agree well with the measured values for signal bandwidths up to 22kHz. Further work is required to evaluate the linear systems theory under higher sea state conditions.

  6. 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…

  7. On the relationship between signal bandwidth and frequency correlation for ocean surface forward scattered signals

    NASA Astrophysics Data System (ADS)

    Culver, R. Lee; Bradley, David L.

    2005-07-01

    The relationship between the bandwidth of a signal and the correlation of that signal with its ocean surface reflected arrival, a quantity we term frequency correlation, has been investigated experimentally and compared with two theories. Decorrelation of wideband surface scattered signals is a direct consequence of time spread. The acoustic measurement utilized a very short pure tone signal, from which time spread has been estimated, and four broadband signals with different bandwidths, for which correlation with the transmitted signal has been measured. An environment-driven model developed by Dahl was used to predict time spread, which agreed favorably with our time spread measurements. The model was also employed in two theories that predict frequency correlation. The first, a theory published by Reeves in 1974, is based upon the ratio of signal temporal resolution to total time spread. This theory compared well with our measurements for 1 kHz bandwidth signals, but is not applicable for signal bandwidths greater than about 2 kHz. The second, a theory developed by Ziomek, models ocean acoustic propagation as transmission through a linear system. This theory agreed well with our frequency correlation measurements for signal bandwidths of 1-22 kHz. .

  8. Signal processing and analyzing works of art

    NASA Astrophysics Data System (ADS)

    Johnson, Don H.; Johnson, C. Richard, Jr.; Hendriks, Ella

    2010-08-01

    In examining paintings, art historians use a wide variety of physico-chemical methods to determine, for example, the paints, the ground (canvas primer) and any underdrawing the artist used. However, the art world has been little touched by signal processing algorithms. Our work develops algorithms to examine x-ray images of paintings, not to analyze the artist's brushstrokes but to characterize the weave of the canvas that supports the painting. The physics of radiography indicates that linear processing of the x-rays is most appropriate. Our spectral analysis algorithms have an accuracy superior to human spot-measurements and have the advantage that, through "short-space" Fourier analysis, they can be readily applied to entire x-rays. We have found that variations in the manufacturing process create a unique pattern of horizontal and vertical thread density variations in the bolts of canvas produced. In addition, we measure the thread angles, providing a way to determine the presence of cusping and to infer the location of the tacks used to stretch the canvas on a frame during the priming process. We have developed weave matching software that employs a new correlation measure to find paintings that share canvas weave characteristics. Using a corpus of over 290 paintings attributed to Vincent van Gogh, we have found several weave match cliques that we believe will refine the art historical record and provide more insight into the artist's creative processes.

  9. 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.

  10. A coherent nonlinear optical signal induced by electron correlations

    PubMed Central

    Mukamel, Shaul; Oszwałdowski, Rafał; Yang, Lijun

    2010-01-01

    The correlated behavior of electrons determines the structure and optical properties of molecules, semiconductors, and other systems. Valuable information on these correlations is provided by measuring the response to femtosecond laser pulses, which probe the very short time period during which the excited particles remain correlated. The interpretation of four-wave-mixing techniques, commonly used to study the energy levels and dynamics of many-electron systems, is complicated by many competing effects and overlapping resonances. Here we propose a coherent optical technique, specifically designed to provide a background-free probe for electronic correlations in many-electron systems. The proposed signal pulse is generated only when the electrons are correlated, which gives rise to an extraordinary sensitivity. The peak pattern in two-dimensional plots, obtained by displaying the signal versus two frequencies conjugated to two pulse delays, provides a direct visualization and specific signatures of the many-electron wave functions. PMID:18081382

  11. Novel sonar signal processing tool using Shannon entropy

    NASA Astrophysics Data System (ADS)

    Quazi, Azizul H.

    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 H0 (that the received process consists of noise alone) is true and decreases when correlated signal is present (H1). 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: H1 is assumed if the difference is large compared to pre-assigned threshold and H0 is otherwise assumed. The test statistics will be different between entropies under H0 and H1. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  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. Signal processing methods for MFE plasma diagnostics

    SciTech Connect

    Candy, J.V.; Casper, T.; Kane, R.

    1985-02-01

    The application of various signal processing methods to extract energy storage information from plasma diamagnetism sensors occurring during physics experiments on the Tandom Mirror Experiment-Upgrade (TMX-U) is discussed. We show how these processing techniques can be used to decrease the uncertainty in the corresponding sensor measurements. The algorithms suggested are implemented using SIG, an interactive signal processing package developed at LLNL.

  18. Signal processing of infrared imaging system

    NASA Astrophysics Data System (ADS)

    Li, Layuan

    1986-01-01

    The signal processing techniques of infrared imaging system are discussed. Performance of PEV for chopping mode in the system and some basic designing principles of the system are described. Main methods for processing signal of infrared imaging system are suggested. Emphasis is laid on the multiple fields accumulation and image difference processing technique. On the basis of describing the main principle of the method, the concrete project is put forward. Some test results are also given.

  19. Signal propagation in cortical networks: a digital signal processing approach.

    PubMed

    Rodrigues, Francisco Aparecido; da Fontoura Costa, Luciano

    2009-01-01

    This work reports a digital signal processing approach to representing and modeling transmission and combination of signals in cortical networks. The signal dynamics is modeled in terms of diffusion, which allows the information processing undergone between any pair of nodes to be fully characterized in terms of a finite impulse response (FIR) filter. Diffusion without and with time decay are investigated. All filters underlying the cat and macaque cortical organization are found to be of low-pass nature, allowing the cortical signal processing to be summarized in terms of the respective cutoff frequencies (a high cutoff frequency meaning little alteration of signals through their intermixing). Several findings are reported and discussed, including the fact that the incorporation of temporal activity decay tends to provide more diversified cutoff frequencies. Different filtering intensity is observed for each community in those networks. In addition, the brain regions involved in object recognition tend to present the highest cutoff frequencies for both the cat and macaque networks. PMID:19668701

  20. Optical Profilometers Using Adaptive Signal Processing

    NASA Technical Reports Server (NTRS)

    Hall, Gregory A.; Youngquist, Robert; Mikhael, Wasfy

    2006-01-01

    A method of adaptive signal processing has been proposed as the basis of a new generation of interferometric optical profilometers for measuring surfaces. The proposed profilometers would be portable, hand-held units. Sizes could be thus reduced because the adaptive-signal-processing method would make it possible to substitute lower-power coherent light sources (e.g., laser diodes) for white light sources and would eliminate the need for most of the optical components of current white-light profilometers. The adaptive-signal-processing method would make it possible to attain scanning ranges of the order of decimeters in the proposed profilometers.

  1. 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

  2. Optical signal processing: Musical score for optical signals

    NASA Astrophysics Data System (ADS)

    Testorf, Markus

    2012-07-01

    Phase-space optics is an indispensable tool for optical imaging and sensing. New optical hardware for light-field photography and pupil engineering for imaging with extended depth of field promote the use of phase-space representations as the primary object of optical signal processing.

  3. Digital signal processing in microwave radiometers

    NASA Technical Reports Server (NTRS)

    Lawrence, R. W.; Stanley, W. D.; Harrington, R. F.

    1980-01-01

    A microprocessor based digital signal processing unit has been proposed to replace analog sections of a microwave radiometer. A brief introduction to the radiometer system involved and a description of problems encountered in the use of digital techniques in radiometer design are discussed. An analysis of the digital signal processor as part of the radiometer is then presented.

  4. Photoacoustic correlation signal-to-noise ratio enhancement by coherent averaging and optical waveform optimization

    NASA Astrophysics Data System (ADS)

    Telenkov, Sergey A.; Alwi, Rudolf; Mandelis, Andreas

    2013-10-01

    Photoacoustic (PA) imaging of biological tissues using laser diodes instead of conventional Q-switched pulsed systems provides an attractive alternative for biomedical applications. However, the relatively low energy of laser diodes operating in the pulsed regime, results in generation of very weak acoustic waves, and low signal-to-noise ratio (SNR) of the detected signals. This problem can be addressed if optical excitation is modulated using custom waveforms and correlation processing is employed to increase SNR through signal compression. This work investigates the effect of the parameters of the modulation waveform on the resulting correlation signal and offers a practical means for optimizing PA signal detection. The advantage of coherent signal averaging is demonstrated using theoretical analysis and a numerical model of PA generation. It was shown that an additional 5-10 dB of SNR can be gained through waveform engineering by adjusting the parameters and profile of optical modulation waveforms.

  5. Neutron coincidence counting with digital signal processing

    NASA Astrophysics Data System (ADS)

    Bagi, Janos; Dechamp, Luc; Dransart, Pascal; Dzbikowicz, Zdzislaw; Dufour, Jean-Luc; Holzleitner, Ludwig; Huszti, Joseph; Looman, Marc; Marin Ferrer, Montserrat; Lambert, Thierry; Peerani, Paolo; Rackham, Jamie; Swinhoe, Martyn; Tobin, Steve; Weber, Anne-Laure; Wilson, Mark

    2009-09-01

    Neutron coincidence counting is a widely adopted nondestructive assay (NDA) technique used in nuclear safeguards to measure the mass of nuclear material in samples. Nowadays, most neutron-counting systems are based on the original-shift-register technology, like the (ordinary or multiplicity) Shift-Register Analyser. The analogue signal from the He-3 tubes is processed by an amplifier/single channel analyser (SCA) producing a train of TTL pulses that are fed into an electronic unit that performs the time- correlation analysis. Following the suggestion of the main inspection authorities (IAEA, Euratom and the French Ministry of Industry), several research laboratories have started to study and develop prototypes of neutron-counting systems with PC-based processing. Collaboration in this field among JRC, IRSN and LANL has been established within the framework of the ESARDA-NDA working group. Joint testing campaigns have been performed in the JRC PERLA laboratory, using different equipment provided by the three partners. One area of development is the use of high-speed PCs and pulse acquisition electronics that provide a time stamp (LIST-Mode Acquisition) for every digital pulse. The time stamp data can be processed directly during acquisition or saved on a hard disk. The latter method has the advantage that measurement data can be analysed with different values for parameters like predelay and gate width, without repeating the acquisition. Other useful diagnostic information, such as die-away time and dead time, can also be extracted from this stored data. A second area is the development of "virtual instruments." These devices, in which the pulse-processing system can be embedded in the neutron counter itself and sends counting data to a PC, can give increased data-acquisition speeds. Either or both of these developments could give rise to the next generation of instrumentation for improved practical neutron-correlation measurements. The paper will describe the rationale for changing to the new technology, give an overview of the hardware and software tools available today and a feedback of the experience gained in the first tests. Associated with the experimental tests, the ESARDA-NDA working group is also performing an intercomparison benchmark exercise on the analysis software for pulse processing.

  6. 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

  7. Optical signal processing of phased array radar

    NASA Astrophysics Data System (ADS)

    Weverka, Robert T.

    This thesis develops optical processors that scale to very high processing speed. Optical signal processing is often promoted on the basis of smaller size, lower weight and lower power consumption as well as higher signal processing speed. While each of these requirements has applications, it is the ones that require processing speed beyond that available in electronics that are most compelling. Thirty years ago, optical processing was the only method fast enough to process Synthetic Aperture Radar (SAR), one of the more demanding signal processing tasks at this time. Since that time electronic processing speed has improved sufficiently to tackle that problem. We have sought out the problems that require significantly higher processing speed and developed optical processors that tackle these more difficult problems. The components that contribute to high signal processing speed are high input signal bandwidth, a large number of parallel input channels each with this high bandwidth, and a large number of parallel operations required on each input channel. Adaptive signal processing for phased array radar has all of these factors. The processors developed for this task scale well in three dimensions, which allows them to maximize parallelism for high speed. This thesis explores an example of a negative feedback adaptive phased array processor and an example of a positive feedback phased array processor. The negative feedback processor uses and array of inputs in up to two dimensions together with the time history of the signal in the third dimension to adapt the array pattern to null out incoming jammer signals. The positive feedback processor uses the incoming signals and assumptions about the radar scene to correct for position errors in a phased array. Discovery and analysis of these new processors are facilitated by an original volume holographic analysis technique developed in the thesis. The thesis includes a new acoustooptic Bragg cell geometry developed with this analysis technique. This Bragg cell provides a low insertion delay making it suitable for the feedback phased array radar systems. This thesis develops a new algorithm for phased array radar processing. This adaptation of the Widrow algorithm requires fewer delay lines allowing us to implement a system that can scale to dense two-dimensional phased array radar. The thesis explores this processor in depth, developing the description of the system evolution, the nonlinear dynamics governing the system and the dynamic range: that can be achieved. The system behavior and dynamics are confirmed experimentally. Finally this thesis explores positive feed back architectures for the phased radar problem posed by Steinberg in which the array itself is poorly surveyed. To our knowledge, optical signal processing solutions to this problem have not been developed prior to this work.

  8. Digital signal processor and programming system for parallel signal processing

    SciTech Connect

    Van den Bout, D.E.

    1987-01-01

    This thesis describes an integrated assault upon the problem of designing high-throughput, low-cost digital signal-processing systems. The dual prongs of this assault consist of: (1) the design of a digital signal processor (DSP) which efficiently executes signal-processing algorithms in either a uniprocessor or multiprocessor configuration, (2) the PaLS programming system which accepts an arbitrary algorithm, partitions it across a group of DSPs, synthesizes an optimal communication link topology for the DSPs, and schedules the partitioned algorithm upon the DSPs. The results of applying a new quasi-dynamic analysis technique to a set of high-level signal-processing algorithms were used to determine the uniprocessor features of the DSP design. For multiprocessing applications, the DSP contains an interprocessor communications port (IPC) which supports simple, flexible, dataflow communications while allowing the total communication bandwidth to be incrementally allocated to achieve the best link utilization. The net result is a DSP with a simple architecture that is easy to program for both uniprocessor and multi-processor modes of operation. The PaLS programming system simplifies the task of parallelizing an algorithm for execution upon a multiprocessor built with the DSP.

  9. Signal processing by the endosomal system.

    PubMed

    Villaseñor, Roberto; Kalaidzidis, Yannis; Zerial, Marino

    2016-04-01

    Cells need to decode chemical or physical signals from their environment in order to make decisions on their fate. In the case of signalling receptors, ligand binding triggers a cascade of chemical reactions but also the internalization of the activated receptors in the endocytic pathway. Here, we highlight recent studies revealing a new role of the endosomal network in signal processing. The diversity of entry pathways and endosomal compartments is exploited to regulate the kinetics of receptor trafficking, and interactions with specific signalling adaptors and effectors. By governing the spatio-temporal distribution of signalling molecules, the endosomal system functions analogously to a digital-analogue computer that regulates the specificity and robustness of the signalling response. PMID:26921695

  10. Digital Signal Processing in Acoustics--Part 2.

    ERIC Educational Resources Information Center

    Davies, H.; McNeill, D. J.

    1986-01-01

    Reviews the potential of a data acquisition system for illustrating the nature and significance of ideas in digital signal processing. Focuses on the fast Fourier transform and the utility of its two-channel format, emphasizing cross-correlation and its two-microphone technique of acoustic intensity measurement. Includes programing format. (ML)

  11. Acquisition of direct sequence spread spectrum signals using digital signal processing techniques

    NASA Astrophysics Data System (ADS)

    Schmitz, Ronald E.

    1992-12-01

    This thesis investigates the use of digital signal processing (DSP) techniques to achieve initial synchronization with Global Positioning System (GPS) Pseudo-Noise (PN) signals. Synchronization with the transmitted PN signal is essential to the despreading of the transmitted Direct Sequence Spread Spectrum (DS/SS) signals and decoding of the transmitted satellite data. The use of DSP methods to decrease the time required to achieve initial synchronization is investigated. This thesis proposes an initial acquisition section of the GPS receiver and derives the equations to show the method is mathematically feasible. Computer simulations of the proposed receiver using received signals corrupted by Doppler shifts and noise and having various code offsets, show that coarse acquisition of GPS signals can be achieved using DSP methods. However, the correlation of the sequences is distorted by zero padding to allow the use of radix-2 FFT's. This distortion can be accounted for and proper coarse acquisition is still achieved.

  12. Adaptive filtering in biological signal processing.

    PubMed

    Iyer, V K; Ploysongsang, Y; Ramamoorthy, P A

    1990-01-01

    The high dependence of conventional optimal filtering methods on the a priori knowledge of the signal and noise statistics render them ineffective in dealing with signals whose statistics cannot be predetermined accurately. Adaptive filtering methods offer a better alternative, since the a priori knowledge of statistics is less critical, real time processing is possible, and the computations are less expensive for this approach. Adaptive filtering methods compute the filter coefficients "on-line", converging to the optimal values in the least-mean square (LMS) error sense. Adaptive filtering is therefore apt for dealing with the "unknown" statistics situation and has been applied extensively in areas like communication, speech, radar, sonar, seismology, and biological signal processing and analysis for channel equalization, interference and echo canceling, line enhancement, signal detection, system identification, spectral analysis, beamforming, modeling, control, etc. In this review article adaptive filtering in the context of biological signals is reviewed. An intuitive approach to the underlying theory of adaptive filters and its applicability are presented. Applications of the principles in biological signal processing are discussed in a manner that brings out the key ideas involved. Current and potential future directions in adaptive biological signal processing are also discussed. PMID:2180633

  13. Signal detection by correlation of Fresnel diffraction patterns.

    PubMed

    De, M; Lohmann, A W

    1967-12-01

    A typical problem of signal detection is the search for key words. This can be done automatically by means of optical matched filtering. Here we describe an alternative method in which the key word is used directly, not in the form of a matched filter. We compute optically the correlation integral of the intensity distributions of the Fresnel diffraction patterns from the input (printed page) and from the reference signal (key word). In the output plane a detection peak (light point) indicates the position of the key word on the input page. PMID:20062381

  14. Methodological framework for estimating the correlation dimension in HRV signals.

    PubMed

    Bolea, Juan; Laguna, Pablo; Remartnez, Jos Mara; Rovira, Eva; Navarro, Augusto; Bailn, 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?, D(2(?)), and D(2(max)). D? and D(2(max)) 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? keeps the 81% of accuracy previously described in the literature while D(2(?)) and D(2(max)) approaches reach 91% of accuracy in the same database. PMID:24592284

  15. 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

  16. Anthropometric and demographic correlates of dual-axis swallowing accelerometry signal characteristics: a canonical correlation analysis.

    PubMed

    Hanna, Fady; Molfenter, Sonja M; Cliffe, Rebecca E; Chau, Tom; Steele, Catriona M

    2010-06-01

    Swallowing accelerometry has been proposed as a potential minimally invasive tool for collecting assessment information about swallowing. The first step toward using sounds and signals for dysphagia detection involves characterizing the healthy swallow. The purpose of this article is to explore systematic variations in swallowing accelerometry signals that can be attributed to demographic factors (such as participant gender and age) and anthropometric factors (such as weight and height). Data from 50 healthy participants (25 women and 25 men), ranging in age from 18 to 80 years and with approximately equal distribution across four age groups (18-35, 36-50, 51-65, 66 and older) were analyzed. Anthropometric and demographic variables of interest included participant age, gender, weight, height, body fat percent, neck circumference, and mandibular length. Dual-axis (superior-inferior and anterior-posterior) swallowing accelerometry signals were obtained for five saliva and five water swallows per participant. Several swallowing signal characteristics were derived for each swallowing task, including variance, amplitude distribution skewness, amplitude distribution kurtosis, signal memory, total signal energy, peak energy scale, and peak amplitude. Canonical correlation analysis was performed between the anthropometric/demographic variables and swallowing signal characteristics. No significant linear relationships were identified for saliva swallows or for superior-inferior axis accelerometry signals on water swallows. In the anterior-posterior axis, signal amplitude distribution kurtosis and signal memory were significantly correlated with age (r = 0.52, P = 0.047). These findings suggest that swallowing accelerometry signals may have task-specific associations with demographic (but not anthropometric) factors. Given the limited sample size, our results should be interpreted with caution and replication studies with larger sample sizes are warranted. PMID:19495874

  17. Correlation identification between internal/external motion signals

    NASA Astrophysics Data System (ADS)

    Wu, Huanmei; Zhao, Qingya; Berbeco, Ross; Nishioka, Seiko; Shirato, Hiroki; Jiang, Steve B.

    2008-03-01

    Tumor motion induced by patient breathing decreases the effectiveness of radiation treatment. Image guided radiation treatment (IGRT) is an advanced approach for cancer radiation treatment. The success of IGRT is largely dependent on the accurate localization of tumor in real-time. There are two major imaging approaches currently in use to localize a tumor: internal imaging and external imaging. Internal imaging determines the tumor locations by directly x-ray of the tumor area. It is accurate however radiation dose is a big concern. External imaging derives the internal tumor locations through an external mark on the patient surface. It is radiation dose free however the insufficient accuracy limits its wide application. Integrating the internal and external signals together is necessary for reliable radiation treatment and acceptable patient radiation exposure. Our work tries to identify the correlation patterns between internal/external signals and the influential factors so that the hybrid signal will give desire accuracy in dose delivery while limiting radiation exposure to the patients. Both theoretical simulation based on sinusoidal functions and statistical analysis on real patient data are performed. The sinusoidal simulation will identify the potential influence factors of different correlation conditions. The results have demonstrated the various correlation patterns with amplitude various, frequency changes (duration changes), phase shifts, and baseline drift. The results will aid the statistical analytical on real-patients to identify the dominant factors of the internal/external motion signals for a specific patients. The described work is very useful in advanced IGRT to update the internal/external correlation in real-time for better cancer patient care.

  18. The behavioral neuroscience of anuran social signal processing.

    PubMed

    Wilczynski, Walter; Ryan, Michael J

    2010-12-01

    Acoustic communication is the major component of social behavior in anuran amphibians (frogs and toads) and has served as a neuroethological model for the nervous system's processing of social signals related to mate choice decisions. The male's advertisement or mating call is its most conspicuous social signal, and the nervous system's analysis of the call is a progressive process. As processing proceeds through neural systems, response properties become more specific to the signal and, in addition, neural activity gradually shifts from representing sensory (auditory periphery and brainstem) to sensorimotor (diencephalon) to motor (forebrain) components of a behavioral response. A comparative analysis of many anuran species shows that the first stage in biasing responses toward conspecific signals over heterospecific signals, and toward particular features of conspecific signals, lies in the tuning of the peripheral auditory system. Biases in processing signals are apparent through the brainstem auditory system, where additional feature detection neurons are added by the time processing reaches the level of the midbrain. Recent work using immediate early gene expression as a marker of neural activity suggests that by the level of the midbrain and forebrain, the differential neural representation of conspecific and heterospecific signals involves both changes in mean activity levels across multiple subnuclei, and in the functional correlations among acoustically active areas. Our data show that in frogs the auditory midbrain appears to play an important role in controlling behavioral responses to acoustic social signals by acting as a regulatory gateway between the stimulus analysis of the brainstem and the behavioral and physiological control centers of the forebrain. We predict that this will hold true for other vertebrate groups such as birds and fish that produce acoustic social signals, and perhaps also in fish where electroreception or vibratory sensing through the lateral line systems plays a role in social signaling, as in all these cases ascending sensory information converges onto midbrain nuclei which relay information to higher brain centers. PMID:20863685

  19. 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

  20. Haotic, Fractal, and Nonlinear Signal Processing. Proceedings

    SciTech Connect

    Katz, R.A.

    1996-10-01

    These proceedings include papers presented at the Third Technical Conference on Nonlinear Dynamics and Full{minus}Spectrum Processing held in Mystic, Connecticut. The Conference focus was on the latest advances in chaotic, fractal and nonlinear signal processing methods. Topics of discussion covered in the Conference include: mathematical frontiers; predictability and control of chaos, detection and classification with applications in acoustics; advanced applied signal processing methods(linear and nonlinear); stochastic resonance; machinery diagnostics; turbulence; geophysics; medicine; and recent novel approaches to modeling nonlinear systems. There were 58 papers in the conference and all have been abstracted for the Energy Science and Technology database. (AIP)

  1. 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.

  2. Time domain cyclostationarity signal-processing tools

    NASA Astrophysics Data System (ADS)

    Léonard, François

    2015-10-01

    This paper proposes four different time-domain tools to estimate first-order time cyclostationary signals without the need of a keyphasor signal. Applied to gearbox signals, these tacho-less methods appear intuitively simple, offer user-friendly graphic interfaces to visualize a pattern and allow the retrieval and removal of the selected cyclostationarity components in order to process higher-order spectra. Two of these tools can deal with time-varying operating conditions since they use an adaptive resampled signal driven by the vibration signal itself for order tracking. Three coherency indicators are proposed, one for every sample of the time pattern, one for each impact (tooth shock) observed in the gear mesh pattern, and one for the whole pattern. These indicators are used to detect a cyclostationarity and analyze the pattern repeatability. A gear mesh graph is also proposed to illustrate the cyclostationarity in 3D.

  3. Process Correlation Analysis Model for Process Improvement Identification

    PubMed Central

    Park, Sooyong

    2014-01-01

    Software process improvement aims at improving the development process of software systems. It is initiated by process assessment identifying strengths and weaknesses and based on the findings, improvement plans are developed. In general, a process reference model (e.g., CMMI) is used throughout the process of software process improvement as the base. CMMI defines a set of process areas involved in software development and what to be carried out in process areas in terms of goals and practices. Process areas and their elements (goals and practices) are often correlated due to the iterative nature of software development process. However, in the current practice, correlations of process elements are often overlooked in the development of an improvement plan, which diminishes the efficiency of the plan. This is mainly attributed to significant efforts and the lack of required expertise. In this paper, we present a process correlation analysis model that helps identify correlations of process elements from the results of process assessment. This model is defined based on CMMI and empirical data of improvement practices. We evaluate the model using industrial data. PMID:24977170

  4. Novel sonar signal processing tool using Shannon entropy

    SciTech Connect

    Quazi, A.H.

    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.}

  5. Signal processing for distributed readout using TESs

    NASA Astrophysics Data System (ADS)

    Smith, Stephen J.; Whitford, Chris H.; Fraser, George W.

    2006-04-01

    We describe optimal filtering algorithms for determining energy and position resolution in position-sensitive Transition Edge Sensor (TES) Distributed Read-Out Imaging Devices (DROIDs). Improved algorithms, developed using a small-signal finite-element model, are based on least-squares minimisation of the total noise power in the correlated dual TES DROID. Through numerical simulations we show that significant improvements in energy and position resolution are theoretically possible over existing methods.

  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. Bacteriorhodopsin Film For Processing SAR Signals

    NASA Technical Reports Server (NTRS)

    Yu, Jeffrey W.; Chao, Tien-Hsin; Margalit, Ruth; Cheng, Li-Jen

    1992-01-01

    "Instant" photographic film based on semisynthetic retinal pigment bacteriorhodopsin proposed for optical processing of synthetic-aperture-radar (SAR) signals. Input image recorded on film by laser operating at writing wavelength of bacteriorhodopsin, and output image recorded on computer by standard frame-grabber. Because it requires no chemical development, enables processing in nearly real time. Fast response and high resolution well suited for application. Film reusable, with concomitant reduction in cost of SAR processing.

  8. Designer cell signal processing circuits for biotechnology.

    PubMed

    Bradley, Robert W; Wang, Baojun

    2015-12-25

    Microorganisms are able to respond effectively to diverse signals from their environment and internal metabolism owing to their inherent sophisticated information processing capacity. A central aim of synthetic biology is to control and reprogramme the signal processing pathways within living cells so as to realise repurposed, beneficial applications ranging from disease diagnosis and environmental sensing to chemical bioproduction. To date most examples of synthetic biological signal processing have been built based on digital information flow, though analogue computing is being developed to cope with more complex operations and larger sets of variables. Great progress has been made in expanding the categories of characterised biological components that can be used for cellular signal manipulation, thereby allowing synthetic biologists to more rationally programme increasingly complex behaviours into living cells. Here we present a current overview of the components and strategies that exist for designer cell signal processing and decision making, discuss how these have been implemented in prototype systems for therapeutic, environmental, and industrial biotechnological applications, and examine emerging challenges in this promising field. PMID:25579192

  9. Designer cell signal processing circuits for biotechnology

    PubMed Central

    Bradley, Robert W.; Wang, Baojun

    2015-01-01

    Microorganisms are able to respond effectively to diverse signals from their environment and internal metabolism owing to their inherent sophisticated information processing capacity. A central aim of synthetic biology is to control and reprogramme the signal processing pathways within living cells so as to realise repurposed, beneficial applications ranging from disease diagnosis and environmental sensing to chemical bioproduction. To date most examples of synthetic biological signal processing have been built based on digital information flow, though analogue computing is being developed to cope with more complex operations and larger sets of variables. Great progress has been made in expanding the categories of characterised biological components that can be used for cellular signal manipulation, thereby allowing synthetic biologists to more rationally programme increasingly complex behaviours into living cells. Here we present a current overview of the components and strategies that exist for designer cell signal processing and decision making, discuss how these have been implemented in prototype systems for therapeutic, environmental, and industrial biotechnological applications, and examine emerging challenges in this promising field. PMID:25579192

  10. Ultrasonic correlator versus signal averager as a signal to noise enhancement instrument

    NASA Technical Reports Server (NTRS)

    Kishoni, Doron; Pietsch, Benjamin E.

    1990-01-01

    Ultrasonic inspection of thick and attenuating materials is hampered by the reduce amplitudes of the propagated waves to a degree that the noise is too high to enable meaningful interpretation of the data. In order to overcome the low signal to noise ratio (S/N), a correlation technique has been developed. In this method, a continuous pseudo-random pattern generated digitally is transmitted and detected by piezoelectric transducers. A correlation is performed in the instrument between the received signal and a variable delayed image of the transmitted one. The result is shown to be proportional to the impulse response of the investigated material, analogous to a signal received from a pulsed system, with an improved S/N ratio. The degree of S/N enhancement depends on the sweep rate. The correlator is described, and it is compared to the method of enhancing S/N ratio by averaging the signals. The similarities and differences between the two are highlighted and the potential advantage of the correlator system is explained.

  11. 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.

  12. Processing oscillatory signals by incoherent feedforward loops

    NASA Astrophysics Data System (ADS)

    Zhang, Carolyn; Wu, Feilun; Tsoi, Ryan; Shats, Igor; You, Lingchong

    From the timing of amoeba development to the maintenance of stem cell pluripotency,many biological signaling pathways exhibit the ability to differentiate between pulsatile and sustained signals in the regulation of downstream gene expression.While networks underlying this signal decoding are diverse,many are built around a common motif, the incoherent feedforward loop (IFFL),where an input simultaneously activates an output and an inhibitor of the output.With appropriate parameters,this motif can generate temporal adaptation,where the system is desensitized to a sustained input.This property serves as the foundation for distinguishing signals with varying temporal profiles.Here,we use quantitative modeling to examine another property of IFFLs,the ability to process oscillatory signals.Our results indicate that the system's ability to translate pulsatile dynamics is limited by two constraints.The kinetics of IFFL components dictate the input range for which the network can decode pulsatile dynamics.In addition,a match between the network parameters and signal characteristics is required for optimal ``counting''.We elucidate one potential mechanism by which information processing occurs in natural networks with implications in the design of synthetic gene circuits for this purpose. This work was partially supported by the National Science Foundation Graduate Research Fellowship (CZ).

  13. Surveillance of industrial processes with correlated parameters

    DOEpatents

    White, Andrew M.; Gross, Kenny C.; Kubic, William L.; Wigeland, Roald A.

    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.

  14. 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.

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

    SciTech Connect

    Simone, Andrea De; Riotto, Antonio; Xue, Wei E-mail: antonio.riotto@unige.ch

    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 τ{sup +}τ{sup −}, although this situation is already severely constrained by gamma-ray measurements.The annihilation into μ{sup +}μ{sup −} is allowed by gamma-rays more than τ{sup +}τ{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.

  16. Signal processing schemes for Doppler global velocimetry

    NASA Technical Reports Server (NTRS)

    Meyers, James F.; Lee, Joseph W.; Cavone, Angelo A.

    1991-01-01

    Two schemes for processing signals obtained from the Doppler global velocimeter are described. The analog approach is a simple, real-time method for obtaining an RS-170 video signal containing the normalized intensity image. Pseudocolors are added using a monochromatic frame grabber producing a standard NTSC video signal that can be monitored and/or recorded. The digital approach is more complicated, but maintains the full resolution of the acquisition cameras with the ability to correct the signal image for pixel sensitivity variations and to remove background light. Prototype circuits for each scheme are described, and example results from the investigation of the vortical flow field above a 75-deg delta wing are presented.

  17. Stimulus Contrast and Retinogeniculate Signal Processing

    PubMed Central

    Rathbun, Daniel L.; Alitto, Henry J.; Warland, David K.; Usrey, W. Martin

    2016-01-01

    Neuronal signals conveying luminance contrast play a key role in nearly all aspects of perception, including depth perception, texture discrimination, and motion perception. Although much is known about the retinal mechanisms responsible for encoding contrast information, relatively little is known about the relationship between stimulus contrast and the processing of neuronal signals between visual structures. Here, we describe simultaneous recordings from monosynaptically connected retinal ganglion cells and lateral geniculate nucleus (LGN) neurons in the cat to determine how stimulus contrast affects the communication of visual signals between the two structures. Our results indicate that: (1) LGN neurons typically reach their half-maximal response at lower contrasts than their individual retinal inputs and (2) LGN neurons exhibit greater contrast-dependent phase advance (CDPA) than their retinal inputs. Further analyses suggests that increased sensitivity relies on spatial convergence of multiple retinal inputs, while increased CDPA is achieved, in part, on temporal summation of arriving signals. PMID:26924964

  18. Signal Processing Schemes for Doppler Global Velocimetry

    NASA Technical Reports Server (NTRS)

    Meyers, James F.; Lee, Joseph W.; Cavone, Angelo A.

    1991-01-01

    Two schemes for processing signals obtained from the Doppler global velocimeter are described. The analog approach is a simple, real time method for obtaining an RS-170 video signal containing the normalized intensity image. Pseudo colors are added using a monochromatic frame grabber producing a standard NTSC video signal that can be monitored and/or recorded. The digital approach is more complicated, but maintains the full resolution of the acquisition cameras with the capabilities to correct the signal image for pixel sensitivity variations and to remove of background light. Prototype circuits for each scheme are described and example results from the investigation of the vortical flow field above a 75-degree delta wing presented.

  19. Stimulus Contrast and Retinogeniculate Signal Processing.

    PubMed

    Rathbun, Daniel L; Alitto, Henry J; Warland, David K; Usrey, W Martin

    2016-01-01

    Neuronal signals conveying luminance contrast play a key role in nearly all aspects of perception, including depth perception, texture discrimination, and motion perception. Although much is known about the retinal mechanisms responsible for encoding contrast information, relatively little is known about the relationship between stimulus contrast and the processing of neuronal signals between visual structures. Here, we describe simultaneous recordings from monosynaptically connected retinal ganglion cells and lateral geniculate nucleus (LGN) neurons in the cat to determine how stimulus contrast affects the communication of visual signals between the two structures. Our results indicate that: (1) LGN neurons typically reach their half-maximal response at lower contrasts than their individual retinal inputs and (2) LGN neurons exhibit greater contrast-dependent phase advance (CDPA) than their retinal inputs. Further analyses suggests that increased sensitivity relies on spatial convergence of multiple retinal inputs, while increased CDPA is achieved, in part, on temporal summation of arriving signals. PMID:26924964

  20. The atmosphere- and hydrosphere-correlated signals in GPS observations

    NASA Astrophysics Data System (ADS)

    Bogusz, Janusz; Boy, Jean-Paul; Klos, Anna; Figurski, Mariusz

    2015-04-01

    The circulation of surface geophysical fluids (e.g. atmosphere, ocean, continental hydrology, etc.) induces global mass redistribution at the Earth's surface, and then surface deformations and gravity variations. The deformations can be reliably recorded by permanent GPS observations nowadays. The loading effects can be precisely modelled by convolving outputs from global general circulation models and Green's functions describing the Earth's response. Previously published papers showed that either surface gravity records or space-based observations can be efficiently corrected for atmospheric loading effects using surface pressure fields from atmospheric models. In a similar way, loading effects due to continental hydrology can be corrected from precise positioning observations. We evaluated 3-D displacement at the selected ITRF2008 core sites that belong to IGS (International GNSS Service) network due to atmospheric, oceanic and hydrological circulation using different models. Atmospheric and induced oceanic loading estimates were computed using the ECMWF (European Centre for Medium Range Weather Forecasts) operational and reanalysis (ERA interim) surface pressure fields, assuming an inverted barometer ocean response or a barotropic ocean model forced by air pressure and winds (MOG2D). The IB (Inverted Barometer) hypothesis was classically chosen, in which atmospheric pressure variations are fully compensated by static sea height variations. This approximation is valid for periods exceeding typically 5 to 20 days. At higher frequencies, dynamic effects cannot be neglected. Hydrological loading were provided using MERRA land (Modern-Era Retrospective Analysis for Research and Applications - NASA reanalysis for the satellite era using a major new version of the Goddard Earth Observing System Data Assimilation System Version 5 (GEOS-5)) for the different stations. After that we compared the results to the GPS-derived time series of North, East and Up components. The analysis of satellite data was performed twofold: firstly, the time series from network solution (NS) processed in Bernese 5.0 software by the Military University of Technology EPN Local Analysis Centre, secondly, the ones from PPP (Precise Point Positioning) from JPL (Jet Propulsion Laboratory) processing in Gipsy-Oasis were analyzed. Both were modelled with wavelet decomposition with Meyer orthogonal mother wavelet. Here, nine levels of decomposition were applied and eighth detail of it was interpreted as changes close to one year. In this way, both NS and PPP time series where presented as curves with annual period with amplitudes and phases changeable in time. The same analysis was performed for atmospheric (ATM) and hydrospheric (HYDR) models. All annual curves (modelled from NS, PPP, ATM and HYDR) were then compared to each other to investigate whether GPS observations contain the atmosphere and hydrosphere correlated signals and in what way the amplitudes of them may disrupt the GPS time series.

  1. Complementary contributions of indeterminism and signaling to quantum correlations

    SciTech Connect

    Hall, Michael J. W.

    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.

  2. Processing of the laser Doppler velocimeter signals

    NASA Technical Reports Server (NTRS)

    Meyers, J. F.; Feller, W. V.

    1973-01-01

    The laser Doppler velocimeter (LDV) is a probeless technique that provides a remote measurement of mean and fluctuating velocities. The measurement is actually obtained from small particles embedded in the flow which scatter light from an illuminating laser beam interference pattern. A portion of this scattered light is collected by a photomultiplier which yields an electronic signal whose frequency is directly proportional to the velocity of the small particles. The purpose of this paper is to describe and critically compare three techniques most used to process this electronic signal. These techniques are: (1) spectrum analyzer - a frequency scanning filter (frequency domain instrument), (2) wide-band frequency tracker - a frequency lock loop (frequency domain instrument), and (3) high-speed frequency counter - an interval timer (time domain instrument). The study determines the ability of each technique to process the LDV signal and yield velocity data to be used in determining the flow characteristics.

  3. Determinantal correlations for classical projection processes

    NASA Astrophysics Data System (ADS)

    Forrester, Peter J.; Nagao, Taro

    2011-08-01

    Recent applications in queuing theory and statistical mechanics have isolated the process formed by the eigenvalues of successive sub-matrices of the GUE. Analogous eigenvalue processes, formed in general from the eigenvalues of nested sequences of matrices resulting from random corank-1 projections of classical random matrix ensembles, are identified for the LUE and JUE. The correlations for all these processes can be computed in a unified way. The resulting expressions can then be analyzed in various scaling limits. At the soft edge, with the rank of the sub-matrices differing by an amount proportional to N2/3, the scaled correlations coincide with those known from the soft edge scaling of the Dyson Brownian motion model.

  4. Computer Aided Teaching of Digital Signal Processing.

    ERIC Educational Resources Information Center

    Castro, Ian P.

    1990-01-01

    Describes a microcomputer-based software package developed at the University of Surrey for teaching digital signal processing to undergraduate science and engineering students. Menu-driven software capabilities are explained, including demonstration of qualitative concepts and experimentation with quantitative data, and examples are given of…

  5. Displays, memories, and signal processing: A compilation

    NASA Technical Reports Server (NTRS)

    1975-01-01

    Articles on electronics systems and techniques were presented. The first section is on displays and other electro-optical systems; the second section is devoted to signal processing. The third section presented several new memory devices for digital equipment, including articles on holographic memories. The latest patent information available is also given.

  6. Phase sensitive Raman process with correlated seeds

    SciTech Connect

    Chen, Bing; Qiu, Cheng; Chen, L. Q. Zhang, Kai; Guo, Jinxian; Yuan, Chun-Hua; Zhang, Weiping; Ou, Z. Y.

    2015-03-16

    A phase sensitive Raman scattering was experimentally demonstrated by injecting a Stokes light seed into an atomic ensemble, whose internal state is set in such a way that it is coherent with the input Stokes seed. Such phase sensitive characteristic is a result of interference effect due to the phase correlation between the injected Stokes light field and the internal state of the atomic ensemble in the Raman process. Furthermore, the constructive interference leads to a Raman efficiency larger than other kinds of Raman processes such as stimulated Raman process with Stokes seed injection alone or uncorrelated light-atom seeding. It may find applications in precision spectroscopy, quantum optics, and precise measurement.

  7. Correlation Between Eddy Current Signal Noise and Peened Surface Roughness

    SciTech Connect

    Wendt, S. E.; Hentscher, S. R.; Raithel, D. C.; Nakagawa, N.

    2007-03-21

    For advanced uses of eddy current (EC) NDE models in, e.g., model-assisted POD, there is a need to understand the origin of EC noise sources so that noise estimations can be made for a given set of inspection conditions, in addition to defect signal predictions. This paper focuses on the material-oriented noise sources that exhibit some universality when isolated from electrical and mechanical noises. Specifically, we report on experimental measurements that show explicit correlations between surface roughness and EC noise as seen in post-peen EC measurements of shot-peened roughness specimens. The samples are 3''-by-3'' Inconel 718 and Ti-6A1-4V blocks, pre-polished and shot-peened at Almen intensities ranging from a low of 4N to as high as 16A, created by smaller ({approx}350 {mu}m) and larger ({approx}1 mm) diameter zirconium oxide shots. Strong correlations are observed between the Almen intensities and the measured surface roughness. The EC noise correlates equally strongly with the Almen intensities for the superalloy specimens. The correlation for the Ti-alloy samples is only apparent at higher intensities, while being weak for lower intensities, indicating the grain noise dominance for smoother surfaces.

  8. 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.

  9. Digital signal processing for ionospheric propagation diagnostics

    NASA Astrophysics Data System (ADS)

    Rino, Charles L.; Groves, Keith M.; Carrano, Charles S.; Gunter, Jacob H.; Parris, Richard T.

    2015-08-01

    For decades, analog beacon satellite receivers have generated multifrequency narrowband complex data streams that could be processed directly to extract total electron content (TEC) and scintillation diagnostics. With the advent of software-defined radio, modern digital receivers generate baseband complex data streams that require intermediate processing to extract the narrowband modulation imparted to the signal by ionospheric structure. This paper develops and demonstrates a processing algorithm for digital beacon satellite data that will extract TEC and scintillation components. For algorithm evaluation, a simulator was developed to generate noise-limited multifrequency complex digital signal realizations with representative orbital dynamics and propagation disturbances. A frequency-tracking procedure is used to capture the slowly changing frequency component. Dynamic demodulation against the low-frequency estimate captures the scintillation. The low-frequency reference can be used directly for dual-frequency TEC estimation.

  10. Exascale Signal Processing for Millimeter-Wavelength Interferometers

    NASA Astrophysics Data System (ADS)

    Hawkins, David

    2014-04-01

    The Exascale Radio Astronomy conference is a platform for scientists and engineers to discuss the challenges of "big data" with their peers in high-performance computing and industry. The "big data" challenge facing interferometers (arrays of radio telescopes) is the volume of antenna-based and cross-correlation data these instruments produce. Interferometers operating at millimeter wavelengths typically have between 10 and 100 antennas, with receiver bandwidths in excess of 60GHz per antenna now considered feasible (via four 15GHz signals from dual-polarization, sideband separating mixers). This talk presents details on the state-of-the art in wideband analog-to-digital converters, antenna-based signal processing, data transport, and correlation processing, along with the challenges faced when implemented these systems.

  11. Neural Correlates of Subliminal Language Processing.

    PubMed

    Axelrod, Vadim; Bar, Moshe; Rees, Geraint; Yovel, Galit

    2015-08-01

    Language is a high-level cognitive function, so exploring the neural correlates of unconscious language processing is essential for understanding the limits of unconscious processing in general. The results of several functional magnetic resonance imaging studies have suggested that unconscious lexical and semantic processing is confined to the posterior temporal lobe, without involvement of the frontal lobe-the regions that are indispensable for conscious language processing. However, previous studies employed a similarly designed masked priming paradigm with briefly presented single and contextually unrelated words. It is thus possible, that the stimulation level was insufficiently strong to be detected in the high-level frontal regions. Here, in a high-resolution fMRI and multivariate pattern analysis study we explored the neural correlates of subliminal language processing using a novel paradigm, where written meaningful sentences were suppressed from awareness for extended duration using continuous flash suppression. We found that subjectively and objectively invisible meaningful sentences and unpronounceable nonwords could be discriminated not only in the left posterior superior temporal sulcus (STS), but critically, also in the left middle frontal gyrus. We conclude that frontal lobes play a role in unconscious language processing and that activation of the frontal lobes per se might not be sufficient for achieving conscious awareness. PMID:24557638

  12. Neural Correlates of Subliminal Language Processing

    PubMed Central

    Axelrod, Vadim; Bar, Moshe; Rees, Geraint; Yovel, Galit

    2015-01-01

    Language is a high-level cognitive function, so exploring the neural correlates of unconscious language processing is essential for understanding the limits of unconscious processing in general. The results of several functional magnetic resonance imaging studies have suggested that unconscious lexical and semantic processing is confined to the posterior temporal lobe, without involvement of the frontal lobe—the regions that are indispensable for conscious language processing. However, previous studies employed a similarly designed masked priming paradigm with briefly presented single and contextually unrelated words. It is thus possible, that the stimulation level was insufficiently strong to be detected in the high-level frontal regions. Here, in a high-resolution fMRI and multivariate pattern analysis study we explored the neural correlates of subliminal language processing using a novel paradigm, where written meaningful sentences were suppressed from awareness for extended duration using continuous flash suppression. We found that subjectively and objectively invisible meaningful sentences and unpronounceable nonwords could be discriminated not only in the left posterior superior temporal sulcus (STS), but critically, also in the left middle frontal gyrus. We conclude that frontal lobes play a role in unconscious language processing and that activation of the frontal lobes per se might not be sufficient for achieving conscious awareness. PMID:24557638

  13. Time-Dependent Statistical and Correlation Properties of Neural Signals during Handwriting

    PubMed Central

    Rupasov, Valery I.; Lebedev, Mikhail A.; Erlichman, Joseph S.; Lee, Stephen L.; Leiter, James C.; Linderman, Michael

    2012-01-01

    To elucidate the cortical control of handwriting, we examined time-dependent statistical and correlational properties of simultaneously recorded 64-channel electroencephalograms (EEGs) and electromyograms (EMGs) of intrinsic hand muscles. We introduced a statistical method, which offered advantages compared to conventional coherence methods. In contrast to coherence methods, which operate in the frequency domain, our method enabled us to study the functional association between different neural regions in the time domain. In our experiments, subjects performed about 400 stereotypical trials during which they wrote a single character. These trials provided time-dependent EMG and EEG data capturing different handwriting epochs. The set of trials was treated as a statistical ensemble, and time-dependent correlation functions between neural signals were computed by averaging over that ensemble. We found that trial-to-trial variability of both the EMGs and EEGs was well described by a log-normal distribution with time-dependent parameters, which was clearly distinguished from the normal (Gaussian) distribution. We found strong and long-lasting EMG/EMG correlations, whereas EEG/EEG correlations, which were also quite strong, were short-lived with a characteristic correlation durations on the order of 100 ms or less. Our computations of correlation functions were restricted to the spectral range (13–30 Hz) of EEG signals where we found the strongest effects related to handwriting. Although, all subjects involved in our experiments were right-hand writers, we observed a clear symmetry between left and right motor areas: inter-channel correlations were strong if both channels were located over the left or right hemispheres, and 2–3 times weaker if the EEG channels were located over different hemispheres. Although we observed synchronized changes in the mean energies of EEG and EMG signals, we found that EEG/EMG correlations were much weaker than EEG/EEG and EMG/EMG correlations. The absence of strong correlations between EMG and EEG signals indicates that (i) a large fraction of the EEG signal includes electrical activity unrelated to low-level motor variability; (ii) neural processing of cortically-derived signals by spinal circuitry may reduce the correlation between EEG and EMG signals. PMID:22984455

  14. Thirty years of underwater acoustic signal processing in China

    NASA Astrophysics Data System (ADS)

    Li, Qihu

    2012-11-01

    Advances in technology and theory in 30 years of underwater acoustic signal processing and its applications in China are presented in this paper. The topics include research work in the field of underwater acoustic signal modeling, acoustic field matching, ocean waveguide and internal wave, the extraction and processing technique for acoustic vector signal information, the space/time correlation characteristics of low frequency acoustic channels, the invariant features of underwater target radiated noise, the transmission technology of underwater voice/image data and its anti-interference technique. Some frontier technologies in sonar design are also discussed, including large aperture towed line array sonar, high resolution synthetic aperture sonar, deep sea siren and deep sea manned subsea vehicle, diver detection sonar and demonstration projector of national ocean monitoring system in China, etc.

  15. 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.

  16. Quantifying two-dimensional nonstationary signal with power-law correlations by detrended fluctuation analysis

    NASA Astrophysics Data System (ADS)

    Fan, Qingju; Wu, Yonghong

    2015-08-01

    In this paper, we develop a new method for the multifractal characterization of two-dimensional nonstationary signal, which is based on the detrended fluctuation analysis (DFA). By applying to two artificially generated signals of two-component ARFIMA process and binomial multifractal model, we show that the new method can reliably determine the multifractal scaling behavior of two-dimensional signal. We also illustrate the applications of this method in finance and physiology. The analyzing results exhibit that the two-dimensional signals under investigation are power-law correlations, and the electricity market consists of electricity price and trading volume is multifractal, while the two-dimensional EEG signal in sleep recorded for a single patient is weak multifractal. The new method based on the detrended fluctuation analysis may add diagnostic power to existing statistical methods.

  17. Photon correlations through Raman virtual processes

    NASA Astrophysics Data System (ADS)

    de Melo E Souza, Reinaldo; Saraiva, Andre; Koiller, Belita

    In Raman inelastic scattering phonons are either absorbed or created, in what is respectively called an anti-Stokes (aS) or a Stokes (S) process. While these two processes are generally uncorrelated, it is possible that the same phonon generated by S is subsequently absorbed by aS. This two photon process is referred to as SaS. In a standard Raman process, conservation of energy forbids virtual phonons to play a role. However, in a SaS process these virtual phonons may be relevant as long as their lifetimes exceed the interval between the two scatterings. We derive the effective photon-photon interaction mediated by the phonon field. The effective hamiltonian is analogue to the one present in BCS superconductivity. The difference lies in the nature of the particles involved - since photons are bosons, there is no Fermi sea instability and no pair condensation. Still it is possible to obtain an attractive photon-photon interaction. Finally, we propose an experiment to detect the correlated photons emerging from a semiconductor. We pinpoint the material properties that might enhance this effect and discuss the possible technological applications of this idea as a correlated photon source. This work is part of the Brazilian National Institute for Science and Technology on Quantum Information. We also acknowledge partial support from the Brazilian agencies FAPERJ, CNPq and CAPES.

  18. Molecular signaling network complexity is correlated with cancer patient survivability

    PubMed Central

    Breitkreutz, Dylan; Hlatky, Lynn; Rietman, Edward; Tuszynski, Jack A.

    2012-01-01

    The 5-y survival for cancer patients after diagnosis and treatment is strongly dependent on tumor type. Prostate cancer patients have a >99% chance of survival past 5 y after diagnosis, and pancreatic patients have <6% chance of survival past 5 y. Because each cancer type has its own molecular signaling network, we asked if there are “signatures” embedded in these networks that inform us as to the 5-y survival. In other words, are there statistical metrics of the network that correlate with survival? Furthermore, if there are, can such signatures provide clues to selecting new therapeutic targets? From the Kyoto Encyclopedia of Genes and Genomes Cancer Pathway database we computed several conventional and some less conventional network statistics. In particular we found a correlation (R2 = 0.7) between degree-entropy and 5-y survival based on the Surveillance Epidemiology and End Results database. This correlation suggests that cancers that have a more complex molecular pathway are more refractory than those with less complex molecular pathway. We also found potential new molecular targets for drugs by computing the betweenness—a statistical metric of the centrality of a node—for the molecular networks. PMID:22615392

  19. Macrocell design for concurrent signal processing

    SciTech Connect

    Pope, S.P.; Brodersen, R.W.

    1983-01-01

    Macrocells serve as subsystems at the top level of the hardware design hierarchy. The authors present the macrocell design technique as applied to the implementation of real-time, sampled-data signal processing functions. The design of such circuits is particularly challenging due to the computationally intensive nature of signal-processing algorithms and the constraints of real-time operation. The most efficient designs make use of a high degree of concurrency-a property facilitated by the microcell approach. Two circuit projects whose development resulted largely from the macrocell methodology described are used as examples throughout the report: a linear-predictive vocoder circuit, and a front-end filter-bank chip for a speech recognition system. Both are monolithic multiprocessor implementations: the lpc vocoder circuit contains three processors, the filter-bank chip two processors. 10 references.

  20. 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.

  1. Enhanced multistatic active sonar signal processing.

    PubMed

    Zhao, Kexin; Liang, Junli; Karlsson, Johan; Li, Jian

    2013-07-01

    Multistatic active sonar systems involve the transmission and reception of multiple probing sequences and can achieve significantly enhanced performance of target detection and localization through exploiting spatial diversity. This paper mainly focuses on two signal processing aspects of such systems, namely, enhanced range-Doppler imaging and improved target parameter estimation. The main contributions of this paper are (1) a hybrid dense-sparse method is proposed to generate range-Doppler images with both low sidelobe levels and high accuracy; (2) a generalized K-Means clustering (GKC) method for target association is developed to associate the range measurements from different transmitter-receiver pairs, which is actually a range fitting procedure; (3) the extended invariance principle-based weighted least-squares method is developed for accurate target position and velocity estimation. The effectiveness of the proposed multistatic active sonar signal processing techniques is verified using numerical examples. PMID:23862808

  2. 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.

  3. Digital signal processing in acoustics. I

    NASA Astrophysics Data System (ADS)

    Davies, H.; McNeil, D. J.

    1985-11-01

    Digital signal processing techniques have gained steadily in importance over the past few years in many areas of science and engineering and have transformed the character of instrumentation used in laboratory and plant. This is particularly marked in acoustics, which has both benefited from the developments in signal processing and provided significant stimulus for these developments. As a result acoustical techniques are now used in a very wide range of applications and acoustics is one area in which digital signal processing is exploited to its limits. For example, the development of fast algorithms for computing Fourier transforms and the associated developments in hardware have led to remarkable advances in the use of spectral analysis as a means of investigating the nature and characteristics of acoustic sources. Speech research has benefited considerably in this respect, and, in a rather more technological application, spectral analysis of machinery noise provides information about changes in machine condition which may indicate imminent failure. More recently the observation that human and animal muscles emit low intensity noise suggests that spectral analysis of this noise may yield information about muscle structure and performance.

  4. Neural Networks for Signal Processing and Control

    NASA Astrophysics Data System (ADS)

    Hesselroth, Ted Daniel

    Neural networks are developed for controlling a robot-arm and camera system and for processing images. The networks are based upon computational schemes that may be found in the brain. In the first network, a neural map algorithm is employed to control a five-joint pneumatic robot arm and gripper through feedback from two video cameras. The pneumatically driven robot arm employed shares essential mechanical characteristics with skeletal muscle systems. To control the position of the arm, 200 neurons formed a network representing the three-dimensional workspace embedded in a four-dimensional system of coordinates from the two cameras, and learned a set of pressures corresponding to the end effector positions, as well as a set of Jacobian matrices for interpolating between these positions. Because of the properties of the rubber-tube actuators of the arm, the position as a function of supplied pressure is nonlinear, nonseparable, and exhibits hysteresis. Nevertheless, through the neural network learning algorithm the position could be controlled to an accuracy of about one pixel (~3 mm) after two hundred learning steps. Applications of repeated corrections in each step via the Jacobian matrices leads to a very robust control algorithm since the Jacobians learned by the network have to satisfy the weak requirement that they yield a reduction of the distance between gripper and target. The second network is proposed as a model for the mammalian vision system in which backward connections from the primary visual cortex (V1) to the lateral geniculate nucleus play a key role. The application of hebbian learning to the forward and backward connections causes the formation of receptive fields which are sensitive to edges, bars, and spatial frequencies of preferred orientations. The receptive fields are learned in such a way as to maximize the rate of transfer of information from the LGN to V1. Orientational preferences are organized into a feature map in the primary visual cortex by the application of lateral interactions during the learning phase. The organization of the mature network is compared to that found in the macaque monkey by several analytical tests. The capacity of the network to process images is investigated. By a method of reconstructing the input images in terms of V1 activities, the simulations show that images can be faithfully represented in V1 by the proposed network. The signal-to-noise ratio of the image is improved by the representation, and compression ratios of well over two-hundred are possible. Lateral interactions between V1 neurons sharpen their orientational tuning. We further study the dynamics of the processing, showing that the rate of decrease of the error of the reconstruction is maximized for the receptive fields used. Lastly, we employ a Fokker-Planck equation for a more detailed prediction of the error value vs. time. The Fokker-Planck equation for an underdamped system with a driving force is derived, yielding an energy-dependent diffusion coefficient which is the integral of the spectral densities of the force and the velocity of the system. The theory is applied to correlated noise activation and resonant activation. Simulation results for the error of the network vs time are compared to the solution of the Fokker-Planck equation.

  5. Using Seismic Signals to Forecast Volcanic Processes

    NASA Astrophysics Data System (ADS)

    Salvage, R.; Neuberg, J. W.

    2012-04-01

    Understanding seismic signals generated during volcanic unrest have the ability to allow scientists to more accurately predict and understand active volcanoes since they are intrinsically linked to rock failure at depth (Voight, 1988). In particular, low frequency long period signals (LP events) have been related to the movement of fluid and the brittle failure of magma at depth due to high strain rates (Hammer and Neuberg, 2009). This fundamentally relates to surface processes. However, there is currently no physical quantitative model for determining the likelihood of an eruption following precursory seismic signals, or the timing or type of eruption that will ensue (Benson et al., 2010). Since the beginning of its current eruptive phase, accelerating LP swarms (< 10 events per hour) have been a common feature at Soufriere Hills volcano, Montserrat prior to surface expressions such as dome collapse or eruptions (Miller et al., 1998). The dynamical behaviour of such swarms can be related to accelerated magma ascent rates since the seismicity is thought to be a consequence of magma deformation as it rises to the surface. In particular, acceleration rates can be successfully used in collaboration with the inverse material failure law; a linear relationship against time (Voight, 1988); in the accurate prediction of volcanic eruption timings. Currently, this has only been investigated for retrospective events (Hammer and Neuberg, 2009). The identification of LP swarms on Montserrat and analysis of their dynamical characteristics allows a better understanding of the nature of the seismic signals themselves, as well as their relationship to surface processes such as magma extrusion rates. Acceleration and deceleration rates of seismic swarms provide insights into the plumbing system of the volcano at depth. The application of the material failure law to multiple LP swarms of data allows a critical evaluation of the accuracy of the method which further refines current understanding of the relationship between seismic signals and volcanic eruptions. It is hoped that such analysis will assist the development of real time forecasting models.

  6. C language algorithms for digital signal processing

    SciTech Connect

    Embree, P.M.; Kimble, B.

    1991-01-01

    The use of the C programming language to construct digital signal-processing (DSP) algorithms for operation on high-performance personal computers is described in a textbook for engineering students. Chapters are devoted to the fundamental principles of DSP, basic C programming techniques, user-interface and disk-storage routines, filtering routines, discrete Fourier transforms, matrix and vector routines, and image-processing routines. Also included is a floppy disk containing a library of standard C mathematics, character-string, memory-allocation, and I/O functions; a library of DSP functions; and several sample DSP programs. 83 refs.

  7. Signal processing for ION mobility spectrometers

    NASA Technical Reports Server (NTRS)

    Taylor, S.; Hinton, M.; Turner, R.

    1995-01-01

    Signal processing techniques for systems based upon Ion Mobility Spectrometry will be discussed in the light of 10 years of experience in the design of real-time IMS. Among the topics to be covered are compensation techniques for variations in the number density of the gas - the use of an internal standard (a reference peak) or pressure and temperature sensors. Sources of noise and methods for noise reduction will be discussed together with resolution limitations and the ability of deconvolution techniques to improve resolving power. The use of neural networks (either by themselves or as a component part of a processing system) will be reviewed.

  8. Mixed signal learning by spike correlation propagation in feedback inhibitory circuits.

    PubMed

    Hiratani, Naoki; Fukai, Tomoki

    2015-04-01

    The brain can learn and detect mixed input signals masked by various types of noise, and spike-timing-dependent plasticity (STDP) is the candidate synaptic level mechanism. Because sensory inputs typically have spike correlation, and local circuits have dense feedback connections, input spikes cause the propagation of spike correlation in lateral circuits; however, it is largely unknown how this secondary correlation generated by lateral circuits influences learning processes through STDP, or whether it is beneficial to achieve efficient spike-based learning from uncertain stimuli. To explore the answers to these questions, we construct models of feedforward networks with lateral inhibitory circuits and study how propagated correlation influences STDP learning, and what kind of learning algorithm such circuits achieve. We derive analytical conditions at which neurons detect minor signals with STDP, and show that depending on the origin of the noise, different correlation timescales are useful for learning. In particular, we show that non-precise spike correlation is beneficial for learning in the presence of cross-talk noise. We also show that by considering excitatory and inhibitory STDP at lateral connections, the circuit can acquire a lateral structure optimal for signal detection. In addition, we demonstrate that the model performs blind source separation in a manner similar to the sequential sampling approximation of the Bayesian independent component analysis algorithm. Our results provide a basic understanding of STDP learning in feedback circuits by integrating analyses from both dynamical systems and information theory. PMID:25910189

  9. Mixed Signal Learning by Spike Correlation Propagation in Feedback Inhibitory Circuits

    PubMed Central

    Hiratani, Naoki; Fukai, Tomoki

    2015-01-01

    The brain can learn and detect mixed input signals masked by various types of noise, and spike-timing-dependent plasticity (STDP) is the candidate synaptic level mechanism. Because sensory inputs typically have spike correlation, and local circuits have dense feedback connections, input spikes cause the propagation of spike correlation in lateral circuits; however, it is largely unknown how this secondary correlation generated by lateral circuits influences learning processes through STDP, or whether it is beneficial to achieve efficient spike-based learning from uncertain stimuli. To explore the answers to these questions, we construct models of feedforward networks with lateral inhibitory circuits and study how propagated correlation influences STDP learning, and what kind of learning algorithm such circuits achieve. We derive analytical conditions at which neurons detect minor signals with STDP, and show that depending on the origin of the noise, different correlation timescales are useful for learning. In particular, we show that non-precise spike correlation is beneficial for learning in the presence of cross-talk noise. We also show that by considering excitatory and inhibitory STDP at lateral connections, the circuit can acquire a lateral structure optimal for signal detection. In addition, we demonstrate that the model performs blind source separation in a manner similar to the sequential sampling approximation of the Bayesian independent component analysis algorithm. Our results provide a basic understanding of STDP learning in feedback circuits by integrating analyses from both dynamical systems and information theory. PMID:25910189

  10. Digital payloads - Enhanced performance through signal processing

    NASA Astrophysics Data System (ADS)

    Bjornstrom, G.

    A transparent signal-processing payload architecture applicable to mobile communication satellites is introduced, and its features and implementation issues are discussed. In its basic form it is characterized by the formation of a large number of narrowband beams directed at the individual users on ground, and is demonstrated to offer improved transmit power efficiency, frequency-reuse capability and traffic-routing flexibility. The processor implementation is envisaged to make extensive use of digital processing functions and ASIC technology combined with advanced SAW techniques. In addition to its inherent attractive features, this architecture provides many of the benefits of full onboard regeneration and processing while preserving most of the flexibility of conventional analog transponders. Simplified derivatives of the basic configuration that offer reduced processing complexity while preserving the essential advantages gained are also presented. Although initially conceived for FDMA/SCPC-type traffic, the concept can also be adapted to other transmission formats.

  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.; Sloan, George R.; Spalding, Richard E.

    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. 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.

  14. An intelligent, onboard signal processing payload concept

    SciTech Connect

    Shriver, P. M.; Harikumar, J.; Briles, S. C.; Gokhale, M.

    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.

  15. Investigating signaling processes in membrane trafficking.

    PubMed

    Sharpe, Laura J; Brown, Andrew J

    2015-01-01

    Signaling and phosphorylation can be very difficult areas to explore, as there can be a lot of cross-talk between signaling pathways, and the stoichiometry of phosphorylation is often very low, and is typically transient. Here we describe an innovative assay using an immunoprecipitation approach, followed by a kinase assay, coupled with a phosphorylated substrate-specific antibody. We also indicate a database and prediction program that can be used in these situations.We apply these methods to investigate the regulation of ER-to-Golgi trafficking by protein phosphorylation of critical components in the trafficking machinery. Key components of this transport step are well known thanks to the pioneering work of the 2013 Nobel Prize winners James Rothman, Randy Schekman, and Thomas Sdhof. However, the regulation aspect of this process is relatively unexplored. PMID:25702110

  16. Discrete-time signal processing with DNA.

    PubMed

    Jiang, Hua; Salehi, Sayed Ahmad; Riedel, Marc D; Parhi, Keshab K

    2013-05-17

    We present a methodology for implementing discrete-time signal processing operations, such as filtering, with molecular reactions. The reactions produce time-varying output quantities of molecules as a function of time-varying input quantities according to a functional specification. This computation is robust and independent of the reaction rates, provided that the rate constants fall within coarse categories. We describe two approaches: one entails synchronization with a clock signal, implemented through sustained chemical oscillations; the other is "self-timed" or asynchronous. We illustrate the methodology by synthesizing a simple moving-average filter, a biquad filter, and a Fast Fourier Transform (FFT). Abstract molecular reactions for these filters and transforms are translated into DNA strand displacement reactions. The computation is validated through mass-action simulations of the DNA kinetics. Although a proof of concept for the time being, molecular filters and transforms have potential applications in fields such as biochemical sensing and drug delivery. PMID:23654264

  17. 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.

  18. Correlation functions in conformal invariant stochastic processes

    NASA Astrophysics Data System (ADS)

    Alcaraz, Francisco C.; Rittenberg, Vladimir

    2015-11-01

    We consider the problem of correlation functions in the stationary states of one-dimensional stochastic models having conformal invariance. If one considers the space dependence of the correlators, the novel aspect is that although one considers systems with periodic boundary conditions, the observables are described by boundary operators. From our experience with equilibrium problems one would have expected bulk operators. Boundary operators have correlators having critical exponents being half of those of bulk operators. If one studies the space-time dependence of the two-point function, one has to consider one boundary and one bulk operators. The Raise and Peel model has conformal invariance as can be shown in the spin 1/2 basis of the Hamiltonian which gives the time evolution of the system. This is an XXZ quantum chain with twisted boundary condition and local interactions. This Hamiltonian is integrable and the spectrum is known in the finite-size scaling limit. In the stochastic base in which the process is defined, the Hamiltonian is not local anymore. The mapping into an SOS model, helps to define new local operators. As a byproduct some new properties of the SOS model are conjectured. The predictions of conformal invariance are discussed in the new framework and compared with Monte Carlo simulations.

  19. 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.

  20. Neural correlates of feedback processing in toddlers.

    PubMed

    Meyer, Marlene; Bekkering, Harold; Janssen, Denise J C; de Bruijn, Ellen R A; Hunnius, Sabine

    2014-07-01

    External feedback provides essential information for successful learning. Feedback is especially important for learning in early childhood, as toddlers strongly rely on external signals to determine the consequences of their actions. In adults, many electrophysiological studies have elucidated feedback processes using a neural marker called the feedback-related negativity (FRN). The neural generator of the FRN is assumed to be the ACC, located in medial frontal cortex. As frontal brain regions are the latest to mature during brain development, it is unclear when in early childhood a functional feedback system develops. Is feedback differentiated on a neural level in toddlers and in how far is neural feedback processing related to children's behavioral adjustment? In an EEG experiment, we addressed these questions by measuring the brain activity and behavioral performance of 2.5-year-old toddlers while they played a feedback-guided game on a touchscreen. Electrophysiological results show differential brain activity for feedback with a more negative deflection for incorrect than correct outcomes, resembling the adult FRN. This provides the first neural evidence for feedback processing in toddlers. Notably, FRN amplitudes were predictive of adaptive behavior: the stronger the differential brain activity for feedback, the better the toddlers' adaptive performance during the game. Thus, already in early childhood toddlers' feedback-guided performance directly relates to the functionality of their neural feedback processing. Implications for early feedback-based learning as well as structural and functional brain development are discussed. PMID:24392905

  1. 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.

  2. 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.

  3. 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.

  4. 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

  5. Digital signal processing for radioactive decay studies

    SciTech Connect

    Miller, D.; Madurga, M.; Paulauskas, S. V.; Ackermann, D.; Heinz, S.; Hessberger, F. P.; Hofmann, S.; Grzywacz, R.; Miernik, K.; Rykaczewski, K.; Tan, H.

    2011-11-30

    The use of digital acquisition system has been instrumental in the investigation of proton and alpha emitting nuclei. Recent developments extend the sensitivity and breadth of the application. The digital signal processing capabilities, used predominately by UT/ORNL for decay studies, include digitizers with decreased dead time, increased sampling rates, and new innovative firmware. Digital techniques and these improvements are furthermore applicable to a range of detector systems. Improvements in experimental sensitivity for alpha and beta-delayed neutron emitters measurements as well as the next generation of superheavy experiments are discussed.

  6. Digital signal processing for radioactive decay studies

    NASA Astrophysics Data System (ADS)

    Miller, D.; Ackermann, D.; Grzywacz, R.; Heinz, S.; Heßberger, F. P.; Hofmann, S.; Madurga, M.; Miernik, K.; Paulauskas, S. V.; Rykaczewski, K.; Tan, H.

    2011-11-01

    The use of digital acquisition system has been instrumental in the investigation of proton and alpha emitting nuclei. Recent developments extend the sensitivity and breadth of the application. The digital signal processing capabilities, used predominately by UT/ORNL for decay studies, include digitizers with decreased dead time, increased sampling rates, and new innovative firmware. Digital techniques and these improvements are furthermore applicable to a range of detector systems. Improvements in experimental sensitivity for alpha and beta-delayed neutron emitters measurements as well as the next generation of superheavy experiments are discussed.

  7. Hardware System for Real-Time EMG Signal Acquisition and Separation Processing during Electrical Stimulation.

    PubMed

    Hsueh, Ya-Hsin; Yin, Chieh; Chen, Yan-Hong

    2015-09-01

    The study aimed to develop a real-time electromyography (EMG) signal acquiring and processing device that can acquire signal during electrical stimulation. Since electrical stimulation output can affect EMG signal acquisition, to integrate the two elements into one system, EMG signal transmitting and processing method has to be modified. The whole system was designed in a user-friendly and flexible manner. For EMG signal processing, the system applied Altera Field Programmable Gate Array (FPGA) as the core to instantly process real-time hybrid EMG signal and output the isolated signal in a highly efficient way. The system used the power spectral density to evaluate the accuracy of signal processing, and the cross correlation showed that the delay of real-time processing was only 250 μs. PMID:26210898

  8. Three-dimensional image signals: processing methods

    NASA Astrophysics Data System (ADS)

    Schiopu, Paul; Manea, Adrian; Craciun, Anca-Ileana; Craciun, Alexandru

    2010-11-01

    Over the years extensive studies have been carried out to apply coherent optics methods in real-time processing, communications and transmission image. This is especially true when a large amount of information needs to be processed, e.g., in high-resolution imaging. The recent progress in data-processing networks and communication systems has considerably increased the capacity of information exchange. We describe the results of literature investigation research of processing methods for the signals of the three-dimensional images. All commercially available 3D technologies today are based on stereoscopic viewing. 3D technology was once the exclusive domain of skilled computer-graphics developers with high-end machines and software. The images capture from the advanced 3D digital camera can be displayed onto screen of the 3D digital viewer with/ without special glasses. For this is needed considerable processing power and memory to create and render the complex mix of colors, textures, and virtual lighting and perspective necessary to make figures appear three-dimensional. Also, using a standard digital camera and a technique called phase-shift interferometry we can capture "digital holograms." These are holograms that can be stored on computer and transmitted over conventional networks. We present some research methods to process "digital holograms" for the Internet transmission and results.

  9. 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%.

  10. GLAST Burst Monitor Signal Processing System

    SciTech Connect

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

    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%.

  11. Computational problems and signal processing in SETI

    NASA Technical Reports Server (NTRS)

    Deans, Stanley R.; Cullers, D. K.; Stauduhar, Richard

    1991-01-01

    The Search for Extraterrestrial Intelligence (SETI), currently being planned at NASA, will require that an enormous amount of data (on the order of 10 exp 11 distinct signal paths for a typical observation) be analyzed in real time by special-purpose hardware. Even though the SETI system design is not based on maximum entropy and Bayesian methods (partly due to the real-time processing constraint), it is expected that enough data will be saved to be able to apply these and other methods off line where computational complexity is not an overriding issue. Interesting computational problems that relate directly to the system design for processing such an enormous amount of data have emerged. Some of these problems are discussed, along with the current status on their solution.

  12. 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.

  13. Digital signal processing using virtual instruments

    NASA Astrophysics Data System (ADS)

    Anderson, James A.; Korrapati, Raghu; Swain, Nikunja K.

    2000-08-01

    The area of test and measurement is changing rapidly because of the recent developments in software and hardware. The test and measurement systems are increasingly becoming PC based. Most of these PC based systems use graphical programming language to design test and measurement modules called virtual instruments (Vis). These Vis provide visual representation of dat or models, and make understanding of abstract concepts and algorithms easier. This allows users to express their ideas in a concise manner. One such virtual instruments package is LabVIEW from National Instruments Corporation at Austin, Texas. This software package is one of the first graphical programming products and is currently used in number of academic institutions, industries, Department of Defense graphical programming products and is currently sued in number of academic institutions, industries, Department of Defense, Department of Energy, and National Aeronautics and Space Administration for various test, measurement, and control applications. LabVIEW has an extensive built-in VI library that can be used to design and develop solutions for different applications. Besides using the built-in VI library that can be used to design and develop solutions for different applications. Besides using the built-in VI modules in LabVIEW, the user can design new VI modules easily. This paper discusses the use of LabVIEW to design and develop digital signal processing VI modules such as Fourier Analysis and Windowing. Instructors can use these modules to teach some of the signal processing concepts effectively.

  14. Digital Signal Processing in the GRETINA Spectrometer

    NASA Astrophysics Data System (ADS)

    Cromaz, Mario

    2015-10-01

    Developments in the segmentation of large-volume HPGe crystals has enabled the development of high-efficiency gamma-ray spectrometers which have the ability to track the path of gamma-rays scattering through the detector volume. This technology has been successfully implemented in the GRETINA spectrometer whose high efficiency and ability to perform precise event-by-event Doppler correction has made it an important tool in nuclear spectroscopy. Tracking has required the spectrometer to employ a fully digital signal processing chain. Each of the systems 1120 channels are digitized by 100 Mhz, 14-bit flash ADCs. Filters that provide timing and high-resolution energies are implemented on local FPGAs acting on the ADC data streams while interaction point locations and tracks, derived from the trace on each detector segment, are calculated in real time on a computing cluster. In this presentation we will give a description of GRETINA's digital signal processing system, the impact of design decisions on system performance, and a discussion of possible future directions as we look towards soon developing larger spectrometers such as GRETA with full 4 π solid angle coverage. This work was supported by the Office of Science in the Department of Energy under grant DE-AC02-05CH11231.

  15. The effects of quantization on signal processing

    NASA Technical Reports Server (NTRS)

    Montgomery, H. E.; Schell, E.

    1978-01-01

    Typically an analog signal from a space system is sampled, quantized by Analog-to-Digital (A/D) conversion, merged into a bit stream, communicated to a ground station, received by the ground station, and processed by the ground station to extract useful information for dissemination to the users. The cost of each of these steps is reduced as the number of quantization steps is reduced in the A/D converter. The number of quantization steps should be as small as possible without losing the required information content. This report deals specifically with the accuracy of averages as a function of the number of quantized samples used to compute the averages with the noise on the analog signal as a parameter. For example, the success of the Visible Infrared Spin Scan Radiometer (VISSR) Atmospheric Sounder (VAS) Demonstration depends upon temporally averaging multiple samples in an effort to reduce noise to a sufficiently low level such that temperature profile sounding is made possible. A tutorial description of this process is presented.

  16. 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.

  17. Active voltammetric microsensors with neural signal processing

    NASA Astrophysics Data System (ADS)

    Vogt, Michael C.; Skubal, Laura R.

    1999-02-01

    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.

  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. Parallel Processing with Digital Signal Processing Hardware and Software

    NASA Technical Reports Server (NTRS)

    Swenson, Cory V.

    1995-01-01

    The assembling and testing of a parallel processing system is described which will allow a user to move a Digital Signal Processing (DSP) application from the design stage to the execution/analysis stage through the use of several software tools and hardware devices. The system will be used to demonstrate the feasibility of the Algorithm To Architecture Mapping Model (ATAMM) dataflow paradigm for static multiprocessor solutions of DSP applications. The individual components comprising the system are described followed by the installation procedure, research topics, and initial program development.

  20. 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, Δt (in seconds), or on the optical spectral bandwidth, Δν (in Hertz), utilized-so long as ΔtΔν≫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 Δt=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

  1. 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

  2. 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.

  3. 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.

  4. The Structural Correlates of Statistical Information Processing during Speech Perception

    PubMed Central

    Deschamps, Isabelle; Hasson, Uri; Tremblay, Pascale

    2016-01-01

    The processing of continuous and complex auditory signals such as speech relies on the ability to use statistical cues (e.g. transitional probabilities). In this study, participants heard short auditory sequences composed either of Italian syllables or bird songs and completed a regularity-rating task. Behaviorally, participants were better at differentiating between levels of regularity in the syllable sequences than in the bird song sequences. Inter-individual differences in sensitivity to regularity for speech stimuli were correlated with variations in surface-based cortical thickness (CT). These correlations were found in several cortical areas including regions previously associated with statistical structure processing (e.g. bilateral superior temporal sulcus, left precentral sulcus and inferior frontal gyrus), as well other regions (e.g. left insula, bilateral superior frontal gyrus/sulcus and supramarginal gyrus). In all regions, this correlation was positive suggesting that thicker cortex is related to higher sensitivity to variations in the statistical structure of auditory sequences. Overall, these results suggest that inter-individual differences in CT within a distributed network of cortical regions involved in statistical structure processing, attention and memory is predictive of the ability to detect structural structure in auditory speech sequences. PMID:26919234

  5. A MUSIC-based method for SSVEP signal processing.

    PubMed

    Chen, Kun; Liu, Quan; Ai, Qingsong; Zhou, Zude; Xie, Sheng Quan; Meng, Wei

    2016-03-01

    The research on brain computer interfaces (BCIs) has become a hotspot in recent years because it offers benefit to disabled people to communicate with the outside world. Steady state visual evoked potential (SSVEP)-based BCIs are more widely used because of higher signal to noise ratio and greater information transfer rate compared with other BCI techniques. In this paper, a multiple signal classification based method was proposed for multi-dimensional SSVEP feature extraction. 2-second data epochs from four electrodes achieved excellent accuracy rates including idle state detection. In some asynchronous mode experiments, the recognition accuracy reached up to 100 %. The experimental results showed that the proposed method attained good frequency resolution. In most situations, the recognition accuracy was higher than canonical correlation analysis, which is a typical method for multi-channel SSVEP signal processing. Also, a virtual keyboard was successfully controlled by different subjects in an unshielded environment, which proved the feasibility of the proposed method for multi-dimensional SSVEP signal processing in practical applications. PMID:26831487

  6. Signal processing for a vestibular neurostimulator.

    PubMed

    Rubinstein, Jay T; Nie, Kaibao; Bierer, Steven; Ling, Leo; Phillips, James O

    2010-01-01

    An implanted vestibular neurostimulator has been developed based on commercial cochlear implant technology. It has been implanted chronically in Rhesus monkeys and the physiology of electrical stimulation of the vestibular periphery has been studied. We are currently proposing a human feasibility study of implantation of the device for the treatment of incapacitating Meniere's disease. Because no animal model of Meniere's disease exists, signal processing for such a device must be based on prior observations of human subjects who have suffered Meniere's attacks while their eye-movements could be quantified. Based on such data, and on the leading theories for the pathophysiology of a Meniere's attack, our animal data suggests that fixed amplitude, constant frequency biphasic pulse trains should be adequate to suppress the symptoms of an attack when they occur. The intensity of the stimuli and efficacy of vertigo suppression should be readily modulated either by amplitude or frequency adjustments. PMID:21097347

  7. 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.

  8. Exponential signal synthesis in digital pulse processing

    NASA Astrophysics Data System (ADS)

    Jordanov, Valentin T.

    2012-04-01

    Digital pulse processing allows the synthesis of exponential signals that can be used in pulse shaping and baseline restoration. A recursive algorithm for the synthesis of high-pass filters is presented and discussed in view of its application as a baseline restorer. The high-pass filter can be arranged in a gated baseline restorer configuration similar to widely used analog implementations. Two techniques to synthesize time-invariant, finite impulse response (FIR) cusp shapers are presented. The first technique synthesizes a true cusp shape in the discrete-time domain. This algorithm may be sensitive to round-off errors and may require a large amount of computational resources. The second method for synthesis of cusp shapes is suitable for implementation using integer arithmetic, particularly in hardware. This algorithm uses linear interpolation to synthesize close approximations of true cusp shapes. The algorithm does not introduce round-off errors and has been tested in hardware.

  9. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2008-11-01

    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 this application. We propose a calibration and beamforming strategy for PAFs including interference mitigation with power spectral density (PSD) estimation bias correction. Key efficiency metrics for single-feed instruments are extended to the array case and used to verify performance of the algorithms. These techniques are validated using numerical simulations and experimental data from a 19-element PAF on the Green Bank 20-m telescope.

  11. Restrictive Correlation Evaluation Of Processing Times In Target Tracking

    NASA Astrophysics Data System (ADS)

    Horn, O.; Ciccotelli, J.; Husson, R.

    1989-04-01

    As far as target tracking is concerned in the robotics field, the picture processing phase consists in finding out the location of the object in the scene within a minimum of time. Therefore, we require quite a new approach of "restrictive correlation" which combines optical function (real time edges extraction) and data processing functions (multilevel correlation). This latter as to show the best matching place between a model of the object and the search area. It consists of a multilevel thresholding followed by a model image mapping at each level. We find out the localization of the object by a weighting addition of each obtained result. The time required to obtain such a result is directly linked to the number of selected points at the thresholding stage.Therefore, we develop an analytical method to count the treated points according to the threshold levels. The grey levels of the picture's points are taken as a realization of a random process of which we measure the statistical characteristics (mean, standard deviation). If we refer to the theory of signal processing, this enables us to determine, by means of calculation, the number of points over a given threshold within an image for a kind of scene. These calculations are carried out for various levels. Afterward, their results are compared with the figures experimentally measured. On this way, we valid a relation which links the execution time of a correlation to its parameters. Consequently, this evaluation gives a quantitative criterion for the values which point out the limits with regard to the choice of thresholds ; the time available for the correlation being previously defined according to the amplitude of the search area and the maximal speed authorized for the target.

  12. Automated Processing of Two-Dimensional Correlation Spectra

    NASA Astrophysics Data System (ADS)

    Sengstschmid, Helmut; Sterk, Heinz; Freeman, Ray

    1998-04-01

    An automated scheme is described which locates the centers of cross peaks in two-dimensional correlation spectra, even under conditions of severe overlap. Double-quantum-filtered correlation (DQ-COSY) spectra have been investigated, but the method is also applicable to TOCSY and NOESY spectra. The search criterion is the intrinsic symmetry (or antisymmetry) of cross-peak multiplets. An initial global search provides the preliminary information to build up a two-dimensional "chemical shift grid." All genuine cross peaks must be centered at intersections of this grid, a fact that reduces the extent of the subsequent search program enormously. The program recognizes cross peaks by examining the symmetry of signals in a test zone centered at a grid intersection. This "symmetry filter" employs a "lowest value algorithm" to discriminate against overlapping responses from adjacent multiplets. A progressive multiplet subtraction scheme provides further suppression of overlap effects. The processed two-dimensional correlation spectrum represents cross peaks as points at the chemical shift coordinates, with some indication of their relative intensities. Alternatively, the information is presented in the form of a correlation table. The authenticity of a given cross peak is judged by a set of "confidence criteria" expressed as numerical parameters. Experimental results are presented for the 400-MHz double-quantum-filtered COSY spectrum of 4-androsten-3,17-dione, a case where there is severe overlap.

  13. Advances in white-light optical signal processing

    NASA Technical Reports Server (NTRS)

    Yu, F. T. S.

    1984-01-01

    A technique that permits signal processing operations which can be carried out by white light source is described. The method performs signal processing that obeys the concept of coherent light rather than incoherent optics. Since the white light source contains all the color wavelengths of the visible light, the technique is very suitable for color signal processing.

  14. Neurophysiological investigation of spontaneous correlated and anticorrelated fluctuations of the BOLD signal

    PubMed Central

    Keller, Corey J.; Bickel, Stephan; Honey, Christopher J.; Groppe, David M.; Entz, Laszlo; Craddock, R. Cameron; Lado, Fred A.; Kelly, Clare; Milham, Michael; Mehta, Ashesh D.

    2013-01-01

    Analyses of intrinsic fMRI BOLD signal fluctuations reliably reveal correlated and anticorrelated functional networks in the brain. Since the BOLD signal is an indirect measure of neuronal activity, and anticorrelations can be introduced by preprocessing steps such as global signal regression (GSR), the neurophysiological significance of correlated and anticorrelated BOLD fluctuations is a source of debate. Here, we address this question by examining the correspondence between the spatial organization of correlated BOLD fluctuations and correlated fluctuations in electrophysiological high gamma power (HGP) signals recorded directly from the cortical surface of 5 patients. We demonstrate that both positive and negative BOLD correlations have neurophysiological correlates reflected in fluctuations of spontaneous neuronal activity. Although applying GSR to BOLD signals results in some BOLD anticorrelations that are not apparent in the ECoG data, it enhances the neuronal-hemodynamic correspondence overall. Together, these findings provide support for the neurophysiological fidelity of BOLD correlations and anticorrelations. PMID:23575832

  15. Interactions between visceral afferent signaling and stimulus processing

    PubMed Central

    Critchley, Hugo D.; Garfinkel, Sarah N.

    2015-01-01

    Visceral afferent signals to the brain influence thoughts, feelings and behavior. Here we highlight the findings of a set of empirical investigations in humans concerning body-mind interaction that focus on how feedback from states of autonomic arousal shapes cognition and emotion. There is a longstanding debate regarding the contribution of the body to mental processes. Recent theoretical models broadly acknowledge the role of (autonomically-mediated) physiological arousal to emotional, social and motivational behaviors, yet the underlying mechanisms are only partially characterized. Neuroimaging is overcoming this shortfall; first, by demonstrating correlations between autonomic change and discrete patterns of evoked, and task-independent, neural activity; second, by mapping the central consequences of clinical perturbations in autonomic response and; third, by probing how dynamic fluctuations in peripheral autonomic state are integrated with perceptual, cognitive and emotional processes. Building on the notion that an important source of the brain's representation of physiological arousal is derived from afferent information from arterial baroreceptors, we have exploited the phasic nature of these signals to show their differential contribution to the processing of emotionally-salient stimuli. This recent work highlights the facilitation at neural and behavioral levels of fear and threat processing that contrasts with the more established observations of the inhibition of central pain processing during baroreceptors activation. The implications of this body-brain-mind axis are discussed. PMID:26379481

  16. Interactions between visceral afferent signaling and stimulus processing.

    PubMed

    Critchley, Hugo D; Garfinkel, Sarah N

    2015-01-01

    Visceral afferent signals to the brain influence thoughts, feelings and behavior. Here we highlight the findings of a set of empirical investigations in humans concerning body-mind interaction that focus on how feedback from states of autonomic arousal shapes cognition and emotion. There is a longstanding debate regarding the contribution of the body to mental processes. Recent theoretical models broadly acknowledge the role of (autonomically-mediated) physiological arousal to emotional, social and motivational behaviors, yet the underlying mechanisms are only partially characterized. Neuroimaging is overcoming this shortfall; first, by demonstrating correlations between autonomic change and discrete patterns of evoked, and task-independent, neural activity; second, by mapping the central consequences of clinical perturbations in autonomic response and; third, by probing how dynamic fluctuations in peripheral autonomic state are integrated with perceptual, cognitive and emotional processes. Building on the notion that an important source of the brain's representation of physiological arousal is derived from afferent information from arterial baroreceptors, we have exploited the phasic nature of these signals to show their differential contribution to the processing of emotionally-salient stimuli. This recent work highlights the facilitation at neural and behavioral levels of fear and threat processing that contrasts with the more established observations of the inhibition of central pain processing during baroreceptors activation. The implications of this body-brain-mind axis are discussed. PMID:26379481

  17. Meteor radar signal processing and error analysis

    NASA Astrophysics Data System (ADS)

    Kang, Chunmei

    Meteor wind radar systems are a powerful tool for study of the horizontal wind field in the mesosphere and lower thermosphere (MLT). While such systems have been operated for many years, virtually no literature has focused on radar system error analysis. The instrumental error may prevent scientists from getting correct conclusions on geophysical variability. The radar system instrumental error comes from different sources, including hardware, software, algorithms and etc. Radar signal processing plays an important role in radar system and advanced signal processing algorithms may dramatically reduce the radar system errors. In this dissertation, radar system error propagation is analyzed and several advanced signal processing algorithms are proposed to optimize the performance of radar system without increasing the instrument costs. The first part of this dissertation is the development of a time-frequency waveform detector, which is invariant to noise level and stable to a wide range of decay rates. This detector is proposed to discriminate the underdense meteor echoes from the background white Gaussian noise. The performance of this detector is examined using Monte Carlo simulations. The resulting probability of detection is shown to outperform the often used power and energy detectors for the same probability of false alarm. Secondly, estimators to determine the Doppler shift, the decay rate and direction of arrival (DOA) of meteors are proposed and evaluated. The performance of these estimators is compared with the analytically derived Cramer-Rao bound (CRB). The results show that the fast maximum likelihood (FML) estimator for determination of the Doppler shift and decay rate and the spatial spectral method for determination of the DOAs perform best among the estimators commonly used on other radar systems. For most cases, the mean square error (MSE) of the estimator meets the CRB above a 10dB SNR. Thus meteor echoes with an estimated SNR below 10dB are discarded due to the potential of producing a biased estimate. The precision of the estimated parameters can then be computed using their CRB values as a proxy for the estimated variance. These errors propagate to form the instrumental errors on the height and horizontal wind measurements. Thirdly, the interferometer configuration of interferometric meteor radar system is studied. The interferometer uses the phase differences measured at different sensor pairs to determine the DOA of the meteor trail. Typically Jones cross is used in most of current meteor radar systems, such as MEDAC and SKYiMet. We have evaluated this configuration with other array geometries,such as 'T', 'L' and circular array to examine their performance on the precision of the DOA estimates. The results show that 'T' array has an overall better CRB than other geometries, while with the yagi antenna pattern as a course determination of the DOA range, the circular array performs the best with the lowest sidelobes on the spatial spectral. A Matlab based planar array design package designed for determination and visualization of the DOA estimation performance for a user designed antenna array was developed. Fourthly, based on the special configuration of the South Pole COBRA system, a low cost computational phase calibration method is proposed. Accurate knowledge of the receiver phase ofsets is another factor that can affect system performance. Lastly, the postprocessing results of the meteor echoes collected during 2005 from the South Pole COBRA system are presented. This radar system is shown to have a precision of 2m/s in the horizontal winds, an azimuth precision of 1o, and an elevation precision of 3o. Preliminary scientific results are presented to verify the effectiveness of our processing scheme, and include the seasonal variation of meteor rates as a function of height, and the vertical structure of large semidiurnal tide observed over the South Pole austral summer. The processing schemes and error analysis methods presented in this dissertation can be easily extended to other meteor radar systems with minor modifications of the associated radar parameters. The analysis results presented herein represent the first detailed study of the errors and biases associated with VHF meteor radar system. With better understanding of radar signal processing and system error propagation, scientists will be able to separate instrumental error from geophysical variability resulting in an improved understanding of short timescale atmospheric variations.

  18. 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

  19. 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.

  20. FPGA Signal Processing for Real-Time Dust Detection

    NASA Astrophysics Data System (ADS)

    Thomas, E.; Auer, S.; Collette, A.; Drake, K.; Horanyi, M.; Munsat, T.; Shu, A. J.; Sternovsky, Z.

    2011-12-01

    The NASA Lunar Science Institute's Colorado Center for Lunar Dust and Atmospheric Studies (CCLDAS) has completed the construction of a 3MV lunar dust accelerator facility to investigate the effects of micrometeoroid impacts on the surface of the Moon. Such impacts are believed to contribute to the lunar exosphere, and might be primarily responsible for the mixing and redistribution of the lunar soil. Beyond physical understanding of lunar and other airless bodies, the accelerator will also offer experimental services for the calibration of future instruments. This system consists of calibrated image-charge detectors sensitive from 1.0E4 - 4.0E6 electrons per particle. A cross-correlation algorithm, implemented on a field programmable gate array (FPGA), is used to detect signals lost within noise. The parallelism and easy implementation of FPGA algorithms offer a good solution for real-time, fast filtration schemes. The implementation of this system, as well as the usefulness of FPGAs to the broader context of digital filtration, is presented. The technique is of general interest for any signal processing problems in a low signal-to-noise environment where the signals are of a known shape and can be easily realizable using National Instruments' LabVIEW development tools.

  1. User's manual SIG: a general-purpose signal processing program

    SciTech Connect

    Lager, D.; Azevedo, S.

    1983-10-25

    SIG is a general-purpose signal processing, analysis, and display program. Its main purpose is to perform manipulations on time- and frequency-domain signals. However, it has been designed to ultimately accommodate other representations for data such as multiplexed signals and complex matrices. Many of the basic operations one would perform on digitized data are contained in the core SIG package. Out of these core commands, more powerful signal processing algorithms may be built. Many different operations on time- and frequency-domain signals can be performed by SIG. They include operations on the samples of a signal, such as adding a scalar to each sample, operations on the entire signal such as digital filtering, and operations on two or more signals such as adding two signals. Signals may be simulated, such as a pulse train or a random waveform. Graphics operations display signals and spectra.

  2. 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.

  3. Closed orbit feedback with digital signal processing

    SciTech Connect

    Chung, Y.; Kirchman, J.; Lenkszus, F.

    1994-08-01

    The closed orbit feedback experiment conducted on the SPEAR using the singular value decomposition (SVD) technique and digital signal processing (DSP) is presented. The beam response matrix, defined as beam motion at beam position monitor (BPM) locations per unit kick by corrector magnets, was measured and then analyzed using SVD. Ten BPMs, sixteen correctors, and the eight largest SVD eigenvalues were used for closed orbit correction. The maximum sampling frequency for the closed loop feedback was measured at 37 Hz. Using the proportional and integral (PI) control algorithm with the gains Kp = 3 and K{sub I} = 0.05 and the open-loop bandwidth corresponding to 1% of the sampling frequency, a correction bandwidth ({minus}3 dB) of approximately 0.8 Hz was achieved. Time domain measurements showed that the response time of the closed loop feedback system for 1/e decay was approximately 0.25 second. This result implies {approximately} 100 Hz correction bandwidth for the planned beam position feedback system for the Advanced Photon Source storage ring with the projected 4-kHz sampling frequency.

  4. Microwave photonic delay line signal processing.

    PubMed

    Diehl, John F; Singley, Joseph M; Sunderman, Christopher E; Urick, Vincent J

    2015-11-01

    This paper provides a path for the design of state-of-the-art fiber-optic delay lines for signal processing. The theoretical forms for various radio-frequency system performance metrics are derived for four modulation types: X- and Z-cut Mach-Zehnder modulators, a phase modulator with asymmetric Mach-Zehnder interferometer, and a polarization modulator with control waveplate and polarizing beam splitter. Each modulation type is considered to cover the current and future needs for ideal system designs. System gain, compression point, and third-order output intercept point are derived from the transfer matrices for each modulation type. A discussion of optical amplifier placement and fiber-effect mitigation is offered. The paper concludes by detailing two high-performance delay lines, built for unique applications, that exhibit performance levels an order of magnitude better than commercial delay lines. This paper should serve as a guide to maximizing the performance of future systems and offer a look into current and future research being done to further improve photonics technologies. PMID:26560620

  5. All GaAs signal processing architecture

    SciTech Connect

    Geideman, W.A.; Rasset, T.L.; Misko, T.A.; Wine, J.W.

    1987-09-01

    The architecture, design, simulation, and evaluation of an all-GaAs vector signal processor for on-board space-system applications are described. The vector processor, whose architecture is based on a modular, building-block approach, consists of three main units: the control/scalar processor, the vector memory, and the execution unit. Each unit functions independently from the other, enabling the data addressing, data processing, and control to operate in parallel rather than serial manner. The GaAs processor's performance was compared with the performance of several commercial processors including the CMOS MIPS processor. When the latter was substituted for the GaAs processor in the same vector processor architecture, the performance/power ratio was nearly equal to that of the GaAs processor, but GaAs has demonstrated a higher performance upper bound. It was found that, in addition to high performance, the GaAs vector processor has fault-tolerant features and is flexible and radiation hard.

  6. 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.

  7. 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.

  8. Volumetric signal processing hardware acceleration for mine detection

    NASA Astrophysics Data System (ADS)

    Desai, Tapan J.; Hintz, Kenneth J.

    2003-09-01

    Digital signal processing algorithms for the detection of landmines using ground penetrating radar are computationally intensive if not due to algorithmic complexity, then due to the vast quantity of data which must be processed in real-time. As a result of this, surface area coverage rates using general purpose computers are limited without an additional investment in multiple central processing units and the parallelization of the executable. This results in an excess of unused resources with the associated cost both in terms of monetary cost and power consumption. The increase in power consumption alone also causes an increase cost in cooling and the requirement for larger prime power and/or reduced battery life. Field programmable gate array (FPGA) hardware devices are reconfigurable in seconds and they can be reprogrammed in the field using relatively standard equipment such as a laptop computer. A secondary advantage of re-configurable dedicated hardware is the flexibility it affords in terms of the specific signal processing algorithm being executed on the re-configurable computing device. As an example of this type of hardware optimization of an algorithm, this paper describes an implementation of volumetric (3D) template matching using re-configurable digital hardware, namely an FPGA. This is a viable alternative for the acceleration of digital signal processing and directly results in an increase in mine detection area coverage rates for a relatively small investment. This also results in a more compact, fieldable real-time implementations of landmine detection algorithms and a common mine detector whose hardware is standard but whose optimized algorithms are downloaded into the FPGA for the particular minefield to be cleared. In this paper we give a quantitative analysis of the increase in execution speed achieved by performing cross correlation of large template sizes on large data.

  9. Intelligent, onboard signal processing payload concept, addendum :

    SciTech Connect

    Shriver, P. M.; Harikumar, J.; Briles, S. C.; Gokhale, M.

    2003-01-01

    This document addresses two issues in the original paper entitled 'An Intelligent, Onboard Signal Processing Payload Concept' submitted to the SPIE AeroSense 2003 C0nference.l Since the original paper submission, and prior to the scheduled presentation, a correction has been made to one of the figures in the original paper and an update has been performed to the software simulation of the payload concept. The figure, referred to as Figure 8. Simulation Results in the original paper, contains an error in the voltage versus the capacity drained chart. This chart does not correctly display the voltage changes experienced by the battery module due to the varying discharge rates. This error is an artifact of the procedure used to graph the data. Additionally, the original version of the Simulation related the algorithm execution rate to the lightning event rate regardless of the number of events in the ring buffer. This feature was mentioned in section 5. Simulation Results of the original paper. A correction was also made to the size of the ring buffer. Incorrect information was provided to the authors that placed the number of possible events at 18,310. Corrected information has since been obtained that specifies the ring buffer can typically hold only 1,000 events. This has a significant impact on the APM process and the number of events lost when the size of the ring buffer is exceeded. Also, upon further analysis, it was realized that the simulation contained an error in the recording of the number of events in the ring buffer. The faster algorithms, LMS and ML, should have been able to process all events during the simulation time interval, but the initial results did not reflect this characteristic. The updated version of the simulation appropriately handles the number of algorithm executions and recording of events in the ring buffer as well as uses the correct size for the ring buffer. These improvements to the simulation and subsequent results are discussed in this document.

  10. 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

  11. 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.

  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. Microwave signal processing with photorefractive dynamic holography

    NASA Astrophysics Data System (ADS)

    Fotheringham, Edeline B.

    Have you ever found yourself listening to the music playing from the closest stereo rather than to the bromidic (uninspiring) person speaking to you? Your ears receive information from two sources but your brain listens to only one. What if your cell phone could distinguish among signals sharing the same bandwidth too? There would be no "full" channels to stop you from placing or receiving a call. This thesis presents a nonlinear optical circuit capable of distinguishing uncorrelated signals that have overlapping temporal bandwidths. This so called autotuning filter is the size of a U.S. quarter dollar and requires less than 3 mW of optical power to operate. It is basically an oscillator in which the losses are compensated with dynamic holographic gain. The combination of two photorefractive crystals in the resonator governs the filter's winner-take-all dynamics through signal-competition for gain. This physical circuit extracts what is mathematically referred to as the largest principal component of its spatio-temporal input space. The circuit's practicality is demonstrated by its incorporation in an RF-photonic system. An unknown mixture of unknown microwave signals, received by an antenna array, constitutes the input to the system. The output electronically returns one of the original microwave signals. The front-end of the system down converts the 10 GHz microwave signals and amplifies them before the signals phase modulate optical beams. The optical carrier is suppressed from these beams so that it may not be considered as a signal itself to the autotuning filter. The suppression is achieved with two-beam coupling in a single photorefractive crystal. The filter extracts the more intense of the signals present on the carrier-suppressed input beams. The detection of the extracted signal restores the microwave signal to an electronic form. The system, without the receiving antenna array, is packaged in a 13 x 18 x 6″ briefcase. Its power consumption equals that of a regular 50 W household light bulb. The system was shipped to different parts of the country for real-time demonstrations of signal separation thus also validating its claim to robustness.

  14. Adaptive Noise Suppression Using Digital Signal Processing

    NASA Technical Reports Server (NTRS)

    Kozel, David; Nelson, Richard

    1996-01-01

    A signal to noise ratio dependent adaptive spectral subtraction algorithm is developed to eliminate noise from noise corrupted speech signals. The algorithm determines the signal to noise ratio and adjusts the spectral subtraction proportion appropriately. After spectra subtraction low amplitude signals are squelched. A single microphone is used to obtain both eh noise corrupted speech and the average noise estimate. This is done by determining if the frame of data being sampled is a voiced or unvoiced frame. During unvoice frames an estimate of the noise is obtained. A running average of the noise is used to approximate the expected value of the noise. Applications include the emergency egress vehicle and the crawler transporter.

  15. Proposal for Memristors in Signal Processing

    NASA Astrophysics Data System (ADS)

    Mouttet, B.

    Recently researchers at Hewlett-Packard have announced the discovery of a new material having resistance switching characteristics and which has been characterized as a fourth fundamental circuit component called the “memristor”[1]. It is proposed to combine such memristors with operational amplifier circuitry and fixed resistor elements so as to form a programmable signal processor capable of selective transmission and multiplexing of multiple signals for applications in communications and programmable drive waveform control.

  16. 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.

  17. Signal processing for passive detection and classification of underwater acoustic signals

    NASA Astrophysics Data System (ADS)

    Chung, Kil Woo

    2011-12-01

    This dissertation examines signal processing for passive detection, classification and tracking of underwater acoustic signals for improving port security and the security of coastal and offshore operations. First, we consider the problem of passive acoustic detection of a diver in a shallow water environment. A frequency-domain multi-band matched-filter approach to swimmer detection is presented. The idea is to break the frequency contents of the hydrophone signals into multiple narrow frequency bands, followed by time averaged (about half of a second) energy calculation over each band. Then, spectra composed of such energy samples over the chosen frequency bands are correlated to form a decision variable. The frequency bands with highest Signal/Noise ratio are used for detection. The performance of the proposed approach is demonstrated for experimental data collected for a diver in the Hudson River. We also propose a new referenceless frequency-domain multi-band detector which, unlike other reference-based detectors, does not require a diver specific signature. Instead, our detector matches to a general feature of the diver spectrum in the high frequency range: the spectrum is roughly periodic in time and approximately flat when the diver exhales. The performance of the proposed approach is demonstrated by using experimental data collected from the Hudson River. Moreover, we present detection, classification and tracking of small vessel signals. Hydroacoustic sensors can be applied for the detection of noise generated by vessels, and this noise can be used for vessel detection, classification and tracking. This dissertation presents recent improvements aimed at the measurement and separation of ship DEMON (Detection of Envelope Modulation on Noise) acoustic signatures in busy harbor conditions. Ship signature measurements were conducted in the Hudson River and NY Harbor. The DEMON spectra demonstrated much better temporal stability compared with the full ship spectra and were measured at distances up to 7 km. The combination of cross-correlation and DEMON methods allows separation of the acoustic signatures of ships in busy urban environments. Finally, we consider the extension of this algorithm for vessel tracking using phase measurement of the DEMON signal recorded by two or more hydrophones. Tests conducted in the Hudson River and NY Bay confirmed opportunity of Direction of Arrival (DOA) funding using the phase DEMON method.

  18. Statistical measures of Planck scale signal correlations in interferometers

    SciTech Connect

    Hogan, Craig J.; Kwon, Ohkyung

    2015-06-22

    A model-independent statistical framework is presented to interpret data from systems where the mean time derivative of positional cross correlation between world lines, a measure of spreading in a quantum geometrical wave function, is measured with a precision smaller than the Planck time. The framework provides a general way to constrain possible departures from perfect independence of classical world lines, associated with Planck scale bounds on positional information. A parametrized candidate set of possible correlation functions is shown to be consistent with the known causal structure of the classical geometry measured by an apparatus, and the holographic scaling of information suggested by gravity. Frequency-domain power spectra are derived that can be compared with interferometer data. As a result, simple projections of sensitivity for specific experimental set-ups suggests that measurements will directly yield constraints on a universal time derivative of the correlation function, and thereby confirm or rule out a class of Planck scale departures from classical geometry.

  19. Psychophysiological correlates of face processing in social phobia.

    PubMed

    Kolassa, Iris-Tatjana; Miltner, Wolfgang H R

    2006-11-01

    Social phobia has been associated with abnormal processing of angry faces, which directly signal disapproval--a situation that social phobics fear. This study investigated the electrophysiological correlates of emotional face processing in socially phobic and non-phobic individuals. Subjects identified either the gender (modified emotional Stroop task) or the expression of angry, happy, or neutral faces. Social phobics showed no deviations from controls in reaction times, heart rates, P1, or P2 amplitudes in response to angry faces, although elevated FSS scores were associated with higher P1 amplitudes in social phobic persons. In addition, social phobic persons showed enhanced right temporo-parietal N170 amplitudes in response to angry faces in the emotion identification task. Furthermore, higher scores on the Social Phobia and Anxiety Inventory (SPAI) were associated as a trend with larger N170 amplitudes in response to angry faces in the emotion identification task. Thus, the present results suggest that social phobics show abnormalities in the early visual processing of angry faces, as reflected by the enhanced right-hemispheric N170 when the emotion of the angry face was the focus of attention, while behavioral responses and heart rates showed no evidence for preferred processing of angry facial expressions. PMID:16970928

  20. Laser heterodyne interferometric signal processing method based on rising edge locking with high frequency clock signal.

    PubMed

    Zhang, Enzheng; Chen, Benyong; Yan, Liping; Yang, Tao; Hao, Qun; Dong, Wenjun; Li, Chaorong

    2013-02-25

    A novel phase measurement method composed of the rising-edge locked signal processing and the digital frequency mixing is proposed for laser heterodyne interferometer. The rising-edge locked signal processing, which employs a high frequency clock signal to lock the rising-edges of the reference and measurement signals, not only can improve the steepness of the rising-edge, but also can eliminate the error counting caused by multi-rising-edge phenomenon in fringe counting. The digital frequency mixing is realized by mixing the digital interference signal with a digital base signal that is different from conventional frequency mixing with analogue signals. These signal processing can improve the measurement accuracy and enhance anti-interference and measurement stability. The principle and implementation of the method are described in detail. An experimental setup was constructed and a series of experiments verified the feasibility of the method in large displacement measurement with high speed and nanometer resolution. PMID:23481996

  1. 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.

  2. 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

  3. Review of biomedical signal and image processing

    PubMed Central

    2013-01-01

    This article is a review of the book “Biomedical Signal and Image Processing” by Kayvan Najarian and Robert Splinter, which is published by CRC Press, Taylor & Francis Group. It will evaluate the contents of the book and discuss its suitability as a textbook, while mentioning highlights of the book, and providing comparison with other textbooks.

  4. 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.

  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. Nonlinear filtering for robust signal processing

    SciTech Connect

    Palmieri, F.

    1987-01-01

    A generalized framework for the description and design of a large class of nonlinear filters is proposed. Such a family includes, among others, the newly defined Ll-estimators, that generalize the order statistic filters (L-filters) and the nonrecursive linear filters (FIR). Such estimators are particularly efficient in filtering signals that do not follow gaussian distributions. They can be designed to restore signals and images corrupted by noise of impulsive type. Such filters are very appealing since they are suitable for being made robust against perturbations on the assumed model, or insensitive to the presence of spurious outliers in the data. The linear part of the filter is used to characterize their essential spectral behavior. It can be constrained to a given shape to obtain nonlinear filters that combine given frequency characteristics and noise immunity. The generalized nonlinear filters can also be used adaptively with the coefficients computed dynamically via LMS or RLS algorithms.

  7. Information processing in multi-step signaling pathways

    NASA Astrophysics Data System (ADS)

    Ganesan, Ambhi; Hamidzadeh, Archer; Zhang, Jin; Levchenko, Andre

    Information processing in complex signaling networks is limited by a high degree of variability in the abundance and activity of biochemical reactions (biological noise) operating in living cells. In this context, it is particularly surprising that many signaling pathways found in eukaryotic cells are composed of long chains of biochemical reactions, which are expected to be subject to accumulating noise and delayed signal processing. Here, we challenge the notion that signaling pathways are insulated chains, and rather view them as parts of extensively branched networks, which can benefit from a low degree of interference between signaling components. We further establish conditions under which this pathway organization would limit noise accumulation, and provide evidence for this type of signal processing in an experimental model of a calcium-activated MAPK cascade. These results address the long-standing problem of diverse organization and structure of signaling networks in live cells.

  8. 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.

  9. Frequency domain laser velocimeter signal processor: A new signal processing scheme

    NASA Technical Reports Server (NTRS)

    Meyers, James F.; Clemmons, James I., Jr.

    1987-01-01

    A new scheme for processing signals from laser velocimeter systems is described. The technique utilizes the capabilities of advanced digital electronics to yield a smart instrument that is able to configure itself, based on the characteristics of the input signals, for optimum measurement accuracy. The signal processor is composed of a high-speed 2-bit transient recorder for signal capture and a combination of adaptive digital filters with energy and/or zero crossing detection signal processing. The system is designed to accept signals with frequencies up to 100 MHz with standard deviations up to 20 percent of the average signal frequency. Results from comparative simulation studies indicate measurement accuracies 2.5 times better than with a high-speed burst counter, from signals with as few as 150 photons per burst.

  10. Fluctuations and correlations as a signal of deconfinement

    SciTech Connect

    Konchakovski, V. P.; Bratkovskaya, E. L.; Cassing, W.; Gorenstein, M. I.

    2012-06-15

    Event-by-event fluctuations of the K/{pi}, K/p, and p/{pi} ratio in central AA collisions have been studied for SPS and RHIC energies. The Hadron-String-Dynamical transport approach (HSD) can qualitatively reproduce the measured excitation function for the K/{pi} ratio fluctuations. The di-jet azimuthal correlations also have been investigated within the HSD model. We found that the suppression of the away-side jet in the hadronic mediumis not enough to explain the experimental data from RHIC. The additional suppression should be attributed to a quark-gluon plasma produced in heavy-ion collisions.

  11. Artificial intelligence applied to process signal analysis

    NASA Technical Reports Server (NTRS)

    Corsberg, Dan

    1988-01-01

    Many space station processes are highly complex systems subject to sudden, major transients. In any complex process control system, a critical aspect of the human/machine interface is the analysis and display of process information. Human operators can be overwhelmed by large clusters of alarms that inhibit their ability to diagnose and respond to a disturbance. Using artificial intelligence techniques and a knowledge base approach to this problem, the power of the computer can be used to filter and analyze plant sensor data. This will provide operators with a better description of the process state. Once a process state is recognized, automatic action could be initiated and proper system response monitored.

  12. 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.,…

  13. The Motor Unit Innervation Process Correlation and Its Effects on EMG Applications.

    PubMed

    Jiang, Ning; Parker, Philip; Englehart, Kevin

    2005-01-01

    It has often been assumed in EMG modeling and signal processing applications, that the Motor Unit Action Potential Trains (MUAPT) of concurrently active motor units during voluntary contractions are not correlated. However, motor unit synchrony, or Motor Unit Innervation Process (MUIP) correlation, which implies MUAPT correlation, has been accepted as a common phenomenon in voluntary contractions. The impact of this MUIP correlation in applications which assume its absence has not been thoroughly studied. In this paper, simulated data with different degrees of MUIP correlation are applied to investigate this issue. Simulation results show that MUIP correlation may compromise the assumption of uncorrelated MUAPTs (depending on recruitment level), and MUIP correlation has a downwards spectrum compression effect on the power spectrum of EMG. PMID:17281170

  14. Time delays in correlated photoemission processes

    NASA Astrophysics Data System (ADS)

    Pazourek, R.; Nagele, S.; Burgdörfer, J.

    2015-09-01

    We theoretically study time-resolved two-photon double ionization (TPDI) of helium as probed by attosecond streaking. We review recent advances in the understanding of the photoelectric effect in the time domain and discuss the differences between one- and two-photon ionization, as well as one- and two-electron emission. We perform exact ab-initio simulations for attosecond streaking experiments in the sequential TPDI regime and compare the results to the two-electron Eisenbud-Wigner-Smith delay for the process. Our calculations directly show that the timing of the emission process sensitively depends on the energy sharing between the two outgoing electrons. In particular, we identify Fano-like interferences in the relative time delay of the two emitted electrons when the sequential ionization channel occurs via intermediate excited ionic (shake-up) states. Furthermore, we find that the photoemission time delays are only weakly dependent on the relative emission angle of the ejected electrons.

  15. Neural Correlates of Verb Argument Structure Processing

    PubMed Central

    Thompson, Cynthia K.; Bonakdarpour, Borna; Fix, Stephen C.; Blumenfeld, Henrike K.; Parrish, Todd B.; Gitelman, Darren R.; Mesulam, M.-Marsel

    2008-01-01

    Neuroimaging and lesion studies suggest that processing of word classes, such as verbs and nouns, is associated with distinct neural mechanisms. Such studies also suggest that subcategories within these broad word class categories are differentially processed in the brain. Within the class of verbs, argument structure provides one linguistic dimension that distinguishes among verb exemplars, with some requiring more complex argument structure entries than others. This study examined the neural instantiation of verbs by argument structure complexity: one-, two-, and three-argument verbs. Stimuli of each type, along with nouns and pseudowords, were presented for lexical decision using an event-related functional magnetic resonance imaging design. Results for 14 young normal participants indicated largely overlapping activation maps for verbs and nouns, with no areas of significant activation for verbs compared to nouns, or vice versa. Pseudowords also engaged neural tissue overlapping with that for both word classes, with more widespread activation noted in visual, motor, and peri-sylvian regions. Examination of verbs by argument structure revealed activation of the supramarginal and angular gyri, limited to the left hemisphere only when verbs with two obligatory arguments were compared to verbs with a single argument. However, bilateral activation was noted when both two- and three-argument verbs were compared to one-argument verbs. These findings suggest that posterior peri-sylvian regions are engaged for processing argument structure information associated with verbs, with increasing neural tissue in the inferior parietal region associated with increasing argument structure complexity. These findings are consistent with processing accounts, which suggest that these regions are crucial for semantic integration. PMID:17958479

  16. Neural correlates of verb argument structure processing.

    PubMed

    Thompson, Cynthia K; Bonakdarpour, Borna; Fix, Stephen C; Blumenfeld, Henrike K; Parrish, Todd B; Gitelman, Darren R; Mesulam, M-Marsel

    2007-11-01

    Neuroimaging and lesion studies suggest that processing of word classes, such as verbs and nouns, is associated with distinct neural mechanisms. Such studies also suggest that subcategories within these broad word class categories are differentially processed in the brain. Within the class of verbs, argument structure provides one linguistic dimension that distinguishes among verb exemplars, with some requiring more complex argument structure entries than others. This study examined the neural instantiation of verbs by argument structure complexity: one-, two-, and three-argument verbs. Stimuli of each type, along with nouns and pseudowords, were presented for lexical decision using an event-related functional magnetic resonance imaging design. Results for 14 young normal participants indicated largely overlapping activation maps for verbs and nouns, with no areas of significant activation for verbs compared to nouns, or vice versa. Pseudowords also engaged neural tissue overlapping with that for both word classes, with more widespread activation noted in visual, motor, and peri-sylvian regions. Examination of verbs by argument structure revealed activation of the supramarginal and angular gyri, limited to the left hemisphere only when verbs with two obligatory arguments were compared to verbs with a single argument. However, bilateral activation was noted when both two- and three-argument verbs were compared to one-argument verbs. These findings suggest that posterior peri-sylvian regions are engaged for processing argument structure information associated with verbs, with increasing neural tissue in the inferior parietal region associated with increasing argument structure complexity. These findings are consistent with processing accounts, which suggest that these regions are crucial for semantic integration. PMID:17958479

  17. 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.

  18. Signal-driven computations in speech processing.

    PubMed

    Peña, Marcela; Bonatti, Luca L; Nespor, Marina; Mehler, Jacques

    2002-10-18

    Learning a language requires both statistical computations to identify words in speech and algebraic-like computations to discover higher level (grammatical) structure. Here we show that these computations can be influenced by subtle cues in the speech signal. After a short familiarization to a continuous speech stream, adult listeners are able to segment it using powerful statistics, but they fail to extract the structural regularities included in the stream even when the familiarization is greatly extended. With the introduction of subliminal segmentation cues, however, these regularities can be rapidly captured. PMID:12202684

  19. Method of digital signal process aided by control signal for burst-mode coherent receivers

    NASA Astrophysics Data System (ADS)

    Yu, Junlei; Wang, Liqian; Liao, Ping; Yan, Zheng; Cui, Xiaoxu; Chen, Xue; Ji, Yongning; Shang, Dongdong; Zhang, Qi; Liu, Yingfeng

    2015-11-01

    We propose a method of digital signal processing for a burst-mode coherent receiver, which can recover the burst data rapidly aided by a control signal. The feasibility and effectiveness of our proposed method are demonstrated in a 128 Gbps polarization division multiplexed quadrature phase shift keying modulation experiment, and the results show that the proposed method can reduce the 70% convergence time on average compared with the traditional digital signal processing without any training overhead or additional computing complexity.

  20. Signal processing at the Poker Flat MST radar

    NASA Technical Reports Server (NTRS)

    Carter, D. A.

    1983-01-01

    Signal processing for Mesosphere-Stratosphere-Troposphere (MST) radar is carried out by a combination of hardware in high-speed, special-purpose devices and software in a general-purpose, minicomputer/array processor. A block diagram of the signal processing system is presented, and the steps in the processing pathway are described. The current processing capabilities are given, and a system offering greater coherent integration speed is advanced which hinges upon a high speed preprocessor.

  1. Signal processing and electronic noise in LZ

    NASA Astrophysics Data System (ADS)

    Khaitan, D.

    2016-03-01

    The electronics of the LUX-ZEPLIN (LZ) experiment, the 10-tonne dark matter detector to be installed at the Sanford Underground Research Facility (SURF), consists of low-noise dual-gain amplifiers and a 100-MHz, 14-bit data acquisition system for the TPC PMTs. Pre-prototypes of the analog amplifiers and the 32-channel digitizers were tested extensively with simulated pulses that are similar to the prompt scintillation light and the electroluminescence signals expected in LZ. These studies are used to characterize the noise and to measure the linearity of the system. By increasing the amplitude of the test signals, the effect of saturating the amplifier and the digitizers was studied. The RMS ADC noise of the digitizer channels was measured to be 1.19± 0.01 ADCC. When a high-energy channel of the amplifier is connected to the digitizer, the measured noise remained virtually unchanged, while the noise added by a low-energy channel was estimated to be 0.38 ± 0.02 ADCC (46 ± 2 μV). A test facility is under construction to study saturation, mitigate noise and measure the performance of the LZ electronics and data acquisition chain.

  2. Signal processing for an infrared array detector

    NASA Astrophysics Data System (ADS)

    Young, M. A.; Smith, G. E.; Pimentel, G. C.

    1989-09-01

    A broadband detection scheme for a time-resolved infrared absorption spectrometer, based on a multielement mercury-cadmium-telluride (MCT) array, has been successfully implemented. The spectrometer achieves a resolution on the 10-ns time scale despite the much larger time constant characteristic of the MCT elements. Our signal-collection circuitry takes advantage of the slow decay by integrating the detector response to pulsed IR radiation. The dynamic range is 100-1 and the resultant noise level is near the detector limit. Data acquisition for the 120 elements is fast enough to allow scan rates of 30-40 Hz. The completed electronics are sufficiently compact to be situated local to the array detector, and the design is relatively inexpensive to construct using commonly found electronic components.

  3. 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.

  4. Statistical mechanics and visual signal processing

    NASA Astrophysics Data System (ADS)

    Potters, Marc; Bialek, William

    1994-11-01

    We show how to use the language of statistical field theory to address and solve problems in which one must estimate some aspect of the environnent from the data in an array of sensors. In the field theory formulation the optimal estimator can be written as an expectation value in an ensemble where the input data act as external field. Problems at low signal-to-noise ratio can be solved in perturbation theory, while high signal-to-noise ratios are treated with a saddle-point approximation. These ideas are illustrated in detail by an example of visual motion estimation which is chosen to model a problem solved by the fly's brain. The optimal estimator bas a rich structure, adapting to various parameters of the environnent such as the mean-square contrast and the corrélation time of contrast fluctuations. This structure is in qualitative accord with existing measurements on motion sensitive neurons in the fly's brain, and the adaptive properties of the optimal estimator may help resolve conficts among different interpretations of these data. Finally we propose some crucial direct tests of the adaptive behavior. Nous montrons comment employer le langage de la théorie statistique des champs pour poser et résoudre des problèmes où l'on doit estimer une caractéristique de l'environnement à l'aide de données provenant d'un ensemble de détecteurs. Dans ce formalisme, l'estimateur optimal peut être écrit comme la valeur moyenne d'un opérateur, l'ensemble des données d'entrée agissant comme un champ externe. Les problèmes à faible rapport signal-bruit sont résolus par la théorie des perturbations. La méthode du col est employée pour ceux à haut rapport signal-bruit. Ces idées sont illustrées en détails sur un modèle d'estimation visuelle du mouvement basé sur un problème résolu par la mouche. L'estimateur optimal a une structure très riche, s'adaptant à divers paramètres de l'environnement tels la variance du contraste et le temps de corrélation des variations de contraste. Cette structure est en accord qualitatif avec les résultats d'expériences sur des neurones du système visuel de la mouche. De plus, les propriétés d'adaptation de l'estimateur optimal peuvent aider à résoudre certains désaccords au sujet de l'interprétation de ces résultats. Nous proposons finalement quelques tests directs de ces propriétés d'adaptation.

  5. Processing electrophysiological signals for the monitoring of alertness

    NASA Technical Reports Server (NTRS)

    Lai, D. C.

    1974-01-01

    Mathematical techniques are described for processing EEG signals associated with varying states of alertness. Fast algorithms for implementing real-time computations of alertness estimates were developed. A realization of the phase-distortionless digital filter is presented which approaches real-time filtering and a transform for EEG signals. This transform provides information for the alertness estimates and can be performed in real time. A statistical test for stationarity in EEG signals is being developed that will provide a method for determining the duration of the EEG signals necessary for estimating the short-time power or energy spectra for nonstationary analysis of EEG signals.

  6. Signal Processing of Ultrasonic Array Data

    NASA Astrophysics Data System (ADS)

    Holmes, C.; Drinkwater, B. W.; Wilcox, P. D.

    2005-04-01

    This paper describes an investigation into the use of post-processing techniques to evaluate the performance of linear phased arrays. Simulated data has been produced for single point reflectors and an array performance indicator has been used to characterize the point spread function for a number of standard test procedures. Experimental results are also presented and these show good quantitative agreement with the simulated data sets. An advanced processing algorithm has been implemented which allows the array to be focused at every point in the target in both transmission and reception. This method is proposed as a superior alternative to the conventional test techniques.

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

    SciTech Connect

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

    2011-08-15

    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{sup 16} m{sup -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.

  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. 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.

  10. An approach for physiological signal processing by laboratory minicomputer.

    PubMed

    Tompkins, W J

    1978-03-01

    Physiological signal-processing instrumentation including the digital oscilloscope is becoming more dependent upon the microprocessor. Minicomputer software has been developed which demonstrates data-processing approaches that should be considered for incorporation into the firmware of digital oscilloscopes. This core-resident software called DATAC operates in an interpretive mode and provides such features as digital signal editing, filtering, and basic processing including differentiation and integration. PMID:639498

  11. Grating geophone signal processing based on wavelet transform

    NASA Astrophysics Data System (ADS)

    Li, Shuqing; Zhang, Huan; Tao, Zhifei

    2008-12-01

    Grating digital geophone is designed based on grating measurement technique benefiting averaging-error effect and wide dynamic range to improve weak signal detected precision. This paper introduced the principle of grating digital geophone and its post signal processing system. The signal acquisition circuit use Atmega 32 chip as core part and display the waveform on the Labwindows through the RS232 data link. Wavelet transform is adopted this paper to filter the grating digital geophone' output signal since the signal is unstable. This data processing method is compared with the FIR filter that widespread use in current domestic. The result indicates that the wavelet algorithm has more advantages and the SNR of seismic signal improve obviously.

  12. Processing of Hydraulic Pressure Sensor Signal Based on Wavelet Analysis

    NASA Astrophysics Data System (ADS)

    Shi, Xin; Zhao, Xiang-mo; Hui, Fei; Yang, Lan

    Hydraulic pressure sensor in the automobile is vulnerable to be polluted by the environment of vehicle, the excitation of road and other factors. In this paper, a method based on wavelet analysis is proposed to solve the interference of hydraulic sensor signal. With the wavelet time-frequency analysis, the development trend of the effective signal is identified by wavelet decomposition. Then on the basis of the estimation method, which estimates the noise variance by correlation coefficients, the sensor signal is treated by use of wavelet threshold de-noising. Finally, the available sample value of the signal is constructed by mean filter. In addition, it has been proved by the experiment that the approach, put forward in this paper, is an effective way on the analysis of hydraulic signal and noise elimination.

  13. Physics-based signal processing algorithms for micromachined cantilever arrays

    DOEpatents

    Candy, James V; Clague, David S; Lee, Christopher L; Rudd, Robert E; Burnham, Alan K; Tringe, Joseph W

    2013-11-19

    A method of using physics-based signal processing algorithms for micromachined cantilever arrays. The methods utilize deflection of a micromachined cantilever that represents the chemical, biological, or physical element being detected. One embodiment of the method comprises the steps of modeling the deflection of the micromachined cantilever producing a deflection model, sensing the deflection of the micromachined cantilever and producing a signal representing the deflection, and comparing the signal representing the deflection with the deflection model.

  14. Preliminary development of digital signal processing in microwave radiometers

    NASA Technical Reports Server (NTRS)

    Stanley, W. D.

    1980-01-01

    Topics covered involve a number of closely related tasks including: the development of several control loop and dynamic noise model computer programs for simulating microwave radiometer measurements; computer modeling of an existing stepped frequency radiometer in an effort to determine its optimum operational characteristics; investigation of the classical second order analog control loop to determine its ability to reduce the estimation error in a microwave radiometer; investigation of several digital signal processing unit designs; initiation of efforts to develop required hardware and software for implementation of the digital signal processing unit; and investigation of the general characteristics and peculiarities of digital processing noiselike microwave radiometer signals.

  15. 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.

  16. Optical correlation of images with signal-dependent noise using constrained-modulation filter devices

    NASA Astrophysics Data System (ADS)

    Downie, John D.

    1995-07-01

    Images with signal-dependent noise present challenges beyond those of images with additive white or colored signal-independent noise in terms of designing the optimal 4-f correlation filter that maximizes correlation-peak signal-to-noise ratio, or combinations of correlation-peak metrics. Determining the proper design becomes more difficult when the filter is to be implemented on a constrained-modulation spatial light modulator device. The design issues involved for updatable optical filters for images with signal-dependent film-grain noise and speckle noise are examined. It is shown that although design of the optimal linear filter in the Fourier domain is impossible for images with signal-dependent noise, proper nonlinear preprocessing of the images allows the application of previously developed design rules for optimal filters to be implemented on constrained-modulation devices. Thus the nonlinear preprocessing becomes necessary for correlation in optical systems with current spatial light modulator technology. These results are illustrated with computer simulations of images with signal-dependent noise correlated with binary-phase-only filters and ternary-phase-amplitude filters.

  17. Optical Correlation of Images With Signal-Dependent Noise Using Constrained-Modulation Filter Devices

    NASA Technical Reports Server (NTRS)

    Downie, John D.

    1995-01-01

    Images with signal-dependent noise present challenges beyond those of images with additive white or colored signal-independent noise in terms of designing the optimal 4-f correlation filter that maximizes correlation-peak signal-to-noise ratio, or combinations of correlation-peak metrics. Determining the proper design becomes more difficult when the filter is to be implemented on a constrained-modulation spatial light modulator device. The design issues involved for updatable optical filters for images with signal-dependent film-grain noise and speckle noise are examined. It is shown that although design of the optimal linear filter in the Fourier domain is impossible for images with signal-dependent noise, proper nonlinear preprocessing of the images allows the application of previously developed design rules for optimal filters to be implemented on constrained-modulation devices. Thus the nonlinear preprocessing becomes necessary for correlation in optical systems with current spatial light modulator technology. These results are illustrated with computer simulations of images with signal-dependent noise correlated with binary-phase-only filters and ternary-phase-amplitude filters.

  18. Modeling laser velocimeter signals as triply stochastic Poisson processes

    NASA Technical Reports Server (NTRS)

    Mayo, W. T., Jr.

    1976-01-01

    Previous models of laser Doppler velocimeter (LDV) systems have not adequately described dual-scatter signals in a manner useful for analysis and simulation of low-level photon-limited signals. At low photon rates, an LDV signal at the output of a photomultiplier tube is a compound nonhomogeneous filtered Poisson process, whose intensity function is another (slower) Poisson process with the nonstationary rate and frequency parameters controlled by a random flow (slowest) process. In the present paper, generalized Poisson shot noise models are developed for low-level LDV signals. Theoretical results useful in detection error analysis and simulation are presented, along with measurements of burst amplitude statistics. Computer generated simulations illustrate the difference between Gaussian and Poisson models of low-level signals.

  19. Neural correlates of processing negative and sexually arousing pictures.

    PubMed

    Bailey, Kira; West, Robert; Mullaney, Kellie M

    2012-01-01

    Recent work has questioned whether the negativity bias is a distinct component of affective picture processing. The current study was designed to determine whether there are different neural correlates of processing positive and negative pictures using event-related brain potentials. The early posterior negativity and late positive potential were greatest in amplitude for erotic pictures. Partial Least Squares analysis revealed one latent variable that distinguished erotic pictures from neutral and positive pictures and another that differentiated negative pictures from neutral and positive pictures. The effects of orienting task on the neural correlates of processing negative and erotic pictures indicate that affective picture processing is sensitive to both stimulus-driven, and attentional or decision processes. The current data, together with other recent findings from our laboratory, lead to the suggestion that there are distinct neural correlates of processing negative and positive stimuli during affective picture processing. PMID:23029071

  20. Synthetic aperture focusing technique signal processing

    NASA Astrophysics Data System (ADS)

    Langenberg, K. J.; Berger, M.; Kreutter, Th.; Mayer, K.; Schmitz, V.

    1986-06-01

    The synthetic aperture focusing technique (SAFT) is briefly reviewed and addressed as a heuristic digital ultrasonic imaging scheme which exploits the idea of back-propagating a set of measured and digitally stored A-scans. It is shown that for a far-field experimental set-up, i.e., for small, isolated defects remote to the transducer, SAFT reduces to the filtered back-projection imaging scheme which is well known within the framework of conventional X-ray computer tomography. Therefore, alternative data processing via Fourier transforms only, similar to the Fourier slice theorem of tomography, is possible, which sheds considerable light upon the heuristic SAFT pixel-space envelope-detection scheme. The far-field assumption is omitted yielding a Fourier-transform-SAFT algorithm (FT-SAFT) whose results are identical to back-propagation imaging with the definite advantage of fast processing capabilities based upon standard hardware and allowing immediate implementation of high resolution procedures as well as inclusion of mode-conversion effects.

  1. Correlation Spectroscopy of Minor Fluorescent Species: Signal Purification and Distribution Analysis

    PubMed Central

    Laurence, Ted A.; Kwon, Youngeun; Yin, Eric; Hollars, Christopher W.; Camarero, Julio A.; Barsky, Daniel

    2007-01-01

    We are performing experiments that use fluorescence resonance energy transfer (FRET) and fluorescence correlation spectroscopy (FCS) to monitor the movement of an individual donor-labeled sliding clamp protein molecule along acceptor-labeled DNA. In addition to the FRET signal sought from the sliding clamp-DNA complexes, the detection channel for FRET contains undesirable signal from free sliding clamp and free DNA. When multiple fluorescent species contribute to a correlation signal, it is difficult or impossible to distinguish between contributions from individual species. As a remedy, we introduce “purified FCS”, which uses single molecule burst analysis to select a species of interest and extract the correlation signal for further analysis. We show that by expanding the correlation region around a burst, the correlated signal is retained and the functional forms of FCS fitting equations remain valid. We demonstrate the use of purified FCS in experiments with DNA sliding clamps. We also introduce “single-molecule FCS”, which obtains diffusion time estimates for each burst using expanded correlation regions. By monitoring the detachment of weakly-bound 30-mer DNA oligomers from a single-stranded DNA plasmid, we show that single-molecule FCS can distinguish between bursts from species that differ by a factor of 5 in diffusion constant. PMID:17189306

  2. HYMOSS signal processing for pushbroom spectral imaging

    NASA Technical Reports Server (NTRS)

    Ludwig, David E.

    1991-01-01

    The objective of the Pushbroom Spectral Imaging Program was to develop on-focal plane electronics which compensate for detector array non-uniformities. The approach taken was to implement a simple two point calibration algorithm on focal plane which allows for offset and linear gain correction. The key on focal plane features which made this technique feasible was the use of a high quality transimpedance amplifier (TIA) and an analog-to-digital converter for each detector channel. Gain compensation is accomplished by varying the feedback capacitance of the integrate and dump TIA. Offset correction is performed by storing offsets in a special on focal plane offset register and digitally subtracting the offsets from the readout data during the multiplexing operation. A custom integrated circuit was designed, fabricated, and tested on this program which proved that nonuniformity compensated, analog-to-digital converting circuits may be used to read out infrared detectors. Irvine Sensors Corporation (ISC) successfully demonstrated the following innovative on-focal-plane functions that allow for correction of detector non-uniformities. Most of the circuit functions demonstrated on this program are finding their way onto future IC's because of their impact on reduced downstream processing, increased focal plane performance, simplified focal plane control, reduced number of dewar connections, as well as the noise immunity of a digital interface dewar. The potential commercial applications for this integrated circuit are primarily in imaging systems. These imaging systems may be used for: security monitoring systems, manufacturing process monitoring, robotics, and for spectral imaging when used in analytical instrumentation.

  3. Correlation dimension analysis of Doppler signals in children with aortic valve disorders.

    PubMed

    Yılmaz, Derya; Güler, N Fatma

    2010-10-01

    In this study, the correlation dimension analysis has been applied to the aortic valve Doppler signals to investigate the complexity of the Doppler signals which belong to aortic stenosis (AS) and aortic insufficiency (AI) diseases and healthy case. The Doppler signals of 20 healthy subjects, ten AS and ten AI patients were acquired via the Doppler echocardiography system that is a noninvasive and reliable technique for assessment of AS and AI diseases. The correlation dimension estimations have been performed for different time delay values to investigate the influence of time delay on the correlation dimension calculation. The correlation dimension of healthy group has been found lower those found in AI and AS disorder groups and the correlation dimension of AS group has also been found higher than those found in AI group, significantly. The results of this study have indicated that the aortic valve Doppler signals exhibit high level chaotic behaviour in AI and AS diseases than healthy case. Additionally, the correlation dimension analysis is sensitive to the time delay and has successfully characterized the blood flow dynamics for proper time delay value. As a result, the correlation dimension can be used as an efficient method to determine the healthy or pathological cases of aortic valve. PMID:20703615

  4. Advanced Signal Processing for Thermal Flaw Detection

    SciTech Connect

    VALLEY, MICHAEL T.; HANSCHE, BRUCE D.; PAEZ, THOMAS L.; URBINA, ANGEL; ASHBAUGH, DENNIS M.

    2001-09-01

    Dynamic thermography is a promising technology for inspecting metallic and composite structures used in high-consequence industries. However, the reliability and inspection sensitivity of this technology has historically been limited by the need for extensive operator experience and the use of human judgment and visual acuity to detect flaws in the large volume of infrared image data collected. To overcome these limitations new automated data analysis algorithms and software is needed. The primary objectives of this research effort were to develop a data processing methodology that is tied to the underlying physics, which reduces or removes the data interpretation requirements, and which eliminates the need to look at significant numbers of data frames to determine if a flaw is present. Considering the strengths and weakness of previous research efforts, this research elected to couple both the temporal and spatial attributes of the surface temperature. Of the possible algorithms investigated, the best performing was a radiance weighted root mean square Laplacian metric that included a multiplicative surface effect correction factor and a novel spatio-temporal parametric model for data smoothing. This metric demonstrated the potential for detecting flaws smaller than 0.075 inch in inspection areas on the order of one square foot. Included in this report is the development of a thermal imaging model, a weighted least squares thermal data smoothing algorithm, simulation and experimental flaw detection results, and an overview of the ATAC (Automated Thermal Analysis Code) software that was developed to analyze thermal inspection data.

  5. Software for biomedical engineering signal processing laboratory experiments.

    PubMed

    Tompkins, Willis J; Wilson, J

    2009-01-01

    In the early 1990's we developed a special computer program called UW DigiScope to provide a mechanism for anyone interested in biomedical digital signal processing to study the field without requiring any other instrument except a personal computer. There are many digital filtering and pattern recognition algorithms used in processing biomedical signals. In general, students have very limited opportunity to have hands-on access to the mechanisms of digital signal processing. In a typical course, the filters are designed non-interactively, which does not provide the student with significant understanding of the design constraints of such filters nor their actual performance characteristics. UW DigiScope 3.0 is the first major update since version 2.0 was released in 1994. This paper provides details on how the new version based on MATLAB! works with signals, including the filter design tool that is the programming interface between UW DigiScope and processing algorithms. PMID:19964035

  6. 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.

  7. Signal processing techniques for synchronization of wireless sensor networks

    NASA Astrophysics Data System (ADS)

    Lee, Jaehan; Wu, Yik-Chung; Chaudhari, Qasim; Qaraqe, Khalid; Serpedin, Erchin

    2010-11-01

    Clock synchronization is a critical component in wireless sensor networks, as it provides a common time frame to different nodes. It supports functions such as fusing voice and video data from different sensor nodes, time-based channel sharing, and sleep wake-up scheduling, etc. Early studies on clock synchronization for wireless sensor networks mainly focus on protocol design. However, clock synchronization problem is inherently related to parameter estimation, and recently, studies of clock synchronization from the signal processing viewpoint started to emerge. In this article, a survey of latest advances on clock synchronization is provided by adopting a signal processing viewpoint. We demonstrate that many existing and intuitive clock synchronization protocols can be interpreted by common statistical signal processing methods. Furthermore, the use of advanced signal processing techniques for deriving optimal clock synchronization algorithms under challenging scenarios will be illustrated.

  8. 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.

  9. Trouble at rest: how correlation patterns and group differences become distorted after global signal regression.

    PubMed

    Saad, Ziad S; Gotts, Stephen J; Murphy, Kevin; Chen, Gang; Jo, Hang Joon; Martin, Alex; Cox, Robert W

    2012-01-01

    Resting-state functional magnetic resonance imaging (RS-FMRI) holds the promise of revealing brain functional connectivity without requiring specific tasks targeting particular brain systems. RS-FMRI is being used to find differences between populations even when a specific candidate target for traditional inferences is lacking. However, the problem with RS-FMRI is a lacking definition of what constitutes noise and signal. RS-FMRI is easy to acquire but is not easy to analyze or draw inferences from. In this commentary we discuss a problem that is still treated lightly despite its significant impact on RS-FMRI inferences; global signal regression (GSReg), the practice of projecting out signal averaged over the entire brain, can change resting-state correlations in ways that dramatically alter correlation patterns and hence conclusions about brain functional connectedness. Although Murphy et al. in 2009 demonstrated that GSReg negatively biases correlations, the approach remains in wide use. We revisit this issue to argue the problem that GSReg is more than negative bias or the interpretability of negative correlations. Its usage can fundamentally alter interregional correlations within a group, or their differences between groups. We used an illustrative model to clearly convey our objections and derived equations formalizing our conclusions. We hope this creates a clear context in which counterarguments can be made. We conclude that GSReg should not be used when studying RS-FMRI because GSReg biases correlations differently in different regions depending on the underlying true interregional correlation structure. GSReg can alter local and long-range correlations, potentially spreading underlying group differences to regions that may never have had any. Conclusions also apply to substitutions of GSReg for denoising with decompositions of signals aggregated over the network's regions to the extent they cannot separate signals of interest from noise. We touch on the need for careful accounting of nuisance parameters when making group comparisons of correlation maps. PMID:22432927

  10. Microscopic realization of cross-correlated noise processes.

    PubMed

    Shit, Anindita; Chattopadhyay, Sudip; Banik, Suman Kumar; Chaudhuri, Jyotipratim Ray

    2010-06-01

    We present a microscopic theory of cross-correlated noise processes, starting from a Hamiltonian system-reservoir description. In the proposed model, the system is nonlinearly coupled to a reservoir composed of harmonic oscillators, which in turn is driven by an external fluctuating force. We show that the resultant Langevin equation derived from the composite system (system+reservoir+external modulation) contains the essential features of cross-correlated noise processes. PMID:20590326

  11. 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.

  12. 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

  13. UCMS - A new signal parameter measurement system using digital signal processing techniques. [User Constraint Measurement System

    NASA Technical Reports Server (NTRS)

    Choi, H. J.; Su, Y. T.

    1986-01-01

    The User Constraint Measurement System (UCMS) is a hardware/software package developed by NASA Goddard to measure the signal parameter constraints of the user transponder in the TDRSS environment by means of an all-digital signal sampling technique. An account is presently given of the features of UCMS design and of its performance capabilities and applications; attention is given to such important aspects of the system as RF interface parameter definitions, hardware minimization, the emphasis on offline software signal processing, and end-to-end link performance. Applications to the measurement of other signal parameters are also discussed.

  14. Processing energy and signals by molecular and supramolecular systems.

    PubMed

    Balzani, Vincenzo; Credi, Alberto; Venturi, Margherita

    2008-01-01

    Any kind of device or machine requires a substrate, energy, and information signals. If we wish to operate at the nanometer scale, we must use molecules as substrates. Energy- and signal-processing at a molecular level relies on cause/effect relationships between the input supplied and the kind of process obtained. We have classified energy- and signal-processing at the molecular level according to the nature of the input (electronic, photonic, or chemical) and the nature of the obtained effect (electronic, photonic, or chemical process that follows). By coupling the three kinds of inputs with the three types of resulting processes, nine types of molecular-based processes (electronic, photonic, chemionic, electrophotonic, electrochemionic, photoelectronic, photochemionic, chemiophotonic, and chemioelectronic) can be identified. In this concept article, looking at molecular transformations in an unconventional way, we have tried to give a flavor of some of the new features that project the old science of chemistry towards novel achievements. PMID:17948331

  15. 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

  16. A Study on Signal Group Processing of AUTOSAR COM Module

    NASA Astrophysics Data System (ADS)

    Lee, Jeong-Hwan; Hwang, Hyun Yong; Han, Tae Man; Ahn, Yong Hak

    2013-06-01

    In vehicle, there are many ECU(Electronic Control Unit)s, and ECUs are connected to networks such as CAN, LIN, FlexRay, and so on. AUTOSAR COM(Communication) which is a software platform of AUTOSAR(AUTomotive Open System ARchitecture) in the international industry standards of automotive electronic software processes signals and signal groups for data communications between ECUs. Real-time and reliability are very important for data communications in the vehicle. Therefore, in this paper, we analyze functions of signals and signal groups used in COM, and represent that functions of signal group are more efficient than signals in real-time data synchronization and network resource usage between the sender and receiver.

  17. Two-dimensional signal processing with application to image restoration

    NASA Technical Reports Server (NTRS)

    Assefi, T.

    1974-01-01

    A recursive technique for modeling and estimating a two-dimensional signal contaminated by noise is presented. A two-dimensional signal is assumed to be an undistorted picture, where the noise introduces the distortion. Both the signal and the noise are assumed to be wide-sense stationary processes with known statistics. Thus, to estimate the two-dimensional signal is to enhance the picture. The picture representing the two-dimensional signal is converted to one dimension by scanning the image horizontally one line at a time. The scanner output becomes a nonstationary random process due to the periodic nature of the scanner operation. Procedures to obtain a dynamical model corresponding to the autocorrelation function of the scanner output are derived. Utilizing the model, a discrete Kalman estimator is designed to enhance the image.

  18. A comparison of signal processing techniques for Intrinsic Optical Signal imaging in mice.

    PubMed

    Turley, Jordan A; Nilsson, Michael; Walker, Frederick Rohan; Johnson, Sarah J

    2015-08-01

    Intrinsic Optical Signal imaging is a technique which allows the visualisation and mapping of activity related changes within the brain with excellent spatial and temporal resolution. We analysed a variety of signal and image processing techniques applied to real mouse imaging data. The results were compared in an attempt to overcome the unique issues faced when performing the technique on mice and improve the understanding of post processing options available. PMID:26737728

  19. An investigation of a correlation/covariance method of signal extraction

    NASA Astrophysics Data System (ADS)

    Langel, Robert A.

    1995-10-01

    A harmonic correlation technique has been used effectively to isolate a primary signal from two independent data sets each of which is contaminated by the presence of interfering signals. Each of the two data sets is decomposed by a harmonic analysis, and then the correlation coefficients and amplitude ratios between the two decompositions are computed for each harmonic. Only harmonics which satisfy predetermined selection criteria are retained. Those criteria are in the form of requiring the correlation coefficient to exceed some magnitude, say, ρ0, and the amplitude ratio not to exceed some value, say, R0. The resulting pair of retained signals are then typically highly correlated. It is suggested that appropriate values of ρ0 lie between 0.25 and 0.6 and of R0 between 3.0 and 6.0, depending on the relative amplitudes of the primary and interfering signals. Critical examination of the technique shows that under many conditions it can be an effective tool for eliminating signals which are not a good approximation to the primary signal. This conclusion is confirmed by simulated examples of satellite magnetic anomaly data with interfering fields from ionospheric currents.

  20. A fast discrete S-transform for biomedical signal processing.

    PubMed

    Brown, Robert A; Frayne, Richard

    2008-01-01

    Determining the frequency content of a signal is a basic operation in signal and image processing. The S-transform provides both the true frequency and globally referenced phase measurements characteristic of the Fourier transform and also generates local spectra, as does the wavelet transform. Due to this combination, the S-transform has been successfully demonstrated in a variety of biomedical signal and image processing tasks. However, the computational demands of the S-transform have limited its application in medicine to this point in time. This abstract introduces the fast S-transform, a more efficient discrete implementation of the classic S-transform with dramatically reduced computational requirements. PMID:19163232

  1. Simplified signal processing for an airborne CO2 Doppler lidar

    NASA Technical Reports Server (NTRS)

    Schwiesow, R. L.; Spowart, M. P.

    1992-01-01

    In the development of the National Center for Atmospheric Research (NCAR) airborne infrared lidar system (NAILS), we have emphasized a simple, modular design to suit the instrument to its mission of providing measurements of atmospheric structure and dynamics from an aircraft platform. Based on our research to this point, we believe that a significant simplification of the signal processing approach compared to that now used is possible by using high speed digitization of the signal. The purpose here is to place signal processing in the context of the overall system design and to explore the basis of the alternative technique so that the community can comment on the approach.

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

    DOEpatents

    Fu, Chi Yung; Petrich, Loren

    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.

  4. Biomedical signal acquisition, processing and transmission using smartphone

    NASA Astrophysics Data System (ADS)

    Roncagliolo, Pablo; Arredondo, Luis; González, Agustín

    2007-11-01

    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 temperature. The contribution of this technology is settled on its portability and low cost, which allows its massive use. Specifically this work analyzes the feasibility of acquisition and the processing of signals from a standard smartphone. Work results allow to state that nowadays these equipments have enough processing capacity to execute signals acquisition systems. These systems along with external servers make it possible to imagine a near future where the possibility of making continuous measures of biomedical variables will not be restricted only to hospitals but will also begin to be more frequently used in the daily life and at home.

  5. Removing Background Noise with Phased Array Signal Processing

    NASA Technical Reports Server (NTRS)

    Podboy, Gary; Stephens, David

    2015-01-01

    Preliminary results are presented from a test conducted to determine how well microphone phased array processing software could pull an acoustic signal out of background noise. The array consisted of 24 microphones in an aerodynamic fairing designed to be mounted in-flow. The processing was conducted using Functional Beam forming software developed by Optinav combined with cross spectral matrix subtraction. The test was conducted in the free-jet of the Nozzle Acoustic Test Rig at NASA GRC. The background noise was produced by the interaction of the free-jet flow with the solid surfaces in the flow. The acoustic signals were produced by acoustic drivers. The results show that the phased array processing was able to pull the acoustic signal out of the background noise provided the signal was no more than 20 dB below the background noise level measured using a conventional single microphone equipped with an aerodynamic forebody.

  6. 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.

  7. Extraction of low frequency signals from cross-correlations of the infrasonic ambient noise

    NASA Astrophysics Data System (ADS)

    Landès, Matthieu; Shapiro, Nikolaï; Le Pichon, Alexis

    2015-04-01

    Cross-correlation of ambient noise are widely used in seismology for imaging and monitoring purposes. The underlying result is the possibility to extract the Green Function between two locations on the Earth by correlating the noise recorded at these two points during long period of time. However, the applicability of this approach in atmospheric infrasound is not yet well established. We present cross-correlations of the infrasonic dataset of the USArray for the year 2012 filtered between 3 and 330 seconds. All cross-correlations were computed daily with a moving window of 3 hours. Only the amplitude normalization has been applied. We observe clear signals on the stacked cross-correlations for inter-station distances smaller than 400 km. The dominant period of this signal is around 60-100 s and its propagation velocity is approximately 320 m/s. We then use the daily cross-correlations to get information on the location of corresponding noise sources. Daily cross-correlations are asymmetric and show seasonal variations. These observations are due to the inhomogeneous noise sources distribution that can be inferred from a beamforming analysis. Our results show the seasonal variations of the back-azimuth of dominant infrasound noise sources generating this low frequency signal. This is a new opportunity to characterize the composition of the infrasonic ambient noise and to promote the application of passive approaches in atmospheric infrasound.

  8. 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.

  9. online Surveillance of Industrial Processes with Correlated Parameters

    Energy Science and Technology Software Center (ESTSC)

    1996-12-18

    SMP is a system for online surveillance of industrial processes or machinery for determination of the incipience or onset of abnormal operating conditions. SMP exploits the cross correlation between all of the sensors that are available on the system under surveillance to provide an extremely high sensitivity for annunciation of subtle disturbances in process variables.

  10. 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…

  11. Analog signal processing for low-power sensor systems

    NASA Astrophysics Data System (ADS)

    Hasler, Paul

    2006-05-01

    We present the potential of using Programmable Analog Signal processing techniques for impacting low-power portable applications like imaging, audio processing, and speech recognition. The range of analog signal processing functions available results in many potential opportunities to incorporate these analog signal processing systems with digital signal processing systems for improved overall system performance. We describes our programmable analog technology based around floating-gate transistors that allow for non-volitile storage as well as computation through the same device. We describe the basic concepts for floating-gate devices, capacitor-based circuits, and the basic charge modification mechanisms that makes this analog technology programmable. We describes the techniques to extend these techniques to program an array of floating-gate devices. We show experimental evidence for the factor of 1000 to 10,000 power efficiency improvement for programmable analog signal processing compared to custom digital implementations in Vector Matrix Multipliers (VMM), CMOS imagers with computation on the pixel plane with high fill factors, and Large-Scale Field Programmable Analog Arrays (FPAA), among others.

  12. The evolution of signal-reward correlations in bee- and hummingbird-pollinated species of Salvia.

    PubMed

    Benitez-Vieyra, Santiago; Fornoni, Juan; Pérez-Alquicira, Jessica; Boege, Karina; Domínguez, César A

    2014-05-01

    Within-individual variation in floral advertising and reward traits is a feature experienced by pollinators that visit different flowers of the same plant. Pollinators can use advertising traits to gather information about the quality and amount of rewards, leading to the evolution of signal-reward correlations. As long as plants differ in the reliability of their signals and pollinators base their foraging decisions on this information, natural selection should act on within-individual correlations between signals and rewards. Because birds and bees differ in their cognitive capabilities, and use different floral traits as signals, we tested the occurrence of adaptive divergence of the within-individual signal-reward correlations among Salvia species that are pollinated either by bees or by hummingbirds. They are expected to use different floral advertising traits: frontal traits in the case of bees and side traits in the case of hummingbirds. We confirmed this expectation as bee- and hummingbird-pollinated species differed in which specific traits are predominantly associated with nectar reward at the within-individual level. Our findings highlight the adaptive value of within-individual variation and covariation patterns, commonly disregarded as 'environmental noise', and are consistent with the hypothesis that pollinator-mediated selection affects the correlation pattern among floral traits. PMID:24648219

  13. Non-linear canonical correlation for joint analysis of MEG signals from two subjects

    PubMed Central

    Campi, Cristina; Parkkonen, Lauri; Hari, Riitta; Hyvärinen, Aapo

    2013-01-01

    Traditional stimulus-based analysis methods of magnetoencephalography (MEG) data are often dissatisfactory when applied to naturalistic experiments where two or more subjects are measured either simultaneously or sequentially. To uncover the commonalities in the brain activity of the two subjects, we propose a method that searches for linear transformations that output maximally correlated signals between the two brains. Our method is based on canonical correlation analysis (CCA), which provides linear transformations, one for each subject, such that the temporal correlation between the transformed MEG signals is maximized. Here, we present a non-linear version of CCA which measures the correlation of energies and allows for a variable delay between the time series to accommodate, e.g., leader–follower changes. We test the method with simulations and with MEG data from subjects who received the same naturalistic stimulus sequence. The method may help analyse future experiments where the two subjects are measured simultaneously while engaged in social interaction. PMID:23785311

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

    PubMed

    Arcaro, Michael J; Honey, Christopher J; Mruczek, Ryan E B; 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

  15. 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.

  16. Digital signal processing of light in holographic 3D imaging

    NASA Astrophysics Data System (ADS)

    Matsushima, Kyoji

    2015-09-01

    Several techniques are introduced and reviewed in high-definition computer holography. The reconstructed object is usually CG-modeled virtual objects, but it is possible to digitally record light of physical objects and reconstruct it by the high-definition computer-generated hologram. The process can be considered as a sort of digital signal processing of light.

  17. 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.

  18. SIG: a general-purpose signal processing program

    SciTech Connect

    Lager, D.; Azevedo, S.

    1986-02-01

    SIG is a general-purpose signal processing, analysis, and display program. Its main purpose is to perform manipulations on time- and frequency-domain signals. It also accommodates other representations for data such as transfer function polynomials. Signal processing operations include digital filtering, auto/cross spectral density, transfer function/impulse response, convolution, Fourier transform, and inverse Fourier transform. Graphical operations provide display of signals and spectra, including plotting, cursor zoom, families of curves, and multiple viewport plots. SIG provides two user interfaces with a menu mode for occasional users and a command mode for more experienced users. Capability exits for multiple commands per line, command files with arguments, commenting lines, defining commands, automatic execution for each item in a repeat sequence, etc. SIG is presently available for VAX(VMS), VAX (BERKELEY 4.2 UNIX), SUN (BERKELEY 4.2 UNIX), DEC-20 (TOPS-20), LSI-11/23 (TSX), and DEC PRO 350 (TSX). 4 refs., 2 figs.

  19. Fear of fat and the dream process: a correlational investigation.

    PubMed

    Kroth, J; Yoneda, D; Hammond, A

    1998-12-01

    Dream characteristics of 27 women from a graduate counseling program were correlated with the Goldfarb Fear of Fat Scale. Significant positive correlations were obtained for scores with recurrent nightmares (.38) and dreaming one is dreaming (.40). An inverse relationship was noted between sexual content of dreams and scores for fear of fat (-.41). Results were discussed in terms of associations among dissociation, body image, and the dream process. PMID:10079715

  20. 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.

  1. 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.

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

    NASA Technical Reports Server (NTRS)

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

    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.

  3. Bicoid Signal Extraction with a Selection of Parametric and Nonparametric Signal Processing Techniques

    PubMed Central

    Ghodsi, Zara; Silva, Emmanuel Sirimal; Hassani, Hossein

    2015-01-01

    The maternal segmentation coordinate gene bicoid plays a significant role during Drosophila embryogenesis. The gradient of Bicoid, the protein encoded by this gene, determines most aspects of head and thorax development. This paper seeks to explore the applicability of a variety of signal processing techniques at extracting bicoid expression signal, and whether these methods can outperform the current model. We evaluate the use of six different powerful and widely-used models representing both parametric and nonparametric signal processing techniques to determine the most efficient method for signal extraction in bicoid. The results are evaluated using both real and simulated data. Our findings show that the Singular Spectrum Analysis technique proposed in this paper outperforms the synthesis diffusion degradation model for filtering the noisy protein profile of bicoid whilst the exponential smoothing technique was found to be the next best alternative followed by the autoregressive integrated moving average. PMID:26197438

  4. The Analysis of Surface EMG Signals with the Wavelet-Based Correlation Dimension Method

    PubMed Central

    Zhang, Yanyan; Wang, Jue

    2014-01-01

    Many attempts have been made to effectively improve a prosthetic system controlled by the classification of surface electromyographic (SEMG) signals. Recently, the development of methodologies to extract the effective features still remains a primary challenge. Previous studies have demonstrated that the SEMG signals have nonlinear characteristics. In this study, by combining the nonlinear time series analysis and the time-frequency domain methods, we proposed the wavelet-based correlation dimension method to extract the effective features of SEMG signals. The SEMG signals were firstly analyzed by the wavelet transform and the correlation dimension was calculated to obtain the features of the SEMG signals. Then, these features were used as the input vectors of a Gustafson-Kessel clustering classifier to discriminate four types of forearm movements. Our results showed that there are four separate clusters corresponding to different forearm movements at the third resolution level and the resulting classification accuracy was 100%, when two channels of SEMG signals were used. This indicates that the proposed approach can provide important insight into the nonlinear characteristics and the time-frequency domain features of SEMG signals and is suitable for classifying different types of forearm movements. By comparing with other existing methods, the proposed method exhibited more robustness and higher classification accuracy. PMID:24868240

  5. The analysis of surface EMG signals with the wavelet-based correlation dimension method.

    PubMed

    Wang, Gang; Zhang, Yanyan; Wang, Jue

    2014-01-01

    Many attempts have been made to effectively improve a prosthetic system controlled by the classification of surface electromyographic (SEMG) signals. Recently, the development of methodologies to extract the effective features still remains a primary challenge. Previous studies have demonstrated that the SEMG signals have nonlinear characteristics. In this study, by combining the nonlinear time series analysis and the time-frequency domain methods, we proposed the wavelet-based correlation dimension method to extract the effective features of SEMG signals. The SEMG signals were firstly analyzed by the wavelet transform and the correlation dimension was calculated to obtain the features of the SEMG signals. Then, these features were used as the input vectors of a Gustafson-Kessel clustering classifier to discriminate four types of forearm movements. Our results showed that there are four separate clusters corresponding to different forearm movements at the third resolution level and the resulting classification accuracy was 100%, when two channels of SEMG signals were used. This indicates that the proposed approach can provide important insight into the nonlinear characteristics and the time-frequency domain features of SEMG signals and is suitable for classifying different types of forearm movements. By comparing with other existing methods, the proposed method exhibited more robustness and higher classification accuracy. PMID:24868240

  6. Cellular phosphatases facilitate combinatorial processing of receptor-activated signals

    PubMed Central

    Kumar, Dhiraj; Dua, Raina; Srikanth, Ravichandran; Jayaswal, Shilpi; Siddiqui, Zaved; Rao, Kanury VS

    2008-01-01

    Background Although reciprocal regulation of protein phosphorylation represents a key aspect of signal transduction, a larger perspective on how these various interactions integrate to contribute towards signal processing is presently unclear. For example, a key unanswered question is that of how phosphatase-mediated regulation of phosphorylation at the individual nodes of the signaling network translates into modulation of the net signal output and, thereby, the cellular phenotypic response. Results To address the above question we, in the present study, examined the dynamics of signaling from the B cell antigen receptor (BCR) under conditions where individual cellular phosphatases were selectively depleted by siRNA. Results from such experiments revealed a highly enmeshed structure for the signaling network where each signaling node was linked to multiple phosphatases on the one hand, and each phosphatase to several nodes on the other. This resulted in a configuration where individual signaling intermediates could be influenced by a spectrum of regulatory phosphatases, but with the composition of the spectrum differing from one intermediate to another. Consequently, each node differentially experienced perturbations in phosphatase activity, yielding a unique fingerprint of nodal signals characteristic to that perturbation. This heterogeneity in nodal experiences, to a given perturbation, led to combinatorial manipulation of the corresponding signaling axes for the downstream transcription factors. Conclusion Our cumulative results reveal that it is the tight integration of phosphatases into the signaling network that provides the plasticity by which perturbation-specific information can be transmitted in the form of a multivariate output to the downstream transcription factor network. This output in turn specifies a context-defined response, when translated into the resulting gene expression profile. PMID:18798986

  7. Research on mud pulse signal data processing in MWD

    NASA Astrophysics Data System (ADS)

    Tu, Bing; Li, De Sheng; Lin, En Huai; Ji, Miao Miao

    2012-12-01

    Wireless measure while drilling (MWD) transmits data by using mud pulse signal ; the ground decoding system collects the mud pulse signal and then decodes and displays the parameters under the down-hole according to the designed encoding rules and the correct detection and recognition of the ground decoding system towards the received mud pulse signal is one kind of the key technology of MWD. This paper introduces digit of Manchester encoding that transmits data and the format of the wireless transmission of data under the down-hole and develops a set of ground decoding systems. The ground decoding algorithm uses FIR (Finite impulse response) digital filtering to make de-noising on the mud pulse signal, then adopts the related base value modulating algorithm to eliminate the pump pulse base value of the denoised mud pulse signal, finally analyzes the mud pulse signal waveform shape of the selected Manchester encoding in three bits cycles, and applies the pattern similarity recognition algorithm to the mud pulse signal recognition. The field experiment results show that the developed device can make correctly extraction and recognition for the mud pulse signal with simple and practical decoding process and meet the requirements of engineering application.

  8. All-optical signal processing technique for secure optical communication

    NASA Astrophysics Data System (ADS)

    Qian, Feng-chen; Su, Bing; Ye, Ya-lin; Zhang, Qian; Lin, Shao-feng; Duan, Tao; Duan, Jie

    2015-10-01

    Secure optical communication technologies are important means to solve the physical layer security for optical network. We present a scheme of secure optical communication system by all-optical signal processing technique. The scheme consists of three parts, as all-optical signal processing unit, optical key sequence generator, and synchronous control unit. In the paper, all-optical signal processing method is key technology using all-optical exclusive disjunction (XOR) gate based on optical cross-gain modulation effect, has advantages of wide dynamic range of input optical signal, simple structure and so on. All-optical XOR gate composed of two semiconductor optical amplifiers (SOA) is a symmetrical structure. By controlling injection current, input signal power, delay and filter bandwidth, the extinction ratio of XOR can be greater than 8dB. Finally, some performance parameters are calculated and the results are analyzed. The simulation and experimental results show that the proposed method can be achieved over 10Gbps optical signal encryption and decryption, which is simple, easy to implement, and error-free diffusion.

  9. 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.

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

    PubMed

    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. PMID:19791987

  11. Parallel Signal Processing and System Simulation using aCe

    NASA Technical Reports Server (NTRS)

    Dorband, John E.; Aburdene, Maurice F.

    2003-01-01

    Recently, networked and cluster computation have become very popular for both signal processing and system simulation. A new language is ideally suited for parallel signal processing applications and system simulation since it allows the programmer to explicitly express the computations that can be performed concurrently. In addition, the new C based parallel language (ace C) for architecture-adaptive programming allows programmers to implement algorithms and system simulation applications on parallel architectures by providing them with the assurance that future parallel architectures will be able to run their applications with a minimum of modification. In this paper, we will focus on some fundamental features of ace C and present a signal processing application (FFT).

  12. 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.

  13. Signal processing for determining water height in steam pipes with dynamic surface conditions

    NASA Astrophysics Data System (ADS)

    Lih, Shyh-Shiuh; Lee, Hyeong Jae; Bar-Cohen, Yoseph

    2015-03-01

    An enhanced signal processing method based on the filtered Hilbert envelope of the auto-correlation function of the wave signal has been developed to monitor the height of condensed water through the steel wall of steam pipes with dynamic surface conditions. The developed signal processing algorithm can also be used to estimate the thickness of the pipe to determine the cut-off frequency for the low pass filter frequency of the Hilbert Envelope. Testing and analysis results by using the developed technique for dynamic surface conditions are presented. A multiple array of transducers setup and methodology are proposed for both the pulse-echo and pitch-catch signals to monitor the fluctuation of the water height due to disturbance, water flow, and other anomaly conditions.

  14. Distributed Signal Processing for Wireless EEG Sensor Networks.

    PubMed

    Bertrand, Alexander

    2015-11-01

    Inspired by ongoing evolutions in the field of wireless body area networks (WBANs), this tutorial paper presents a conceptual and exploratory study of wireless electroencephalography (EEG) sensor networks (WESNs), with an emphasis on distributed signal processing aspects. A WESN is conceived as a modular neuromonitoring platform for high-density EEG recordings, in which each node is equipped with an electrode array, a signal processing unit, and facilities for wireless communication. We first address the advantages of such a modular approach, and we explain how distributed signal processing algorithms make WESNs more power-efficient, in particular by avoiding data centralization. We provide an overview of distributed signal processing algorithms that are potentially applicable in WESNs, and for illustration purposes, we also provide a more detailed case study of a distributed eye blink artifact removal algorithm. Finally, we study the power efficiency of these distributed algorithms in comparison to their centralized counterparts in which all the raw sensor signals are centralized in a near-end or far-end fusion center. PMID:25850092

  15. Remote laser interferometer with pseudo-heterodyne signal processing

    NASA Astrophysics Data System (ADS)

    Liokumovich, Leonid B.; Markov, Sergey I.

    2000-11-01

    Optic and fiber optic interference (phase) scheme are successfully used in creating of hydro-acoustic sensors, vibration sensors and measurers of other magnitudes. The most actual type of the interference sensors is a construction which utilize remote passive all optics sensitive interferometer (Fig. 1). In such devices the additional phase modulation and special methods of signal processing are traditionally used. The resolution of the interference sensor is limited by the noise factor of its elements. The final output noise level of the sensor depends of the optical scheme and method of signal processing. This report is devoted to the neutralization of the influence of the light intensity fluctuations on the sensor resolution using pseudo-heterodyne signal processing. Suppression of this factor in phase optical sensors is not often discussed in literature because laser intensity noise is usually insignificant relatively to other noise mechanisms. However in remote sensors with long distance between signal processing unit and sensitive element we have another situation. External influence (acoustics, vibrations) on lead in and lead out optical paths gives an essential income in the intensity noise at the optics exit. This income is especially sizable (up to tens percents) in remote sensors with opened air optical lead in and out. Sometimes they can even make signal measuring impossible.

  16. Single photon laser altimeter simulator and statistical signal processing

    NASA Astrophysics Data System (ADS)

    Vacek, Michael; Prochazka, Ivan

    2013-05-01

    Spaceborne altimeters are common instruments onboard the deep space rendezvous spacecrafts. They provide range and topographic measurements critical in spacecraft navigation. Simultaneously, the receiver part may be utilized for Earth-to-satellite link, one way time transfer, and precise optical radiometry. The main advantage of single photon counting approach is the ability of processing signals with very low signal-to-noise ratio eliminating the need of large telescopes and high power laser source. Extremely small, rugged and compact microchip lasers can be employed. The major limiting factor, on the other hand, is the acquisition time needed to gather sufficient volume of data in repetitive measurements in order to process and evaluate the data appropriately. Statistical signal processing is adopted to detect signals with average strength much lower than one photon per measurement. A comprehensive simulator design and range signal processing algorithm are presented to identify a mission specific altimeter configuration. Typical mission scenarios (celestial body surface landing and topographical mapping) are simulated and evaluated. The high interest and promising single photon altimeter applications are low-orbit (˜10 km) and low-radial velocity (several m/s) topographical mapping (asteroids, Phobos and Deimos) and landing altimetry (˜10 km) where range evaluation repetition rates of ˜100 Hz and 0.1 m precision may be achieved. Moon landing and asteroid Itokawa topographical mapping scenario simulations are discussed in more detail.

  17. 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…

  18. Phosphorelays Provide Tunable Signal Processing Capabilities for the Cell

    PubMed Central

    Kothamachu, Varun B.; Feliu, Elisenda; Wiuf, Carsten; Cardelli, Luca; Soyer, Orkun S.

    2013-01-01

    Achieving a complete understanding of cellular signal transduction requires deciphering the relation between structural and biochemical features of a signaling system and the shape of the signal-response relationship it embeds. Using explicit analytical expressions and numerical simulations, we present here this relation for four-layered phosphorelays, which are signaling systems that are ubiquitous in prokaryotes and also found in lower eukaryotes and plants. We derive an analytical expression that relates the shape of the signal-response relationship in a relay to the kinetic rates of forward, reverse phosphorylation and hydrolysis reactions. This reveals a set of mathematical conditions which, when satisfied, dictate the shape of the signal-response relationship. We find that a specific topology also observed in nature can satisfy these conditions in such a way to allow plasticity among hyperbolic and sigmoidal signal-response relationships. Particularly, the shape of the signal-response relationship of this relay topology can be tuned by altering kinetic rates and total protein levels at different parts of the relay. These findings provide an important step towards predicting response dynamics of phosphorelays, and the nature of subsequent physiological responses that they mediate, solely from topological features and few composite measurements; measuring the ratio of reverse and forward phosphorylation rate constants could be sufficient to determine the shape of the signal-response relationship the relay exhibits. Furthermore, they highlight the potential ways in which selective pressures on signal processing could have played a role in the evolution of the observed structural and biochemical characteristic in phosphorelays. PMID:24244132

  19. Signal Processing For Chemical Sensing: Statistics or Biological Inspiration

    NASA Astrophysics Data System (ADS)

    Marco, Santiago

    2011-09-01

    Current analytical instrumentation and continuous sensing can provide huge amounts of data. Automatic signal processing and information evaluation is needed to overcome drowning in data. Today, statistical techniques are typically used to analyse and extract information from continuous signals. However, it is very interesting to note that biology (insects and vertebrates) has found alternative solutions for chemical sensing and information processing. This is a brief introduction to the developments in the European Project: Bio-ICT NEUROCHEM: Biologically Inspired Computation for Chemical Sensing (grant no. 216916) Fp7 project devoted to biomimetic olfactory systems.

  20. Digital signal processing utilizing a generic instruction set

    NASA Astrophysics Data System (ADS)

    Mosley, V. V. W.; Bronder, J.; Wenk, A.

    In order to maintain a degree of technological equivalence between software and hardware in advanced VLSI development efforts, a set of generic instructions has been defined in the form of Ada-callable procedures which invoke a complex sequence of events for the execution of vector instructions in signal processing modules. Attention is presently given to real time signal processing functions in the cases of fighter aircraft fire control radar, passive sonar surveillance, communications systems' FSK demodulation and bit regeneration, and electronic warfare support measures and countermeasures. Generalized examples of each application are given as data flow graphs.

  1. [Fiberoptic measurement of myocardial contraction--correlation of the signal with hemodynamic values].

    PubMed

    Müller, S; Kloppe, A; Mügge, A; Werner, J

    2002-01-01

    In addition to the intracardial ECG, the mechanical myocard contraction should be used as another input signal for cardiac pacemakers and implantable defibrillators. Therefore a fiberoptical measurement system was designed. A sensor-fiber was placed in the coronary venous system. An opto-electronic system converts the optical losses, caused by bending of the fiber, into a proportional voltage. This method allows measuring of the left ventricular myocard contraction strength. By theoretical calculations it was shown, that a good correlation of the sensor-signal and the left ventricular radius can be expected. Additional investigations using an isolated beating pig heart were performed. A high correlation of the sensor-signal and the left ventricular stroke volume was shown. PMID:12465226

  2. Limitations of signal averaging due to temporal correlation in laser remote-sensing measurements

    NASA Technical Reports Server (NTRS)

    Menyuk, N.; Killinger, D. K.; Menyuk, C. R.

    1982-01-01

    Laser remote sensing involves the measurement of laser-beam transmission through the atmosphere and is subject to uncertainties caused by strong fluctuations due primarily to speckle, glint, and atmospheric-turbulence effects. These uncertainties are generally reduced by taking average values of increasing numbers of measurements. An experiment was carried out to directly measure the effect of signal averaging on back-scattered laser return signals from a diffusely reflecting target using a direct-detection differential-absorption lidar (DIAL) system. The improvement in accuracy obtained by averaging over increasing numbers of data points was found to be smaller than that predicted for independent measurements. The experimental results are shown to be in excellent agreement with a theoretical analysis which considers the effect of temporal correlation. The analysis indicates that small but long-term temporal correlation severely limits the improvement available through signal averaging.

  3. Signal correlation in the tandem of a spin oscillator and microwave frequency discriminator with laser-pumped alkali atoms

    NASA Astrophysics Data System (ADS)

    Baranov, A. A.; Ermak, S. V.; Sagitov, E. A.; Smolin, R. V.; Semenov, V. V.

    2016-02-01

    We have studied the influence of low-frequency noise on the stability of resonance frequency of a self-oscillating magnetometer on 87Rb vapor with simultaneous monitoring of the signal of radio-optical resonance on the magnetic-field-dependent microwave transition under laser pumping at the D 2 line of the head doublet. The difference of synchronous records of detected signals reduced to the same scale in magnetic field units was processed to determine the Allan variance as a function of the averaging time. The correlation coefficient characterizing the coupling of detected signals determined by the pumping rate and intensity of radio fields generated in the region of the absorption chamber. The self-oscillating magnetometer can only operate provided that there is laser tuning to the long-wavelength component of the electric-dipole transition.

  4. Correlational analysis of electroencephalographic and end-tidal carbon dioxide signals during breath-hold exercise.

    PubMed

    Morelli, Maria Sole; Vanello, Nicola; Giannoni, Alberto; Frijia, Francesca; Hartwig, Valentina; Maestri, Michelangelo; Bonanni, Enrica; Carnicelli, Luca; Positano, Vincenzo; Passino, Claudio; Emdin, Michele; Landini, Luigi

    2015-08-01

    The central mechanism of breathing control is not totally understood. Several studies evaluated the correlation between electroencephalographic (EEG) power spectra and respiratory signals by performing resting state tasks or adopting hypercapnic/hypoxic stimuli. The observation of brain activity during voluntary breath hold tasks, might be an useful approach to highlight the areas involved in mechanism of breath regulation. Nevertheless, studies of brain activity with EEG could present some limitations due to presence of severe artifacts. When artifact rejection methods, as independent component analysis, cannot reliably clean EEG data, it is necessary to exclude noisy segments. In this study, global field power in the delta band and end-tidal CO2 were derived from EEG and CO2 signals respectively in 4 healthy subjects during a breath-hold task. The cross correlation function between the two signals was estimated taking into account the presence of missing samples. The statistical significance of the correlation coefficients at different time lags was assessed using surrogate data. Some simulations are introduced to evaluate the effect of missing data on the correlational analysis and their results are discussed. Results obtained on subjects show a significant correlation between changes in EEG power in the delta band and end-tidal CO2. Moreover, the changes in end-tidal CO2 were found to precede those of global field power. These results might help to better understand the cortical mechanisms involved in the control of breathing. PMID:26737684

  5. Advanced study of video signal processing in low signal to noise environments

    NASA Technical Reports Server (NTRS)

    Carden, F.; Gilbert, A.

    1972-01-01

    The frame to frame correlation properties of the video process are utilized to reduce the mean squared error of the demodulated video where zero mean noise is a factor. An interpolative estimator is used for continuous estimation with the output process delayed in time by one frame. Theoretical development shows that for the model herein developed reduction of the mean squared error by 1.0 to 4.0 db possible for parameter ranges of interest. Interpolative estimation using inter-frame correlation properties of a video process is then applied to the Apollo 17 parameters to yield a model for application on that mission.

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

    PubMed Central

    Kudla, Jörg; Batistič, 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

  7. 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.

  8. Cross-correlation of the cosmic 21-cm signal and Lyman alpha emitters during reionization

    NASA Astrophysics Data System (ADS)

    Sobacchi, Emanuele; Mesinger, Andrei; Greig, Bradley

    2016-04-01

    Interferometry of the cosmic 21-cm signal is set to revolutionize our understanding of the Epoch of Reionization (EoR), eventually providing 3D maps of the early Universe. Initial detections however will be low signal-to-noise, limited by systematics. To confirm a putative 21-cm detection, and check the accuracy of 21-cm data analysis pipelines, it would be very useful to cross-correlate against a genuine cosmological signal. The most promising cosmological signals are wide-field maps of Lyman alpha emitting galaxies (LAEs), expected from the Subaru Hyper-Suprime Cam (HSC) Ultra-Deep field. Here we present estimates of the correlation between LAE maps at z ˜ 7 and the 21-cm signal observed by both the Low Frequency Array (LOFAR) and the planned Square Kilometer Array Phase 1 (SKA1). We adopt a systematic approach, varying both: (i) the prescription of assigning LAEs to host halos; and (ii) the large-scale structure of neutral and ionized regions (i.e. EoR morphology). We find that the LAE-21cm cross-correlation is insensitive to (i), thus making it a robust probe of the EoR. A 1000 h observation with LOFAR would be sufficient to discriminate at ≳ 1 σ a fully ionized Universe from one with a mean neutral fraction of bar{x}_HI≈ 0.50, using the LAE-21cm cross-correlation function on scales of R ≈3-10 Mpc. Unlike LOFAR, whose detection of the LAE-21cm cross-correlation is limited by noise, SKA1 is mostly limited by ignorance of the EoR morphology. However, the planned 100 h wide-field SKA1-Low survey will be sufficient to discriminate an ionized Universe from one with bar{x}_HI=0.25, even with maximally pessimistic assumptions.

  9. Canonical Correlation to Estimate the Degree of Parkinsonism from Local Field Potential and Electroencephalographic Signals

    PubMed Central

    Sanders, Teresa H.; Devergnas, Annaelle; Wichmann, Thomas; Clements, Mark A.

    2016-01-01

    In this study, modulation index (MI) features derived from local field potential (LFP) recordings in the subthalamic nucleus (STN) and electroencephalographic recordings (EEGs) from the primary motor cortex are shown to correlate with both the overall motor impairment and motor subscores in a monkey model of parkinsonism. The MI features used are measures of phase-amplitude cross frequency coupling (CFC) between frequency sub-bands. We used complex wavelet transforms to extract six spectral sub-bands within the 3–60 Hz range from LFP and EEG signals. Using the method of canonical correlation, we show that weighted combinations of the MI features in LFP or EEG signals correlate significantly with individual and composite scores on a scale for parkinsonian disability.

  10. Analysis of signal processing techniques in pulsed thermography

    NASA Astrophysics Data System (ADS)

    Lopez, Fernando; Ibarra-Castanedo, Clemente; Maldague, Xavier; de Paulo Nicolau, Vicente

    2013-05-01

    Pulsed Thermography (PT) is one of the most widely used approaches for the inspection of composites materials, being its main attraction the deployment in transient regime. However, due to the physical phenomena involved during the inspection, the signals acquired by the infrared camera are nearly always affected by external reflections and local emissivity variations. Furthermore, non-uniform heating at the surface and thermal losses at the edges of the material also represent constraints in the detection capability. For this reason, the thermographics signals should be processed in order to improve - qualitatively and quantitatively - the quality of the thermal images. Signal processing constitutes an important step in the chain of thermal image analysis, especially when defects characterization is required. Several of the signals processing techniques employed nowadays are based on the one-dimensional solution of Fourier's law of heat conduction. This investigation brings into discussion the three-most used techniques based on the 1D Fourier's law: Thermographic Signal Reconstruction (TSR), Differential Absolute Contrast (DAC) and Pulsed Phase Thermography (PPT), applied on carbon fiber laminated composites. It is of special interest to determine the detection capabilities of each technique, allowing in this way more reliable results when performing an inspection by PT.

  11. 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.

  12. dNSP: a biologically inspired dynamic Neural network approach to Signal Processing.

    PubMed

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

    2008-09-01

    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 power density spectrum functions are suitable tools to manage this issue. These functions are usually defined with statistical formulation. On the other hand, in biology there can be found numerous processes in which signals are processed to give a feature vector; for example, the processing of sound by the auditory system. In this work, the dNSP (dynamic Neural Signal Processing) architecture is proposed. This architecture allows representing a time-varying signal by a spatial (thus statical) vector. Inspired by the aforementioned biological processes, the dNSP performs frequency decomposition using an analogical parallel algorithm carried out by simple processing units. The architecture has been developed under the paradigm of a multilayer neural network, where the different layers are composed by units whose activation functions have been extracted from the theory of Neural Dynamic [Grossberg, S. (1988). Nonlinear neural networks principles, mechanisms and architectures. Neural Networks, 1, 17-61]. A theoretical study of the behavior of the dynamic equations of the units and their relationship with some statistical functions allows establishing a parallelism between the unit activations and correlation and power density spectrum functions. To test the capabilities of the proposed approach, several testbeds have been employed, i.e. the frequencial study of mathematical functions. As a possible application of the architecture, a highly interesting problem in the field of automatic control is addressed: the recognition of a controlled DC motor operating state. PMID:18579344

  13. Comparative effects of optical-correlator signal-dependent and signal-independent noise on pattern-recognition performance with the phase-only filter

    NASA Astrophysics Data System (ADS)

    Terrillon, Jean-Christophe

    1995-11-01

    The comparative effects of optical-correlator signal-dependent and additive signal-independent noise on correlation-filter performance are analyzed by three different performance measures. For an identical value of the signal-to-noise ratio imposed on each type of noise in a binary input image, computer simulations performed with the phase-only filter show (i) that additive Gaussian signal-independent noise yields a much larger correlation-performance degradation than signal-dependent noise and (ii) that the different types of signal-dependent noise lead to similar correlation results because of similar effects on the input image that are inherent to the nature of the noise.

  14. Fault Detection of Gearbox from Inverter Signals Using Advanced Signal Processing Techniques

    NASA Astrophysics Data System (ADS)

    Pislaru, C.; Lane, M.; Ball, A. D.; Gu, F.

    2012-05-01

    The gear faults are time-localized transient events so time-frequency analysis techniques (such as the Short-Time Fourier Transform, Wavelet Transform, motor current signature analysis) are widely used to deal with non-stationary and nonlinear signals. Newly developed signal processing techniques (such as empirical mode decomposition and Teager Kaiser Energy Operator) enabled the recognition of the vibration modes that coexist in the system, and to have a better understanding of the nature of the fault information contained in the vibration signal. However these methods require a lot of computational power so this paper presents a novel approach of gearbox fault detection using the inverter signals to monitor the load, rather than the motor current. The proposed technique could be used for continuous monitoring as well as on-line damage detection systems for gearbox maintenance.

  15. 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.

  16. Neural Correlates of Sublexical Processing in Phonological Working Memory

    ERIC Educational Resources Information Center

    McGettigan, Carolyn; Warren, Jane E.; Eisner, Frank; Marshall, Chloe R.; Shanmugalingam, Pradheep; Scott, Sophie K.

    2011-01-01

    This study investigated links between working memory and speech processing systems. We used delayed pseudoword repetition in fMRI to investigate the neural correlates of sublexical structure in phonological working memory (pWM). We orthogonally varied the number of syllables and consonant clusters in auditory pseudowords and measured the neural

  17. Neural Correlates of Sublexical Processing in Phonological Working Memory

    ERIC Educational Resources Information Center

    McGettigan, Carolyn; Warren, Jane E.; Eisner, Frank; Marshall, Chloe R.; Shanmugalingam, Pradheep; Scott, Sophie K.

    2011-01-01

    This study investigated links between working memory and speech processing systems. We used delayed pseudoword repetition in fMRI to investigate the neural correlates of sublexical structure in phonological working memory (pWM). We orthogonally varied the number of syllables and consonant clusters in auditory pseudowords and measured the neural…

  18. 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…

  19. Multiple-channel optical signal processing with wavelength-waveform conversions, pulsewidth tunability, and signal regeneration.

    PubMed

    Nguyen Tan, Hung; Matsuura, Motoharu; Katafuchi, Tomoya; Kishi, Naoto

    2009-12-01

    A multiple-channel multiple-function optical signal processor (MCMF-OSP) including wavelength-waveform conversions, pulsewidth tunability, and signal regeneration is realized through AND logic gate based on optical parametric processing with a pulsewidth-tunable RZ clock pump. The proposed scheme simultaneously offers four signal processing functions which are useful in wavelength-division multiplexing (WDM) transmission systems, and at network nodes with the necessity for multiple-channel data processing. After the discussions on the concept of MCMF-OSP, a proof-of concept experiment is demonstrated on four 10 Gb/s nonreturn-to-zero (NRZ) data format channels using nonlinearities in semiconductor optical amplifier (SOA) and highly nonlinear fiber (HNLF). A wavelength and waveform conversions to return-to-zero (RZ) modulation format are obtained together with pulsewidth-tunable range from 20% to 80% duty cycles for all input signals. The converted signals inherit the timing and waveform of the RZ clock pump, thus resulting in a time regeneration and large tolerance to narrow-band optical filtering (NAOF) and fiber accumulated chromatic dispersion (CD). PMID:20052222

  20. Smart signal processing for an evolving electric grid

    NASA Astrophysics Data System (ADS)

    Silva, Leandro Rodrigues Manso; Duque, Calos Augusto; Ribeiro, Paulo F.

    2015-12-01

    Electric grids are interconnected complex systems consisting of generation, transmission, distribution, and active loads, recently called prosumers as they produce and consume electric energy. Additionally, these encompass a vast array of equipment such as machines, power transformers, capacitor banks, power electronic devices, motors, etc. that are continuously evolving in their demand characteristics. Given these conditions, signal processing is becoming an essential assessment tool to enable the engineer and researcher to understand, plan, design, and operate the complex and smart electronic grid of the future. This paper focuses on recent developments associated with signal processing applied to power system analysis in terms of characterization and diagnostics. The following techniques are reviewed and their characteristics and applications discussed: active power system monitoring, sparse representation of power system signal, real-time resampling, and time-frequency (i.e., wavelets) applied to power fluctuations.

  1. Signal processing and physiological modeling--part 1: Surface analysis.

    PubMed

    Coatrieux, Jean-Louis

    2002-01-01

    Signal processing offers a wide spectrum of theories, methods, and algorithms for addressing a variety of problems ranging from noise reduction, restoration, detection (of events or changes), spatiotemporal dynamics estimation, source localization, and pattern recognition. However, the classical assumptions (stationarity, linearity, etc.) usually do not apply in real situations. Recent advances, such as time-scale and time-frequency transforms, data fusion, long-range dependence, and higher order moments, do not always provide sufficiently robust solutions. In this article, the basic properties and generic features of biomedical signals are examined using a wide range of examples. Algorithmic results are presented to show not only the potential performance but also the limitations of the processing resources at our disposal. The last section describes and discusses signal matching, scenario recognition, and data fusion. PMID:12650284

  2. SoC-based architecture for biomedical signal processing.

    PubMed

    Gutiérrez-Rivas, R; Hernández, A; García, J J; Marnane, W

    2015-08-01

    Over the last decades, many algorithms have been proposed for processing biomedical signals. Most of these algorithms have been focused on the elimination of noise and artifacts existing in these signals, so they can be used for automatic monitoring and/or diagnosis applications. With regard to remote monitoring, the use of portable devices often requires a reduced number of resources and power consumption, being necessary to reach a trade-off between the accuracy of algorithms and their computational complexity. This paper presents a SoC (System-on-Chip) architecture, based on a FPGA (Field-Programmable Gate Array) device, suitable for the implementation of biomedical signal processing. The proposal has been successfully validated by implementing an efficient QRS complex detector. The results show that, using a reduced amount of resources, values of sensitivity and positive predictive value above 99.49% are achieved, which make the proposed approach suitable for telemedicine applications. PMID:26737663

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

    SciTech Connect

    Li, Xuefeng; Cao, Guangzhan; Liu, Hongjun

    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.

  4. 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. (Inventor)

    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.

  5. 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].

  6. Parallel Processing of Broad-Band PPM Signals

    NASA Technical Reports Server (NTRS)

    Gray, Andrew; Kang, Edward; Lay, Norman; Vilnrotter, Victor; Srinivasan, Meera; Lee, Clement

    2010-01-01

    A parallel-processing algorithm and a hardware architecture to implement the algorithm have been devised for timeslot synchronization in the reception of pulse-position-modulated (PPM) optical or radio signals. As in the cases of some prior algorithms and architectures for parallel, discrete-time, digital processing of signals other than PPM, an incoming broadband signal is divided into multiple parallel narrower-band signals by means of sub-sampling and filtering. The number of parallel streams is chosen so that the frequency content of the narrower-band signals is low enough to enable processing by relatively-low speed complementary metal oxide semiconductor (CMOS) electronic circuitry. The algorithm and architecture are intended to satisfy requirements for time-varying time-slot synchronization and post-detection filtering, with correction of timing errors independent of estimation of timing errors. They are also intended to afford flexibility for dynamic reconfiguration and upgrading. The architecture is implemented in a reconfigurable CMOS processor in the form of a field-programmable gate array. The algorithm and its hardware implementation incorporate three separate time-varying filter banks for three distinct functions: correction of sub-sample timing errors, post-detection filtering, and post-detection estimation of timing errors. The design of the filter bank for correction of timing errors, the method of estimating timing errors, and the design of a feedback-loop filter are governed by a host of parameters, the most critical one, with regard to processing very broadband signals with CMOS hardware, being the number of parallel streams (equivalently, the rate-reduction parameter).

  7. The Khoros software development environment for image and signal processing.

    PubMed

    Konstantinides, K; Rasure, J R

    1994-01-01

    Data flow visual language systems allow users to graphically create a block diagram of their applications and interactively control input, output, and system variables. Khoros is an integrated software development environment for information processing and visualization. It is particularly attractive for image processing because of its rich collection of tools for image and digital signal processing. This paper presents a general overview of Khoros with emphasis on its image processing and DSP tools. Various examples are presented and the future direction of Khoros is discussed. PMID:18291923

  8. 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.

  9. An Interactive Graphics Program for Investigating Digital Signal Processing.

    ERIC Educational Resources Information Center

    Miller, Billy K.; And Others

    1983-01-01

    Describes development of an interactive computer graphics program for use in teaching digital signal processing. The program allows students to interactively configure digital systems on a monitor display and observe their system's performance by means of digital plots on the system's outputs. A sample program run is included. (JN)

  10. Error compensation via signal correlation in high-precision closed-loop fiber optic gyros

    NASA Astrophysics Data System (ADS)

    Spahlinger, Guenter; Kemmler, Manfred W.; Ruf, Markus; Ribes, Mauricio A.; Zimmermann, Steffen

    1996-11-01

    Fiber optic gyroscopes (FOGs) are preferably driven as closed-loop controlled systems, if linearity and dynamic range are of major concern. Proper modulation of the Sagnac interferometer (SIF) feedback signal is necessary to minimize low frequency signal perturbation and to reliably detect luminance intensity in the linear regions of the sinusoidal Sagnac phase to intensity mapping. Deterministic modulation however, is accompanied by well known 'dead zones' and bias errors due to unavoidable crosstalk between the modulator and the optical detector. In the paper we propose a high precision closed-loop FOG system with deadbeat control and pseudorandom modulation of the SIF feedback signal. The random modulation principle completely eliminates 'dead zones' in the detection of small rotation rates, and bears an inherent potential for compensation and control of several error sources encountered in non-ideal systems by means of signal correlation. The principle of correlation based control is introduced in a general context and applied to a set of dedicated control loops within the proposed closed-loop FOG. Results obtained form several prototype realizations of the correlation controlled high precision FOG indicate a potential for bias error reduction by two orders of magnitude and considerable decrease in random walk.

  11. Coherent broadband sonar signal processing with the environmentally corrected matched filter

    NASA Astrophysics Data System (ADS)

    Camin, Henry John, III

    The matched filter is the standard approach for coherently processing active sonar signals, where knowledge of the transmitted waveform is used in the detection and parameter estimation of received echoes. Matched filtering broadband signals provides higher levels of range resolution and reverberation noise suppression than can be realized through narrowband processing. Since theoretical processing gains are proportional to the signal bandwidth, it is typically desirable to utilize the widest band signals possible. However, as signal bandwidth increases, so do environmental effects that tend to decrease correlation between the received echo and the transmitted waveform. This is especially true for ultra wideband signals, where the bandwidth exceeds an octave or approximately 70% fractional bandwidth. This loss of coherence often results in processing gains and range resolution much lower than theoretically predicted. Wiener filtering, commonly used in image processing to improve distorted and noisy photos, is investigated in this dissertation as an approach to correct for these environmental effects. This improved signal processing, Environmentally Corrected Matched Filter (ECMF), first uses a Wiener filter to estimate the environmental transfer function and then again to correct the received signal using this estimate. This process can be viewed as a smarter inverse or whitening filter that adjusts behavior according to the signal to noise ratio across the spectrum. Though the ECMF is independent of bandwidth, it is expected that ultra wideband signals will see the largest improvement, since they tend to be more impacted by environmental effects. The development of the ECMF and demonstration of improved parameter estimation with its use are the primary emphases in this dissertation. Additionally, several new contributions to the field of sonar signal processing made in conjunction with the development of the ECMF are described. A new, nondimensional wideband ambiguity function is presented as a way to view the behavior of the matched filter with and without the decorrelating environmental effects; a new, integrated phase broadband angle estimation method is developed and compared to existing methods; and a new, asymptotic offset phase angle variance model is presented. Several data sets are used to demonstrate these new contributions. High fidelity Sonar Simulation Toolset (SST) synthetic data is used to characterize the theoretical performance. Two in-water data sets were used to verify assumptions that were made during the development of the ECMF. Finally, a newly collected in-air data set containing ultra wideband signals was used in lieu of a cost prohibitive underwater experiment to demonstrate the effectiveness of the ECMF at improving parameter estimates.

  12. Two-Dimensional Signal Processing in Radon Space

    NASA Astrophysics Data System (ADS)

    Easton, Roger Lee, Jr.

    This dissertation considers a method for processing two-dimensional (2-D) signals (e.g. imagery) by transformation to a coordinate space where the 2-D operation separates into orthogonal 1-D operations. After processing, the 2-D output is reconstructed by a second coordinate transformation. This approach is based on the Radon transform, which maps a two-dimensional Cartesian representation of a signal into a series of one-dimensional signals by line-integral projection. The mathematical principles of this transformation are well -known as the basis for medical computed tomography. This approach can process signals more rapidly than conventional digital processing and more flexibly and precisely than optical techniques. A new formulation of the Radon transform is introduced that employs a new transformation--the central-slice transform --to symmetrize the operations between the Cartesian and Radon representations of the signal and to aid in analyzing operations that may be susceptible to solution in this manner. It is well-known that 2-D Fourier transforms and convolutions can be performed by 1-D operations after Radon transformation, as proven by the central-slice and filter theorems. Demonstrations of these operations via Radon transforms are described. An optical system has been constructed to derive the line-integral projections of 2-D transmissive or reflective input data. Fourier transforms of the projections are derived by a surface-acoustic-wave chirp Fourier transformer, and filtering is performed in a surface-acoustic-wave convolver. Reconstruction of the processed 2-D signal is performed optically. The system can process 2-D imagery at approximately 5 frames/second, though rates to 30 frames/second are achievable if a faster image rotator is added. Other signal processing operations in Radon space are demonstrated, including Labeyrie stellar speckle interferometry, the Hartley transform, and the joint coordinate-frequency representations such as the Wigner distribution function. Other operations worthy of further study include derivation of the 2-D cepstrum, and several spectrum estimation algorithms.

  13. Quantum process estimation via generic two-body correlations

    NASA Astrophysics Data System (ADS)

    Mohseni, M.; Rezakhani, A. T.; Barreiro, J. T.; Kwiat, P. G.; Aspuru-Guzik, A.

    2010-03-01

    Performance of quantum process estimation is naturally limited by fundamental, random, and systematic imperfections of preparations and measurements. These imperfections may lead to considerable errors in the process reconstruction because standard data-analysis techniques usually presume ideal devices. Here, by utilizing generic auxiliary quantum or classical correlations, we provide a framework for the estimation of quantum dynamics via a single measurement apparatus. By construction, this approach can be applied to quantum tomography schemes with calibrated faulty-state generators and analyzers. Specifically, we present a generalization of the work begun by M. Mohseni and D. A. Lidar [Phys. Rev. Lett. 97, 170501 (2006)] with an imperfect Bell-state analyzer. We demonstrate that for several physically relevant noisy preparations and measurements, classical correlations and a small data-processing overhead suffice to accomplish the full system identification. Furthermore, we provide the optimal input states whereby the error amplification due to inversion of the measurement data is minimal.

  14. Entropy bounds for quantum processes with initial correlations

    NASA Astrophysics Data System (ADS)

    Vinjanampathy, Sai; Modi, Kavan

    2015-11-01

    Quantum technology is progressing towards fast quantum control over systems interacting with small environments. Hence such technologies are operating in a regime where the environment remembers the system's past, and the applicability of complete-positive trace-preserving maps is no longer valid. The departure from complete positivity means many useful bounds, such as entropy production, Holevo, and data processing inequality are no longer applicable to such systems. We address these issues by deriving a generalized bound for entropy valid for quantum dynamics with arbitrary system-environment correlations. We employ superchannels, which map quantum operations performed by the experimenter, represented in terms of completely positive maps, to states. Our bound has information-theoretic applications, as it generalizes the data processing inequality and the Holevo bound. We prove that both data processing inequality and the Holevo are valid even when a system is correlated with the environment.

  15. Advanced signal processing methods for pulsed laser vibrometry.

    PubMed

    Totems, Julien; Jolivet, Véronique; Ovarlez, Jean-Philippe; Martin, Nadine

    2010-07-10

    Although pulsed coherent laser radar vibrometry has been introduced as an improvement over its continuous wave (CW) counterpart, it remains very sensitive to decorrelation noises, such as speckle, and other disturbances of its measurement. Taking advantage of more polyvalent polypulse waveforms, we address the issue with advanced signal processing. We have conducted what we believe is the first extensive comparison of processing techniques considering CW, pulse-pair, and polypulse emissions. In this framework, we introduce a computationally efficient maximum likelihood estimator and test signal tracking on pseudo-time-frequency representations (TFRs), which, respectively, help deal with speckle noise and fading of the signal in harsh noise conditions. Our comparison on simulated signals is validated on a 1.55 microm all-fiber vibrometer experiment with an apparatus simulating vibration and strong speckle noise. Results show the advantage of the estimators that take into account actual noise statistics, and call for a wider use of TFRs to track the vibration-modulated signal. PMID:20648175

  16. 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.

  17. The effects of notch filters on the correlation properties of a PN signal

    NASA Technical Reports Server (NTRS)

    Sussman, S. M.; Ferrari, E. J.

    1974-01-01

    With wideband pseudo-noise (PN) communications systems, it is sometimes desirable to supplement the inherent interference rejection capabilities by adding notch filters to attenuate relatively narrowband interference. This correspondence presents an investigation of the effects of notch filters on the performance of PN correlation receivers. A theoretical analysis of the correlation drop due to filter distortion has been conducted and confirmed by experimentation. Additional measurements and analysis have established the trade-off between correlation drop and interference suppression as a function of interference bandwidth. A typical result is that by incurring a penalty of a 1-dB drop in correlation peak, interfering signals having bandwidths of 2 to 3% of the PN chip rate can be attenuated by 25 dB.

  18. Real-Time Signal Processing Data Acquisition Subsystem

    NASA Astrophysics Data System (ADS)

    Sarafinas, George A.; Stein, Alan J.; Bisson, Kenneth J.

    A digital signal processing sub-system has been developed for a coherent carbon dioxide laser radar system at Lincoln Laboratory's Firepond Research Facility. This high-resolution radar is capable of operating with a variety of waveforms; hence, the signal processing requirements of the sub-system vary from one application to the next, and require a sub-system with a high degree of flexibility. The primary function of the Data Acquisition sub-system is to provide range-Doppler images in real-time. Based on this objective, the sub-system must have the ability to route large amounts of digitized data at high rates between specialized processors performing the functions of data acquisition, digital signal processing, archiving, and image processing. A distributed processing design approach was used and the hardware design implemented was configured using all off-the-shelf commercially available products. The sub-system uses a high speed 24 MB/sec central bus and associated processor acting as the hub of the system. Attached to the bus is a large RAM memory buffer. Also attached to the central bus are individual processors which interface to specialized peripherals, performing the tasks of digitizing, vector processing, imaging, and archiving. The software for the complete Data Acquisition and Signal Processing sub-system was developed on a Digital Equipment MicroVAX IITM computer. Software developed for the completed system is coded mostly in a high level language to promote flexibility, modularity, and reducing development time. Some microcode had to be used where speed is essential. All Software design, development, and testing was done under VMSTM.

  19. SEMICONDUCTOR TECHNOLOGY A signal processing method for the friction-based endpoint detection system of a CMP process

    NASA Astrophysics Data System (ADS)

    Chi, Xu; Dongming, Guo; Zhuji, Jin; Renke, Kang

    2010-12-01

    A signal processing method for the friction-based endpoint detection system of a chemical mechanical polishing (CMP) process is presented. The signal process method uses the wavelet threshold denoising method to reduce the noise contained in the measured original signal, extracts the Kalman filter innovation from the denoised signal as the feature signal, and judges the CMP endpoint based on the feature of the Kalman filter innovation sequence during the CMP process. Applying the signal processing method, the endpoint detection experiments of the Cu CMP process were carried out. The results show that the signal processing method can judge the endpoint of the Cu CMP process.

  20. Tracking of electroencephalography signals across brain lobes using motion estimation and cross-correlation

    NASA Astrophysics Data System (ADS)

    Lim, Seng Hooi; Nisar, Humaira; Yap, Vooi Voon; Shim, Seong-O.

    2015-11-01

    Electroencephalography (EEG) is the signal generated by electrical activity in the human brain. EEG topographic maps (topo-maps) give an idea of brain activation. Functional connectivity helps to find functionally integrated relationship between spatially separated brain regions. Brain connectivity can be measured by several methods. The classical methods calculate the coherence and correlation of the signal. We have developed an algorithm to map functional neural connectivity in the brain by using a full search block matching motion estimation algorithm. We have used oddball paradigm to examine the flow of activation across brain lobes for a specific activity. In the first step, the EEG signal is converted into topo-maps. The flow of activation between consecutive frames is tracked using full search block motion estimation, which appears in the form of motion vectors. In the second step, vector median filtering is used to obtain a smooth motion field by removing the unwanted noise. For each topo-map, several activation paths are tracked across various brain lobes. We have also developed correlation activity maps by following the correlation coefficient paths between electrodes. These paths are selected when the correlation coefficient between electrodes is >70%. We have compared the motion estimation path with the correlation coefficient activation maps. The tracked paths obtained by using motion estimation and correlation give very similar results. The inter-subject comparison shows that four out of five subjects tracked path involves all four (occipital, temporal, parietal, frontal) brain lobes for the same stimuli. The intra-subject analysis shows that three out of five subjects show different tracked lobes for different stimuli.

  1. 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.

  2. A digital signal processing system for coherent laser radar

    NASA Technical Reports Server (NTRS)

    Hampton, Diana M.; Jones, William D.; Rothermel, Jeffry

    1991-01-01

    A data processing system for use with continuous-wave lidar is described in terms of its configuration and performance during the second survey mission of NASA'a Global Backscatter Experiment. The system is designed to estimate a complete lidar spectrum in real time, record the data from two lidars, and monitor variables related to the lidar operating environment. The PC-based system includes a transient capture board, a digital-signal processing (DSP) board, and a low-speed data-acquisition board. Both unprocessed and processed lidar spectrum data are monitored in real time, and the results are compared to those of a previous non-DSP-based system. Because the DSP-based system is digital it is slower than the surface-acoustic-wave signal processor and collects 2500 spectra/s. However, the DSP-based system provides complete data sets at two wavelengths from the continuous-wave lidars.

  3. Signaling-mediated Regulation of MicroRNA Processing

    PubMed Central

    Shen, Jia; Hung, Mien-Chie

    2015-01-01

    MicroRNAs (miRNAs) are important regulatory elements for gene expression that are involved in diverse physiological and pathological processes. Canonical miRNA biogenesis consists of a two-step processing, from primary transcripts (pri-miRNAs) to precursor miRNAs (pre-miRNAs) mediated by Drosha in the nucleus and from pre-miRNAs to mature miRNAs mediated by Dicer in the cytoplasm. Various routes of miRNA maturation that are tightly regulated by signaling cascades and specific to an individual or a subclass of miRNAs have been recently identified. Here, we review the current findings in signaling-mediated miRNA processing as well as their potential clinical relevance in cancer. PMID:25660948

  4. 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

  5. New challenges in signal processing in astrophysics: the SKA case

    NASA Astrophysics Data System (ADS)

    Faulkner, Andrew; Zarb-Adami, Kristian; Geralt Bij de Vaate, Jan

    2015-07-01

    Signal processing and communications are driving the latest generation of radio telescopes with major developments taking place for use on the Square Kilometre Array, SKA, the next generation low frequency radio telescope. The data rates and processing performance that can be achieved with currently available components means that concepts from the earlier days of radio astronomy, phased arrays, can be used at higher frequencies, larger bandwidths and higher numbers of beams. Indeed it has been argued that the use of dishes as a mechanical beamformer only gained strong acceptance to mitigate the processing load from phased array technology. The balance is changing and benefits in both performance and cost can be realised. In this paper we will mostly consider the signal processing implementation and control for very large phased arrays consisting of hundreds of thousands of antennas or even millions of antennas. They can use current technology for the initial deployments. These systems are very large extending to hundreds of racks with thousands of signal processing modules that link through high-speed, but commercially available data networking devices. There are major challenges to accurately calibrate the arrays, mitigate power consumption and make the system maintainable.

  6. 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.

  7. 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

  8. 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.

  9. A self-regulating biomolecular comparator for processing oscillatory signals.

    PubMed

    Agrawal, Deepak K; Franco, Elisa; Schulman, Rebecca

    2015-10-01

    While many cellular processes are driven by biomolecular oscillators, precise control of a downstream on/off process by a biochemical oscillator signal can be difficult: over an oscillator's period, its output signal varies continuously between its amplitude limits and spends a significant fraction of the time at intermediate values between these limits. Further, the oscillator's output is often noisy, with particularly large variations in the amplitude. In electronic systems, an oscillating signal is generally processed by a downstream device such as a comparator that converts a potentially noisy oscillatory input into a square wave output that is predominantly in one of two well-defined on and off states. The comparator's output then controls downstream processes. We describe a method for constructing a synthetic biochemical device that likewise produces a square-wave-type biomolecular output for a variety of oscillatory inputs. The method relies on a separation of time scales between the slow rate of production of an oscillatory signal molecule and the fast rates of intermolecular binding and conformational changes. We show how to control the characteristics of the output by varying the concentrations of the species and the reaction rates. We then use this control to show how our approach could be applied to process different in vitro and in vivo biomolecular oscillators, including the p53-Mdm2 transcriptional oscillator and two types of in vitro transcriptional oscillators. These results demonstrate how modular biomolecular circuits could, in principle, be combined to build complex dynamical systems. The simplicity of our approach also suggests that natural molecular circuits may process some biomolecular oscillator outputs before they are applied downstream. PMID:26378119

  10. Signal processing techniques for surveillance radar - An overview

    NASA Astrophysics Data System (ADS)

    Farina, A.; Galati, G.

    1985-06-01

    The present paper is concerned with a survey of the signal processing techniques presently employed in modern air defense and surveillance radars and those techniques likely to be applied in the future. Attention is given to the requirements for enhancing performance in surveillance radar, current processing techniques, advanced techniques, low probability of intercept (LPI) and anti-ARM (anti-radiation missile), anti-stealth, digital beamforming (DBF), adaptivity, high directivity and high resolution, multidimensional processing, target classification, and fieldability. Stealth is the term given to means of reducing the radar cross section of a target and the reduction of infrared emissions from the engine exhaust.

  11. Improved fundamental frequency coding in cochlear implant signal processing.

    PubMed

    Milczynski, Matthias; Wouters, Jan; van Wieringen, Astrid

    2009-04-01

    A new signal processing algorithm for improved pitch perception in cochlear implants is proposed. The algorithm realizes fundamental frequency (F0) coding by explicitly modulating the amplitude of the electrical stimulus. The proposed processing scheme is compared with the standard advanced combination encoder strategy in psychophysical music perception related tasks. Possible filter-bank and loudness cues between the strategies under study were minimized to predominantly focus on differences in temporal processing. The results demonstrate significant benefits provided by the new coding strategy for pitch ranking, melodic contour identification, and familiar melody identification. PMID:19354401

  12. Pre-Processing and Cross-Correlation Techniques for Time-Distance Helioseismology

    NASA Astrophysics Data System (ADS)

    Wang, N.; de Ridder, S.; Zhao, J.

    2014-12-01

    In chaotic wave fields excited by a random distribution of noise sources a cross-correlation of the recordings made at two stations yield the interstation wave-field response. After early successes in helioseismology, laboratory studies and earth-seismology, this technique found broad application in global and regional seismology. This development came with an increasing understanding of pre-processing and cross-correlation workflows to yield an optimal signal-to-noise ratio (SNR). Helioseismologist rely heavily on stacking to increase the SNR. Until now, they have not studied different spectral-whitening and cross-correlation workflows and relies heavily on stacking to increase the SNR. The recordings vary considerably between sunspots and regular portions of the sun. Within the sunspot the periodic effects of the observation satellite orbit are difficult to remove. We remove a running alpha-mean from the data and apply a soft clip to deal with data glitches. The recordings contain energy of both flow and waves. A frequency domain filter selects the wave energy. Then the data is input to several pre-processing and cross-correlation techniques, common to earth seismology. We anticipate that spectral whitening will flatten the energy spectrum of the cross-correlations. We also expect that the cross-correlations converge faster to their expected value when the data is processed over overlapping windows. The result of this study are expected to aid in decreasing the stacking while maintaining good SNR.

  13. Analog integrated circuits design for processing physiological signals.

    PubMed

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

    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 paper, techniques for designing the analog front-end circuits with these three characteristics will be reviewed, including subthreshold circuits, bulk-driven MOSFETs, floating gate MOSFETs, and log-domain circuits to reduce power consumption; methods for designing fully integrated low cutoff frequency circuits; as well as chopper stabilization (CHS) and other techniques that can be used to achieve a high signal-to-noise performance. Novel applications using these techniques will also be discussed. PMID:22275203

  14. Method for measuring radial impurity emission profiles using correlations of line integrated signals

    NASA Astrophysics Data System (ADS)

    Kuldkepp, M.; Brunsell, P. R.; Drake, J.; Menmuir, S.; Rachlew, E.

    2006-04-01

    A method of determining radial impurity emission profiles is outlined. The method uses correlations between line integrated signals and is based on the assumption of cylindrically symmetric fluctuations. Measurements at the reversed field pinch EXTRAP T2R show that emission from impurities expected to be close to the edge is clearly different in raw as well as analyzed data to impurities expected to be more central. Best fitting of experimental data to simulated correlation coefficients yields emission profiles that are remarkably close to emission profiles determined using more conventional techniques. The radial extension of the fluctuations is small enough for the method to be used and bandpass filtered signals indicate that fluctuations below 10kHz are cylindrically symmetric. The novel method is not sensitive to vessel window attenuation or wall reflections and can therefore complement the standard methods in the impurity emission reconstruction procedure.

  15. Correlated and uncorrelated invisible temporal white noise alters mesopic rod signaling.

    PubMed

    Hathibelagal, Amithavikram R; Feigl, Beatrix; Kremers, Jan; Zele, Andrew J

    2016-03-01

    We determined how rod signaling at mesopic light levels is altered by extrinsic temporal white noise that is correlated or uncorrelated with the activity of one (magnocellular, parvocellular, or koniocellular) postreceptoral pathway. Rod and cone photoreceptor excitations were independently controlled using a four-primary photostimulator. Psychometric (Weibull) functions were measured for incremental rod pulses (50 to 250 ms) in the presence (or absence; control) of perceptually invisible subthreshold extrinsic noise. Uncorrelated (rod) noise facilitates rod detection. Correlated postreceptoral pathway noise produces differential changes in rod detection thresholds and decreases the slope of the psychometric functions. We demonstrate that invisible extrinsic noise changes rod-signaling characteristics within the three retinogeniculate pathways at mesopic illumination depending on the temporal profile of the rod stimulus and the extrinsic noise type. PMID:26974946

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

    PubMed

    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

    2013-07-01

    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

  17. 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

  18. Method for measuring radial impurity emission profiles using correlations of line integrated signals

    SciTech Connect

    Kuldkepp, M.; Brunsell, P.R.; Drake, J.; Menmuir, S.; Rachlew, E.

    2006-04-15

    A method of determining radial impurity emission profiles is outlined. The method uses correlations between line integrated signals and is based on the assumption of cylindrically symmetric fluctuations. Measurements at the reversed field pinch EXTRAP T2R show that emission from impurities expected to be close to the edge is clearly different in raw as well as analyzed data to impurities expected to be more central. Best fitting of experimental data to simulated correlation coefficients yields emission profiles that are remarkably close to emission profiles determined using more conventional techniques. The radial extension of the fluctuations is small enough for the method to be used and bandpass filtered signals indicate that fluctuations below 10 kHz are cylindrically symmetric. The novel method is not sensitive to vessel window attenuation or wall reflections and can therefore complement the standard methods in the impurity emission reconstruction procedure.

  19. Abrogation of TGF-β 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-β signaling has been linked to poor patient prognosis. However, the mechanisms through which TGF-β regulates these processes remain largely unknown. In an effort to address this issue, we have now identified gene expression signatures associated with the TGF-β signaling pathway in human mammary carcinoma cells. The results strongly suggest that TGF-β 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-β–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-β 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-β 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

  20. Radio signal correlation at 32 MHz with extensive air showers parameters

    NASA Astrophysics Data System (ADS)

    Knurenko, Stanislav; Petrov, Igor

    2015-08-01

    The paper presents correlations of radio signals measured at the Yakutsk array with air shower parameters: the shower energy E0 and the depth of maximum Xmax. It is shown that from radio emission measurements of air showers one can obtain individual shower parameters and hence, the mass composition of cosmic rays. In addition, we also derived a generalized formula for calculating the primary energy of the air showers.

  1. 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.

  2. Comparing the similarity of time-series gene expression using signal processing metrics.

    PubMed

    Butte, A J; Bao, L; Reis, B Y; Watkins, T W; Kohane, I S

    2001-12-01

    Many algorithms have been used to cluster genes measured by microarray across a time series. Instead of clustering, our goal was to compare all pairs of genes to determine whether there was evidence of a phase shift between them. We describe a technique where gene expression is treated as a discrete time-invariant signal, allowing the use of digital signal-processing tools, including power spectral density, coherence, and transfer gain and phase shift. We used these on a public RNA expression set of 2467 genes measured every 7 min for 119 min and found 18 putative associations. Two of these were known in the biomedical literature and may have been missed using correlation coefficients. Digital signal processing tools can be embedded and enhance existing clustering algorithms. PMID:12198759

  3. Digital signal processing algorithms for automatic voice recognition

    NASA Technical Reports Server (NTRS)

    Botros, Nazeih M.

    1987-01-01

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

  4. A review of channel selection algorithms for EEG signal processing

    NASA Astrophysics Data System (ADS)

    Alotaiby, Turky; El-Samie, Fathi E. Abd; Alshebeili, Saleh A.; Ahmad, Ishtiaq

    2015-12-01

    Digital processing of electroencephalography (EEG) signals has now been popularly used in a wide variety of applications such as seizure detection/prediction, motor imagery classification, mental task classification, emotion classification, sleep state classification, and drug effects diagnosis. With the large number of EEG channels acquired, it has become apparent that efficient channel selection algorithms are needed with varying importance from one application to another. The main purpose of the channel selection process is threefold: (i) to reduce the computational complexity of any processing task performed on EEG signals by selecting the relevant channels and hence extracting the features of major importance, (ii) to reduce the amount of overfitting that may arise due to the utilization of unnecessary channels, for the purpose of improving the performance, and (iii) to reduce the setup time in some applications. Signal processing tools such as time-domain analysis, power spectral estimation, and wavelet transform have been used for feature extraction and hence for channel selection in most of channel selection algorithms. In addition, different evaluation approaches such as filtering, wrapper, embedded, hybrid, and human-based techniques have been widely used for the evaluation of the selected subset of channels. In this paper, we survey the recent developments in the field of EEG channel selection methods along with their applications and classify these methods according to the evaluation approach.

  5. Signal Processing in Periodically Forced Gradient Frequency Neural Networks

    PubMed Central

    Kim, Ji Chul; Large, Edward W.

    2015-01-01

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

  6. 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

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

    PubMed

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

    2014-03-28

    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. PMID:24577191

  8. 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.

  9. Biological signal processing with a genetic toggle switch.

    PubMed

    Hillenbrand, Patrick; Fritz, Georg; Gerland, Ulrich

    2013-01-01

    Complex gene regulation requires responses that depend not only on the current levels of input signals but also on signals received in the past. In digital electronics, logic circuits with this property are referred to as sequential logic, in contrast to the simpler combinatorial logic without such internal memory. In molecular biology, memory is implemented in various forms such as biochemical modification of proteins or multistable gene circuits, but the design of the regulatory interface, which processes the input signals and the memory content, is often not well understood. Here, we explore design constraints for such regulatory interfaces using coarse-grained nonlinear models and stochastic simulations of detailed biochemical reaction networks. We test different designs for biological analogs of the most versatile memory element in digital electronics, the JK-latch. Our analysis shows that simple protein-protein interactions and protein-DNA binding are sufficient, in principle, to implement genetic circuits with the capabilities of a JK-latch. However, it also exposes fundamental limitations to its reliability, due to the fact that biological signal processing is asynchronous, in contrast to most digital electronics systems that feature a central clock to orchestrate the timing of all operations. We describe a seemingly natural way to improve the reliability by invoking the master-slave concept from digital electronics design. This concept could be useful to interpret the design of natural regulatory circuits, and for the design of synthetic biological systems. PMID:23874595

  10. 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.

  11. 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

  12. The Open Host Network Packet Process Correlator for Windows

    Energy Science and Technology Software Center (ESTSC)

    2014-06-17

    The Hone sensors are packet-process correlation engines that log the relationships between applications and the communications they are responsible for. Hone sensors are available for a variety of platforms including Linux, Windows, and MacOSX. Hone sensors are designed to help analysts understand the meaning of communications on a deeper level by associating the origin or destination process to the communication. They do this by tracing communications on a per-packet basis, through the kernel of themore » operating system to determine their ultimate source/destination on the monitored machine.« less

  13. The Open Host Network Packet Process Correlator for Windows

    SciTech Connect

    2014-06-17

    The Hone sensors are packet-process correlation engines that log the relationships between applications and the communications they are responsible for. Hone sensors are available for a variety of platforms including Linux, Windows, and MacOSX. Hone sensors are designed to help analysts understand the meaning of communications on a deeper level by associating the origin or destination process to the communication. They do this by tracing communications on a per-packet basis, through the kernel of the operating system to determine their ultimate source/destination on the monitored machine.

  14. Anomalous diffusion for a correlated process with long jumps

    NASA Astrophysics Data System (ADS)

    Srokowski, Tomasz

    2011-09-01

    We discuss diffusion properties of a dynamical system, which is characterised by long-tail distributions and finite correlations. The particle velocity has the stable Lévy distribution; it is assumed as a jumping process (the kangaroo process) with a variable jumping rate. Both the exponential and the algebraic form of the covariance-defined for the truncated distribution-are considered. It is demonstrated by numerical calculations that the stationary solution of the master equation for the case of power-law correlations decays with time, but a simple modification of the process makes the tails stable. The main result of the paper is a finding that-in contrast to the velocity fluctuations-the position variance may be finite. It rises with time faster than linearly: the diffusion is anomalously enhanced. On the other hand, a process which follows from a superposition of the Ornstein-Uhlenbeck-Lévy processes always leads to position distributions with a divergent variance which means accelerated diffusion.

  15. Improved motion contrast and processing efficiency in OCT angiography using complex-correlation algorithm

    NASA Astrophysics Data System (ADS)

    Guo, Li; Li, Pei; Pan, Cong; Liao, Rujia; Cheng, Yuxuan; Hu, Weiwei; Chen, Zhong; Ding, Zhihua; Li, Peng

    2016-02-01

    The complex-based OCT angiography (Angio-OCT) offers high motion contrast by combining both the intensity and phase information. However, due to involuntary bulk tissue motions, complex-valued OCT raw data are processed sequentially with different algorithms for correcting bulk image shifts (BISs), compensating global phase fluctuations (GPFs) and extracting flow signals. Such a complicated procedure results in massive computational load. To mitigate such a problem, in this work, we present an inter-frame complex-correlation (CC) algorithm. The CC algorithm is suitable for parallel processing of both flow signal extraction and BIS correction, and it does not need GPF compensation. This method provides high processing efficiency and shows superiority in motion contrast. The feasibility and performance of the proposed CC algorithm is demonstrated using both flow phantom and live animal experiments.

  16. UniBoard: generic hardware for radio astronomy signal processing

    NASA Astrophysics Data System (ADS)

    Hargreaves, J. E.

    2012-09-01

    UniBoard is a generic high-performance computing platform for radio astronomy, developed as a Joint Research Activity in the RadioNet FP7 Programme. The hardware comprises eight Altera Stratix IV Field Programmable Gate Arrays (FPGAs) interconnected by a high speed transceiver mesh. Each FPGA is connected to two DDR3 memory modules and three external 10Gbps ports. In addition, a total of 128 low voltage differential input lines permit connection to external ADC cards. The DSP capability of the board exceeds 644E9 complex multiply-accumulate operations per second. The first production run of eight boards was distributed to partners in The Netherlands, France, Italy, UK, China and Korea in May 2011, with a further production runs completed in December 2011 and early 2012. The function of the board is determined by the firmware loaded into its FPGAs. Current applications include beamformers, correlators, digital receivers, RFI mitigation for pulsar astronomy, and pulsar gating and search machines The new UniBoard based correlator for the European VLBI network (EVN) uses an FX architecture with half the resources of the board devoted to station based processing: delay and phase correction and channelization, and half to the correlation function. A single UniBoard can process a 64MHz band from 32 stations, 2 polarizations, sampled at 8 bit. Adding more UniBoards can expand the total bandwidth of the correlator. The design is able to process both prerecorded and real time (eVLBI) data.

  17. 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.

  18. Nonlinear Signal Processing Using Fiber-Optics Neurograms

    NASA Astrophysics Data System (ADS)

    Szu, Harold

    1986-02-01

    A novel optical device for nonlinear signal processing is described based upon the following observations: (a) A phase space for signal processing is identified with a time-frequency joint representation (TFJR) that appears almost everywhere naturally, for example in bats, in music, etc. (b) A sudden slow down mechanism is responsible for the transition from a phase coherent-to-incoherent wavefront and provides us the sharpest tone transduction from a Bekesy traveling wave in a model of the inner ear. The cause of the slowdown is physically identified to be due to three forces. This has been used to derive a cubic deceleration polynomial responsible for a cusp bifurcation phenomenon which occur for every tone transducted along the nonuniform elastic membrane. The liquid-filled inner ear cochlea channel is divided by the membrane into an upper duct that has hair cells for the forward sound-generated flow and the lower duct for the backward balance-return flow.

  19. Signal processing for Internet video streaming: a review

    NASA Astrophysics Data System (ADS)

    Lu, Jian

    2000-04-01

    Despite the commercial success, video streaming remains a black art owing to its roots in proprietary commercial development. As such, many challenging technological issues that need to be addressed are not even well understood. The purpose of this paper is to review several important signal processing issues related to video streaming, and put them in the context of a client-server based media streaming architecture on the Internet. Such a context is critical, as we shall see that a number of solutions proposed by signal processing researchers are simply unrealistic for real-world video streaming on the Internet. We identify a family of viable solutions and evaluate their pros and cons. We further identify areas of research that have received less attention and point to the problems to which a better solution is eagerly sought by the industry.

  20. Communications, Signal Processing, and Telemetering Research Program Review

    NASA Technical Reports Server (NTRS)

    1999-01-01

    A Communications, Signal Processing, and Telemetering Research Program Review was held on February 23, 1999. Research conducted under the grant was presented and reviewed, for progress, and for possible technology transfers. The research reviewed was in the following areas: (1) Bandwidth-efficient Modulation and nonlinear equalization; (2) Investigation of an architecture for parallel signal processing applicable to communications problems; (3)Coded partial response over satellites; (4) synchronization at Low SNR; (5) Serial concatenated convolutional codes and some implementation issues on high rate turbo codes; (6) Flight experiments; (7) Real time doppler tracking; (8) Space protocol testing; (9) Lightweight optical communications without carrying a laser in space. The presentations are given by the graduate students who performed the research.

  1. Statistical signal processing methods for ultrasonic nondestructive evaluation

    SciTech Connect

    Saniie, J. . Dept. of Electrical and Computer Engineering)

    1992-06-01

    Order statistics and morphological filters belong to a class of nonlinear filters that have recently found many applications in signal analysis and image processing. In this paper, order statistics and morphological filters have been applied to enhance the features of the ultrasonic signal when it has been contaminated by multiple interfering microstructure echoes with random amplitudes and phases. These interfering echoes (i.e., speckles or grain scattering noise) often become significant to the point where detection of flaw echoes becomes very difficult. We have examined order statistic, and morphological filters for improved ultrasonic flaw detection. In particular, the performance of these filters has been evaluated using different ranks of order statistics (minimum, median, maximum), and different shapes of structuring elements in the application of morphological filters. The processed experimental results in testing steel samples demonstrate that these filters are capable of improving flaw detection in ultrasonic systems.

  2. Adaptive control technique for accelerators using digital signal processing

    SciTech Connect

    Eaton, L.; Jachim, S.; Natter, E.

    1987-01-01

    The use of present Digital Signal Processing (DSP) techniques can drastically reduce the residual rf amplitude and phase error in an accelerating rf cavity. Accelerator beam loading contributes greatly to this residual error, and the low-level rf field control loops cannot completely absorb the fast transient of the error. A feedforward technique using DSP is required to maintain the very stringent rf field amplitude and phase specifications. 7 refs.

  3. 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.

  4. Programmable rate modem utilizing digital signal processing techniques

    NASA Technical Reports Server (NTRS)

    Naveh, Arad

    1992-01-01

    The need for a Programmable Rate Digital Satellite Modem capable of supporting both burst and continuous transmission modes with either Binary Phase Shift Keying (BPSK) or Quadrature Phase Shift Keying (QPSK) modulation is discussed. The preferred implementation technique is an all digital one which utilizes as much digital signal processing (DSP) as possible. The design trade-offs in each portion of the modulator and demodulator subsystem are outlined.

  5. Developments in signal processing and interpretation in laser tapping

    NASA Astrophysics Data System (ADS)

    Perton, M.; Neron, C.; Blouin, A.; Monchalin, J.-P.

    2013-01-01

    A novel technique, called laser-tapping, based on the thermoelastic excitation by laser like laser-ultrasonics has been previously introduced for inspecting honeycomb and foam core structures. If the top skin is delaminated or detached from the substrate, the detached layer is driven into vibration. The interpretation of the vibrations in terms of Lamb wave resonances is first discussed for a flat bottom hole configuration and then used to determine appropriate signal processing for samples such as honeycomb structures.

  6. Using radial basis functions to set thresholds for segmentation of signal from background on matched filter correlation surfaces

    NASA Astrophysics Data System (ADS)

    Edmondson, Richard; Rodgers, Michael

    2008-04-01

    Using matched filters to find targets in cluttered images is an old idea. Human operators can interactively find threshold values to be applied to the correlation surface that will do a good job of binarizing it into signal/non-signal pixel regions. Automating the thresholding process with nine measured image statistics is the goal of this paper. The nine values are the mean, maximum, and standard deviation of three images: the input image presumed to have some signal, an NxN matched filter kernel in the shape of the signal, and the correlation surface generated by convolving the input image with the matched filter kernel. Several thousand input images with known target locations and reference images were run through a correlator with kernels that resembled the targets. The nine numbers referred to above were calculated in addition to a threshold found with a time consuming brutal algorithm. Multidimensional radial basis functions were associated with each nine number set. The bump height corresponded to the threshold value. The bump location was within a nine dimensional hypercube corresponding to the nine numbers scaled so that all the data fell within the interval 0 to 1 on each axis. The sigma (sharpness of the radial basis function) was calculated as a fraction of the squared distance to the closest neighboring bump. A new threshold is calculated as a weighted sum of all the Gaussian bumps in the vicinity of the input 9D vector. The paper will conclude with a table of results using this method compared to other methods.

  7. 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.

  8. Biomedical signal processing using a new class of wavelets

    NASA Astrophysics Data System (ADS)

    Shi, Zhuoer; Zhang, DeSheng; Wang, Haixiang; Kouri, Donald J.; Hoffman, David K.

    2000-04-01

    We design a new compactly-supported interpolating wavelet- distributed approximating functional (DAF) wavelet for biomedical signal/image processing. DAF class is a smooth, continuous interpolating function system which is symmetric and fast-decaying. DAF neural networks are designed for time varying electrocardiogram signal filtering. The neural nets use the Hermite-DAF as the basis function and implement a 3- layer structure. DAF wavelets and the corresponding subband filters are constructed for image processing. Edge- enhancement normalization and device-adapted visual group normalization algorithms are presented which sharpen the desired image features without prior knowledge of the spatial characteristics of the images. We design a nonlinear multiscale gradient-stretch method for feature extraction of mammograms. A fractal technique is introduced to characterize microcalcifications in localized regions of breast tissue. We employ a DAF wavelet-based multiscale edge detection and Dijkstra fractal technique is introduced to characterize microcalcifications in localized regions of breast tissue. We employ a DAF wavelet-based multiscale edge detection and Dijkstra fractal technique to identify micro calcification regions, and use a stochastic thresholding method to detect the calcified spots. The combined perceptual techniques produce natural high-quality images based on the human vision system. The underlying technologies significantly facilitate the creation of generic signal processing and computer-aided diagnostic systems. The system is implemented in the JAVA language, which is cross-platform friendly and is facilitated for telemedicine application.

  9. Signal Processing Effects for Ultrasonic Guided Wave Scanning of Composites

    SciTech Connect

    Roth, D.J.; Cosgriff, L.M.; Martin, R.E.; Burns, E.A.; Teemer, L.

    2005-04-09

    The goal of this ongoing work is to optimize experimental variables for a guided wave scanning method to obtain the most revealing and accurate images of defect conditions in composite materials. This study focuses on signal processing effects involved in forming guided wave scan images. Signal processing is involved at two basic levels for deriving ultrasonic guided wave scan images. At the primary level, NASA GRC has developed algorithms to extract over 30 parameters from the multimode signal and its power spectral density. At the secondary level, there are many variables for which values must be chosen that affect actual computation of these parameters. In this study, a ceramic matrix composite sample having a delamination is characterized using the ultrasonic guided wave scan method. Energy balance and decay rate parameters of the guided wave at each scan location are calculated to form images. These images are compared with ultrasonic c-scan and thermography images. The effect of the time portion of the waveform processed on image quality is assessed by comparing with images formed using the total waveform acquired.

  10. 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.

  11. Frequency of Spontaneous BOLD Signal Shifts during Infancy and Correlates with Cognitive Performance

    PubMed Central

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

    2016-01-01

    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

  12. Power optimization in wearable biomedical systems: a signal processing perspective

    NASA Astrophysics Data System (ADS)

    Ghasemzadeh, Hassan

    2012-10-01

    Wearable monitoring systems have caught considerable attention recently due to their potential in many domains including smart health and well-being. These new biomedical monitoring systems aim to provide continuous patient monitoring and proactive care options. Realization of this vision requires research that addresses a number of challenges, in particular, regarding limited resources that the wearable sensor networks offer. This paper presents an overview of different strategies for prolonging system lifetimes through power optimization in such systems. Particular emphasis is given to enhancing processing and communication architectures with respect to the signal processing requirements of the system.

  13. CMF Signal Processing Method Based on Feedback Corrected ANF and Hilbert Transformation

    NASA Astrophysics Data System (ADS)

    Tu, Yaqing; Yang, Huiyue; Zhang, Haitao; Liu, Xiangyu

    2014-02-01

    In this paper, we focus on CMF signal processing and aim to resolve the problems of precision sharp-decline occurrence when using adaptive notch filters (ANFs) for tracking the signal frequency for a long time and phase difference calculation depending on frequency by the sliding Goertzel algorithm (SGA) or the recursive DTFT algorithm with negative frequency contribution. A novel method is proposed based on feedback corrected ANF and Hilbert transformation. We design an index to evaluate whether the ANF loses the signal frequency or not, according to the correlation between the output and input signals. If the signal frequency is lost, the ANF parameters will be adjusted duly. At the same time, singular value decomposition (SVD) algorithm is introduced to reduce noise. And then, phase difference between the two signals is detected through trigonometry and Hilbert transformation. With the frequency and phase difference obtained, time interval of the two signals is calculated. Accordingly, the mass flow rate is derived. Simulation and experimental results show that the proposed method always preserves a constant high precision of frequency tracking and a better performance of phase difference measurement compared with the SGA or the recursive DTFT algorithm with negative frequency contribution

  14. Real-Time Video Signal Processing System For Dynamic Images

    NASA Astrophysics Data System (ADS)

    Yagi, Nobuyuki; Yajima, Ryoichi; Enami, Kazumasa; Fukui, Kazuo; Sasaki, Nobuyuki; Hoshino, Kouji; Harukawa, Kazuhiro; Kogure, Masaru

    1989-11-01

    A real-time video signal processing system (Picot-system) has been developed which processes multiple color time-varying images at video-rate and carries out various image processing functions such as edge detection, and geometrical transformation. The system is a multi-processor system including several hundred processors, and is divided into cascaded clusters, each of which has 16 processors. Each processor has an image memory to store all data required for its own processing, thus eliminating memory-access conflict. These processors and cluster inputs/outputs are connected by a crossbar network, which carries out all combinations of connections, and processors operate in both parallel and pipeline fashion. Micro-program controlled system has a control mechanism and arithmetic functions suitable for image signal processing. Performance of the system improves in proportion to the number of processors. The processors and network are virtually all LSIs, which use CMOS gate-array technology. The Picot-system can be applied to various fields such as medical imaging, robot vision, video CODEC, broadcast video production, and so on.

  15. Innovative surface NMR signal processing to significantly improve data quality

    NASA Astrophysics Data System (ADS)

    Neyer, F. M.; Hertrich, M.; Greenhalgh, S. A.

    2010-12-01

    Surface Nuclear Magnetic Resonance (SNMR) is a relatively new geophysical technique primarily used for water detection in the shallow subsurface. Magnetic fields arising from current pulses in a surface loop antenna penetrate the subsurface and interact with the hydrogen protons of liquid water. Among the various geophysical methods, surface NMR is unique in that it is directly sensitive to water molecules. Hence it has the powerful potential to quantitatively map the water distribution with depth. The signal measurement relies on the principle of induction that creates a weak voltage in the range of nV to a few μV in the surface receiver loop. However, the record is obscured by (i) man-made, industrial, and cultural (harmonic) noise such as power-lines and railway tracks, (ii) spike events (incoherent noise), and (iii) atmospheric background noise (random). Extreme hardware requirements and the weakness of the signal cause the records to be heavily noise contaminated in general. As a consequence, efficient noise suppression techniques are required to extract the weak surface NMR signal, i.e. stacking, loop design, and digital post-processing. In this study, we present a state-of-the-art workflow for full time series NMR data processing. As a first step, random spike events are removed from all records. Reference channels are further used to create a shaping filter by which the noise component in signal record is largely reduced. In the latter stage, signal extraction is performed using digital quadrature detection with an additional phase correction. The filter design is based on a least-squares approach using different input channels. This multi-dimensional Wiener filter method allows for a multi-channel noise reduction. Today, state-of-the-art full bandwidth multi-channel recording systems offer the possibility to record four channels simultaneously. Therefore, it is possible to use up to three reference channels for noise attenuation. By analyzing the optimal filter length and reference receiver combinations, we were able to to extract the NMR signal from highly noise contaminated records. In the case where one reference channel for noise suppression fails, the NMR signal can be successfully extracted using the multi-dimensional Wiener filter.

  16. Neural correlates of processing "self-conscious" vs. "basic" emotions.

    PubMed

    Gilead, Michael; Katzir, Maayan; Eyal, Tal; Liberman, Nira

    2016-01-29

    Self-conscious emotions are prevalent in our daily lives and play an important role in both normal and pathological behavior. Despite their immense significance, the neural substrates that are involved in the processing of such emotions are surprisingly under-studied. In light of this, we conducted an fMRI study in which participants thought of various personal events which elicited feelings of negative and positive self-conscious (i.e., guilt, pride) or basic (i.e., anger, joy) emotions. We performed a conjunction analysis to investigate the neural correlates associated with processing events that are related to self-conscious vs. basic emotions, irrespective of valence. The results show that processing self-conscious emotions resulted in activation within frontal areas associated with self-processing and self-control, namely, the mPFC extending to the dACC, and within the lateral-dorsal prefrontal cortex. Processing basic emotions resulted in activation throughout relatively phylogenetically-ancient regions of the cortex, namely in visual and tactile processing areas and in the insular cortex. Furthermore, self-conscious emotions differentially activated the mPFC such that the negative self-conscious emotion (guilt) was associated with a more dorsal activation, and the positive self-conscious emotion (pride) was associated with a more ventral activation. We discuss how these results shed light on the nature of mental representations and neural systems involved in self-reflective and affective processing. PMID:26707717

  17. Mouse submandibular gland morphogenesis: a paradigm for embryonic signal processing.

    PubMed

    Melnick, M; Jaskoll, T

    2000-01-01

    Signal processing is the sine qua non of embryogenesis. At its core, any single signal transduction pathway may be understood as classic Information Theory, adapted as an open system such that, because of networking, the "receiver" is presented with more information than was initially signaled by the "source". Over 40 years ago, Waddington presented his "Epigenetic Landscape" as a metaphor for the hierarchical nature of embryogenesis. Mathematically, Waddington's landscape may be modeled as a neural net. The "black box" of the neural net is an interacting network of signal transduction pathways (using hormones, growth factors, cytokines, neurotransmitters, and others) which inform the Boolean logic gates. An emerging theme in developmental biology is that defined sets of epigenetic circuits are used in multiple places, at multiple times, for similar and sometimes different purposes during organogenesis. As we show here, submandibular gland embryonic and fetal development is a splendid paradigm of these epigenetic circuits and their phenotypic outcomes, such as branching and lumen formation. PMID:12002815

  18. A Signal Processing Analysis of Purkinje Cells in vitro

    PubMed Central

    Abrams, Ze'ev R.; Warrier, Ajithkumar; Trauner, Dirk; Zhang, Xiang

    2010-01-01

    Cerebellar Purkinje cells in vitro fire recurrent sequences of Sodium and Calcium spikes. Here, we analyze the Purkinje cell using harmonic analysis, and our experiments reveal that its output signal is comprised of three distinct frequency bands, which are combined using Amplitude and Frequency Modulation (AM/FM). We find that the three characteristic frequencies – Sodium, Calcium and Switching – occur in various combinations in all waveforms observed using whole-cell current clamp recordings. We found that the Calcium frequency can display a frequency doubling of its frequency mode, and the Switching frequency can act as a possible generator of pauses that are typically seen in Purkinje output recordings. Using a reversibly photo-switchable kainate receptor agonist, we demonstrate the external modulation of the Calcium and Switching frequencies. These experiments and Fourier analysis suggest that the Purkinje cell can be understood as a harmonic signal oscillator, enabling a higher level of interpretation of Purkinje signaling based on modern signal processing techniques. PMID:20508748

  19. Processing the tort deterrent signal: a qualitative study.

    PubMed

    Hupert, N; Lawthers, A G; Brennan, T A; Peterson, L M

    1996-07-01

    Medical mistakes often are responsible for patient injury and suffering, but not all such mistakes are negligent. In the United States, injured patients have recourse to legal action under the common law. The medical malpractice tort trial system is intended to provide compensation for patients who have been negligently injured and to deter future negligent acts by physicians. The deterrent function of torts largely rests on practitioners' capacity and willingness to internalize, or 'process', the lessons of tort trials. However, physicians' willingness or ability to process the tort deterrent signal, while widely assumed in much contemporary legal writing on medical malpractice, has never been empirically verified. This study is a qualitative assessment of how practicing physicians process the tort deterrent signal. We interviewed a random sample of 47 internists, surgeons, and obstetrician/gynecologists from New York State as part of the Harvard Medical Practice Study. The interviews reveal three notable findings: physicians in our sample largely define medical negligence by reference to moral qualities of the practitioner; they claim that lawyers and the legal process of tort trials lack the moral authority to guide medical practice; and finally, while they consequently reject the lessons of lawyer-dominated, confrontational tort trials, they indicate that they would respond more favorably to hospital-based, physician-led, educational quality-control measures. Based on these findings, we identify several potential impediments to the receipt and processing of the tort deterrent signal by individual physicians and we suggest that the interview results support the notion of institutional liability for medical malpractice. PMID:8816005

  20. 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.

  1. Simplified electronic signal processing in the small nuclear physics laboratory

    NASA Astrophysics Data System (ADS)

    DeYoung, P. A.; Peaslee, G. F.

    2005-10-01

    Small nuclear physics laboratories of all kinds traditionally have processed the signals from radiation detectors with a variety of discrete NIM- or CAMAC-based electronic modules. The logic signals associated with signal processing are often passed through gate generators, coincidence modules, fan-in/fan-out modules, delay units, counters, and other assorted logic modules. These multi-component systems generate gates for acquisition systems, gates for specific linear electronics modules (ADCs and TDCs), or measure count rates and dead times. This can involve a significant number of individual modules each of which can be quite costly and each of which provides only limited functions. We describe here an upgrade to our acquisition system where all the needed logic functions are performed in just a single unit: a Universal Logic Module based on a Field Programmable Gate Array (FPGA) from JTEC Corporation. This module also contains flash memory that holds three separate configurations allowing for rapid changes from one electronics configuration to a different one. Both CAMAC and VME versions of the unit are available. The system described here is just one example of the huge variety of functionality that can be programmed into this single module. It can accommodate very complicated circuits and is easily reprogrammed. In the small nuclear physics laboratory the Universal Logic Module can save cost when upgrading systems and reduce the number of instances where one has an insufficient number of channels of a particular function.

  2. Signal detection in FDA AERS database using Dirichlet process.

    PubMed

    Hu, Na; Huang, Lan; Tiwari, Ram C

    2015-08-30

    In the recent two decades, data mining methods for signal detection have been developed for drug safety surveillance, using large post-market safety data. Several of these methods assume that the number of reports for each drug-adverse event combination is a Poisson random variable with mean proportional to the unknown reporting rate of the drug-adverse event pair. Here, a Bayesian method based on the Poisson-Dirichlet process (DP) model is proposed for signal detection from large databases, such as the Food and Drug Administration's Adverse Event Reporting System (AERS) database. Instead of using a parametric distribution as a common prior for the reporting rates, as is the case with existing Bayesian or empirical Bayesian methods, a nonparametric prior, namely, the DP, is used. The precision parameter and the baseline distribution of the DP, which characterize the process, are modeled hierarchically. The performance of the Poisson-DP model is compared with some other models, through an intensive simulation study using a Bayesian model selection and frequentist performance characteristics such as type-I error, false discovery rate, sensitivity, and power. For illustration, the proposed model and its extension to address a large amount of zero counts are used to analyze statin drugs for signals using the 2006-2011 AERS data. PMID:25924820

  3. Molecularly imprinted polymers as optical sensing receptors: correlation between analytical signals and binding isotherms.

    PubMed

    Ng, Sing Muk; Narayanaswamy, R

    2011-10-10

    Despite the increasing number of usage of molecularly imprinted polymers (MIPs) in optical sensor application, the correlation between the analytical signals and the binding isotherms has yet to be fully understood. This work investigates the relationship between the signals generated from MIPs sensors to its respective binding affinity variables generated using binding isotherm models. Two different systems based on the imprinting of metal ion and organic compound have been selected for the study, which employed reflectance and fluorescence sensing schemes, respectively. Batch binding analysis using the standard binding isotherm models was employed to evaluate the affinity of the binding sites. Evaluation using the discrete bi-Langmuir isotherm model found both the MIPs studied have generally two classes of binding sites that was of low and high affinities, while the continuous Freundlich isotherm model has successfully generated a distribution of affinities within the investigated analytical window. When the MIPs were incorporated as sensing receptors, the changes in the analytical signal due to different analyte concentrations were found to have direct correlation with the binding isotherm variables. Further data analyses based on this observation have generated robust models representing the analytical performance of the optical sensors. The best constructed model describing the sensing trend for each of the sensor has been tested and demonstrated to give accurate prediction of concentration for a series of spiked analytes. PMID:21889638

  4. 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.

  5. Time Reversal Signal Processing in Communications - A Feasibility Study

    SciTech Connect

    Meyer, A W; Candy, J V; Poggio, A J

    2002-01-30

    A typical communications channel is subjected to a variety of signal distortions, including multipath, that corrupt the information being transmitted and reduce the effective channel capacity. The mitigation of the multipath interference component is an ongoing concern for communication systems operating in complex environments such as might be experienced inside buildings, urban environments, and hilly or heavily wooded areas. Communications between mobile units and distributed sensors, so important to national security, are dependent upon flawless conveyance of information in complex environments. The reduction of this multipath corruption necessitates better channel equalization, i.e., the removal of channel distortion to extract the transmitted information. But, the current state of the art in channel equalization either requires a priori knowledge of the channel or the use of a known training sequence and adaptive filtering. If the ''assumed'' model within the equalization processor does not at least capture the dominant characteristics of the channel, then the received information may still be highly distorted and possibly useless. Also, the processing required for classical equalization is demanding in computational resources. To remedy this situation, many techniques have been investigated to replace classical equalization. Such a technique, the subject of this feasibility study, is Time Reversal Signal Processing (TRSP). Multipath is particularly insidious and a major factor in the deterioration of communication channels. Unlike most other characteristics that corrupt a communications channel, the detrimental effects of multipath cannot be overcome by merely increasing the transmitted power. Although the power in a signal diminishes as a function of the distance between the transmitter and receiver, multipath further degrades a signal by creating destructive interference that results in a loss of received power in a very localized area, a loss often referred to as fading. Furthermore, multipath can reduce the effectiveness of a channel by increasing inter-symbol interference. Here, a symbol is the fundamental unit of information. Although a signal may have a sufficient signal-to-noise ratio (SNR) at a receiving site, the signal may not be interpretable because it is composed of time-delayed replicas of the original transmission due to the multiple paths between transmitter and receiver. Although not previously employed for communications systems, developments in Time Reversal Signal Processing (TRSP) indicate the potential for compensating the transmission channel while mitigating the need for detailed a priori knowledge of the channel characteristics. Furthermore its simplicity, viz. a viz. equalization, makes it particularly attractive. The successful use of TRSP can increase channel bandwidth, thereby enabling the proportional increase in the volume of information. It implicitly compensates for distortion by using the equivalent of an imbedded phase conjugation technique for the equalization. This is an astounding property of the TRSP than can be taken advantage of for this problem. This feasibility study is directed toward showing that TRSP is a viable method for mitigating the effects of multipath on the transmission of information through a communications channel. In this report, we first briefly describe the theory behind the use of TRSP in communications. The channel is composed of a single transmitter-receiver pair operating in an unknown, possibly inhomogeneous, medium that includes scatterers that can contribute to multiple paths between the transmitter and receiver. These multiple paths (multipath) express themselves as reverberation in the received signal and attendant distortion in the information. Once having established the theory behind the use of TRSP to mitigate multipath distortion, we will describe simulations of the performance of suggested systems using this approach. Finally, we will establish conclusions based on our observations in the simulations.

  6. 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

  7. Comprehending prehending: neural correlates of processing verbs with motor stems.

    PubMed

    Rüschemeyer, Shirley-Ann; Brass, Marcel; Friederici, Angela D

    2007-05-01

    The interaction between language and action systems has become an increasingly interesting topic of discussion in cognitive neuroscience. Several recent studies have shown that processing of action verbs elicits activation in the cerebral motor system in a somatotopic manner. The current study extends these findings to show that the brain responses for processing of verbs with specific motor meanings differ not only from that of other motor verbs, but, crucially, that the comprehension of verbs with motor meanings (i.e., greifen, to grasp) differs fundamentally from the processing of verbs with abstract meanings (i.e., denken, to think). Second, the current study investigated the neural correlates of processing morphologically complex verbs with abstract meanings built on stems with motor versus abstract meanings (i.e., begreifen, to comprehend vs. bedenken, to consider). Although residual effects of motor stem meaning might have been expected, we see no evidence for this in our data. Processing of morphologically complex verbs built on motor stems showed no differences in involvement of the motor system when compared with processing complex verbs with abstract stems. Complex verbs built on motor stems did show increased activation compared with complex verbs built on abstract stems in the right posterior temporal cortex. This result is discussed in light of the involvement of the right temporal cortex in comprehension of metaphoric or figurative language. PMID:17488209

  8. Illumination-invariant pattern recognition using fringe-adjusted joint transform correlator and monogenic signal

    NASA Astrophysics Data System (ADS)

    Sidike, Paheding; Asari, Vijayan K.; Alam, Mohammad S.

    2014-03-01

    The joint transform correlator (JTC) technique has shown attractive performance for real-time pattern recognition applications. Among the various JTC techniques proposed in the literature, the fringe-adjusted JTC (FJTC) yields remarkable promise for object recognition, and it has been shown that the FJTC produces a better correlation output than alternate JTCs under varying illumination conditions of the input scene; however, it has been found that the FJTC is not illumination invariant. Therefore, to alleviate this drawback of the FJTC, an illumination-invariant FJTC, based on combination of the fringe-adjusted filter (FAF) and the monogenic signal, is presented. The performance of the FJTC and the proposed local phase based FJTC technique in unknown input-image with varying illumination is investigated and compared. The proposed detection algorithm makes use of the monogenic signal from a two dimensional object region to extract the local phase information for assisting the FJTC robust to illumination effects. Experimental results show that by utilizing the monogenic phase information enables the FAF-based JTC to produce sharper correlation peaks and higher peak-to-clutter ratio compared to alternate JTCs. The proposed technique may be used as a real-time region-ofinterest identifier in wide-area surveillance for automatic object recognition when the target under very dark or bright condition that beyond human vision.

  9. Information processing and signal integration in bacterial quorum sensing

    NASA Astrophysics Data System (ADS)

    Mehta, Pankaj

    2009-03-01

    Bacteria communicate with each other using secreted chemical signaling molecules called autoinducers (AIs) in a process known as quorum sensing. Quorum sensing enables bacteria to collectively regulate their behavior depending on the number and/or species of bacteria present. The quorum-sensing network of the marine-bacteria Vibrio harveyi consists of three AIs encoding distinct ecological information, each detected by its own histidine-kinase sensor protein. The sensor proteins all phosphorylate a common response regulator and transmit sensory information through a shared phosphorelay that regulates expression of downstream quorum-sensing genes. Despite detailed knowledge of the Vibrio quorum-sensing circuit, it is still unclear how and why bacteria integrate information from multiple input signals to coordinate collective behaviors. Here we develop a mathematical framework for analyzing signal integration based on Information Theory and use it to show that bacteria must tune the kinase activities of sensor proteins in order to transmit information from multiple inputs. This is demonstrated within a quantitative model that allows us to quantify how much Vibrio's learn about individual inputs and explains experimentally measured input-output relations. Furthermore, we predicted and experimentally verified that bacteria manipulate the production rates of AIs in order to increase information transmission and argue that the quorum-sensing circuit is designed to coordinate a multi-cellular developmental program. Our results show that bacteria can successfully learn about multiple signals even when they are transmitted through a shared pathway and suggest that Information Theory may be a powerful tool for analyzing biological signaling networks.

  10. 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

  11. Predicting protein subcellular location using digital signal processing.

    PubMed

    Pan, Yu-Xi; Li, Da-Wei; Duan, Yun; Zhang, Zhi-Zhou; Xu, Ming-Qing; Feng, Guo-Yin; He, Lin

    2005-02-01

    The biological functions of a protein are closely related to its attributes in a cell. With the rapid accumulation of newly found protein sequence data in databanks, it is highly desirable to develop an automated method for predicting the subcellular location of proteins. The establishment of such a predictor will expedite the functional determination of newly found proteins and the process of prioritizing genes and proteins identified by genomic efforts as potential molecular targets for drug design. The traditional algorithms for predicting these attributes were based solely on amino acid composition in which no sequence order effect was taken into account. To improve the prediction quality, it is necessary to incorporate such an effect. However, the number of possible patterns in protein sequences is extremely large, posing a formidable difficulty for realizing this goal. To deal with such difficulty, a well-developed tool in digital signal processing named digital Fourier transform (DFT) [1] was introduced. After being translated to a digital signal according to the hydrophobicity of each amino acid, a protein was analyzed by DFT within the frequency domain. A set of frequency spectrum parameters, thus obtained, were regarded as the factors to represent the sequence order effect. A significant improvement in prediction quality was observed by incorporating the frequency spectrum parameters with the conventional amino acid composition. One of the crucial merits of this approach is that many existing tools in mathematics and engineering can be easily applied in the predicting process. It is anticipated that digital signal processing may serve as a useful vehicle for many other protein science areas. PMID:15685365

  12. [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

  13. [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

  14. Correlation between a loss of auxin signaling and a loss of proliferation in maize antipodal cells.

    PubMed

    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

  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. Digital signal processing and numerical analysis for radar in geophysical applications

    NASA Astrophysics Data System (ADS)

    Molina, María G.; Cabrera, M. A.; Ezquer, R. G.; Fernandez, P. M.; Zuccheretti, E.

    2013-05-01

    Numerical solutions for signal processing are described in this work as a contribution to study of echo detection methods for ionospheric sounder design. The ionospheric sounder is a high frequency radar for geophysical applications. The main detection approach has been done by implementing the spread-spectrum techniques using coding methods to improve the radar's range resolution by transmitting low power. Digital signal processing has been performed and the numerical methods were checked. An algorithm was proposed and its computational complexity was calculated.The proposed detection process combines two channels correlations with the local code and calculates threshold (Vt) by statistical evaluation of the background noise to design a detection algorithm. The noisy signals treatment was performed depending on the threshold and echo amplitude. In each case, the detection was improved by using coherent integration. Synthetic signals, close loop and actual echoes, obtained from the Advanced Ionospheric Sounder (AIS-INGV) at Rome Ionospheric Observatory, were used to verify the process.The results showed that, even in highly noisy environments, the echo detection is possible.Given that these are preliminary results, further studies considering data sets corresponding to other geophysical conditions are needed.

  17. Coherent detection and digital signal processing for fiber optic communications

    NASA Astrophysics Data System (ADS)

    Ip, Ezra

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

  18. Color interpolation algorithm of CCD based on green components and signal correlation

    NASA Astrophysics Data System (ADS)

    Liang, Xiaofen; Qiao, Weidong; Yang, Jianfeng; Xue, Bin; Qin, Jia

    2013-09-01

    Signal CCD/CMOS sensors capture image information by covering the sensor surface with a color filter array(CFA). For each pixel, only one of three primary colors(red, green and blue) can pass through the color filter array(CFA). The other two missing color components are estimated by the values of the surrounding pixels. In Bayer array, the green components are half of the total pixels, but both red pixel and blue pixel components are quarter, so green components contain more information, which can be reference to color interpolation of red components and blue components. Based on this principle, in this paper, a simple and effective color interpolation algorithm based on green components and signal correlation for Bayer pattern images was proposed. The first step is to interpolate R, G and B components using the method-bilinear interpolation. The second step is to revise the results of bilinear interpolation by adding some green components on the results of bilinear interpolation. The calculation of the values to be added should consider the influence of correlation between the three channels. There are two major contributions in the paper. The first one is to demosaick G component more precisely. The second one is the spectral-spatial correlations between the three color channels is taken into consideration. At last, through MATLAB simulation experiments, experimental pictures and quantitative data for performance evaluation-Peak Signal to Noise Ratio(PSNR) were gotten. The results of simulation experiments show, compared with other color interpolation algorithms, the proposed algorithm performs well in both visual perception and PSNR measurement. And the proposed algorithm does not increase the complexity of calculation but ensures the real-time of system. Theory and experiments show the method is reasonable and has important engineering significance.

  19. Digital signal processing - 84; Proceedings of the International Conference, Florence, Italy, September 5-8, 1984

    NASA Astrophysics Data System (ADS)

    Cappellini, V.; Constantinides, A. G.

    1984-09-01

    Various papers on digital signal processing are presented. The general topics addressed include: 1-D digital filters and design methods, 2-D and M-D digital filters and design methods, digital transformations, spectral estimation, adaptive processing, implementation techniques and architectures, special devices and dedicated realizations, and VLSI processors. Other general subjects include: digital signal processing techniques, speech processing, digital image processing, digital signal processing and communications, radar applications, remote sensing, digital processing of biomedical signals and images, and pattern recognition and robotics.

  20. Stochastic simulation of spatially correlated geo-processes

    USGS Publications Warehouse

    Christakos, G.

    1987-01-01

    In this study, developments in the theory of stochastic simulation are discussed. The unifying element is the notion of Radon projection in Euclidean spaces. This notion provides a natural way of reconstructing the real process from a corresponding process observable on a reduced dimensionality space, where analysis is theoretically easier and computationally tractable. Within this framework, the concept of space transformation is defined and several of its properties, which are of significant importance within the context of spatially correlated processes, are explored. The turning bands operator is shown to follow from this. This strengthens considerably the theoretical background of the geostatistical method of simulation, and some new results are obtained in both the space and frequency domains. The inverse problem is solved generally and the applicability of the method is extended to anisotropic as well as integrated processes. Some ill-posed problems of the inverse operator are discussed. Effects of the measurement error and impulses at origin are examined. Important features of the simulated process as described by geomechanical laws, the morphology of the deposit, etc., may be incorporated in the analysis. The simulation may become a model-dependent procedure and this, in turn, may provide numerical solutions to spatial-temporal geologic models. Because the spatial simu??lation may be technically reduced to unidimensional simulations, various techniques of generating one-dimensional realizations are reviewed. To link theory and practice, an example is computed in detail. ?? 1987 International Association for Mathematical Geology.

  1. MR of Toxoplasma encephalitis: Signal characteristics on T2-weighted images and pathologic correlation

    SciTech Connect

    Brightbill, T.C.; Hensley, G.T.; Ruiz, A.

    1996-05-01

    Our goal was to determine if there are any T2-weighted MR signal characteristics of Toxoplasma encephalitis that might be useful in diagnosis and/or in gauging the effectiveness of medical therapy. We retrospectively analyzed the MR, CT, thallium-201 SPECT brain scans, and medical records of 27 patients with medically proven (26) and biopsy proven (1) Toxoplasma encephalitis, supplemented by autopsy findings in 4 additional patients, 2 of whom had postmortem MR correlation. The neuropathologic literature was also reviewed. Among the 27 patients, we discovered three distinct imaging patterns. Ten (37%) patients had predominantly T2-weighted hyperintense lesions and had been on medical therapy an average of 3 days (excluding one outlier). Ten (37%) patients had T2-weighted isointense lesions and had received medical therapy an average of 61 days. Seven (26%) patients had lesions with mixed signal on T2-weighted images and bad been on treatment an average of 6 days. Analysis of autopsy material from the four additional patients revealed the presence of organizing abscesses in three and necrotizing encephalitis in one, while the patient who had a brain biopsy demonstrated both types of pathologic lesions. In both cases having postmortem MRI, organizing abscesses appeared isointense to hypointense on T2-weighted images. There is a definite variation in the appearance of lesions of Toxoplasma encephalitis on T2-weighted images that precludes a definitive diagnosis based on signal characteristics alone. Pathologically, our data suggest that T2-weighted hyperintensity correlates with necrotizing encephalitis and T2-weighted isointensity with organizing abscesses. Furthermore, in patients on medical therapy the T2-weighted MR appearance may be a transition from hyperintensity to isointensity as a function of a positive response to antibiotic treatment, indicating that the signal change might be used to gauge the effectiveness of medical therapy. 15 refs., 6 figs.

  2. 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.

  3. Potential applicability of the VHSIC program to Army digital signal processing

    NASA Astrophysics Data System (ADS)

    Houts, R. C.; Burlage, D. W.

    The Department of Defense has instituted a Very High Speed Integrated Circuit (VHSIC) to Army digital signal processing. This program will reduce chip feature sizes to submicron levels in order to achieve a functional throughput rate (gates/chip x throughput operations/sec) which is one to three orders of magnitude higher than that which is currently available. The VHSIC program consists of two phases: VHSIC-I will reduce minimum feature size from 2 to 1.25 microns and have a gate density throughput speed product of 10 to the 11th gate-Hz; VHSIC-II will alter these figures still further to 0.5 microns and 10 to the 13th gate-Hz respectively. The current state-of-the-art of the VHSIC program is summarized, and various candidate VHSIC digital signal processing applications are identified. Improvements in speed and gate density are demonstrated by the use of two proposed single chips: the Butterfly (BFY) chip, basic to digital signal processing operations, such as correlation and matched filtering, using the Fast Fourier Transform algorithm; and the CONCOR chip, applicable to direct implementation of convolution and correlation operations.

  4. Correlations of the Time Dependent Signal and the State of a Continuously Monitored Quantum System.

    PubMed

    Foroozani, N; Naghiloo, M; Tan, D; Mølmer, K; Murch, K W

    2016-03-18

    In quantum physics, measurements give random results and yield a corresponding random backaction on the state of the system subject to measurement. If a quantum system is probed continuously over time, its state evolves along a stochastic quantum trajectory. To investigate the characteristic properties of such dynamics, we perform weak continuous measurements on a superconducting qubit that is driven to undergo Rabi oscillations. From the data we observe a number of striking temporal correlations within the time dependent signals and the quantum trajectories of the qubit, and we discuss their explanation in terms of quantum measurement and photodetection theory. PMID:27035288

  5. Correlations of the Time Dependent Signal and the State of a Continuously Monitored Quantum System

    NASA Astrophysics Data System (ADS)

    Foroozani, N.; Naghiloo, M.; Tan, D.; Mølmer, K.; Murch, K. W.

    2016-03-01

    In quantum physics, measurements give random results and yield a corresponding random backaction on the state of the system subject to measurement. If a quantum system is probed continuously over time, its state evolves along a stochastic quantum trajectory. To investigate the characteristic properties of such dynamics, we perform weak continuous measurements on a superconducting qubit that is driven to undergo Rabi oscillations. From the data we observe a number of striking temporal correlations within the time dependent signals and the quantum trajectories of the qubit, and we discuss their explanation in terms of quantum measurement and photodetection theory.

  6. Strong Monogamies of No-Signaling Violations for Bipartite Correlation Bell Inequalities

    NASA Astrophysics Data System (ADS)

    Ramanathan, Ravishankar; Horodecki, Paweł

    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.

  7. 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.

  8. Signal Processing System for the CASA Integrated Project I Radars

    SciTech Connect

    Bharadwaj, Nitin; Chandrasekar, V.; Junyent, Francesc

    2010-09-01

    This paper describes the waveform design space and signal processing system for dual-polarization Doppler weather radar operating at X band. The performance of the waveforms is presented with ground clutter suppression capability and mitigation of range velocity ambiguity. The operational waveform is designed based on operational requirements and system/hardware requirements. A dual Pulse Repetition Frequency (PRF) waveform was developed and implemented for the first generation X-band radars deployed by the Center for Collaborative Adaptive Sensing of the Atmosphere (CASA). This paper presents an evaluation of the performance of the waveforms based on simulations and data collected by the first-generation CASA radars during operations.

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

    SciTech Connect

    Sato, Toru; Takeda, Kenya; Nagamatsu, Takashi; Wakayama, Toshio; Kimura, Iwane; Shinbo, Tetsuya

    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.

  10. 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.

  11. Signal processing for an optical wide band data transmission system

    SciTech Connect

    Nakamura, M.; Leskovar, B.; Turko, B.T.

    1988-02-01

    The signal processing for an optical wide band transmission system using gallium arsenide (GaAs) digital integrated circuits and optical fibers has been investigated. Multiplexing, coding, synchronization, demultiplexing, and error checking at 780 Mbits/ data rates are described. Data storage in memory for linking to a computer is also considered. The design uses available GaAs and silicon components. The reliability of GaAs components is discussed as well as the layout and thermal considerations required for a high speed system.

  12. 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.

  13. 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

  14. 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

  15. 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

  16. 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

  17. TOPICAL REVIEW: A survey of signal processing algorithms in brain computer interfaces based on electrical brain signals

    NASA Astrophysics Data System (ADS)

    Bashashati, Ali; Fatourechi, Mehrdad; Ward, Rabab K.; Birch, Gary E.

    2007-06-01

    Brain computer interfaces (BCIs) aim at providing a non-muscular channel for sending commands to the external world using the electroencephalographic activity or other electrophysiological measures of the brain function. An essential factor in the successful operation of BCI systems is the methods used to process the brain signals. In the BCI literature, however, there is no comprehensive review of the signal processing techniques used. This work presents the first such comprehensive survey of all BCI designs using electrical signal recordings published prior to January 2006. Detailed results from this survey are presented and discussed. The following key research questions are addressed: (1) what are the key signal processing components of a BCI, (2) what signal processing algorithms have been used in BCIs and (3) which signal processing techniques have received more attention?

  18. Correlation between sensors' signals and internal resolution of a strip detector

    SciTech Connect

    Samedov, V. V.

    2011-07-01

    In this work, the theory of branching cascade processes is applied to the description of signal formation in a strip detector for soft X-rays. The theory is applicable to detectors' absorbers that have a single type of intrinsic particles. Intrinsic particles are particles that are generated by incident particle in detector's absorber and cause signals at the strip detector sensors' electronics. From this theory, it follows the new method of experimental determination of the Fano factor. It is shown, that the relative covariance between two signals of a strip detector depends on the fundamental combination of the Fano factor and the effective energy of the intrinsic particle creation in the absorber material. The important advantage of proposed method is its independence from the sensors' electronic gains and noises. (authors)

  19. Long-Range Correlations in the Sequence of Human Heartbeats and Other Biological Signals

    NASA Astrophysics Data System (ADS)

    Teich, Malvin C.

    1998-03-01

    The sequence of heartbeat occurrence times provides information about the state of health of the heart. We used a variety of measures, including multiresolution wavelet analysis, to identify the form of the point process that describes the human heartbeat. These measures, which are based on both interbeat (R-R) intervals and counts (heart rate), have been applied to records for both normal and heart-failure patients drawn from a standard database, and various surrogate versions thereof. Several of these measures reveal scaling behavior (1/f-type fluctuations; long-range power-law correlations).(R. G. Turcott and M. C. Teich, Proc. SPIE) 2036 (Chaos in Biology and Medicine), 22--39 (1993). Essentially all of the R-R and count-based measures we investigated, including those that exhibit scaling, differ in statistically significant ways for the normal and heart-failure patients. The wavelet measures, however, reveal a heretofore unknown scale window, between 16 and 32 heartbeats, over which the magnitudes of the wavelet-coefficient variances fall into disjoint sets for the normal and heart-failure patients.(R. G. Turcott and M. C. Teich, Ann. Biomed. Eng.) 24, 269--293 (1996).^,(S. Thurner, M. C. Feurstein, and M. C. Teich, Phys. Rev. Lett.) (in press). This enables us to correctly classify every patient in the standard data set as either belonging to the heart-failure or normal group with 100% accuracy, thereby providing a clinically significant measure of the presence of heart-failure. Previous approaches have provided only statistically significant measures. The tradeoff between sensitivity and specificity for various salient measures, as a function of data length, is determined by the use of ROC analysis. A phase-space reconstruction based on generalized heart rate is used to obtain a putative attractor's capacity dimension. Though the dependence of this dimension on the embedding dimension is consistent with that of a low-dimensional dynamical system, surrogate-data analysis shows that identical behavior emerges from long-range temporal correlations in a stochastic process.^2 An integrate-and-fire model, comprising a fractal-Gaussian-noise kernel and Gaussian event-jittering,(S. Thurner, S. B. Lowen, M. C. Feurstein, C. Heneghan, H. G. Feichtinger, and M. C. Teich, Fractals) 5, No. 4 (1997). provides a realistic simulation of heartbeat sequences for both normal and heart-failure patients, over all time scales. These results could be of use in generating an artificial heartbeat that mimics the healthy heartbeat sequence for applications such as pacemakers. The presentation will be concluded with a brief discussion of the application of these methods to other unitary biological signals.

  20. Gravity Influences Top-Down Signals in Visual Processing

    PubMed Central

    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

  1. 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

  2. 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.

  3. 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.

  4. Cognitive tasks during walking affect cerebral blood flow signal features in middle cerebral arteries and their correlation to gait characteristics.

    PubMed

    Gatouillat, Arthur; Bleton, Héloïse; VanSwearingen, Jessie; Perera, Subashan; Thompson, Scott; Smith, Traci; Sejdić, Ervin

    2015-01-01

    Gait is a complex process involving both cognitive and sensory ability and is strongly impacted by the environment. In this paper, we propose to study of the impact of a cognitive task during gait on the cerebral blood flow velocity, the blood flow signal features and the correlation of gait and blood flow features through a dual task methodology. Both cerebral blood flow velocity and gait characteristics of eleven participants with no history of brain or gait conditions were recorded using transcranial Doppler on mid-cerebral artery while on a treadmill. The cognitive task was induced by a backward counting starting from 10,000 with decrement of 7. Central blood flow velocity raw and envelope features were extracted in both time, frequency and time-scale domain; information-theoretic metrics were also extracted and statistical significances were inspected. A similar feature extraction was performed on the stride interval signal. Statistical differences between the cognitive and baseline trials, between the left and right mid-cerebral arteries signals and the impact of the antropometric variables where studied using linear mixed models. No statistical differences were found between the left and right mid-cerebral arteries flows or the baseline and cognitive state gait features, while statistical differences for specific features were measured between cognitive and baseline states. These statistical differences found between the baseline and cognitive states show that cognitive process has an impact on the cerebral activity during walking. The state was found to have an impact on the correlation between the gait and blood flow features. PMID:26409878

  5. Channel modeling, signal processing and coding for perpendicular magnetic recording

    NASA Astrophysics Data System (ADS)

    Wu, Zheng

    With the increasing areal density in magnetic recording systems, perpendicular recording has replaced longitudinal recording to overcome the superparamagnetic limit. Studies on perpendicular recording channels including aspects of channel modeling, signal processing and coding techniques are presented in this dissertation. To optimize a high density perpendicular magnetic recording system, one needs to know the tradeoffs between various components of the system including the read/write transducers, the magnetic medium, and the read channel. We extend the work by Chaichanavong on the parameter optimization for systems via design curves. Different signal processing and coding techniques are studied. Information-theoretic tools are utilized to determine the acceptable region for the channel parameters when optimal detection and linear coding techniques are used. Our results show that a considerable gain can be achieved by the optimal detection and coding techniques. The read-write process in perpendicular magnetic recording channels includes a number of nonlinear effects. Nonlinear transition shift (NLTS) is one of them. The signal distortion induced by NLTS can be reduced by write precompensation during data recording. We numerically evaluate the effect of NLTS on the read-back signal and examine the effectiveness of several write precompensation schemes in combating NLTS in a channel characterized by both transition jitter noise and additive white Gaussian electronics noise. We also present an analytical method to estimate the bit-error-rate and use it to help determine the optimal write precompensation values in multi-level precompensation schemes. We propose a mean-adjusted pattern-dependent noise predictive (PDNP) detection algorithm for use on the channel with NLTS. We show that this detector can offer significant improvements in bit-error-rate (BER) compared to conventional Viterbi and PDNP detectors. Moreover, the system performance can be further improved by combining the new detector with a simple write precompensation scheme. Soft-decision decoding for algebraic codes can improve performance for magnetic recording systems. In this dissertation, we propose two soft-decision decoding methods for tensor-product parity codes. We also present a list decoding algorithm for generalized error locating codes.

  6. Brain correlates of mathematical competence in processing mathematical representations.

    PubMed

    Grabner, Roland H; Reishofer, Gernot; Koschutnig, Karl; Ebner, Franz

    2011-01-01

    The ability to extract numerical information from different representation formats (e.g., equations, tables, or diagrams) is a key component of mathematical competence but little is known about its neural correlate. Previous studies comparing mathematically less and more competent adults have focused on mental arithmetic and reported differences in left angular gyrus (AG) activity which were interpreted to reflect differential reliance on arithmetic fact retrieval during problem solving. The aim of the present functional magnetic resonance imaging study was to investigate the brain correlates of mathematical competence in a task requiring the processing of typical mathematical representations. Twenty-eight adults of lower and higher mathematical competence worked on a representation matching task in which they had to evaluate whether the numerical information of a symbolic equation matches that of a bar chart. Two task conditions without and one condition with arithmetic demands were administered. Both competence groups performed equally well in the non-arithmetic conditions and only differed in accuracy in the condition requiring calculation. Activation contrasts between the groups revealed consistently stronger left AG activation in the more competent individuals across all three task conditions. The finding of competence-related activation differences independently of arithmetic demands suggests that more and less competent individuals differ in a cognitive process other than arithmetic fact retrieval. Specifically, it is argued that the stronger left AG activity in the more competent adults may reflect their higher proficiency in processing mathematical symbols. Moreover, the study demonstrates competence-related parietal activation differences that were not accompanied by differential experimental performance. PMID:22069387

  7. Optical fibre sensors based on multi-mode fibres and MIMO signal processing: an experimental approach

    NASA Astrophysics Data System (ADS)

    Ahrens, Andreas; Sandmann, Andre; Bremer, Kort; Roth, Bernhard; Lochmann, Steffen

    2015-09-01

    In this paper multiple-input multiple-output (MIMO) signal processing is investigated for fibre optic sensor applications. A (2 2) MIMO implementation is realized by using lower-order and higher-order mode groups of a graded-index (GI) multi-mode fibre (MMF) as separate transmission channels. A micro-bending pressure sensor changes these separate transmission characteristics and introduces additional crosstalk. By observing the weight-factors of the MIMO system the amount of load applied was determined. Experiments verified a good correlation between the change of the MIMO weight coefficients and the load applied to the sensor and thus verified that MIMO signal processing can beneficially be used for fibre optic sensor applications.

  8. Characterization and matched-field processing localization of photoacoustic signals

    NASA Astrophysics Data System (ADS)

    Yonak, Serdar Hakki

    2000-09-01

    This dissertation presents the results of an investigation performed to characterize photoacoustic sound from gases in an open environment and to determine its utility for localizing small gas clouds. Photoacoustics is the generation of acoustic waves due to unsteady heating from a light source. It is well understood for trace gas detection and spectroscopy when the gases are placed in chambers. However, it is poorly understood in an open environment. Leak detection and localization are critical quality control processes because many industrial and domestic machines use or convey pressurized gases or liquids. Unintended leaks from machine components may be detrimental to consumers, manufacturers, and the environment. Current leak testing methods are either subjective, time consuming, or lack automated localization capability. The use of photoacoustic signals measured with multiple microphones for the localization of leaks is examined to address the shortcomings of the current leak testing methods. Scaling laws for photoacoustic sound pressure are developed with dimensional analysis and verified with experiments using a carbon dioxide laser and sulfur hexafluoride as the tracer gas to generate the photoacoustic sound. A photoacoustic signal model based on first principles is developed and takes in to account gas cloud shape and realistic gas absorption. For acoustically distributed gas clouds, the model and experiments agree to within 3 dB in a 10-120 kHz bandwidth. For acoustically compact gas clouds, the model and experiments agree to within 3 dB in a 30-120 kHz bandwidth. Matched-field processing is applied to photoacoustic measurements made by a four-microphone array. The photoacoustic sound is generated by scanning a carbon dioxide laser beam over a calibrated leak source of sulfur hexafluoride. The results of this study indicate that measured photoacoustic signals processed using matched-field processing can be used to accurately localize gas clouds from leak sources that leak at a rate of 1.19 × 10-5 CM3/S to within +/-1 mm Different processing techniques are demonstrated and acoustic propagation model robustness studies are performed.

  9. Bacteriorhodopsin films for optical signal processing and data storage

    NASA Technical Reports Server (NTRS)

    Walkup, John F. (Principal Investigator); Mehrl, David J. (Principal Investigator)

    1996-01-01

    This report summarizes the research results obtained on NASA Ames Grant NAG 2-878 entitled 'Investigations of Bacteriorhodopsin Films for Optical Signal Processing and Data Storage.' Specifically we performed research, at Texas Tech University, on applications of Bacteriorhodopisin film to both (1) dynamic spatial filtering and (2) holographic data storage. In addition, measurements of the noise properties of an acousto-optical matrix-vestor multiplier built for NASA Ames by Photonic Systems Inc. were performed at NASA Ames' Photonics Laboratory. This research resulted in two papers presented at major optical data processing conferences and a journal paper which is to appear in APPLIED OPTICS. A new proposal for additional BR research has recently been submitted to NASA Ames Research Center.

  10. A methodology for time-frequency image processing applied to the classification of non-stationary multichannel signals using instantaneous frequency descriptors with application to newborn EEG signals

    NASA Astrophysics Data System (ADS)

    Boashash, Boualem; Boubchir, Larbi; Azemi, Ghasem

    2012-12-01

    This article presents a general methodology for processing non-stationary signals for the purpose of classification and localization. The methodology combines methods adapted from three complementary areas: time-frequency signal analysis, multichannel signal analysis and image processing. The latter three combine in a new methodology referred to as multichannel time-frequency image processing which is applied to the problem of classifying electroencephalogram (EEG) abnormalities in both adults and newborns. A combination of signal related features and image related features are used by merging key instantaneous frequency descriptors which characterize the signal non-stationarities. The results obtained show that, firstly, the features based on time-frequency image processing techniques such as image segmentation, improve the performance of EEG abnormalities detection in the classification systems based on multi-SVM and neural network classifiers. Secondly, these discriminating features are able to better detect the correlation between newborn EEG signals in a multichannel-based newborn EEG seizure detection for the purpose of localizing EEG abnormalities on the scalp.

  11. 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.

  12. Electrophysiological correlates of morphological processing in Chinese compound word recognition

    PubMed Central

    Du, Yingchun; Hu, Weiping; Fang, Zhuo; Zhang, John X.

    2013-01-01

    The present study investigated the electrophysiological correlates of morphological processing in Chinese compound word reading using a delayed repetition priming paradigm. Participants were asked to passively view lists of two-character compound words containing prime-target pairs separated by a few items. In a Whole Word repetition condition, the prime and target were the same real words (e.g., , manager-manager). In a Constituent repetition condition, the prime and target were swapped in terms of their constituent position (e.g., , the former is a pseudo-word and the later means nurse). Two ERP components including N200 and N400 showed repetition effects. The N200 showed a negative shift upon repetition in the Whole Word condition but this effect was delayed for the Constituent condition. The N400 showed comparable amplitude reduction across the two priming conditions. The results reveal different aspects of morphological processing with an early stage associated with N200 and a late stage with N400. There was also a possibility that the N200 effect reflect general cognitive processing, i.e., the detection of low-probability stimuli. PMID:24068994

  13. Neural correlates of post-error slowing during a stop signal task: a functional magnetic resonance imaging study.

    PubMed

    Li, Chiang-shan Ray; Huang, Cong; Yan, Peisi; Paliwal, Prashni; Constable, Robert Todd; Sinha, Rajita

    2008-06-01

    The ability to detect errors and adjust behavior accordingly is essential for maneuvering in an uncertain environment. Errors are particularly prone to occur when multiple, conflicting responses are registered in a situation that requires flexible behavioral outputs; for instance, when a go signal requires a response and a stop signal requires inhibition of the response during a stop signal task (SST). Previous studies employing the SST have provided ample evidence indicating the importance of the medial cortical brain regions in conflict/error processing. Other studies have also related these regional activations to postconflict/error behavioral adjustment. However, very few studies have directly explored the neural correlates of postconflict/error behavioral adjustment. Here we employed an SST to elicit errors in approximately half of the stop trials despite constant behavioral adjustment of the observers. Using functional magnetic resonance imaging, we showed that prefrontal loci including the ventrolateral prefrontal cortex are involved in post-error slowing in reaction time. These results delineate the neural circuitry specifically involved in error-associated behavioral modifications. PMID:18211230

  14. μ-opioid receptors: correlation of agonist efficacy for signalling with ability to activate internalization.

    PubMed

    McPherson, Jamie; Rivero, Guadalupe; Baptist, Myma; Llorente, Javier; Al-Sabah, Suleiman; Krasel, Cornelius; Dewey, William L; Bailey, Chris P; Rosethorne, Elizabeth M; Charlton, Steven J; Henderson, Graeme; Kelly, Eamonn

    2010-10-01

    We have compared the ability of a number of μ-opioid receptor (MOPr) ligands to activate G proteins with their abilities to induce MOPr phosphorylation, to promote association of arrestin-3 and to cause MOPr internalization. For a model of G protein-coupled receptor (GPCR) activation where all agonists stabilize a single active conformation of the receptor, a close correlation between signaling outputs might be expected. Our results show that overall there is a very good correlation between efficacy for G protein activation and arrestin-3 recruitment, whereas a few agonists, in particular endomorphins 1 and 2, display apparent bias toward arrestin recruitment. The agonist-induced phosphorylation of MOPr at Ser(375), considered a key step in MOPr regulation, and agonist-induced internalization of MOPr were each found to correlate well with arrestin-3 recruitment. These data indicate that for the majority of MOPr agonists the ability to induce receptor phosphorylation, arrestin-3 recruitment, and internalization can be predicted from their ability as agonists to activate G proteins. For the prototypic MOPr agonist morphine, its relatively weak ability to induce MOPr internalization can be explained by its low agonist efficacy. PMID:20647394

  15. 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.

  16. 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

  17. Multivariate analysis of correlation between electrophysiological and hemodynamic responses during cognitive processing

    PubMed Central

    Kujala, Jan; Sudre, Gustavo; Vartiainen, Johanna; Liljeström, Mia; Mitchell, Tom; Salmelin, Riitta

    2014-01-01

    Animal and human studies have frequently shown that in primary sensory and motor regions the BOLD signal correlates positively with high-frequency and negatively with low-frequency neuronal activity. However, recent evidence suggests that this relationship may also vary across cortical areas. Detailed knowledge of the possible spectral diversity between electrophysiological and hemodynamic responses across the human cortex would be essential for neural-level interpretation of fMRI data and for informative multimodal combination of electromagnetic and hemodynamic imaging data, especially in cognitive tasks. We applied multivariate partial least squares correlation analysis to MEG–fMRI data recorded in a reading paradigm to determine the correlation patterns between the data types, at once, across the cortex. Our results revealed heterogeneous patterns of high-frequency correlation between MEG and fMRI responses, with marked dissociation between lower and higher order cortical regions. The low-frequency range showed substantial variance, with negative and positive correlations manifesting at different frequencies across cortical regions. These findings demonstrate the complexity of the neurophysiological counterparts of hemodynamic fluctuations in cognitive processing. PMID:24518260

  18. 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.

  19. TRIM5 Retroviral Restriction Activity Correlates with the Ability To Induce Innate Immune Signaling

    PubMed Central

    Lascano, Josefina; Uchil, Pradeep D.; Mothes, Walther

    2015-01-01

    ABSTRACT Host restriction factor TRIM5 inhibits retroviral transduction in a species-specific manner by binding to and destabilizing the retroviral capsid lattice before reverse transcription is completed. However, the restriction mechanism may not be that simple since TRIM5 E3 ubiquitin ligase activity, the proteasome, autophagy, and TAK1-dependent AP-1 signaling have been suggested to contribute to restriction. Here, we show that, among a panel of seven primate and Carnivora TRIM5 orthologues, each of which has potential for potent retroviral restriction activity, all activated AP-1 signaling. In contrast, TRIM family paralogues most closely related to TRIM5 did not. While each primate species has a single TRIM5 gene, mice have at least seven TRIM5 homologues that cluster into two groups, Trim12a, -b, and -c and Trim30a, -b, -c, and -d. The three Trim12 proteins activated innate immune signaling, while the Trim30 proteins did not, though none of the murine Trim5 homologues restricted any of a panel of cloned retroviruses. To determine if any mouse TRIM5 homologues had potential for restriction activity, each was fused to the human immunodeficiency virus type 1 (HIV-1) CA binding protein cyclophilin A (CypA). The three Trim12-CypA fusions all activated AP-1 and restricted HIV-1 transduction, whereas the Trim30-CypA fusions did neither. AP-1 activation and HIV-1 restriction by the Trim12-CypA fusions were inhibited by disruption of TAK1. Overall then, these experiments demonstrate that there is a strong correlation between TRIM5 retroviral restriction activity and the ability to activate TAK1-dependent innate immune signaling. IMPORTANCE The importance of retroviruses for the evolution of susceptible host organisms cannot be overestimated. Eight percent of the human genome is retrovirus sequence, fixed in the germ line during past infection. Understanding how metazoa protect their genomes from mutagenic retrovirus infection is therefore of fundamental importance to biology. TRIM5 is a cellular protein that protects host genome integrity by disrupting the retroviral capsid as it transports viral nucleic acid to the host cell nucleus. Previous data suggest that innate immune signaling contributes to TRIM5-mediated restriction. Here, we show that activation of innate immune signaling is conserved among primate and carnivore TRIM5 orthologues and among 3 of the 7 mouse Trim5 homologues and that such activity is required for TRIM5-mediated restriction activity. PMID:26468522

  20. Internal wave signal processing: A model-based approach

    SciTech Connect

    Candy, J.V.; Chambers, D.H.

    1995-02-22

    A model-based approach is proposed to solve the oceanic internal wave signal processing problem that is based on state-space representations of the normal-mode vertical velocity and plane wave horizontal velocity propagation models. It is shown that these representations can be utilized to spatially propagate the modal (depth) vertical velocity functions given the basic parameters (wave numbers, Brunt-Vaisala frequency profile etc.) developed from the solution of the associated boundary value problem as well as the horizontal velocity components. These models are then generalized to the stochastic case where an approximate Gauss-Markov theory applies. The resulting Gauss-Markov representation, in principle, allows the inclusion of stochastic phenomena such as noise and modeling errors in a consistent manner. Based on this framework, investigations are made of model-based solutions to the signal enhancement problem for internal waves. In particular, a processor is designed that allows in situ recursive estimation of the required velocity functions. Finally, it is shown that the associated residual or so-called innovation sequence that ensues from the recursive nature of this formulation can be employed to monitor the model`s fit to the data.

  1. Signal Processing by Transducer Channels in Mammalian Outer Hair Cells

    NASA Astrophysics Data System (ADS)

    Dinklo, T.; van Netten, S. M.; Marcotti, W.; Kros, C. J.

    2003-02-01

    Transducer channels of mammalian outer hair cells may not be fully silenced during stimulation of the hair bundle into the inhibitory direction (< -50 nm). A recently formulated three-state model, assuming a state-dependent mechanical engagement of the transducer channel, accounts for this incomplete deactivation [1]. Moreover, the model suggests a specific function for calcium in controlling the transducer current, by modulating the energy gaps between the conformational states of the channel. Combining this differentially activating model with experimental results on the gating of transducer currents, we attempted to estimate the consequences of this mode of engagement for the processing of mechanical signals by sensory hair cells. We found that the channels transduce small mechanical signals most efficiently into transducer currents when the hair bundle is deflected some tens of nanometers away from its equilibrium position. The results are in line with a specific role of calcium in optimising the transducer efficiency and are possibly related to the calcium-dependent phenomenon of adaptation in mechano-electrical transduction.

  2. 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 β- and γ-secretases releases the amyloid-β peptide (Aβ), which deposits in senile plaques and contributes to the etiology of Alzheimer's disease (AD). The α-secretase cleaves APP in the Aβ peptide sequence to generate soluble APPα (sAPPα). Upregulation of α-secretase activity through the 5-hydroxytryptamine 4 (5-HT4) receptor has been shown to reduce Aβ 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 α-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 α-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 α-secretase activity. Our findings provide a novel route to explore the treatment of AD through 5-HT4 receptor-induced α-secretase activation. PMID:24466315

  3. Optimal Signal Processing in Small Stochastic Biochemical Networks

    PubMed Central

    Ziv, Etay; Nemenman, Ilya; Wiggins, Chris H.

    2007-01-01

    We quantify the influence of the topology of a transcriptional regulatory network on its ability to process environmental signals. By posing the problem in terms of information theory, we do this without specifying the function performed by the network. Specifically, we study the maximum mutual information between the input (chemical) signal and the output (genetic) response attainable by the network in the context of an analytic model of particle number fluctuations. We perform this analysis for all biochemical circuits, including various feedback loops, that can be built out of 3 chemical species, each under the control of one regulator. We find that a generic network, constrained to low molecule numbers and reasonable response times, can transduce more information than a simple binary switch and, in fact, manages to achieve close to the optimal information transmission fidelity. These high-information solutions are robust to tenfold changes in most of the networks' biochemical parameters; moreover they are easier to achieve in networks containing cycles with an odd number of negative regulators (overall negative feedback) due to their decreased molecular noise (a result which we derive analytically). Finally, we demonstrate that a single circuit can support multiple high-information solutions. These findings suggest a potential resolution of the “cross-talk” phenomenon as well as the previously unexplained observation that transcription factors that undergo proteolysis are more likely to be auto-repressive. PMID:17957259

  4. Developments in cardiovascular ultrasound: Part 1: Signal processing and instrumentation.

    PubMed

    Fish, P J; Hoskins, P R; Moran, C; McDicken, W N

    1997-11-01

    One of the major contributions to the improvement of spectral Doppler and colour flow imaging instruments has been the development of advanced signal-processing techniques made possible by increasing computing power. Model-based or parametric spectral estimators, time-frequency transforms, station-arising algorithms and spectral width correction techniques have been investigated as possible improvements on the FFT-based estimators currently used for real-time spectral estimation of Doppler signals. In colour flow imaging some improvement on velocity estimation accuracy has been achieved by the use of new algorithms but at the expense of increased computational complexity compared with the conventional autocorrelation method. Polynomial filters have been demonstrated to have some advantages over IIR filters for stationary echo cancellation. Several methods of velocity vector estimation to overcome the problem of angle dependence have been studied, including 2D feature tracking, two and three beam approaches and the use of spectral width in addition to mean frequency. 3D data acquisition and display and Doppler power imaging have also been investigated. The use of harmonic imaging, using the second harmonic generated by encapsulated bubble contrast media, seems promising particularly for imaging slow flow. Parallel image data acquisition using non-sequential scanning or broad beam transmission, followed by simultaneous reception along a number of beams, has been studied to speed up 'real-time' imaging. PMID:9538529

  5. A new method to process borehole strainmeter data; least squares with correlated data

    NASA Astrophysics Data System (ADS)

    Langbein, J.

    2008-12-01

    The newly installed Plate Boundary Observatory (PBO) strainmeters record signals from tectonic activity, Earth tides, and atmospheric pressure. Some of the tectonic signals have amplitudes close to those of tides and pressure loading. If incorrect assumptions are made regarding the background noise in the data, then adjusting these strain data will produce incorrect results that can obscure or contaminate any underlying tectonic signal. The use of simplifying assumptions that data are uncorrelated can lead to such incorrect results and, for example, pressure loading will not be completely removed from the raw data. Instead, any algorithm used to process strainmeter data must incorporate the strong temporal correlations that are inherent with these data. For instance, techniques based on auto-regressive methods or Kalman filters can successfully remove the pressure load and the Earth tides. The technique described here is adapted from error analysis of geodetic time-series of ground displacements. The technique uses least squares but employs data covariance that describes the temporal correlation of strainmeter data. There are several advantages to this method since many parameters are estimated simultaneously. These parameters include: 1) functional terms that describe the underlying error model, 2) the tidal terms, 3) the pressure loading term(s) 4) amplitudes of offsets, either those from earthquakes or from the instrument, 5) rate and changes in rate, and 6) the amplitudes and time constants of either logarithmic or exponential curves that can characterize postseismic deformation or diffusion of fluids near the strainmeter. With the proper error model, realistic estimates of the standard errors of the various parameters are obtained; this is especially critical in determining the statistical significance of a postulated, tectonic strain signal. Because the algorithm uses a maximum likelihood method, it is cpu-intensive. However, obtaining the error model by fitting a power-law relation to the power spectrum of the adjusted data greatly reduces the computations. The algorithm described here also provides a method of tracking the various adjustments required to process strainmeter data. In addition, the algorithm provides several plots to assist with identifying either tectonic signals or other signals that may need to be removed before any geophysical signal can be identified.

  6. Spatiotemporal Correlations between Cytosolic and Mitochondrial Ca2+ Signals Using a Novel Red-Shifted Mitochondrial Targeted Cameleon

    PubMed Central

    Waldeck-Weiermair, Markus; Alam, Muhammad Rizwan; Khan, Muhammad Jadoon; Deak, Andras T.; Vishnu, Neelanjan; Karsten, Felix; Imamura, Hiromi; Graier, Wolfgang F.; Malli, Roland

    2012-01-01

    The transfer of Ca2+ from the cytosol into the lumen of mitochondria is a crucial process that impacts cell signaling in multiple ways. Cytosolic Ca2+ ([Ca2+]cyto) can be excellently quantified with the ratiometric Ca2+ probe fura-2, while genetically encoded Förster resonance energy transfer (FRET)-based fluorescent Ca2+ sensors, the cameleons, are efficiently used to specifically measure Ca2+ within organelles. However, because of a significant overlap of the fura-2 emission with the spectra of the cyan and yellow fluorescent protein of most of the existing cameleons, the measurement of fura-2 and cameleons within one given cell is a complex task. In this study, we introduce a novel approach to simultaneously assess [Ca2+]cyto and mitochondrial Ca2+ ([Ca2+]mito) signals at the single cell level. In order to eliminate the spectral overlap we developed a novel red-shifted cameleon, D1GO-Cam, in which the green and orange fluorescent proteins were used as the FRET pair. This ratiometric Ca2+ probe could be successfully targeted to mitochondria and was suitable to be used simultaneously with fura-2 to correlate [Ca2+]cyto and [Ca2+]mito within same individual cells. Our data indicate that depending on the kinetics of [Ca2+]cyto rises there is a significant lag between onset of [Ca2+]cyto and [Ca2+]mito signals, pointing to a certain threshold of [Ca2+]cyto necessary to activate mitochondrial Ca2+ uptake. The temporal correlation between [Ca2+]mito and [Ca2+]cyto as well as the efficiency of the transfer of Ca2+ from the cytosol into mitochondria varies between different cell types. Moreover, slow mitochondrial Ca2+ extrusion and a desensitization of mitochondrial Ca2+ uptake cause a clear difference in patterns of mitochondrial and cytosolic Ca2+ oscillations of pancreatic beta-cells in response to D-glucose. PMID:23029314

  7. Effect of extreme data loss on long-range correlated and anticorrelated signals quantified by detrended fluctuation analysis

    PubMed Central

    Ma, Qianli D. Y.; Bartsch, Ronny P.; Bernaola-Galván, Pedro; Yoneyama, Mitsuru; Ivanov, Plamen Ch.

    2012-01-01

    Detrended fluctuation analysis (DFA) is an improved method of classical fluctuation analysis for nonstationary signals where embedded polynomial trends mask the intrinsic correlation properties of the fluctuations. To better identify the intrinsic correlation properties of real-world signals where a large amount of data is missing or removed due to artifacts, we investigate how extreme data loss affects the scaling behavior of long-range power-law correlated and anticorrelated signals. We introduce a segmentation approach to generate surrogate signals by randomly removing data segments from stationary signals with different types of long-range correlations. The surrogate signals we generate are characterized by four parameters: (i) the DFA scaling exponent α of the original correlated signal u(i), (ii) the percentage p of the data removed from u(i), (iii) the average length μ of the removed (or remaining) data segments, and (iv) the functional form P(l) of the distribution of the length l of the removed (or remaining) data segments. We find that the global scaling exponent of positively correlated signals remains practically unchanged even for extreme data loss of up to 90%. In contrast, the global scaling of anticorrelated signals changes to uncorrelated behavior even when a very small fraction of the data is lost. These observations are confirmed on two examples of real-world signals: human gait and commodity price fluctuations. We further systematically study the local scaling behavior of surrogate signals with missing data to reveal subtle deviations across scales. We find that for anticorrelated signals even 10% of data loss leads to significant monotonic deviations in the local scaling at large scales from the original anticorrelated to uncorrelated behavior. In contrast, positively correlated signals show no observable changes in the local scaling for up to 65% of data loss, while for larger percentage of data loss, the local scaling shows overestimated regions (with higher local exponent) at small scales, followed by underestimated regions (with lower local exponent) at large scales. Finally, we investigate how the scaling is affected by the average length, probability distribution, and percentage of the remaining data segments in comparison to the removed segments. We find that the average length μr of the remaining segments is the key parameter which determines the scales at which the local scaling exponent has a maximum deviation from its original value. Interestingly, the scales where the maximum deviation occurs follow a power-law relationship with μr. Whereas the percentage of data loss determines the extent of the deviation. The results presented in this paper are useful to correctly interpret the scaling properties obtained from signals with extreme data loss. PMID:20365691

  8. Carbon nanotube based composite fibers for strain sensing, signal processing, and computing

    NASA Astrophysics Data System (ADS)

    Vardhan, Harsh; Roy Mahapatra, D.

    2012-04-01

    Carbon nanotubes dispersed in polymer matrix have been aligned in the form of fibers and interconnects and cured electrically and by UV light. Conductivity and effective semiconductor tunneling against reverse to forward bias field have been designed to have differentiable current-voltage response of each of the fiber/channel. The current-voltage response is a function of the strain applied to the fibers along axial direction. Biaxial and shear strains are correlated by differentiating signals from the aligned fibers/channels. Using a small doping of magnetic nanoparticles in these composite fibers, magneto-resistance properties are realized which are strong enough to use the resulting magnetostriction as a state variable for signal processing and computing. Various basic analog signal processing tasks such as addition, convolution and filtering etc. can be performed. These preliminary study shows promising application of the concept in combined analog-digital computation in carbon nanotube based fibers. Various dynamic effects such as relaxation, electric field dependent nonlinearities and hysteresis on the output signals are studied using experimental data and analytical model.

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

    PubMed

    Ebner, Natalie C; He, Yi; Fichtenholtz, Harlan M; McCarthy, Gregory; Johnson, Marcia K

    2011-09-01

    The 'own-age bias' in face processing suggests that the age of a face constitutes one important factor that influences attention to and memory for faces. The present experiment investigated electrophysiological correlates of processing faces of younger and older individuals. Younger participants were presented with pictures of unfamiliar younger and older faces in the context of a gender categorization task. A comparison of event-related potentials showed that early components are sensitive to faces of different ages: (i) larger positive potential peaking at 160 ms (P200) for older than younger faces at fronto-central electrodes; (ii) larger negative potential peaking at 252 ms (N200) for younger than older faces at fronto-central electrodes; (iii) larger negative-going deflection peaking at 320 ms (N250) for younger than older faces at occipito-temporal electrodes; and (iv) larger late positive potential peaking at 420 ms (LPP 420) for older than younger faces at parietal and other electrodes. We discuss similarities between the present study and a previously published study of faces of different races as suggesting involvement of comparable electrophysiological responses when differentiating between stimulus categories. PMID:21030480

  10. Quantum correlation dynamics in photosynthetic processes assisted by molecular vibrations

    SciTech Connect

    Giorgi, G.L.; Roncaglia, M.; Raffa, F.A.; Genovese, M.

    2015-10-15

    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.

  11. 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

  12. 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.

  13. Neurological Tremor: Sensors, Signal Processing and Emerging Applications

    PubMed Central

    Grimaldi, Giuliana; Manto, Mario

    2010-01-01

    Neurological tremor is the most common movement disorder, affecting more than 4% of elderly people. Tremor is a non linear and non stationary phenomenon, which is increasingly recognized. The issue of selection of sensors is central in the characterization of tremor. This paper reviews the state-of-the-art instrumentation and methods of signal processing for tremor occurring in humans. We describe the advantages and disadvantages of the most commonly used sensors, as well as the emerging wearable sensors being developed to assess tremor instantaneously. We discuss the current limitations and the future applications such as the integration of tremor sensors in BCIs (brain-computer interfaces) and the need for sensor fusion approaches for wearable solutions. PMID:22205874

  14. Signal Processing Strategies for Cochlear Implants Using Current Steering

    NASA Astrophysics Data System (ADS)

    Nogueira, Waldo; Litvak, Leonid; Edler, Bernd; Ostermann, Jörn; Büchner, Andreas

    2009-12-01

    In contemporary cochlear implant systems, the audio signal is decomposed into different frequency bands, each assigned to one electrode. Thus, pitch perception is limited by the number of physical electrodes implanted into the cochlea and by the wide bandwidth assigned to each electrode. The Harmony HiResolution bionic ear (Advanced Bionics LLC, Valencia, CA, USA) has the capability of creating virtual spectral channels through simultaneous delivery of current to pairs of adjacent electrodes. By steering the locus of stimulation to sites between the electrodes, additional pitch percepts can be generated. Two new sound processing strategies based on current steering have been designed, SpecRes and SineEx. In a chronic trial, speech intelligibility, pitch perception, and subjective appreciation of sound were compared between the two current steering strategies and standard HiRes strategy in 9 adult Harmony users. There was considerable variability in benefit, and the mean results show similar performance with all three strategies.

  15. Quantum signal processing-based visual cryptography with unexpanded shares

    NASA Astrophysics Data System (ADS)

    Das, Surya Sarathi; Sharma, Kaushik Das; Chandra, Jayanta K.; Bera, Jitendra Nath

    2015-09-01

    This paper proposes a visual cryptography scheme (VCS) based on quantum signal processing (QSP). VCS is an image encryption technique that is very simple in formulation and is secure. In (k,n)-VCS, a secret binary image is encoded into n share images and minimum k shares are needed to decrypt the secret image. The efforts to encrypt a grayscale image are few in number and the majority are related to grayscale to binary conversion. Thus, a generalized approach of encryption for all types of images, i.e., binary, gray, and color is needed. Here, a generic VCS is proposed based on QSP where all types of images can be encrypted without pixel expansion along with a smoothing technique to enhance the quality of the decrypted image. The proposed scheme is tested and compared for benchmark images, and the result shows the effectiveness of the scheme.

  16. Digital Signal Processing for the Event Horizon Telescope

    NASA Astrophysics Data System (ADS)

    Weintroub, Jonathan

    2015-08-01

    A broad international collaboration is building the Event Horizon Telescope (EHT). The aim is to test Einstein’s theory of General Relativity in one of the very few places it could break down: the strong gravity regime right at the edge of a black hole. The EHT is an earth-size VLBI array operating at the shortest radio wavelengths, that has achieved unprecedented angular resolution of a few tens of μarcseconds. For nearby super massive black holes (SMBH) this size scale is comparable to the Schwarzschild Radius, and emission in the immediate neighborhood of the event horizon can be directly observed. We give an introduction to the science behind the CASPER-enabled EHT, and outline technical developments, with emphasis on the secret sauce of high speed signal processing.

  17. 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.

  18. Digital signal processing techniques for coherent optical communication

    NASA Astrophysics Data System (ADS)

    Goldfarb, Gilad

    Coherent detection with subsequent digital signal processing (DSP) is developed, analyzed theoretically and numerically and experimentally demonstrated in various fiber-optic transmission scenarios. The use of DSP in conjunction with coherent detection unleashes the benefits of coherent detection which rely on the preservaton of full information of the incoming field. These benefits include high receiver sensitivity, the ability to achieve high spectral-efficiency and the use of advanced modulation formats. With the immense advancements in DSP speeds, many of the problems hindering the use of coherent detection in optical transmission systems have been eliminated. Most notably, DSP alleviates the need for hardware phase-locking and polarization tracking, which can now be achieved in the digital domain. The complexity previously associated with coherent detection is hence significantly diminished and coherent detection is once gain considered a feasible detection alternative. In this thesis, several aspects of coherent detection (with or without subsequent DSP) are addressed. Coherent detection is presented as a means to extend the dispersion limit of a duobinary signal using an analog decision-directed phase-lock loop. Analytical bit-error ratio estimation for quadrature phase-shift keying signals is derived. To validate the promise for high spectral efficiency, the orthogonal-wavelength-division multiplexing scheme is suggested. In this scheme the WDM channels are spaced at the symbol rate, thus achieving the spectral efficiency limit. Theory, simulation and experimental results demonstrate the feasibility of this approach. Infinite impulse response filtering is shown to be an efficient alternative to finite impulse response filtering for chromatic dispersion compensation. Theory, design considerations, simulation and experimental results relating to this topic are presented. Interaction between fiber dispersion and nonlinearity remains the last major challenge deterministic effects pose for long-haul optical data transmission. Experimental results which demonstrate the possibility to digitally mitigate both dispersion and nonlinearity are presented. Impairment compensation is achieved using backward propagation by implementing the split-step method. Efficient realizations of the dispersion compensation operator used in this implementation are considered. Infinite-impulse response and wavelet-based filtering are both investigated as a means to reduce the required computational load associated with signal backward-propagation. Possible future research directions conclude this dissertation.

  19. Correlation of Radiation and Electron and Neutron Signals at PF-1000

    SciTech Connect

    Kubes, P.; Kravarik, J.; Barvir, P.; Klir, D.; Scholz, M.; Paduch, M.; Tomaszewski, K.; Ivanova-Stanik, I.; Bienkowska, B.; Ryc, L.; Karpinski, L.; Juha, L.; Krasa, J.; Sadowski, M. J.; Skladnik-Sadowska, E.; Jakubowski, L.; Szydlowski, A.; Malinowska, A.; Malinowski, K.; Schmidt, H.

    2006-01-15

    At the signals of x-rays usually 2 peaks were observed. The first peak corresponded to the time of the minimum diameter of the imploding plasma sheath (pinch phase) recorded by the visible frames. The second peak occurred 150-200 ns later at the time of the development of instabilities. High-energy electrons registered in the upstream and downstream directions differed in the intensity (ratio 3:1) and in the time of production. Their peaks correlated with x-rays. The energy of neutrons and time of their generation were determined by time-of-flight method from the pulses of seven scintillation detectors positioned in the axial direction. At the rise-time, each neutron pulse has registered downstream energies in range of 2.7-3.2 MeV. The final part of neutron pulse has isotropic energy distribution with energies up to 2.6-2.7 MeV. The evolution of the neutron pulses correlates with the visible frames. The first pulse correlates with the fast downstream zipper-effect of the dense plasma in the pinch and with the forming of the radiating ball-shaped structure at the bottom of the dilating plasma sheath. The second neutron pulse correlates with the second pinching and exploding of the plasma of lower density and with existence of the structure of the dense plasma positioned at the bottom of the dilating current sheath, similarly to the first pulse. The neutrons have a non-thermal beam-target origin. A possible influence of the zipper-effect on the acceleration of deuterons and on the plasma heating is discussed.

  20. Correlation of Radiation and Electron and Neutron Signals at PF-1000

    NASA Astrophysics Data System (ADS)

    Kubes, P.; Kravarik, J.; Barvir, P.; Klir, D.; Scholz, M.; Paduch, M.; Tomaszewski, K.; Ivanova-Stanik, I.; Bienkowska, B.; Karpinski, L.; Ryc, L.; Juha, L.; Krasa, J.; Sadowski, M. J.; Skladnik-Sadowska, E.; Jakubowski, L.; Szydlowski, A.; Malinowska, A.; Malinowski, K.; Schmidt, H.

    2006-01-01

    At the signals of x-rays usually 2 peaks were observed. The first peak corresponded to the time of the minimum diameter of the imploding plasma sheath (pinch phase) recorded by the visible frames. The second peak occurred 150-200 ns later at the time of the development of instabilities. High-energy electrons registered in the upstream and downstream directions differed in the intensity (ratio 3:1) and in the time of production. Their peaks correlated with x-rays. The energy of neutrons and time of their generation were determined by time-of-flight method from the pulses of seven scintillation detectors positioned in the axial direction. At the rise-time, each neutron pulse has registered downstream energies in range of 2.7-3.2 MeV. The final part of neutron pulse has isotropic energy distribution with energies up to 2.6-2.7 MeV. The evolution of the neutron pulses correlates with the visible frames. The first pulse correlates with the fast downstream zipper-effect of the dense plasma in the pinch and with the forming of the radiating ball-shaped structure at the bottom of the dilating plasma sheath. The second neutron pulse correlates with the second pinching and exploding of the plasma of lower density and with existence of the structure of the dense plasma positioned at the bottom of the dilating current sheath, similarly to the first pulse. The neutrons have a non-thermal beam-target origin. A possible influence of the zipper-effect on the acceleration of deuterons and on the plasma heating is discussed.