Science.gov

Sample records for signal processing correlation

  1. Correlation theory-based signal processing method for CMF signals

    NASA Astrophysics Data System (ADS)

    Shen, Yan-lin; Tu, Ya-qing

    2016-06-01

    Signal processing precision of Coriolis mass flowmeter (CMF) signals affects measurement accuracy of Coriolis mass flowmeters directly. To improve the measurement accuracy of CMFs, a correlation theory-based signal processing method for CMF signals is proposed, which is comprised of the correlation theory-based frequency estimation method and phase difference estimation method. Theoretical analysis shows that the proposed method eliminates the effect of non-integral period sampling signals on frequency and phase difference estimation. The results of simulations and field experiments demonstrate that the proposed method improves the anti-interference performance of frequency and phase difference estimation and has better estimation performance than the adaptive notch filter, discrete Fourier transform and autocorrelation methods in terms of frequency estimation and the data extension-based correlation, Hilbert transform, quadrature delay estimator and discrete Fourier transform methods in terms of phase difference estimation, which contributes to improving the measurement accuracy of Coriolis mass flowmeters.

  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. 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.

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

    PubMed

    Caplan, David

    2010-07-01

    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. 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

  6. 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

  7. 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

  8. Spectral correlation in ultrasonic pulse echo signal processing.

    PubMed

    Donohue, K D; Bressler, J M; Varghese, T; Bilgutay, N M

    1993-01-01

    The effects of using spectral correlation in a maximum-likelihood estimator (MLE) for backscattered energy corresponding to coherent reflectors embedded in media of microstructure scatterers is considered. The spectral autocorrelation (SAC) function is analyzed for various scatterer configurations based on the regularity of the interspacing distance between scatterers. It is shown that increased regularity gives rise to significant spectral correlation, whereas uniform distribution of scatters throughout a resolution cell results in no significant correlation between spectral components. This implies that when a true uniform distribution for the effective scatterers exists, the power spectral density (PSD) is sufficient to characterize their echoes. However, as the microstructure scatterer distribution becomes more regular, SAC terms become more significant. MLE results for 15 A-scans from stainless steel specimens with three different grain sizes indicate an average 6-dB signal-to-noise ratio (SNR) improvement in the coherent scatterer (flat-bottom hole) echo intensities for estimators using the SAC characterization as opposed to the PSD characterization. PMID:18263188

  9. Signals of strong electronic correlation in ion scattering processes

    NASA Astrophysics Data System (ADS)

    Bonetto, F.; Gonzalez, C.; Goldberg, E. C.

    2016-05-01

    Previous measurements of neutral atom fractions for S r+ scattered by gold polycrystalline surfaces show a singular dependence with the target temperature. There is still not a theoretical model that can properly describe the magnitude and the temperature dependence of the neutralization probabilities found. Here, we applied a first-principles quantum-mechanical theoretical formalism to describe the time-dependent scattering process. Three different electronic correlation approaches consistent with the system analyzed are used: (i) the spinless approach, where two charge channels are considered (S r0 and S r+ ) and the spin degeneration is neglected; (ii) the infinite-U approach, with the same charge channels (S r0 and S r+ ) but considering the spin degeneration; and (iii) the finite-U approach, where the first ionization and second ionization energy levels are considered very, but finitely, separated. Neutral fraction magnitudes and temperature dependence are better described by the finite-U approach, indicating that e -correlation plays a significant role in charge-transfer processes. However, none of them is able to explain the nonmonotonous temperature dependence experimentally obtained. Here, we suggest that small changes in the surface work function introduced by the target heating, and possibly not detected by experimental standard methods, could be responsible for that singular behavior. Additionally, we apply the same theoretical model using the infinite-U approximation for the Mg-Au system, obtaining an excellent description of the experimental neutral fractions measured.

  10. 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

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. Model-based inversion algorithm for ground penetration radar signal processing with correlation for target classification

    NASA Astrophysics Data System (ADS)

    Patz, Mark David

    A non-intrusive buried object classifier for a ground penetrating radar (GPR) system is developed. Various GPR data sets and the implemented processing are described. A model based inversion algorithm that utilizes correlation methodology for target classification is introduced. Experimental data was collected with a continuous wave GPR. Synthetic data was generated with a newly developed software package that implements mathematical models to predict the electromagnetic returns from an underground object. Sample targets and geometries were chosen to produce nine configurations/scenarios for analysis. The real measurement sets for each configuration and the synthetic sets for a family of similar configurations were imaged with the same state-of-the-art signal processing algorithms. The imaged results for the real data measurements were correlated with the imaged results for the synthetic data sets to produce performance measurements, thus producing a procedure that provides a non-invasive assessment of the object and medium determined by the synthetic data set that maximally correlated with the real data return. Synthetic results and experiment results showed good correlations. For the synthetic data, a mathematical model was developed for electromagnetic returns from an object shape (i.e., cylinder, parallelepiped, sphere) composed of a uniform construction (i.e., metal, wood, plastic, clay) within a uniform dielectric material (i.e., air, sand, loam, clay, water). This model was then implemented within a software package, thus providing the ability to generate simulated measurements from any combination of object, construction, and dielectric.

  16. 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

  17. 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.

  18. 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.

  19. Correlation of infrared thermographic patterns and acoustic emission signals with tensile deformation and fracture processes

    NASA Astrophysics Data System (ADS)

    Venkataraman, B.; Raj, Baldev; Mukhopadhyay, C. K.; Jayakumar, T.

    2001-04-01

    During tensile deformation, part of the mechanical work done on the specimen is transformed into heat and acoustic activity. The amount of acoustic activity and the thermal emissions depend on the test conditions and the deformation behavior of the specimen during loading. Authors have used thermography and acoustic emission (AE) simultaneously for monitoring tensile deformation in AISI type 316 SS. Tensile testing was carried out at 298 K at three different strain rates. It has been shown that the simultaneous use of these techniques can provide complementary information for characterizing the tensile deformation and fracture processes.

  20. 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.

  1. Correlation of the antimicrobial activity of salicylaldehydes with broadening of the NMR signal of the hydroxyl proton. Possible involvement of proton exchange processes in the antimicrobial activity.

    PubMed

    Elo, Hannu; Kuure, Matti; Pelttari, Eila

    2015-03-01

    Certain substituted salicylaldehydes are potent antibacterial and antifungal agents and some of them merit consideration as potential chemotherapeutic agents against Candida infections, but their mechanism of action has remained obscure. We report here a distinct correlation between broadening of the NMR signal of the hydroxyl proton of salicylaldehydes and their activity against several types of bacteria and fungi. When proton NMR spectra of the compounds were determined using hexadeuterodimethylsulfoxide as solvent and the height of the OH proton signal was measured, using the signal of the aldehyde proton as an internal standard, it was discovered that a prerequisite of potent antimicrobial activity is that the proton signal is either unobservable or relatively very low, i.e. that it is extremely broadened. Thus, none of the congeners whose OH proton signal was high were potent antimicrobial agents. Some congeners that gave a very low OH signal were, however, essentially inactive against the microbes, indicating that although drastic broadening of the OH signal appears to be a prerequisite, also other (so far unknown) factors are needed for high antimicrobial activity. Because broadening of the hydroxyl proton signal is related to the speed of the proton exchange process(es) involving that proton, proton exchange may be involved in the mechanism of action of the compounds. Further studies are needed to analyze the relative importance of different factors (such as electronic effects, strength of the internal hydrogen bond, co-planarity of the ring and the formyl group) that determine the rates of those processes. PMID:25621992

  2. 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

  3. 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 3×10-6 refractive index unit (RIU) can be obtained using this cross-correlation signal processing method. In addition, a measurement sensitivity up to 3×103 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.

  4. Signal processing for microcalorimeters

    NASA Astrophysics Data System (ADS)

    Szymkowiak, A. E.; Kelley, R. L.; Moseley, S. H.; Stahle, C. K.

    1993-11-01

    Most of the power in the signals from microcalorimeters occurs at relatively low frequencies. At these frequencies, typical amplifiers will have significant amounts of 1/f noise. Our laboratory systems can also suffer from pickup at several harmonics of the AC power line, and from microphonic pickup at frequencies that vary with the configuration of the apparatus. We have developed some optimal signal processing techniques in order to construct the best possible estimates of our pulse heights in the presence of these non-ideal effects. In addition to a discussion of our laboratory systems, we present our plans for providing this kind of signal processing in flight experiments.

  5. 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.

  6. 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.

  7. RASSP signal processing architectures

    NASA Astrophysics Data System (ADS)

    Shirley, Fred; Bassett, Bob; Letellier, J. P.

    1995-06-01

    The rapid prototyping of application specific signal processors (RASSP) program is an ARPA/tri-service effort to dramatically improve the process by which complex digital systems, particularly embedded signal processors, are specified, designed, documented, manufactured, and supported. The domain of embedded signal processing was chosen because it is important to a variety of military and commercial applications as well as for the challenge it presents in terms of complexity and performance demands. The principal effort is being performed by two major contractors, Lockheed Sanders (Nashua, NH) and Martin Marietta (Camden, NJ). For both, improvements in methodology are to be exercised and refined through the performance of individual 'Demonstration' efforts. The Lockheed Sanders' Demonstration effort is to develop an infrared search and track (IRST) processor. In addition, both contractors' results are being measured by a series of externally administered (by Lincoln Labs) six-month Benchmark programs that measure process improvement as a function of time. The first two Benchmark programs are designing and implementing a synthetic aperture radar (SAR) processor. Our demonstration team is using commercially available VME modules from Mercury Computer to assemble a multiprocessor system scalable from one to hundreds of Intel i860 microprocessors. Custom modules for the sensor interface and display driver are also being developed. This system implements either proprietary or Navy owned algorithms to perform the compute-intensive IRST function in real time in an avionics environment. Our Benchmark team is designing custom modules using commercially available processor ship sets, communication submodules, and reconfigurable logic devices. One of the modules contains multiple vector processors optimized for fast Fourier transform processing. Another module is a fiberoptic interface that accepts high-rate input data from the sensors and provides video-rate output data to a

  8. Digital signal processing

    NASA Astrophysics Data System (ADS)

    Morgera, Salvatore D.; Krishna, Hari

    Computationally efficient digital signal-processing algorithms over finite fields are developed analytically, and the relationship of these algorithms to algebraic error-correcting codes is explored. A multidisciplinary approach is employed, in an effort to make the results accessible to engineers, mathematicians, and computer scientists. Chapters are devoted to systems of bilinear forms, efficient finite-field algorithms, multidimensional methods, a new class of linear codes, and a new error-control scheme.

  9. 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.

  10. [Signal Processing Suite Design

    NASA Technical Reports Server (NTRS)

    Sahr, John D.; Mir, Hasan; Morabito, Andrew; Grossman, Matthew

    2003-01-01

    Our role in this project was to participate in the design of the signal processing suite to analyze plasma density measurements on board a small constellation (3 or 4) satellites in Low Earth Orbit. As we are new to space craft experiments, one of the challenges was to simply gain understanding of the quantity of data which would flow from the satellites, and possibly to interact with the design teams in generating optimal sampling patterns. For example, as the fleet of satellites were intended to fly through the same volume of space (displaced slightly in time and space), the bulk plasma structure should be common among the spacecraft. Therefore, an optimal, limited bandwidth data downlink would take advantage of this commonality. Also, motivated by techniques in ionospheric radar, we hoped to investigate the possibility of employing aperiodic sampling in order to gain access to a wider spatial spectrum without suffering aliasing in k-space.

  11. Correlation properties of the vector signal representation for speckle pattern.

    PubMed

    Wang, Wei; Zhang, Shun; Ma, Ning

    2014-04-01

    In one-dimensional (1D) signal analysis, the complex analytic signal built from a real-valued signal and its Hilbert transform is an important tool providing a mathematical foundation for 1D statistical analysis. For a natural extension beyond 1D signal, Riesz transform has been applied to high-dimensional signal processing as a generalized Hilbert transform to construct a vector signal representation and therefore, to enlarge the traditional analytic signal concept. In this paper, we introduce the vector correlations as new mathematical tools for vector calculus for statistical speckle analysis. Based on vector correlations of a real-valued speckle pattern, we present the associated correlation properties, which can be regarded as mathematical foundation for the vector analysis in speckle metrology. PMID:24787197

  12. Analog and digital signal processing

    NASA Astrophysics Data System (ADS)

    Baher, H.

    The techniques of signal processing in both the analog and digital domains are addressed in a fashion suitable for undergraduate courses in modern electrical engineering. The topics considered include: spectral analysis of continuous and discrete signals, analysis of continuous and discrete systems and networks using transform methods, design of analog and digital filters, digitization of analog signals, power spectrum estimation of stochastic signals, FFT algorithms, finite word-length effects in digital signal processes, linear estimation, and adaptive filtering.

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

    NASA Technical Reports Server (NTRS)

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

    1996-01-01

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

  14. 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.

  15. 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.

  16. Digital processing of bandpass signals

    NASA Astrophysics Data System (ADS)

    Jackson, M. C.; Matthewson, P.

    Modern radar and radio systems rely on digital signal processing to enhance the quality of received signals. Prior to such processing, these signals must be converted to digital form. The historical development of signal digitization is briefly discussed in this paper and leads to a description of some current work on digital mixing. A method of directly sampling a band-limited intermediate frequency (i.f.) signal is presented, using a pair of digital mixer channels to produce complex low-pass samples of the signal envelope. The method is found to produce well matched channel outputs. Finally, the applicability of the method to radar is discussed.

  17. 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

  18. 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.

  19. Secrecy extraction from no-signaling correlations

    SciTech Connect

    Scarani, Valerio; Gisin, Nicolas; Brunner, Nicolas; Masanes, Lluis; Pino, Sergi; Acin, Antonio

    2006-10-15

    Quantum cryptography shows that one can guarantee the secrecy of correlation on the sole basis of the laws of physics, that is, without limiting the computational power of the eavesdropper. The usual security proofs suppose that the authorized partners, Alice and Bob, have a perfect knowledge and control of their quantum systems and devices; for instance, they must be sure that the logical bits have been encoded in true qubits and not in higher dimensional systems. In this paper, we present an approach that circumvents this strong assumption. We define protocols, both for the case of bits and for generic d-dimensional outcomes, in which the security is guaranteed by the very structure of the Alice-Bob correlations, under the no-signaling condition. The idea is that if the correlations cannot be produced by shared randomness, then Eve has poor knowledge of Alice's and Bob's symbols. The present study assumes on the one hand that the eavesdropper Eve performs only individual attacks (this is a limitation to be removed in further work), and on the other hand that Eve can distribute any correlation compatible with the no-signaling condition (in this sense her power is greater than what quantum physics allows). Under these assumptions, we prove that the protocols defined here allow extracting secrecy from noisy correlations, when these correlations violate a Bell-type inequality by a sufficiently large amount. The region in which secrecy extraction is possible extends within the region of correlations achievable by measurements on entangled quantum states.

  20. Signal processing in SETI.

    PubMed

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

    1985-11-01

    The development of a multi-channel spectrum analyzer (MCSA) for the SETI program is described. The spectrum analyzer is designed for both all-sky surveys and targeted searches. The mechanisms of the MCSA are explained and a diagram is provided. Detection of continuous wave signals, pulses, and patterns is examined. PMID:11542023

  1. Fiber-optic lattice signal processing

    NASA Astrophysics Data System (ADS)

    Moslehi, B.; Goodman, J. W.; Shaw, H. J.; Tur, M.

    1984-07-01

    It is pointed out that fiber-optic signal processing devices can be constructed to perform various functions, such as convolution, correlation, matrix operations, and frequency filtering. Previous studies have concentrated on classical tapped-delay-line forms (transversal filters). The present investigation is concerned with different fiber-optic structures, taking into account lattice (or ladder) forms, which can be used as alternatives for performing optical signal processing. The elements to perform the various signal processing operations are considered along with fiber-optic lattice configurations. Aspects of mathematical analysis are discussed, taking into account Z-transform techniques, transfer-matrix and chain-matrix formulations, modern control theory formulations, and positive optical systems. Attention is given to time-domain signal processing applications, and frequency-domain signal processing applications.

  2. 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.

  3. 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.

  4. 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.

  5. Signal processing in magnetoencephalography.

    PubMed

    Vrba, J; Robinson, S E

    2001-10-01

    The subject of this article is detection of brain magnetic fields, or magnetoencephalography (MEG). The brain fields are many orders of magnitude smaller than the environmental magnetic noise and their measurement represent a significant metrological challenge. The only detectors capable of resolving such small fields and at the same time handling the large dynamic range of the environmental noise are superconducting quantum interference devices (or SQUIDs). The SQUIDs are coupled to the brain magnetic fields using combinations of superconducting coils called flux transformers (primary sensors). The environmental noise is attenuated by a combination of shielding, primary sensor geometry, and synthetic methods. One of the most successful synthetic methods for noise elimination is synthetic higher-order gradiometers. How the gradiometers can be synthesized is shown and examples of their noise cancellation effectiveness are given. The MEG signals measured on the scalp surface must be interpreted and converted into information about the distribution of currents within the brain. This task is complicated by the fact that such inversion is nonunique. Additional mathematical simplifications, constraints, or assumptions must be employed to obtain useful source images. Methods for the interpretation of the MEG signals include the popular point current dipole, minimum norm methods, spatial filtering, beamformers, MUSIC, and Bayesian techniques. The use of synthetic aperture magnetometry (a class of beamformers) is illustrated in examples of interictal epileptic spiking and voluntary hand-motor activity. PMID:11812209

  6. Signal processing development

    NASA Astrophysics Data System (ADS)

    Barrett, T. B.; Marshall, R.; Bloom, J.; Comer, C.; Caulfield, J.; Warde, C.; Salour, M.

    1989-11-01

    This electron microscope has been applied to the study of the growth of thin epitaxial films on silicon substrates. The study of the nature of platinum-silicide films formed by heating evaporated platinum films on these substrates is discussed. The use of ultra high vacuum systems together with a residual gas analyzer (RGA) is discussed as they relate to the preparation of silicides, a dielectric layer of silicon monoxide is evaporated and an ion beam implanter is used to form a special buried layer as a step toward silicon devices. Synthesis and single crystal growth of indium phosphide in a one-step in-situ process at high ambient pressures is discussed. Analysis of heat transfer by convection, conduction, and radiation in a closed pressure vessel is given. A set of source modules and NOS procedures have been prepared to permit easy access to a 3-dimensional, non-isotrophic ray-tracing program (the Jones - Stephenson program). This system is designed to be run on a CDC CYBER computer system or equivalent using the operating system.

  7. Distribution of first-return times in correlated stationary signals

    NASA Astrophysics Data System (ADS)

    Palatella, Luigi; Pennetta, Cecilia

    2011-04-01

    We present an analytical expression for the first return time (FRT) probability density function of a stationary correlated signal. Precisely, we start by considering a stationary discrete-time Ornstein-Uhlenbeck (OU) process with exponential decaying correlation function. The first return time distribution for this process is derived by adopting a well-known formalism typically used in the study of the FRT statistics for nonstationary diffusive processes. Then, by a subordination approach, we treat the case of a stationary process with power-law tail correlation function and diverging correlation time. We numerically test our findings, obtaining in both cases a good agreement with the analytical results. We notice that neither in the standard OU nor in the subordinated case a simple form of waiting time statistics, like stretched-exponential or similar, can be obtained while it is apparent that long time transient may shadow the final asymptotic behavior.

  8. Systolic processor for signal processing

    SciTech Connect

    Frank, G.A.; Greenawalt, E.M.; Kulkarni, A.V.

    1982-01-01

    A systolic array is a natural architecture for a high-performance signal processor, in part because of the extensive use of inner-product operations in signal processing. The modularity and simple interconnection of systolic arrays promise to simplify the development of cost-effective, high-performance, special-purpose processors. ESL incorporated has built a proof of concept model of a systolic processor. It is flexible enough to permit experimentation with a variety of algorithms and applications. ESL is exploring the application of systolic processors to image- and signal-processing problems. This paper describes this experimental system and some of its applications to signal processing. ESL is also pursuing new types of systolic architectures, including the VLSI implementation of systolic cells for solving systems of linear equations. These new systolic architectures allow the real-time design of adaptive filters. 14 references.

  9. Long-time Correlations in Electromyography Signals

    NASA Astrophysics Data System (ADS)

    Zurcher, Ulrich; Maynard, Rachel

    2006-10-01

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

  10. New Optical Methods for Signal Processing

    NASA Astrophysics Data System (ADS)

    Zhang, Yan

    This doctoral thesis studies the optical implementations of various new algorithms and methods for large bandwidth signal and image processing. Among the schemes to be studied are the long data stream convolution/correlation, the Gabor and the wavelet transforms, and their applications to system failure prediction, dense target signal processing and image coding. Based on the Chinese remainder theorem, optically implementable algorithms are described, which convert the convolution/correlation of long data streams to relatively small scale linear operations such as a group of short -term vector-matrix multiplications or short-term convolutions/correlations. The proposed algorithms can be realized by using the existing optical analog data processors. Simulations were performed to prove their validity. Technical problems and fundamental limitations of the above schemes are studied. Following the consideration of the above time domain operations, signal's representations in joint time -frequency (scale) domain are then considered. An opto -electronic Gabor coefficient processor is designed to perform the Gabor transform on short one-dimensional (1-D) signals in real-time. Some experimental results are presented to confirm the operational principle of the system. As an application of this processor, Gabor transform based transient signal detection is studied. Other schemes for implementing Gabor transform of long 1-D signals based on the long data stream convolver, and 2-D signals are also investigated. Following the study of the Gabor transform, the newly suggested wavelet transform is considered for its optical implementation. Using commercially available opto-electronic components, an optical wavelet processor is designed and built to perform the wavelet transforms on short 1-D signals in real-time. As an extension, architectures for 2-D optical wavelet transform are also described and computer simulated with the consideration of their technical problems of optical

  11. 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.

  12. 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)

    Mejía-Uriarte, E. V.; Navarrete, M.; Villagrán-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 (ΔT), 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.

  13. [Anesthesia in the Signal Processing Methods].

    PubMed

    Gu, Jiajun; Huang, Yan; Ye, Jilun; Wang, Kaijun; Zhang, Meimei

    2015-09-01

    Anesthesia plays an essential role in clinical operations. Guiding anesthesia by EEG signals is one of the most promising methods at present and it has obtained good results. The analysis and process of the EEG signals in anesthesia can provide clean signal for further research. This paper used variance threshold method to remove the mutation fast and large interfering signals; and used notch filter to remove frequency interference, smoothing filter to remove baseline drift and Butterworth low-pass filter to remove high frequency noise at the same time. In addition to this, the translation invariant wavelet method to remove interference noise on the signals which was after the classical filter and retained non-stationary characteristics was used to evaluate parameter calculation. By comparing the calculated parameters from treated signal using this paper's methods and untreated signal and standard signal, the standard deviation and correlation has been improved, particularly the major parameters BetaR, which provides better signal for integration of multi-parameter to evaluate depth of anesthesia index for the latter. PMID:26904870

  14. 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.

  15. Acoustic signal processing toolbox for array processing

    NASA Astrophysics Data System (ADS)

    Pham, Tien; Whipps, Gene T.

    2003-08-01

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

  16. 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.

  17. 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.

  18. Signal processing of anthropometric data

    NASA Technical Reports Server (NTRS)

    Zimmermann, W. J.

    1983-01-01

    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.

  19. DLP switched blaze grating: the heart of optical signal processing

    NASA Astrophysics Data System (ADS)

    Duncan, Walter M.; Lee, Benjamin L.; Rancuret, Paul; Sawyers, Bryce D.; Endsley, Lynn; Powell, Donald

    2003-01-01

    We have developed an approach for processing communication signals in the optical domain using a DLP digital mirror array driven by a Digital Signal Processor (DSP). In optical communication systems, modulation rates of 10 GB/s and above are common, hence, direct processing of Dense Wavelength Division Multiplexed (DWDM) optical signals without undergoing Optical to Electrical conversion has become a key requirement for cost effective deployment of dynamic optical networks. This work will discuss primarily applications of Optical Signal Processing (OSP) to coherent DWDM signals. Optical Signal Processing has also found applications in spectroscopy, microscopy, sensing, optical correlation, and testing.

  20. EEG Correlates of Self-Referential Processing

    PubMed Central

    Knyazev, Gennady G.

    2013-01-01

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

  1. EEG correlates of self-referential processing.

    PubMed

    Knyazev, Gennady G

    2013-01-01

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

  2. Lagrange wavelets for signal processing.

    PubMed

    Shi, Z; Wei, G W; Kouri, D J; Hoffman, D K; Bao, Z

    2001-01-01

    This paper deals with the design of interpolating wavelets based on a variety of Lagrange functions, combined with novel signal processing techniques for digital imaging. Halfband Lagrange wavelets, B-spline Lagrange wavelets and Gaussian Lagrange (Lagrange distributed approximating functional (DAF)) wavelets are presented as specific examples of the generalized Lagrange wavelets. Our approach combines the perceptually dependent visual group normalization (VGN) technique and a softer logic masking (SLM) method. These are utilized to rescale the wavelet coefficients, remove perceptual redundancy and obtain good visual performance for digital image processing. PMID:18255493

  3. Wave-based signal processing

    NASA Astrophysics Data System (ADS)

    McClure, Mark Richard

    The efficacy of imbedding knowledge of wave-scattering phenomenology into the processing of remote-sensing data is examined. In particular, the processing of radar and sonar phase history and synthetic-aperture imagery is considered. Algorithms are developed for effecting signal denoising, feature extraction (for use in target identification/classification) and detection. Three classes of algorithms are presented: (1) superresolution, (2) adaptive-signal decomposition, and (3) template matching. A superresolution signal-processing algorithm is used for the identification of wavefronts from the fields scattered from several canonical targets. Particular wave objects that are examined are single and multiple edge diffraction, scattering from flat and curved surfaces, cone diffraction, and creeping waves. General properties of superresolution processing of such data--independent of the particular algorithm used--are assessed through examination of the Cramer-Rao bounds. The method of matching pursuits is used to effect data-adaptive signal decomposition. This algorithm utilizes a nonlinear iterative procedure to project a given waveform onto a particular dictionary. For scattering problems, the most appropriate dictionary is composed of waveobjects consistent with the underlying wave phenomenology. A signal scattered from most targets of interest can be decomposed in terms of wavefronts, resonances, and chirps--and each of these subclasses can be further subdivided based on characteristic wave physics. Here the efficacy of applying the method of matching pursuits with a wave-based dictionary is examined, for the processing of scattering data. Detection test statistics are derived based on matching-pursuits results from each dictionary separately as well as with the cumulative results from multiple dictionaries. Examples are presented using measured data, for wideband, time-domain acoustic scattering from a submerged elastic shell. Finally, a full-wave electromagnetic

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. Synthetic aperture radar signal processing: Trends and technologies

    NASA Technical Reports Server (NTRS)

    Curlander, John C.

    1993-01-01

    An overview of synthetic aperture radar (SAR) technology is presented in vugraph form. The following topics are covered: an SAR ground data system; SAR signal processing algorithms; SAR correlator architectures; and current and future trends.

  11. 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.

  12. 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

  13. 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.

  14. 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.

  15. BPSK Demodulation Using Digital Signal Processing

    NASA Technical Reports Server (NTRS)

    Garcia, Thomas R.

    1996-01-01

    A digital communications signal is a sinusoidal waveform that is modified by a binary (digital) information signal. The sinusoidal waveform is called the carrier. The carrier may be modified in amplitude, frequency, phase, or a combination of these. In this project a binary phase shift keyed (BPSK) signal is the communication signal. In a BPSK signal the phase of the carrier is set to one of two states, 180 degrees apart, by a binary (i.e., 1 or 0) information signal. A digital signal is a sampled version of a "real world" time continuous signal. The digital signal is generated by sampling the continuous signal at discrete points in time. The rate at which the signal is sampled is called the sampling rate (f(s)). The device that performs this operation is called an analog-to-digital (A/D) converter or a digitizer. The digital signal is composed of the sequence of individual values of the sampled BPSK signal. Digital signal processing (DSP) is the modification of the digital signal by mathematical operations. A device that performs this processing is called a digital signal processor. After processing, the digital signal may then be converted back to an analog signal using a digital-to-analog (D/A) converter. The goal of this project is to develop a system that will recover the digital information from a BPSK signal using DSP techniques. The project is broken down into the following steps: (1) Development of the algorithms required to demodulate the BPSK signal; (2) Simulation of the system; and (3) Implementation a BPSK receiver using digital signal processing hardware.

  16. 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

  17. 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

  18. 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.

  19. Study Of Adaptive-Array Signal Processing

    NASA Technical Reports Server (NTRS)

    Satorius, Edgar H.; Griffiths, Lloyd

    1990-01-01

    Report describes study of adaptive signal-processing techniques for suppression of mutual satellite interference in mobile (on ground)/satellite communication system. Presents analyses and numerical simulations of performances of two approaches to signal processing for suppression of interference. One approach, known as "adaptive side lobe canceling", second called "adaptive temporal processing".

  20. 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.

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

    SciTech Connect

    Laurence, T A; Kwon, Y; Yin, E; Hollars, C; Camarero, J A; Barsky, D

    2006-06-21

    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'' (PFCS), 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 PFCS 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.

  2. 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.

  3. 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.

  4. Processing of real ELT signals for Sarsat

    NASA Astrophysics Data System (ADS)

    Chung, T.; Carter, C. R.

    1987-01-01

    The performance of different processing strategies on real signals recorded from an emergency locator transmitter (ELT) test bed in Ottawa is examined. A processor based on the use of ordered statistics is developed. This new processor greatly reduces the interference produced by the ELT sidebands while maintaining good detection performance on weak signals. In addition, the maximum entropy method is found to be effective in processing ELT signals having noncoherent characteristics.

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  6. Correlation autoregressive processes with application to helicopter noise

    NASA Technical Reports Server (NTRS)

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

    1990-01-01

    This paper introduces a new class of random processes X(t), the autocorrelations R sub x (t1, t2) of which satisfy a linear relation for all t1 and t2 in some interval of the time axis. Such random processes are denoted as 'correlation-autoregressive'. This class is shown to include the familiar stationary and periodically correlated processes as well as many other, both harmonizable and nonharmonizable, nonstationary processes. When a process is correlation-autoregressive for all times and harmonizable, its two-dimensional power spectral density is shown to take a particularly simple form. The relationship of such processes to the class of stationary processes is examined. In addition, the application of such processes in the analysis of typical helicopter noise signals is described.

  7. Correlation of nighttime MF signal strength with solar activity

    NASA Astrophysics Data System (ADS)

    Kohata, Hiroki; Kimura, Iwane; Wakai, Noboru; Ogawa, Tadahiko

    Observations of the signal strength of MF broadcasting signals (774/770 kHz) transmitted from Akita, Japan, on board the Japanese Antarctic ice breaker Fuji, bound from Japan to Syowa station, Antarctica, have revealed an interesting positive correlation between strengths of long distance signals propagating at night and solar activity. It is already known that MF propagation characteristics in North America show a negative correlation with solar activity. The present paper, interprets the results by using the multihop method with full-wave analysis. The difference in correlation with solar activity between the results of Fuji and those in North America can be elucidated if it is assumed that there is a ledge in the electron-density profile around an altitude range of 85 to 90 km and that the density of the ledge is smaller in the North American region than in the equatorial region.

  8. Weighted parallel contributions of binocular correlation and match signals to conscious perception of depth.

    PubMed

    Fujita, Ichiro; Doi, Takahiro

    2016-06-19

    Binocular disparity is detected in the primary visual cortex by a process similar to calculation of local cross-correlation between left and right retinal images. As a consequence, correlation-based neural signals convey information about false disparities as well as the true disparity. The false responses in the initial disparity detectors are eliminated at later stages in order to encode only disparities of the features correctly matched between the two eyes. For a simple stimulus configuration, a feed-forward nonlinear process can transform the correlation signal into the match signal. For human observers, depth judgement is determined by a weighted sum of the correlation and match signals rather than depending solely on the latter. The relative weight changes with spatial and temporal parameters of the stimuli, allowing adaptive recruitment of the two computations under different visual circumstances. A full transformation from correlation-based to match-based representation occurs at the neuronal population level in cortical area V4 and manifests in single-neuron responses of inferior temporal and posterior parietal cortices. Neurons in area V5/MT represent disparity in a manner intermediate between the correlation and match signals. We propose that the correlation and match signals in these areas contribute to depth perception in a weighted, parallel manner.This article is part of the themed issue 'Vision in our three-dimensional world'. PMID:27269600

  9. Linearly-Constrained Adaptive Signal Processing Methods

    NASA Astrophysics Data System (ADS)

    Griffiths, Lloyd J.

    1988-01-01

    In adaptive least-squares estimation problems, a desired signal d(n) is estimated using a linear combination of L observation values samples xi (n), x2(n), . . . , xL-1(n) and denoted by the vector X(n). The estimate is formed as the inner product of this vector with a corresponding L-dimensional weight vector W. One particular weight vector of interest is Wopt which minimizes the mean-square between d(n) and the estimate. In this context, the term `mean-square difference' is a quadratic measure such as statistical expectation or time average. The specific value of W which achieves the minimum is given by the prod-uct of the inverse data covariance matrix and the cross-correlation between the data vector and the desired signal. The latter is often referred to as the P-vector. For those cases in which time samples of both the desired and data vector signals are available, a variety of adaptive methods have been proposed which will guarantee that an iterative weight vector Wa(n) converges (in some sense) to the op-timal solution. Two which have been extensively studied are the recursive least-squares (RLS) method and the LMS gradient approximation approach. There are several problems of interest in the communication and radar environment in which the optimal least-squares weight set is of interest and in which time samples of the desired signal are not available. Examples can be found in array processing in which only the direction of arrival of the desired signal is known and in single channel filtering where the spectrum of the desired response is known a priori. One approach to these problems which has been suggested is the P-vector algorithm which is an LMS-like approximate gradient method. Although it is easy to derive the mean and variance of the weights which result with this algorithm, there has never been an identification of the corresponding underlying error surface which the procedure searches. The purpose of this paper is to suggest an alternative

  10. 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.

  11. Electronics Signal Processing for Medical Imaging

    NASA Astrophysics Data System (ADS)

    Turchetta, Renato

    This paper describes the way the signal coming from a radiation detector is conditioned and processed to produce images useful for medical applications. First of all, the small signal produce by the radiation is processed by analogue electronics specifically designed to produce a good signal-over-noise ratio. The optimised analogue signal produced at this stage can then be processed and transformed into digital information that is eventually stored in a computer, where it can be further processed as required. After an introduction to the general requirements of the processing electronics, we will review the basic building blocks that process the `tiny' analogue signal coming from a radiation detector. We will in particular analyse how it is possible to optimise the signal-over-noise ratio of the electronics. Some exercises, developed in the tutorial, will help to understand this fundamental part. The blocks needed to process the analogue signal and transform it into a digital code will be described. The description of electronics systems used for medical imaging systems will conclude the lecture.

  12. SignalPlant: an open signal processing software platform.

    PubMed

    Plesinger, F; Jurco, J; Halamek, J; Jurak, P

    2016-07-01

    The growing technical standard of acquisition systems allows the acquisition of large records, often reaching gigabytes or more in size as is the case with whole-day electroencephalograph (EEG) recordings, for example. Although current 64-bit software for signal processing is able to process (e.g. filter, analyze, etc) such data, visual inspection and labeling will probably suffer from rather long latency during the rendering of large portions of recorded signals. For this reason, we have developed SignalPlant-a stand-alone application for signal inspection, labeling and processing. The main motivation was to supply investigators with a tool allowing fast and interactive work with large multichannel records produced by EEG, electrocardiograph and similar devices. The rendering latency was compared with EEGLAB and proves significantly faster when displaying an image from a large number of samples (e.g. 163-times faster for 75  ×  10(6) samples). The presented SignalPlant software is available free and does not depend on any other computation software. Furthermore, it can be extended with plugins by third parties ensuring its adaptability to future research tasks and new data formats. PMID:27243208

  13. Multiwavelet design for cardiac signal processing.

    PubMed

    Peelers, R L M; Karel, J M H; Westra, R L; Haddad, S A P; Serdijn, W A

    2006-01-01

    An approach for designing multiwavelets is introduced, for use in cardiac signal processing. The parameterization of the class of multiwavelets is in terms of associated FIR polyphase all-pass filters. Orthogonality and a balanced vanishing moment of order 1 are built into the parameterization. An optimization criterion is developed to associate the wavelets with different meaningful segments of a signal. This approach is demonstrated on the simultaneous detection of QRS-complexes and T-peaks in ECG signals. PMID:17946917

  14. 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.

  15. 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

  16. Sparse representation in speech signal processing

    NASA Astrophysics Data System (ADS)

    Lee, Te-Won; Jang, Gil-Jin; Kwon, Oh-Wook

    2003-11-01

    We review the sparse representation principle for processing speech signals. A transformation for encoding the speech signals is learned such that the resulting coefficients are as independent as possible. We use independent component analysis with an exponential prior to learn a statistical representation for speech signals. This representation leads to extremely sparse priors that can be used for encoding speech signals for a variety of purposes. We review applications of this method for speech feature extraction, automatic speech recognition and speaker identification. Furthermore, this method is also suited for tackling the difficult problem of separating two sounds given only a single microphone.

  17. 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

  18. 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.

  19. 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

  20. Intelligent Signal Processing for Detection System Optimization

    SciTech Connect

    Fu, C Y; Petrich, L I; Daley, P F; Burnham, A K

    2004-06-18

    A wavelet-neural network signal processing method has demonstrated approximately tenfold improvement in the detection limit of various nitrogen and phosphorus compounds over traditional signal-processing methods in analyzing the output of a thermionic detector attached to the output of a gas chromatograph. A blind test was conducted to validate the lower detection limit. All fourteen of the compound spikes were detected when above the estimated threshold, including all three within a factor of two above. In addition, two of six were detected at levels 1/2 the concentration of the nominal threshold. We would have had another two correct hits if we had allowed human intervention to examine the processed data. One apparent false positive in five nulls was traced to a solvent impurity, whose presence was identified by running a solvent aliquot evaporated to 1% residual volume, while the other four nulls were properly classified. We view this signal processing method as broadly applicable in analytical chemistry, and we advocate that advanced signal processing methods be applied as directly as possible to the raw detector output so that less discriminating preprocessing and post-processing does not throw away valuable signal.

  1. Intelligent Signal Processing for Detection System Optimization

    SciTech Connect

    Fu, C Y; Petrich, L I; Daley, P F; Burnham, A K

    2004-12-05

    A wavelet-neural network signal processing method has demonstrated approximately tenfold improvement over traditional signal-processing methods for the detection limit of various nitrogen and phosphorus compounds from the output of a thermionic detector attached to a gas chromatograph. A blind test was conducted to validate the lower detection limit. All fourteen of the compound spikes were detected when above the estimated threshold, including all three within a factor of two above the threshold. In addition, two of six spikes were detected at levels of 1/2 the concentration of the nominal threshold. Another two of the six would have been detected correctly if we had allowed human intervention to examine the processed data. One apparent false positive in five nulls was traced to a solvent impurity, whose presence was subsequently identified by analyzing a solvent aliquot evaporated to 1% residual volume, while the other four nulls were properly classified. We view this signal processing method as broadly applicable in analytical chemistry, and we advocate that advanced signal processing methods should be applied as directly as possible to the raw detector output so that less discriminating preprocessing and post-processing does not throw away valuable signal.

  2. 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

  3. Modeling and a correlation algorithm for spaceborne SAR signals

    NASA Technical Reports Server (NTRS)

    Wu, C.; Liu, K. Y.; Jin, M.

    1982-01-01

    A mathematical model of a spaceborne synthetic aperture radar (SAR) response is presented. Thhe associated SAR system performance, in terms of the resolution capability, is also discussed. The analysis of spaceborne SAR target response indicates that the SAR correlation problem is a two-dimensional one with a linear shift-variant response function. A new digital processing algorithm is proposed here in order to realize an economical digital SAR correlation system. The proposed algorithm treats the two-dimensional correlation by a combination of frequency domain fast correlation in the azimuth dimension and a time-domain convolver type of operation in the range dimension. Finally, digitally correlated SEASAT satellite SAR imagery is used in an exemplary sense to validate the SAR response model and the new digital processing technique developed.

  4. 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)

  5. 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.

  6. Complexity of Receptor Tyrosine Kinase Signal Processing

    PubMed Central

    Volinsky, Natalia; Kholodenko, Boris N.

    2013-01-01

    Our knowledge of molecular mechanisms of receptor tyrosine kinase (RTK) signaling advances with ever-increasing pace. Yet our understanding of how the spatiotemporal dynamics of RTK signaling control specific cellular outcomes has lagged behind. Systems-centered experimental and computational approaches can help reveal how overlapping networks of signal transducers downstream of RTKs orchestrate specific cell-fate decisions. We discuss how RTK network regulatory structures, which involve the immediate posttranslational and delayed transcriptional controls by multiple feed forward and feedback loops together with pathway cross talk, adapt cells to the combinatorial variety of external cues and conditions. This intricate network circuitry endows cells with emerging capabilities for RTK signal processing and decoding. We illustrate how mathematical modeling facilitates our understanding of RTK network behaviors by unraveling specific systems properties, including bistability, oscillations, excitable responses, and generation of intricate landscapes of signaling activities. PMID:23906711

  7. 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.

  8. 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

  9. Signal processing in cryogenic particle detection

    NASA Astrophysics Data System (ADS)

    Yuryev, Y. N.; Jang, Y. S.; Kim, S. K.; Lee, K. B.; Lee, M. K.; Lee, S. J.; Yoon, W. S.; Kim, Y. H.

    2011-04-01

    We describe a signal-processing program for a data acquisition system for cryogenic particle detectors. The program is based on an optimal-filtering method for high-resolution measurement of calorimetric signals with a significant amount of noise of unknown origin and non-stationary behavior. The program was applied to improve the energy resolution of the alpha particle spectrum of an 241Am source.

  10. 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.}

  11. Discrete Signal Processing on Graphs: Sampling Theory

    NASA Astrophysics Data System (ADS)

    Chen, Siheng; Varma, Rohan; Sandryhaila, Aliaksei; Kovacevic, Jelena

    2015-12-01

    We propose a sampling theory for signals that are supported on either directed or undirected graphs. The theory follows the same paradigm as classical sampling theory. We show that perfect recovery is possible for graph signals bandlimited under the graph Fourier transform. The sampled signal coefficients form a new graph signal, whose corresponding graph structure preserves the first-order difference of the original graph signal. For general graphs, an optimal sampling operator based on experimentally designed sampling is proposed to guarantee perfect recovery and robustness to noise; for graphs whose graph Fourier transforms are frames with maximal robustness to erasures as well as for Erd\\H{o}s-R\\'enyi graphs, random sampling leads to perfect recovery with high probability. We further establish the connection to the sampling theory of finite discrete-time signal processing and previous work on signal recovery on graphs. To handle full-band graph signals, we propose a graph filter bank based on sampling theory on graphs. Finally, we apply the proposed sampling theory to semi-supervised classification on online blogs and digit images, where we achieve similar or better performance with fewer labeled samples compared to previous work.

  12. 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

  13. 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

  14. 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

  15. 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.

  16. Array algebra estimation in signal processing

    NASA Astrophysics Data System (ADS)

    Rauhala, U. A.

    A general theory of linear estimators called array algebra estimation is interpreted in some terms of multidimensional digital signal processing, mathematical statistics, and numerical analysis. The theory has emerged during the past decade from the new field of a unified vector, matrix and tensor algebra called array algebra. The broad concepts of array algebra and its estimation theory cover several modern computerized sciences and technologies converting their established notations and terminology into one common language. Some concepts of digital signal processing are adopted into this language after a review of the principles of array algebra estimation and its predecessors in mathematical surveying sciences.

  17. Processing Oscillatory Signals by Incoherent Feedforward Loops.

    PubMed

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

    2016-09-01

    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 the 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 exhibit temporal adaptation, where the system is desensitized to a sustained input. This property serves as the foundation for distinguishing input 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 the IFFL components dictate the input range for which the network is able to decode pulsatile dynamics. In addition, a match between the network parameters and input signal characteristics is required for optimal "counting". We elucidate one potential mechanism by which information processing occurs in natural networks, and our work has implications in the design of synthetic gene circuits for this purpose. PMID:27623175

  18. 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).

  19. 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

  20. 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

  1. 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.

  2. 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.

  3. Cross-frequency Doppler sensitive signal processing

    NASA Astrophysics Data System (ADS)

    Wagstaff, Ronald A.

    2005-04-01

    When there is relative motion between an acoustic source and a receiver, a signal can be Doppler shifted in frequency and enter or leave the processing bins of the conventional signal processor. The amount of the shift is determined by the frequency and the rate of change in the distance between the source and the receiver. This frequency Doppler shifting can cause severe reductions in the processors performance. Special cross-frequency signal processing algorithms have recently been developed to mitigate the effects of Doppler. They do this by using calculation paths that cut across frequency bins in order to follow signals during frequency shifting. Cross-frequency spectral grams of a fast-flying sound source were compared to conventional grams, to evaluate the performance of this new signal processing method. The Doppler shifts in the data ranged up to 70 contiguous frequency bins. The resulting cross-frequency grams showed that three paths provided small to no improvement. Four paths showed improvements for either up-frequency or down-frequency shifting, but not for both. Two paths showed substantial improvement for both up-frequency and down-frequency shifting. The cross-frequency paths will be defined, and comparisons between conventional and cross-frequency grams will be presented. [Work supported by Miltec Corporation.

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

    NASA Technical Reports Server (NTRS)

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

    1983-01-01

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

  5. 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.

  6. Visual signal processing, speechreading, and related issues

    NASA Astrophysics Data System (ADS)

    Levitt, Harry

    2003-06-01

    People with hearing loss make use of visual speech cues to supplement the impoverished speech signal. This process, known as speechreading (or lipreading) can be very effective because of the complementary nature of auditory and visual speech cues. Despite the importance of visual speech cues (for both normal-hearing and hearing-impaired people) research on the visual characteristics of speech has lagged behind research on the acoustic characteristics of speech. The field of acoustic phonetics benefited substantially from the availability of powerful techniques for acoustic signal analysis. The substantial, recent advances in optical signal processing have opened up new vistas for visual speech analysis analogous to the way technological innovation revolutionized the field of acoustic phonetics. This paper describes several experiments in the emerging field of optic phonetics.

  7. 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.

  8. 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.

  9. Signal processing aspects of windshear detection

    NASA Technical Reports Server (NTRS)

    Aalfs, David D.; Baxa, Ernest G., Jr.; Bracalente, Emedio M.

    1993-01-01

    Low-altitude windshear (LAWS) has been identified as a major hazard to aircraft, particularly during takeoff and landing. The Federal Aviation Administration (FAA) has been involved with developing technology to detect LAWS. A key element in this technology is high resolution pulse Doppler weather radar equipped with signal and data processing to provide timely information about possible hazardous conditions.

  10. Efficient multiprocessor architecture for digital signal processing

    SciTech Connect

    Auguin, M.; Boeri, F.

    1982-01-01

    There is a continuing pressure of better processing performances in numerical signal processing. Effective utilization of LSI semiconductor technology allows the consideration of multiprocessor architectures. The problem of interconnecting the components of the architecture arises. The authors describe a control algorithm of the Benes interconnection network in a asynchronous multiprocessor system. A simulation study of the time-shared bus, of the omega network, of the benes network and of the crossbar network gives a comparison of performances. 8 references.

  11. Signal processing of ultrasonic tomographic data

    NASA Astrophysics Data System (ADS)

    Tsihrintzis, George A.; Devaney, Anthony J.

    1992-12-01

    We process a set of data measured with a prototype ultrasonic scanner developed by the Norwegian company Norwave Development AS, Oslo, Norway in collaboration with the American company A.J. Devaney Associates, Boston, Massachusetts. In particular, we apply signal processing algorithms, recently developed by the authors to locate known test objects in a fluid background. Possible applications of the research include locating and identifying cancerous tumors in human tissue. These and other avenues for future research are discussed in the paper.

  12. 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

    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.

  13. 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.

  14. 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.

  15. Signal processing in impulsive electromagnetic interference

    NASA Astrophysics Data System (ADS)

    Zabin, Serena M.

    1991-06-01

    Statistical signal processing functions such as signal detection, estimating, and identification play a key role in the development of effective communications, radar, and sonar systems. For example, advanced statistical methods are emerging as being particularly important in digital communications systems operating in channels corrupted by interference from such phenomena as multiple-access noise, intentional jamming, and impulsive noise sources. Conventional demodulation methods, such as coherent matched filtering, often suffer serious performance degradation when subjected to interference of these types; however, this degradation can frequently be eliminated through the use of more sophisticated signal processing techniques. A central issue in the design of effective signal processing procedures for system operating in channels such as those noted above is that of channel identification. Although certain aspects of channel identification have been studied extensively, one area in which there is a pressing need for further research is that of identification of impulsive channels. Communication systems are seldom interfered with by white Gaussian noise alone, yet receiving systems in general use are those which are optimum for white Gaussian noise.

  16. 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.

  17. Multitime correlation functions in nonclassical stochastic processes

    NASA Astrophysics Data System (ADS)

    Krumm, F.; Sperling, J.; Vogel, W.

    2016-06-01

    A general method is introduced for verifying multitime quantum correlations through the characteristic function of the time-dependent P functional that generalizes the Glauber-Sudarshan P function. Quantum correlation criteria are derived which identify quantum effects for an arbitrary number of points in time. The Magnus expansion is used to visualize the impact of the required time ordering, which becomes crucial in situations when the interaction problem is explicitly time dependent. We show that the latter affects the multi-time-characteristic function and, therefore, the temporal evolution of the nonclassicality. As an example, we apply our technique to an optical parametric process with a frequency mismatch. The resulting two-time-characteristic function yields full insight into the two-time quantum correlation properties of such a system.

  18. 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.

  19. Source and processing effects on noise correlations

    NASA Astrophysics Data System (ADS)

    Fichtner, Andreas

    2014-05-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2007-03-01

    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 (˜350 μm) and larger (˜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.

  1. 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.

  2. Data processing in ``Radioastron'' mission. ASC Correlator.

    NASA Astrophysics Data System (ADS)

    Andrianov, Andrey

    The ``Radioastron'' space mission is the unique project of Russian Space Agency (Roscosmos) and Russian Academy of Sciences to investigate the Universe by means of implementation of VLBI principles with 'Spectr-R' space vehicle. The 10-m radiotelescop onboard ``Spectr-R'' is fully operational since 15 November, 2011 as the Space element of Ground-to-Space interferometer at the orbit with the apogee up to 350000 km. The correlator for Radioastron mission is a part of a ASL (Astro Space Locator) computer complex for Windows environment fully developed at Astro Space Center (ASC) of Lebedev Physical Institute. In the report the main features and operational procedures of the ASC correlator are described with the emphasis on the differences in data-processing from the ground VLBI. The description is given of the algorithm of time delay and its derivatives calculations that is a question of principle for a correlation procedure of the ground-space interferometer data. Methods of extracting of the correlation results are analyzed in terms of efficiency and parameterization of the correlator operations. Some scientific results of a number of observing sessions are given as illustrations.

  3. 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

  4. Research on Signal Processing Algorithms in GPS Receivers

    NASA Astrophysics Data System (ADS)

    Cai, Fan; Yin, Yan; Zhang, Xiu-Zhong

    2007-03-01

    The modern standard satellite navigation receivers are commonly based on ASICs for signal processing and fast microprocessors for application calculations. The software satellite navigation receiver is also developed in recent years. The research on software receivers becomes one trend of satellite navigation receiver. For algorithms on signal processing play an important role in satellite navigation receivers, the paper illuminates the signal processing algorithms in detail. The GPS receiver is widely used at present. So the paper places emphasis on signal processing algorithms about GPS receiver. Signal processing algorithms include three aspects: the algorithm on signal acquisition, the algorithm on carrier tracking and the algorithm on PRN (pseudo random noise) code tracking. In the part of signal acquisition, the method of using FFT to get the result of circular correlation is introduced. The paper carefully researches the method and discusses the derivation process of the method. In the part of carrier tracking, the paper describes the principle of frequency locked loop (FLL) and phase locked loop (PLL) and analyzes the principle of loop filter. The method of transition from s-domain to z-domain is introduced. The computation of noise bandwidth of the loop filter are expatiated and the structures of one-step digital loop filter, two-step digital loop filter and three step are given. Other parameters of loop filters are also given. In the part of code tracking, delay-early locked loop (DLL) is introduced. Theoretical analysis and experiment results demonstrate the algorithms in the paper. Through the simulation testing, the performance of combination of PLL and FLL can be acknowledged.

  5. 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.

  6. Parallel digital signal processing architectures for image processing

    NASA Astrophysics Data System (ADS)

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

    1994-10-01

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

  7. 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.

  8. A correlation polarimeter for noise-like signals. [optimum estimation of linearly polarized electromagnetic wave

    NASA Technical Reports Server (NTRS)

    Ohlson, J. E.

    1976-01-01

    Optimum estimation (tracking) of the polarization plane of a linearly polarized electromagnetic wave is determined when the signal is a narrow-band Gaussian random process with a polarization plane angle which is also a Gaussian random process. This model is compared to previous work and is applicable to space communication. The estimator performs a correlation operation similar to an amplitude-comparison monopulse angle tracker, giving the name correlation polarimeter. Under large signal-to-noise ratio (SNR), the estimator is causal. Performance of the causal correlation polarimeter is evaluated for arbitrary SNR. Optimum precorrelation filtering is determined. With low SNR, the performance of this system is far better than that of previously developed systems. Practical implementation is discussed. A scheme is given to reduce the effect of linearly polarized noise.

  9. Signal Subspace Processing Of Experimental Radio Data

    NASA Astrophysics Data System (ADS)

    Martin, Gordon E.

    1988-02-01

    The research related to this paper was concerned with the application of EigenVector EigenValue ( EVEV ) signal processing techniques to experimental data. The signal subspace methods of Schmidt (called MUSIC), Johnson, and Pisarenko were considered and compared with results of conventional beamformers. Almost all oral and written papers regarding these EVEV processors involve theoretical studies, possibly using simulated data and incoherent noise, but not experimental data. Contrary to that trend, we have reported behavior of EVEV processors using experimental data in this and other papers. The data used here are predominantly due to an HF radio experiment, but the distribution of eigenvalues is also reported for acoustic data. The paper emphasizes two general subtopics of signal subspace processing. First, the eigenvalues of sampled covariance matrices are examined and related to those of incoherent noise. These results include actual data, all of which we found were not Gaussian incoherent noise. A new test related to the ratio of eigenvalues is developed. The MDL and AIC criteria give misleading results with actual noise. Second, directional responses of EVEV and conventional processors are compared using HF radio data that has high signal-to-noise ratio in the non-Gaussian noise. MUSIC is found to have very favorable directional characteristics.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. Neural Networks for Signal Processing and Control

    NASA Astrophysics Data System (ADS)

    Hesselroth, Ted Daniel

    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.

  15. 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

  16. 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.

  17. 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.

  18. NOVEL SIGNAL PROCESSING WITH NONLINEAR TRANSMISSION LINES

    SciTech Connect

    D. REAGOR; ET AL

    2000-08-01

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

  19. 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

  20. Signal processing in impulsive electromagnetic interference

    NASA Astrophysics Data System (ADS)

    Zabin, Serena M.

    1993-06-01

    Statistical signal processing functions such as signal detection, estimation, and identification play a key role in the development of effective communications, radar, and sonar systems. For example, advanced statistical methods are emerging as being particularly important in digital communications systems operating in channels corrupted by interference from such phenomena as multiple-access noise, intentional jamming, and impulsive noise sources. Conventional demodulation methods, such as coherent matched filtering, often suffer serious performance degradation when subject to interference of these types; however, this degradation can frequently be eliminated through the use of more sophisticated signal processing techniques. During this reporting period, the focus of our work has been on the problem of obtaining optimum and efficient identification and detection procedures for impulsive channels. Of particular interest is the Middleton Class A noise model, which is a widely-accepted statistical-physical model for impulsive interference superimposed on a Gaussian background. The model has two basic parameters that can be adjusted to fit a wide variety of impulsive noise phenomena occurring in practice.

  1. 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.

  2. 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.

  3. 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.

  4. Optical signal processing at Essex Corporation

    NASA Astrophysics Data System (ADS)

    Franklin, William R.

    1996-02-01

    The most current research and development in optical signal processing and its application at Essex Corporation is summarized. In progress for more than a decade, this work has evolved from the development of highly specialized algorithms for the intelligence community to more general domains embracing such diverse areas as radar signal processing, medical ultrasound and magnetic resonance imaging, acoustic tomography, and cellular and satellite communications. Essex develops algorithms and designs, fabricates, and tests breadboard designs and transforms these into rugged, compact products for use in harsh environments. Descriptions of the most important investigations in these areas are presented. An image synthesizer called ImSynTM is described that forms images from the measured spatial Fourier components of the object to be imaged. Applications to synthetic aperture radar, acoustic tomography, medical resonance imaging, and synthetic aperture microscopy are shown. An acousto-optic radar signal processor is described that can produce high-resolution, high-dynamic-range range Doppler maps from instantaneous wideband radar returns. A design for a fiber optic true-time delay beamformer is presented. Finally, an optoelectronic telecommunications switch is discussed.

  5. Automatic generation of signal processing integrated circuits

    SciTech Connect

    Pope, S.P.

    1985-01-01

    A system for the automated design of signal processing integrated circuits is described in this thesis. The system is based on a library of circuit cells, and a software package that can configure the cells into complete integrated circuits. The architecture of the cell library is optimized for low and medium bandwidth digital signal processing applications. Circuits designed with the system use a multiprocessor architecture. Input to the system is a design file written in a specialized programming language. Software emulation from the design file is used to verify performance. A two-pass silicon compiler is used to translate the design file into a mask-level description of an integrated circuit. A major goal of the project is to make the system useable by those with little or no formal training in integrated circuits. A second goal is to reduce the time and cost associated with performing an integrated circuit design, while still producing designs which are reasonably efficient in their use of the technology. Development of the system was guided by basic research on appropriate architectures and circuit constructs for signal processors. As part of this research an integrated circuit was designed which performs speech analysis and synthesis. This vocoder circuit is intended for use in low-bit-rate digital speech transmission systems.

  6. 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.

  7. Blind Channel Shortening for Block Transmission of Correlated Signals

    NASA Astrophysics Data System (ADS)

    Miyajima, Teruyuki; Watanabe, Yoshihisa

    In block transmission systems, blind channel shortening methods are known to be effective to reduce the influence of interblock interference which degrades the performance when the length of a channel impulse response is extremely long. Conventional methods assume that the transmitted signal is uncorrelated; however, this assumption is invalid in practical systems such as OFDM with null carriers and MC-CDMA. In this paper, we consider blind channel shortening methods for block transmissions when the transmitted samples within a block are correlated. First, the channel shortening ability of a conventional method is clarified. Next, a new method which exploits the fact that the transmitted samples in different blocks are uncorrelated is introduced. It is shown that the proposed method can shorten the channel properly under certain conditions. Finally, simulation results of OFDM and MC-CDMA systems are shown to verify the effectiveness of the proposed method compared with a conventional one.

  8. Optomechanical correlations and signal self-amplification in interferometric measurements

    NASA Astrophysics Data System (ADS)

    Cohadon, P.-F.; Verlot, P.; Tavernarakis, A.; Briant, T.; Heidmann, A.

    2010-05-01

    Radiation pressure exerted by light in interferometric measurements is responsible for displacements of mirrors which appear as an additional back-action noise and limit the sensitivity of the measurement. We experimentally study these effects by monitoring in a very high-finesse optical cavity the displacements of a mirror with a sensitivity at the 10-20 m/ level. This very high sensitivity is a step towards the observation of fundamental quantum effects of radiation pressure such as the standard quantum limit in interferometric measurements. We report the observation of optomechanical correlations between two optical beams sent into the same moving mirror cavity. We also observed a self-amplification of a signal, which is a consequence of dynamical back-action of radiation pressure in a detuned cavity, and may improve the interferometric measurement sensitivity beyond the standard quantum limit.

  9. Signal processing electronics for a capacitive microsensor

    NASA Astrophysics Data System (ADS)

    Amendola, Gilles; Lu, Guo N.

    2000-04-01

    An interface circuit in a 0.8-micrometers CMOS process for the on- chip integration of a capacitive micro-sensor used as a microphone is presented. In order to circumvent 1/f noise contributions and to improve the signal/noise ratio, a synchronous modulation-demodulation technique has been applied. For the implementation of this technique, we have studied and designed several functional block, such as modulator with signal conversion, low-noise amplifier, demodulator, etc. To deal with problems related to dispersion of intrinsic capacitance of the sensor, a feedback compensating solution is suggested. The designed circuit has a sensibility of 1200 V/pF, with a minimum detectable capacitance variation of 2 10-6 pF.

  10. 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.

  11. 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

  12. 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

  13. Developmental changes of BOLD signal correlations with global human EEG power and synchronization during working memory.

    PubMed

    Michels, Lars; Lüchinger, Rafael; Koenig, Thomas; Martin, Ernst; Brandeis, Daniel

    2012-01-01

    In humans, theta band (5-7 Hz) power typically increases when performing cognitively demanding working memory (WM) tasks, and simultaneous EEG-fMRI recordings have revealed an inverse relationship between theta power and the BOLD (blood oxygen level dependent) signal in the default mode network during WM. However, synchronization also plays a fundamental role in cognitive processing, and the level of theta and higher frequency band synchronization is modulated during WM. Yet, little is known about the link between BOLD, EEG power, and EEG synchronization during WM, and how these measures develop with human brain maturation or relate to behavioral changes. We examined EEG-BOLD signal correlations from 18 young adults and 15 school-aged children for age-dependent effects during a load-modulated Sternberg WM task. Frontal load (in-)dependent EEG theta power was significantly enhanced in children compared to adults, while adults showed stronger fMRI load effects. Children demonstrated a stronger negative correlation between global theta power and the BOLD signal in the default mode network relative to adults. Therefore, we conclude that theta power mediates the suppression of a task-irrelevant network. We further conclude that children suppress this network even more than adults, probably from an increased level of task-preparedness to compensate for not fully mature cognitive functions, reflected in lower response accuracy and increased reaction time. In contrast to power, correlations between instantaneous theta global field synchronization and the BOLD signal were exclusively positive in both age groups but only significant in adults in the frontal-parietal and posterior cingulate cortices. Furthermore, theta synchronization was weaker in children and was--in contrast to EEG power--positively correlated with response accuracy in both age groups. In summary we conclude that theta EEG-BOLD signal correlations differ between spectral power and synchronization and that

  14. 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.

  15. 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

  16. 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.

  17. Inertial processing of vestibulo-ocular signals

    NASA Technical Reports Server (NTRS)

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

    1999-01-01

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

  18. 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.

  19. 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.

  20. 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.

  1. 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%.

  2. 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.

  3. 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.

  4. 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

  5. The correlation dimension: A robust chaotic feature for classifying acoustic emission signals generated in construction materials

    NASA Astrophysics Data System (ADS)

    Kacimi, S.; Laurens, S.

    2009-07-01

    In the field of acoustic emission (AE) source recognition, this paper presents a classification feature based on the paradigm of nonlinear dynamical systems, often referred to as chaos theory. The approach considers signals as time series expressing an underlying dynamical phenomenon and enclosing all the information regarding the dynamics. The scientific knowledge on nonlinear dynamical systems has considerably improved for the past 40 years. The dynamical behavior is analyzed in the phase space, which is the space generated by the state variables of the system. The time evolution of a system is expressed in the phase space by trajectories, and the asymptotic behavior of trajectories defines a space area which is referred to as a system attractor. Dynamical systems may be characterized by the topological properties of attractors, such as the correlation dimension, which is a fractal dimension. According to Takens theorem, even if the system is not clearly defined, it is possible to infer topological information about the attractor from experimental observations. Such a method, which is called phase space reconstruction, was successfully applied for the classification of acoustic emission waveforms propagating in more or less complex materials such as granite and concrete. Laboratory tests were carried out in order to collect numerous AE waveforms from various controlled acoustic sources. Then, each signal was processed to extract a reconstructed attractor from which the correlation dimension was computed. The first results of this research show that the correlation dimension assessed after phase space reconstruction is very relevant and robust for classifying AE signals. These promising results may be explained by the fact that the totality of the signal is used to achieve classifying information. Moreover, due to the self-similar nature of attractors, the correlation dimension, and thus a correlation dimension-based classification approach, is theoretically

  6. 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.

  7. 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.

  8. Ultrasonic signal processing and tissue characterization

    NASA Astrophysics Data System (ADS)

    Mu, Zhiping

    Ultrasound imaging has become one of the most widely used diagnostic tools in medicine. While it has advantages, compared with other modalities, in terms of safety, low-cost, accessibility, portability and capability of real-time imaging, it has limitations. One of the major disadvantages of ultrasound imaging is the relatively low image quality, especially the low signal-to-noise ratio (SNR) and the low spatial resolution. Part of this dissertation is dedicated to the development of digital ultrasound signal and image processing methods to improve ultrasound image quality. Conventional B-mode ultrasound systems display the demodulated signals, i.e., the envelopes, in the images. In this dissertation, I introduce the envelope matched quadrature filtering (EMQF) technique, which is a novel demodulation technique generating optimal performance in envelope detection. In ultrasonography, the echo signals are the results of the convolution of the pulses and the medium responses, and the finite pulse length is a major source of the degradation of the image resolution. Based on the more appropriate complex-valued medium response assumption rather than the real-valued assumption used by many researchers, a nonparametric iterative deconvolution method, the Least Squares method with Point Count regularization (LSPC), is proposed. This method was tested using simulated and experimental data, and has produced excellent results showing significant improvements in resolution. During the past two decades, ultrasound tissue characterization (UTC) has emerged as an active research field and shown potentials of applications in a variety of clinical areas. Particularly interesting to me is a group of methods characterizing the scatterer spatial distribution. For resolvable regular structures, a deconvolution based method is proposed to estimate parameters characterizing such structures, including mean scatterer spacing, and has demonstrated superior performance when compared to

  9. 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.

  10. 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

  11. 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.

  12. Ultrasound perfusion signal processing for tumor detection

    NASA Astrophysics Data System (ADS)

    Kim, MinWoo; Abbey, Craig K.; Insana, Michael F.

    2016-04-01

    Enhanced blood perfusion in a tissue mass is an indication of neo-vascularity and a sign of a potential malignancy. Ultrasonic pulsed-Doppler imaging is a preferred modality for noninvasive monitoring of blood flow. However, the weak blood echoes and disorganized slow flow make it difficult to detect perfusion using standard methods without the expense and risk of contrast enhancement. Our research measures the efficiency of conventional power-Doppler (PD) methods at discriminating flow states by comparing measurement performance to that of an ideal discriminator. ROC analysis applied to the experimental results shows that power Doppler methods are just 30-50 % efficient at perfusion flows less than 1ml/min, suggesting an opportunity to improve perfusion assessment through signal processing. A new perfusion estimator is proposed by extending the statistical discriminator approach. We show that 2-D perfusion color imaging may be enhanced using this approach.

  13. 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

  14. 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

  15. Tunable signal processing through modular control of transcription factor translocation

    PubMed Central

    Hao, Nan; Budnik, Bogdan A.; Gunawardena, Jeremy; O’Shea, Erin K.

    2013-01-01

    Signaling pathways can induce different dynamics of transcription factor (TF) activation. We explored how TFs process signaling inputs to generate diverse dynamic responses. The budding yeast general stress responsive TF Msn2 acted as a tunable signal processor that could track, filter, or integrate signals in an input dependent manner. This tunable signal processing appears to originate from dual regulation of both nuclear import and export by phosphorylation, as mutants with one form of regulation sustained only one signal processing function. Versatile signal processing by Msn2 is crucial for generating distinct dynamic responses to different natural stresses. Our findings reveal how complex signal processing functions are integrated into a single molecule and provide a guide for the design of TFs with “programmable” signal processing functions. PMID:23349292

  16. 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.

  17. 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.

  18. Dynamic range control of audio signals by digital signal processing

    NASA Astrophysics Data System (ADS)

    Gilchrist, N. H. C.

    It is often necessary to reduce the dynamic range of musical programs, particularly those comprising orchestral and choral music, for them to be received satisfactorily by listeners to conventional FM and AM broadcasts. With the arrival of DAB (Digital Audio Broadcasting) a much wider dynamic range will become available for radio broadcasting, although some listeners may prefer to have a signal with a reduced dynamic range. This report describes a digital processor developed by the BBC to control the dynamic range of musical programs in a manner similar to that of a trained Studio Manager. It may be used prior to transmission in conventional broadcasting, replacing limiters or other compression equipment. In DAB, it offers the possibility of providing a dynamic range control signal to be sent to the receiver via an ancillary data channel, simultaneously with the uncompressed audio, giving the listener the option of the full dynamic range or a reduced dynamic range.

  19. Signal processing schemes for optical voltage transducer

    NASA Astrophysics Data System (ADS)

    Chen, Jinling; Xie, Delin; Chen, Hongbin; Xie, Latang; Song, Jianhe; Luo, Xiaoni

    2006-02-01

    This paper describes an optical voltage transducer(OVT) for a 35kV system based on Pockels effect in a BGO(Bi 4Ge 3O 12) crystal. OVT used to measure the voltage of power are superior to conventional electromagnet-induced voltage transducer in many aspects, thus it has great potential to applications. It has some advantages. These advantages are: 1)Optics provides total galvanic separation between the measuring point at high voltage (HV) potential and the measuring equipment at ground potential. 2)Transmission of measuring signals in optical fibers is immune to induced electromagnetic noise even in EMI-environment of switchyards and other high voltage installations. 3)Optics and especially optical fibers make the insulation costs independent of voltage levels thus giving an economical advantage at voltage levels above 100kV. 4)The use of optics is expected to reduce the weight of the transducers. 5)Optical transducers are expected to have a large bandwidth than conventional transducers. 6)The output-signals from an optical transducer are easily interfaced with computers and electronically operated equipment such as digital relays. New techniques developed in electronics and optical field including fiber optic technology bring new contributions to the measurement of voltage and electric field. A Pockels voltage sensor has been widely introduced to electrical power transmission and distribution systems and some advantage of the optical voltage measuring techniques are reported. In this paper, a brief summary of electro-optic effects and the principle of OVT is proposed. The signal processing schemes of different optical path and features are analyzed. The basic principle of OVT is to modulate the irradiance of the light-directed to OVT by an optical fiber-according to the potential difference between the HV-line and the ground potential. The modulation of the light is accomplished by placing a material-that has an optical property (the birefringence), which is

  20. 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

  1. Investigating the correlation between increases in spectral gamma ray signals observed from wireline logging, geochemistry of the recovered core and reef processes in Tahiti coral reef formations (IODP Expedition 310)

    NASA Astrophysics Data System (ADS)

    Inwood, J.; Brewer, T.

    2009-04-01

    The last deglacial reef sequence in Tahiti consists of a series of successive reef terraces seaward of the living barrier reef. IODP Expedition 310 recovered core from 37 boreholes within three locations. The recovered core can be assigned to (i) the last deglacial reef sequence and (ii) an older Pleistocene unit, each comprising a series of distinctive coral assemblages with microbialites locally forming the major component of the reef. Spectral gamma measurements were acquired for eight boreholes in total from both south (Maraa area) and north (Tiarei area) of the main island of Tahiti. In general, gamma counts are low (< 50 cps) for all boreholes, although there is a significant interval of elevated gamma counts in Hole M0005D. This ~ 20 m thick interval is located in the Pleistocene succession a few metres below the boundary with the last deglacial sequence. Few logging measurements were obtained across this boundary due to hostile borehole conditions; thus the spectral gamma log of Hole M0005D is useful for establishing some characteristics of this horizon. Analysis of the individual elements contributing to the raised gamma counts show that U is the major contributor to the higher counts in the upper part of this interval. Lithologies here comprise the coralgal-microbialite reef frameworks that dominate much of the reef terraces. High levels of U in carbonates have previously been linked to diagenetic processes, subaerial exposure, higher levels of organic material and the presence of red algae. Higher counts in the lower section of raised counts result from raised Th and K concentrations and correlate with silt dominated lithology at these depths. We selected 104 core samples from the interval of raised counts for standard geochemical analyses (XRF). Major element correlation diagrams including our new data and published data on Tahiti igneous rocks imply that igneous fragments were incorporated during carbonate precipitation. Detailed thin section analyses

  2. 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

  3. 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

  4. Correlated signals and causal transport in ocean circulation

    NASA Astrophysics Data System (ADS)

    Jeffress, Stephen

    2014-05-01

    This paper presents a framework for interpreting the time-lagged correlation of oceanographic data in terms of physical transport mechanisms. Previous studies have inferred aspects of ocean circulation by correlating fluctuations in temperature and salinity measurements at distant stations. Typically, the time-lag of greatest correlation is interpreted as an advective transit time and hence the advective speed of the current. In this paper we relate correlation functions directly to the underlying equations of fluid transport. This is accomplished by expressing the correlation functions in terms of the Green's function of the transport equation. Two types of correlation functions are distinguished: field-forcing correlation and field-field correlation. Their unique relationships to the Green's function are illustrated in two idealized models of geophysical transport: a leaky pipe model and an advective-diffusive model. Both models show that the field-forcing correlation function converges to the Green's function as the characteristic (time or length) scale of forcing autocorrelation decreases. The leaky pipe model provides an explanation for why advective speeds inferred from time-lagged correlations are often less than the speed of the main current. The advective-diffusive model reveals a structural bias in the field-field correlation function when used to estimate transit times.

  5. 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.

  6. Fine tuning the correlation limit of spatio-temporal signal space separation for magnetoencephalography.

    PubMed

    Medvedovsky, Mordekhay; Taulu, Samu; Bikmullina, Rozaliya; Ahonen, Antti; Paetau, Ritva

    2009-02-15

    Head, jaw and tongue movements contribute to speech artifacts in magnetoencephalography (MEG). Their sources lay close to MEG sensors, therefore, the spatio-temporal signal space separation method (tSSS), specifically suppressing nearby artifacts, can be used for speech artifact suppression. After data reconstruction by signal space separation (referred as SSS), tSSS identifies artifacts by their correlated temporal behavior inside and outside the sensor helmet. The artifacts to be eliminated are thresholded by the quantitative level of this correlation determined by correlation limit (CL). Unnecessarily high CL value may result in suboptimal interference suppression. We evaluated the performance of tSSS with different CLs on MEG data containing speech artifacts. MEG was recorded with 204 planar gradiometers and 102 magnetometers in two subjects counting aloud. The recorded data were processed by tSSS using CLs 0.98, 0.8 and 0.6, and traces were compared. The speech artifact was increasingly suppressed with decreasing CL, but sufficient suppression was achieved at different CL in each subject. Alpha rhythm was not suppressed with CL 0.98 or 0.8; some amplitude reduction with CL 0.6 occurred in one subject. The tSSS is a robust tool suppressing MEG artifacts. It can be fine tuned for challenging artifacts which, after insufficient rejection might resemble brain signals. PMID:18996412

  7. Spatial acoustic signal processing for immersive communication

    NASA Astrophysics Data System (ADS)

    Atkins, Joshua

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

  8. Optical signal processing using photonic reservoir computing

    NASA Astrophysics Data System (ADS)

    Salehi, Mohammad Reza; Dehyadegari, Louiza

    2014-10-01

    As a new approach to recognition and classification problems, photonic reservoir computing has such advantages as parallel information processing, power efficient and high speed. In this paper, a photonic structure has been proposed for reservoir computing which is investigated using a simple, yet, non-partial noisy time series prediction task. This study includes the application of a suitable topology with self-feedbacks in a network of SOA's - which lends the system a strong memory - and leads to adjusting adequate parameters resulting in perfect recognition accuracy (100%) for noise-free time series, which shows a 3% improvement over previous results. For the classification of noisy time series, the rate of accuracy showed a 4% increase and amounted to 96%. Furthermore, an analytical approach was suggested to solve rate equations which led to a substantial decrease in the simulation time, which is an important parameter in classification of large signals such as speech recognition, and better results came up compared with previous works.

  9. 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

  10. Signal processing of aircraft flyover noise

    NASA Technical Reports Server (NTRS)

    Kelly, J. J.

    1993-01-01

    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 level uniform flyover is considered in the study, but the code can accept more general flight profiles. The effects of spectral smearing and its removal are discussed. Using test data acquired from an XV-15 tilt-rotor flyover, comparisons are made between the measured and corrected spectra. Frequency shifts are accurately accounted for by the de-Dopplerization procedure. It is shown that by correcting for spherical spreading and Doppler amplitude, along with frequency, can give some idea about noise source directivity. The analysis indicated that smearing increases with frequency and is more severe on approach than recession.

  11. 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.

  12. Signal processing techniques for damage detection with piezoelectric wafer active sensors and embedded ultrasonic structural radar

    NASA Astrophysics Data System (ADS)

    Yu, Lingyu; Bao, Jingjing; Giurgiutiu, Victor

    2004-07-01

    Embedded ultrasonic structural radar (EUSR) algorithm is developed for using piezoelectric wafer active sensor (PWAS) array to detect defects within a large area of a thin-plate specimen. Signal processing techniques are used to extract the time of flight of the wave packages, and thereby to determine the location of the defects with the EUSR algorithm. In our research, the transient tone-burst wave propagation signals are generated and collected by the embedded PWAS. Then, with signal processing, the frequency contents of the signals and the time of flight of individual frequencies are determined. This paper starts with an introduction of embedded ultrasonic structural radar algorithm. Then we will describe the signal processing methods used to extract the time of flight of the wave packages. The signal processing methods being used include the wavelet denoising, the cross correlation, and Hilbert transform. Though hardware device can provide averaging function to eliminate the noise coming from the signal collection process, wavelet denoising is included to ensure better signal quality for the application in real severe environment. For better recognition of time of flight, cross correlation method is used. Hilbert transform is applied to the signals after cross correlation in order to extract the envelope of the signals. Signal processing and EUSR are both implemented by developing a graphical user-friendly interface program in LabView. We conclude with a description of our vision for applying EUSR signal analysis to structural health monitoring and embedded nondestructive evaluation. To this end, we envisage an automatic damage detection application utilizing embedded PWAS, EUSR, and advanced signal processing.

  13. 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

  14. 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.

  15. 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.

  16. Statistical signal processing in sensor networks

    NASA Astrophysics Data System (ADS)

    Guerriero, Marco

    In this dissertation we focus on decentralized signal processing in Sensor Networks (SN). Four topics are studied: (i) Direction of Arrival (DOA) estimation using a Wireless Sensor network (WSN), (ii) multiple target tracking in large SN, (iii) decentralized target detection in SN and (iv) decentralized sequential detection in SN with communication constraints. The first topic of this thesis addresses the problem of estimating the DOA of an acoustic wavefront using a a WSN made of isotropic (hence individually useless) sensors. The WSN was designed according to the SENMA (SEnsor Network with Mobile Agents) architecture with a mobile agent (MA) that successively queries the sensors lying inside its field of view. We propose both fast/simple and optimal DOA-estimation schemes, and an optimization of the MAs observation management is also carried out, with the surprising finding that the MA ought to orient itself at an oblique angle to the expected DOA, rather than directly toward it. We also consider the extension to multiple sources; intriguingly, per-source DOA accuracy is higher when there is more than one source. In all cases, performance is investigated by simulation and compared, when appropriate, with asymptotic bounds; these latter are usually met after a moderate number of MA dwells. In the second topic, we study the problem of tracking multiple targets in large SN. While these networks hold significant potential for surveillance, it is of interest to address fundamental limitations in large-scale implementations. We first introduce a simple analytical tracker performance model. Analysis of this model suggests that scan-based tracking performance improves with increasing numbers of sensors, but only to a certain point beyond which degradation is observed. Correspondingly, we address model-based optimization of the local sensor detection threshold and the number of sensors. Next, we propose a two-stage tracking approach (fuse-before-track) as a possible

  17. 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

  18. Basic concepts in the processing of SARSAT signals

    NASA Astrophysics Data System (ADS)

    Chung, T.; Carter, C. R.

    1987-03-01

    Search and rescue satellite-aided tracking (SARSAT) involves the use of satellites in low-polar orbits which relay the emergency signals of distressed vehicles to an earth station for signal analysis. In this paper, some basic concepts and a theoretical analysis of the spectra produced by coherent and noncoherent emergency locator transmitter signals are presented. It is shown that coherent signals can be easily processed using linear spectral analysis. Noncoherent signals, however, require more advanced methods.

  19. 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.

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

    NASA Astrophysics Data System (ADS)

    Zhang, Guang-Ming; Harvey, David M.

    2012-03-01

    Various signal processing techniques have been used for the enhancement of defect detection and defect characterisation. Cross-correlation, filtering, autoregressive analysis, deconvolution, neural network, wavelet transform and sparse signal representations have all been applied in attempts to analyse ultrasonic signals. In ultrasonic nondestructive evaluation (NDE) applications, a large number of materials have multilayered structures. NDE of multilayered structures leads to some specific problems, such as penetration, echo overlap, high attenuation and low signal-to-noise ratio. The signals recorded from a multilayered structure are a class of very special signals comprised of limited echoes. Such signals can be assumed to have a sparse representation in a proper signal dictionary. Recently, a number of digital signal processing techniques have been developed by exploiting the sparse constraint. This paper presents a review of research to date, showing the up-to-date developments of signal processing techniques made in ultrasonic NDE. A few typical ultrasonic signal processing techniques used for NDE of multilayered structures are elaborated. The practical applications and limitations of different signal processing methods in ultrasonic NDE of multilayered structures are analysed.

  1. 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.

  2. 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

  3. Across-frequency envelope correlation discrimination and masked signal detection

    PubMed Central

    Grose, John H.; Buss, Emily; Porter, Heather L.; Hall, Joseph W.

    2013-01-01

    This study compared the dependence of comodulation masking release (CMR) and monaural envelope correlation perception (MECP) on the degree of envelope correlation for the same narrowband noise stimuli. Envelope correlation across noise bands was systematically varied by mixing independent bands with a base set of comodulated bands. The magnitude of CMR fell monotonically with reductions in envelope correlation, and CMR varied over a range of envelope correlations that were not discriminable from each other in the MECP paradigm. For complexes of 100-Hz-wide noise bands, discrimination thresholds in the MECP task were similar whether the standard was a comodulated set of noise bands or a completely independent set of noise bands. This was not the case for 25-Hz-wide noise bands. Although the data demonstrate that CMR and MECP exhibit different dependencies on the degree of envelope correlation, some commonality across the two phenomena was observed. Specifically, for 25-Hz-wide bands of noise, there was a robust relationship between individual listeners' sensitivity to decorrelation from an otherwise comodulated set of noise bands and the magnitude of CMR measured for those same comodulated noise bands. PMID:23927119

  4. 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

  5. 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.

  6. Vibrotactile identification of signal-processed sounds from environmental events.

    PubMed

    Ranjbar, Parivash; Stranneby, Dag; Borg, Erik

    2009-01-01

    This study compared three different signal-processing principles (eight basic algorithms)-transposing, modulating, and filtering-to find the principle(s)/algorithm(s) that resulted in the best tactile identification of environmental sounds. The subjects were 19 volunteers (9 female/10 male) who were between 18 and 50 years old and profoundly hearing impaired. We processed sounds produced by 45 representative environmental events with the different algorithms and presented them to subjects as tactile stimuli using a wide-band stationary vibrator. We compared eight algorithms based on the three principles (one unprocessed, as reference). The subjects identified the stimuli by choosing among 10 alternatives drawn from the 45 events. We found that algorithm and subject were significant factors affecting the results (repeated measures analysis of variance, p < 0.001). We also found large differences between individuals regarding which algorithm was best. The test-retest variability was small (mean +/- 95% confidence interval = 8 +/- 3 percentage units), and no correlation was noted between identification score and individual vibratory thresholds. One transposing algorithm and two modulating algorithms led to significantly better results than did the unprocessed signals (p < 0.05). Thus, the two principles of transposing and modulating were appropriate, whereas filtering was unsuccessful. In future work, the two transposing algorithms and the modulating algorithm will be used in tests with a portable vibrator for people with dual sensory impairment (hearing and vision). PMID:20157859

  7. 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.

  8. 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

  9. 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.

  10. 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

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.,…

  16. 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.

  17. 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.

  18. 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

  19. 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.

  20. 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.

  1. Establishing the diffuse correlation spectroscopy signal relationship with blood flow.

    PubMed

    Boas, David A; Sakadžić, Sava; Selb, Juliette; Farzam, Parisa; Franceschini, Maria Angela; Carp, Stefan A

    2016-07-01

    Diffuse correlation spectroscopy (DCS) measurements of blood flow rely on the sensitivity of the temporal autocorrelation function of diffusively scattered light to red blood cell (RBC) mean square displacement (MSD). For RBCs flowing with convective velocity [Formula: see text], the autocorrelation is expected to decay exponentially with [Formula: see text], where [Formula: see text] is the delay time. RBCs also experience shear-induced diffusion with a diffusion coefficient [Formula: see text] and an MSD of [Formula: see text]. Surprisingly, experimental data primarily reflect diffusive behavior. To provide quantitative estimates of the relative contributions of convective and diffusive movements, we performed Monte Carlo simulations of light scattering through tissue of varying vessel densities. We assumed laminar vessel flow profiles and accounted for shear-induced diffusion effects. In agreement with experimental data, we found that diffusive motion dominates the correlation decay for typical DCS measurement parameters. Furthermore, our model offers a quantitative relationship between the RBC diffusion coefficient and absolute tissue blood flow. We thus offer, for the first time, theoretical support for the empirically accepted ability of the DCS blood flow index ([Formula: see text]) to quantify tissue perfusion. We find [Formula: see text] to be linearly proportional to blood flow, but with a proportionality modulated by the hemoglobin concentration and the average blood vessel diameter. PMID:27335889

  2. [Dynamic Pulse Signal Processing and Analyzing in Mobile System].

    PubMed

    Chou, Yongxin; Zhang, Aihua; Ou, Jiqing; Qi, Yusheng

    2015-09-01

    In order to derive dynamic pulse rate variability (DPRV) signal from dynamic pulse signal in real time, a method for extracting DPRV signal was proposed and a portable mobile monitoring system was designed. The system consists of a front end for collecting and wireless sending pulse signal and a mobile terminal. The proposed method is employed to extract DPRV from dynamic pulse signal in mobile terminal, and the DPRV signal is analyzed both in the time domain and the frequency domain and also with non-linear method in real time. The results show that the proposed method can accurately derive DPRV signal in real time, the system can be used for processing and analyzing DPRV signal in real time. PMID:26904868

  3. Signal processing using artificial neural network for BOTDA sensor system.

    PubMed

    Azad, Abul Kalam; Wang, Liang; Guo, Nan; Tam, Hwa-Yaw; Lu, Chao

    2016-03-21

    We experimentally demonstrate the use of artificial neural network (ANN) to process sensing signals obtained from Brillouin optical time domain analyzer (BOTDA). The distributed temperature information is extracted directly from the local Brillouin gain spectra (BGSs) along the fiber under test without the process of determination of Brillouin frequency shift (BFS) and hence conversion from BFS to temperature. Unlike our previous work for short sensing distance where ANN is trained by measured BGSs, here we employ ideal BGSs with different linewidths to train the ANN in order to take the linewidth variation due to different conditions from the training and testing phases into account, making it feasible for long distance sensing. Moreover, the performance of ANN is compared with other two techniques, Lorentzian curve fitting and cross-correlation method, and our results show that ANN has higher accuracy and larger tolerance to measurement error, especially at large frequency scanning step. We also show that the temperature extraction from BOTDA measurements employing ANN is significantly faster than the other two approaches. Hence ANN can be an excellent alternative tool to process BGSs measured by BOTDA and obtain temperature distribution along the fiber, especially when large frequency scanning step is adopted to significantly reduce the measurement time but without sacrifice of sensing accuracy. PMID:27136863

  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 corr

  5. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-08-01

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

  7. A comb filter based signal processing method to effectively reduce motion artifacts from photoplethysmographic signals.

    PubMed

    Peng, Fulai; Liu, Hongyun; Wang, Weidong

    2015-10-01

    A photoplethysmographic (PPG) signal can provide very useful information about a subject's cardiovascular status. Motion artifacts (MAs), which usually deteriorate the waveform of a PPG signal, severely obstruct its applications in the clinical diagnosis and healthcare area. To reduce the MAs from a PPG signal, in the present study we present a comb filter based signal processing method. Firstly, wavelet de-noising was implemented to preliminarily suppress a part of the MAs. Then, the PPG signal in the time domain was transformed into the frequency domain by a fast Fourier transform (FFT). Thirdly, the PPG signal period was estimated from the frequency domain by tracking the fundamental frequency peak of the PPG signal. Lastly, the MAs were removed by the comb filter which was designed based on the obtained PPG signal period. Experiments with synthetic and real-world datasets were implemented to validate the performance of the method. Results show that the proposed method can effectively restore the PPG signals from the MA corrupted signals. Also, the accuracy of blood oxygen saturation (SpO2), calculated from red and infrared PPG signals, was significantly improved after the MA reduction by the proposed method. Our study demonstrates that the comb filter can effectively reduce the MAs from a PPG signal provided that the PPG signal period is obtained. PMID:26334000

  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. 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.

  10. Electrophysiological Correlates of Stimulus Equivalence Processes

    PubMed Central

    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., wrist, corn). For pairs of both types, event-related cortical potentials were recorded during and immediately after the presentation of the second word. The obtained waveforms differentiated these two types of pairs. For the unrelated pairs, the waveforms were significantly more negative about 400 ms after the second word was presented, thus replicating the “N400” phenomenon of the cognitive neuroscience literature. In addition, there was a strong positive-tending wave form difference post-stimulus presentation (peaked at about 500 ms) that also differentiated the unrelated from related stimulus pairs. In Experiment 2, the procedures were extended to study arbitrary stimulus–stimulus relations established via matching-to-sample training. Participants were experimentally naïve adults. Sample stimuli (Set A) were trigrams, and comparison stimuli (Sets B, C, D, E, and F) were nonrepresentative forms. Behavioral tests evaluated potentially emergent equivalence relations (i.e., BD, DF, CE, etc.). All participants exhibited classes consistent with the arbitrary matching training. They were also exposed also to an event-related potential procedure like that used in Experiment 1. Some received the ERP procedure before equivalence tests and some after. Only those participants who received ERP procedures after equivalence tests exhibited robust N400 differentiation initially. The positivity observed in Experiment 1 was absent for all participants. These results support speculations that equivalence tests may provide contextual support for the formation of equivalence classes including those that emerge gradually during testing