Science.gov

Sample records for signal processing correlation

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

    DOEpatents

    Erskine, David J. (Oakland, CA)

    1999-01-01

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

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

    DOEpatents

    Erskine, D.J.

    1999-08-24

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

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

    NASA Astrophysics Data System (ADS)

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

    2000-05-01

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

  4. Thermographic signal processing through correlation operators in pulsed thermography

    NASA Astrophysics Data System (ADS)

    Klein, Matthieu T.; Ibarra-Castanedo, Clemente; Bendada, Abdelhakim; Maldague, Xavier P.

    2008-03-01

    In non-destructive testing by Infrared Thermography it is usually needed to locate defects and region of interests suspected to contain defects. The defects cannot always be observed directly from one single IR image taken at a single given time t. Thus, in the case of pulsed thermography, direct course techniques as the Fourier transform process the information of many images recorded for a given duration into one resulting image. Another way to compile the temporal information of a sequence of images into a single one is to compute a correlation image. This paper details an approach to use a statistical correlation operator to help improving defect detection in pulsed infrared thermography.

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

    PubMed Central

    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

  6. 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.

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

    NASA Astrophysics Data System (ADS)

    Wirnitzer, B.

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

  8. 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.

  9. 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

  10. 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.

  11. Optical signal processing

    NASA Astrophysics Data System (ADS)

    Dorey, J.

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

  12. 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

  13. OPTIMAL CORRELATION ESTIMATORS FOR QUANTIZED SIGNALS

    SciTech Connect

    Johnson, M. D.; Chou, H. H.; Gwinn, C. R. E-mail: cgwinn@physics.ucsb.edu

    2013-03-10

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

  14. 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.

  15. Digital signal processing

    NASA Astrophysics Data System (ADS)

    Steiglitz, Ken; Liu, Bede

    1992-05-01

    A wide variety of problems in digital signal processing were studied, with emphasis on the scalability of architectures for large array processors, timing and reliability limits in large arrays, delay performance of statistical multiplexers, robust signal processing, and digital image coding and processing. Results in the study of array processors include the development of a particular architecture that scales very well for iterative computations on a regular lattice, and a testing method particularly suited to lattice-gas computations. Related work describes design methods for redundant arrays, and arrays that incorporate error detection and correction. In the study of the delay performance of statistical multiplexers, a method is given for computation of the queue-length probability distribution function in the presence of voice traffic. The work in robust signal processing studies the effect of incomplete information on the performance of matched filters. An approach is presented for the compression of color images with limited palette size that does not require color quantization of the decoded image. For comparable quality and bit rates, the proposed technique significantly reduces the decoder computational complexity. Finally, different approaches are compared for block motion compensation coding of interlaced sequences. It is shown that proper use of that redundancy can significantly improve the coding efficiency.

  16. [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.

  17. Accurate estimator of correlations between asynchronous signals

    NASA Astrophysics Data System (ADS)

    Tóth, Bence; Kertész, János

    2009-04-01

    The estimation of the correlation between time series is often hampered by the asynchronicity of the signals. Cumulating data within a time window suppresses this source of noise but weakens the statistics. We present a method to estimate correlations without applying long time windows. We decompose the correlations of data cumulated over a long window using decay of lagged correlations as calculated from short window data. This increases the accuracy of the estimated correlation significantly and decreases the necessary effort of calculations both in real and computer experiments.

  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-signalling correlations

    E-print Network

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

    2006-06-23

    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-signalling 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), on the other hand that Eve can distribute any correlation compatible with the no-signalling 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. High-Resolution Signal Processing

    E-print Network

    Nehorai, Arye

    signal processing is indeed recognized in such fields as astronomy, radar, sonar, seismology of the cortex. Evoked responses are used to study sensory and cognitive processing in the brain [51], and 393

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

    PubMed Central

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

    2015-01-01

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

  2. Nonlinear transfer of signal and noise correlations in cortical networks.

    PubMed

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

    2015-05-27

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

  3. 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

  4. Signal processing for semiconductor detectors

    SciTech Connect

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

    1982-02-01

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

  5. Psychoacoustic processing of test signals

    NASA Astrophysics Data System (ADS)

    Kadlec, Frantisek

    2003-10-01

    For the quantitative evaluation of electroacoustic system properties and for psychoacoustic testing it is possible to utilize harmonic signals with fixed frequency, sweeping signals, random signals or their combination. This contribution deals with the design of various test signals with emphasis on audible perception. During the digital generation of signals, some additional undesirable frequency components and noise are produced, which are dependent on signal amplitude and sampling frequency. A mathematical analysis describes the origin of this distortion. By proper selection of signal frequency and amplitude it is possible to minimize those undesirable components. An additional step is to minimize the audible perception of this signal distortion by the application of additional noise (dither). For signals intended for listening tests a dither with triangular or Gaussian probability density function was found to be most effective. Signals modified this way may be further improved by the application of noise shaping, which transposes those undesirable products into frequency regions where they are perceived less, according to psychoacoustic principles. The efficiency of individual processing steps was confirmed both by measurements and by listening tests. [Work supported by the Czech Science Foundation.

  6. 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.

  7. Signal processor for processing ultrasonic receiver signals

    DOEpatents

    Fasching, George E. (Morgantown, WV)

    1980-01-01

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

  8. 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.

  9. IEEE WIRELESS COMMUNICATIONS LETTERS 1 Binary Signaling of Correlated Sources

    E-print Network

    Wehlau, David

    source-matched modulation scheme for the reliable transmission of binary correlated sources overIEEE WIRELESS COMMUNICATIONS LETTERS 1 Binary Signaling of Correlated Sources Over Orthogonal allocations for minimizing the joint symbol-error rate for binary signaling of two correlated sources over

  10. 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

  11. 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.

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

    E-print Network

    Erck, Eric Stephenson

    2004-11-15

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

  13. Nuclear sensor signal processing circuit

    DOEpatents

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

    2007-02-20

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

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

    SciTech Connect

    Seevinck, M. P.

    2011-03-28

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

  15. Seismic signal processing on heterogeneous supercomputers

    NASA Astrophysics Data System (ADS)

    Gokhberg, Alexey; Ermert, Laura; Fichtner, Andreas

    2015-04-01

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

  16. Variation in signal–preference genetic correlations in Enchenopa treehoppers (Hemiptera: Membracidae)

    PubMed Central

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

    2015-01-01

    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. 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.

  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. Process Dissociation and Mixture Signal Detection Theory

    ERIC Educational Resources Information Center

    DeCarlo, Lawrence T.

    2008-01-01

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

  20. Computational Aspects in Statistical Signal Processing

    E-print Network

    Kundu, Debasis

    , such as geophysics, acoustics, texture classifi- cations, voice recognition and meteorology among many others. During effectively in solving various important signal processing problems. Various problem specific algorithms have

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

    NASA Astrophysics Data System (ADS)

    Khaleghi, Salman

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

  2. Processing Aftershock Sequences Using Waveform Correlation

    NASA Astrophysics Data System (ADS)

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

    2008-12-01

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

  3. 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. 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.

  5. Multiresolution Signal Processing for Meshes Igor Guskov

    E-print Network

    Desbrun, Mathieu

    Multiresolution Signal Processing for Meshes Igor Guskov Princeton University Wim Sweldens Bell connectivity triangle meshes. This is accomplished through the design of a non-uniform relax- ation procedure applications. Our goal is the construction of signal processing style analyses and algorithms for triangle

  6. Improved television signal processing system

    NASA Technical Reports Server (NTRS)

    Wong, R. Y.

    1967-01-01

    Digital system processes spacecraft television pictures by converting images sensed on a photostorage vidicon to pulses which can be transmitted by telemetry. This system can be applied in the processing of medical X ray photographs and in electron microscopy.

  7. 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.

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

    ERIC Educational Resources Information Center

    Davies, H.; McNeill, D. J.

    1986-01-01

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

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

    NASA Technical Reports Server (NTRS)

    Vonglahn, U.; Krejsa, E. A.

    1982-01-01

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

  10. Periodically correlated processes and their stationary dilations

    NASA Technical Reports Server (NTRS)

    Miamee, A. G.

    1990-01-01

    An explicit form for a stationary dilation for periodically correlated random processes is obtained. This is then used to give spectral conditions for a periodically correlated process to be non-deterministic, purely deterministic, minimal, and to have a positive angle between its past and future.

  11. Periodically correlated processes and their stationary dilations

    NASA Technical Reports Server (NTRS)

    Miamee, A. G.

    1988-01-01

    An explicit form for a stationary dilation for periodically correlated random processes is obtained. This is then used to give spectral conditions for a periodically correlated process to be non-deterministic, purely deterministic, minimal, and to have a positive angle between its past and future.

  12. 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

  13. Using acoustic emission signals for monitoring of production processes.

    PubMed

    Tönshoff, H K; Jung, M; Männel, S; Rietz, W

    2000-07-01

    The systems for in-process quality assurance offer the possibility of estimating the workpiece quality during machining. Especially for finishing processes like grinding or turning of hardened steels, it is important to control the process continuously in order to avoid rejects and refinishing. This paper describes the use of on-line monitoring systems with process-integrated measurement of acoustic emission to evaluate hard turning and grinding processes. The correlation between acoustic emission signals and subsurface integrity is determined to analyse the progression of the processes and the workpiece quality. PMID:10950351

  14. Optical signal processing of phased array radar

    NASA Astrophysics Data System (ADS)

    Weverka, Robert T.

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

  15. Using Many-Core Hardware to Correlate Radio Astronomy Signals

    E-print Network

    van Nieuwpoort, Rob V.

    Using Many-Core Hardware to Correlate Radio Astronomy Signals Rob V. van Nieuwpoort nieuwpoort@astron.nl John W. Romein romein@astron.nl ASTRON, Netherlands Institute for Radio Astronomy, Dwingeloo, The Netherlands ABSTRACT A recent development in radio astronomy is to replace traditional dishes with many small

  16. 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.}

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

    PubMed Central

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

    2009-01-01

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

  18. Infinite Correlation in Measured Quantum Processes

    E-print Network

    Karoline Wiesner; James P. Crutchfield

    2006-11-14

    We show that quantum dynamical systems can exhibit infinite correlations in their behavior when repeatedly measured. We model quantum processes using quantum finite-state generators and take the stochastic language they generate as a representation of their behavior. We analyze two spin-1 quantum systems that differ only in how they are observed. The corresponding language generated has short-range correlation in one case and infinite correlation in the other.

  19. Degenerate intracavity parametric processes with injected signal

    NASA Astrophysics Data System (ADS)

    Olsen, M. K.; Dechoum, K.; Plimak, L. I.

    2003-07-01

    A common way of increasing the efficiency of optical frequency conversion processes is by the injection of a coherent signal at the desired frequency. We study the efficiency of this method and its effect on the quantum statistics of the fields by performing theoretical analyses of the intracavity parametric ?(2) processes of second harmonic generation and degenerate optical parametric oscillation with injected signal fields. We find that the threshold behaviour of the optical parametric oscillator with an injected signal field gives further insight into the normal threshold behaviour, considered as a limiting case as the signal field goes to zero. An injected signal is also shown to change the critical points of the systems, which define the region where the maximum of noise suppression and other quantum effects may be expected. We also investigate the self-pulsing behaviour of second harmonic generation, showing how an injected signal can affect the oscillations. We show the process of second harmonic generation can be blocked by an injected signal of the appropriate intensity, effectively removing the crystal from the cavity.

  20. Tool Integration for Signal Processing Architectural Exploration

    E-print Network

    Davis, Rhett

    -specific Intellectual Property (IP) cores for system level signal processing algorithms. We present our view the designer to make final decisions in selecting an optimized IP core. We used a GUI- based framework invoked. A solution for mitigating the design process is providing open source IP cores and system-level synthesizers

  1. Automated Architectural Exploration for Signal Processing Algorithms

    E-print Network

    Davis, Rhett

    Property (IP) cores for system level signal processing algorithms. We present our view of a framework generates the dedicated IP cores and estimates the performance such as area, critical path delay. A solution for mitigating the design process is providing open source IP cores and system-level synthesizers

  2. Time domain cyclostationarity signal-processing tools

    NASA Astrophysics Data System (ADS)

    Léonard, François

    2015-10-01

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

  3. 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.

  4. A unified approach to sparse signal processing

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  5. Optical Signal Processing using Nonlinear Periodic Lukasz Brzozowski

    E-print Network

    Pelinovsky, Dmitry

    Optical Signal Processing using Nonlinear Periodic Structures by Lukasz Brzozowski A thesis;Abstract Optical Signal Processing using Nonlinear Periodic Structures Lukasz Brzozowski Doctor advances the field of optical signal processing using nonlinear periodic struc- tures. A novel approach

  6. State-Signal Correlations of a Continuously Monitored Superconducting Qubit

    E-print Network

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

    2015-01-01

    A superconducting transmon qubit undergoing driven unitary evolution is continuously monitored to observe the time evolution of its quantum state. If projective measurements are used to herald a definite initial state, the average of many measurement records displays damped Rabi oscillations. If instead the average of many measurements is conditioned on the outcome of a final post-selection measurement, the result exhibits similar damped Rabi oscillations with the exception that the damping of the signal occurs backwards in time. Such pre- and post-selections are specific examples of qubit state and signal temporal correlations and stimulate a more general discussion of the temporal correlations in stochastic quantum trajectories associated with continuous quantum measurements.

  7. 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

  8. 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

  9. 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.

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

    E-print Network

    Xin, Jack

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

  11. Exascale Signal Processing for Millimeter-Wavelength Interferometers

    NASA Astrophysics Data System (ADS)

    Hawkins, David

    2014-04-01

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

  12. Correlated activity supports efficient cortical processing

    PubMed Central

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

    2015-01-01

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

  13. Computer Aided Teaching of Digital Signal Processing.

    ERIC Educational Resources Information Center

    Castro, Ian P.

    1990-01-01

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

  14. 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.

  15. 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.

  16. Signal and Image Processing with Sinlets

    E-print Network

    Alexander Y. Davydov

    2012-09-17

    This paper presents a new family of localized orthonormal bases - sinlets - which are well suited for both signal and image processing and analysis. One-dimensional sinlets are related to specific solutions of the time-dependent harmonic oscillator equation. By construction, each sinlet is infinitely differentiable and has a well-defined and smooth instantaneous frequency known in analytical form. For square-integrable transient signals with infinite support, one-dimensional sinlet basis provides an advantageous alternative to the Fourier transform by rendering accurate signal representation via a countable set of real-valued coefficients. The properties of sinlets make them suitable for analyzing many real-world signals whose frequency content changes with time including radar and sonar waveforms, music, speech, biological echolocation sounds, biomedical signals, seismic acoustic waves, and signals employed in wireless communication systems. One-dimensional sinlet bases can be used to construct two- and higher-dimensional bases with variety of potential applications including image analysis and representation.

  17. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  19. 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.

  20. IEEE SIGNAL PROCESSING MAGAZINE8 NOVEMBER 2004 leadership reflections

    E-print Network

    Nehorai, Arye

    processing to improve data-transmission perfor- mance. Wow, bummer, I thought-- this signal processingIEEE SIGNAL PROCESSING MAGAZINE8 NOVEMBER 2004 leadership reflections hat? Provide leadership re of my career, signal processing was declared dead, especially for anyone who wanted to use signal

  1. Suprathreshold stochastic resonance in neural processing tuned by correlation

    NASA Astrophysics Data System (ADS)

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

    2011-07-01

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

  2. Surveillance of industrial processes with correlated parameters

    DOEpatents

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

    1996-01-01

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

  3. 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.

  4. 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.

  5. 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

  6. 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 ?m) 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.

  7. Nonlinear Cochlear Signal Processing and Phoneme Perception

    NASA Astrophysics Data System (ADS)

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

    2009-02-01

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

  8. 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.

  9. Determinantal correlations for classical projection processes

    NASA Astrophysics Data System (ADS)

    Forrester, Peter J.; Nagao, Taro

    2011-08-01

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

  10. 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.

  11. Neural Networks for Signal Processing and Control

    NASA Astrophysics Data System (ADS)

    Hesselroth, Ted Daniel

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

  12. 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.

  13. 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.

  14. 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.

  15. Signal Processing Systems With Dimensional Transducers

    NASA Astrophysics Data System (ADS)

    Bartelt, H. O.; Lohmann, A. W.

    1984-02-01

    A system with dimensional transducers typically consists of three parts: a dimensional transducer, a processor, and again a dimensional transducer. The first transducer may, for example, convert a two-dimensional (2-D) picture into a one-dimensional (1-D) temporal signal. That signal is processed by a digital computer. The computer output is again a 1-D temporal signal, which is converted back into a picture by the second dimensional transducer. The job of the first transducer is to adapt the format of the original signal to the capabilities of the processor. The second transducer converts the processor output into a format suitable for the user or receiver. Systems with dimensional transducers usually consist of more than one type of hardware: optics, TV electronics, digital electronics, and movie technology are all examples. We discuss the virtues of such systems and review briefly some historical examples that are not well known. Finally we present some new experiments with optical processors characterized by input and output dimensional transducers.

  16. 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.

  17. Source and processing effects on noise correlations

    NASA Astrophysics Data System (ADS)

    Fichtner, Andreas

    2014-05-01

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

  18. 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.

  19. Radar transponder apparatus and signal processing technique

    DOEpatents

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

    1996-01-01

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

  20. 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.

  1. Nonlinear real-time optical signal processing

    SciTech Connect

    Sawchuk, A.A.; Strand, T.C.; Tanguay, J.A.R.

    1982-06-01

    The results of a one year research program in nonlinear real-time optical signal processing are described. The goal of the program is to extend fast parallel nonlinear operations to optical processing systems with large time-bandwidth and space-bandwidth products. The research has concentrated on optical mode (vgm) liquid crystal real-time spatial light modulators. Parallel and twisted nematic liquid crystal light valve (lclv) devices have been used as a nonlinear element in a feedback arrangement in the sequential logic systems. A computer generated hologram fabricated on an e-beam system serves as a beam steering interconnection element. A completely optical oscillator and frequency divider have been experimentally demonstrated. Research has continued on variable-grating mode (VGM) liquid crystal devices that perform local spatial frequency modulation as a function of the incident intensity. These devices can be used for nonlinear processing by selection abd recombination of these spatial frequency conponents. Theses devices have many interesting physical effects with useful applications in both analog and numerical optical signal processing. Preliminary theoretical modeling work to explain these effects is given, and an improved implementation of the intensity level slice function with VGM devices has been demonstrated.

  2. Signal Processing in Photonic Crystals and Nanostructures

    NASA Astrophysics Data System (ADS)

    Wabnitz, S.

    Optical devices employing photonic crystals and novel nanostructure materials may exhibit useful properties for applications to all-optical signal processing. In this work we analyze as a first example four-wave mixing of polarized beams in photonic crystal fibers. We show that by properly tuning the pump wavelength and the linear dispersion properties of the fiber one may obtain broadband parametric amplification and frequency conversion. Next we consider the in-line periodic amplification of short optical pulses by means of quantum-dot semiconductor optical amplifiers. We show by numerical simulations that pattern-free amplification of a 40 Gbit/s soliton signal at 1300 nm is possible without any inter-symbol interference or nonlinear pulse distortion caused by the fast gain dynamics.

  3. Unique portable signal acquisition/processing station

    SciTech Connect

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

    1983-05-16

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

  4. Efficient audio signal processing for embedded systems

    NASA Astrophysics Data System (ADS)

    Chiu, Leung Kin

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

  5. 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.

  6. 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.

  7. 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.

  8. Electromagnetics-Related Aspects of Signaling and Signal Processing for UWB Short Range Radios*

    E-print Network

    Southern California, University of

    Electromagnetics-Related Aspects of Signaling and Signal Processing for UWB Short Range Radios* A numerical electromagnetic (EM) analysis, thereby enabling predictions of the channel performance under in electromagnetic-related aspects of UWB signaling schemas and signal processing. First, pulse shaping is developed

  9. The effects of quantization on signal processing

    NASA Technical Reports Server (NTRS)

    Montgomery, H. E.; Schell, E.

    1978-01-01

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

  10. 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.

  11. Image and Signal Processing LISP Environment (ISLE)

    SciTech Connect

    Azevedo, S.G.; Fitch, J.P.; Johnson, R.R.; Lager, D.L.; Searfus, R.M.

    1987-10-02

    We have developed a multidimensional signal processing software system called the Image and Signal LISP Environment (ISLE). It is a hybrid software system, in that it consists of a LISP interpreter (used as the command processor) combined with FORTRAN, C, or LISP functions (used as the processing and display routines). Learning the syntax for ISLE is relatively simple and has the additional benefit of introducing a subset of commands from the general-purpose programming language, Common LISP. Because Common LISP is a well-documented and complete language, users do not need to depend exclusively on system developers for a description of the features of the command language, nor do the developers need to generate a command parser that exhaustively satisfies all the user requirements. Perhaps the major reason for selecting the LISP environment is that user-written code can be added to the environment through a ''foreign function'' interface without recompiling the entire system. The ability to perform fast prototyping of new algorithms is an important feature of this environment. As currently implemented, ISLE requires a Sun color or monochrome workstation and a license to run Franz Extended Common LISP. 16 refs., 4 figs.

  12. RF signal analysis using combined acousto-optical correlator and spectrum analyzer

    NASA Astrophysics Data System (ADS)

    Gurevich, Boris S.; Andreyev, Sergei V.; Belyaev, Andrey V.; Akimjanova, Ch.; Sagymbaeva, K. A.

    2004-06-01

    Acousto-optic correlators AOC are commonly used not only for the signal correlation function obtaining but also for providing the wideband RF signal spectrum analysis. The AOC basic configuration is also known as a scheme of acousto-optic spectrum analyzer (AOSA) with time integration. The RF signal spectrum analysis using this device allows to obtain high frequency resolution but requires rather long time. We have proposed to combine the advantages of AOC and common spectrum analyzer based on single Bragg cell (also known as analyzer with space integration) to obtain higher processing productivity which requires both big processing speed and high frequency resolution. It has been shown that if the panoramic spectrum observation is performed using the mode of sequential processing of sub-bands, so the frequency range of about 1...2 GHz can be processed with frequency resolving power of 10...100 Hz. The experimental realization of AOSA and AOC application for the purpose of radio air panoramic observation have been presented. The acousto-optic units have been created using Bragg cells based on tellurium dioxide single crystals with piezoelectric transducers based on the plates of lithium niobate. Different operation modes have been considered from the point of view of maximum information productivity.

  13. 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.

  14. Multidimensional signal processing in spatial-spectral holographic media

    NASA Astrophysics Data System (ADS)

    Schlottau, Friso

    In this thesis I present the analyses, simulations and demonstrations of a number of novel optical signal processing systems, which are designed to explore the large bandwidths (10's--100's of GHz), time-bandwidth products (105 and greater) and massive spatial parallelism that spatial-spectral holography and photon-echo (PE) processing can provide. The systems investigated include RF spectrum analyzers, a time-integrating correlator, an RF-array multibeam imager, and a high-bandwidth LIDAR range-Doppler processor, all of which were built around a Tm3+:YAG crystal as the spatial-spectral holographic (SSH) medium. The time-integrating correlator (TIC) is the first SSH experiment that illustrates spatial coherence across parallel channels of PE processors. In this experiment, ˜150 SSH gratings with linearly increasing time-delays are recorded in the SSH, which, when read out, result in the scanned output required for the TIC. In the high-bandwidth RF spectrum analyzer; the spectral components from an RF signal are modulated onto an optical carrier and burned into the spectrally selective absorption band of the SSH. This altered absorption profile is then recovered by a frequency-swept source and a high dynamic range, low bandwidth detector. This is the first experimental SSH system to process RF signals with bandwidths in excess of 10 GHz, and was enabled by a novel linearized readout technique. In the LIDAR experiment, the Doppler and range information of targets is encoded in the position and spectral period of sinusoidal SSH gratings. These gratings (spanning ˜16 GHz) are snapped out with the linearized readout technique and post processed to recover the Doppler and range of the targets. The required experimental infrastructure and the spectrally-linearized chirped readout laser are discussed in detail.

  15. 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.

  16. Optimization of Signal Processing Software for Control System Implementation

    E-print Network

    Bhattacharyya, Shuvra S.

    . Bhattacharyya and William S. Levine Abstract-- Signal processing plays a fundamental role in the design for design and optimization of signal processing software are important in achieving efficient controller implementations. Motivated by these relationships, this paper reviews tech- niques for modeling signal processing

  17. A Signal Processing Approach To Fair Surface Design Charles Robertson

    E-print Network

    Kazhdan, Michael

    A Signal Processing Approach To Fair Surface Design Slide 1 Charles Robertson A Signal Processing: Charles Robertson A Signal Processing Approach To Fair Surface Design Slide 2 Charles Robertson Overview Slide 3 Charles Robertson Introduction Motivation Fairing surfaces Medical data Goals Quick, linear

  18. Signal Processing Institute Swiss Federal Institute of Technology, Lausanne

    E-print Network

    Histace, Aymeric

    1 Signal Processing Institute Swiss Federal Institute of Technology, Lausanne 1 Reconnaissance desProf. Jean--Philippe THIRANPhilippe THIRAN Cours 3: Contours actifs Signal Processing Institute Swiss Federal de ces régions.de ces régions. Contours actifs #12;2 Signal Processing Institute Swiss Federal

  19. Correlation functions in conformal invariant stochastic processes

    NASA Astrophysics Data System (ADS)

    Alcaraz, Francisco C.; Rittenberg, Vladimir

    2015-11-01

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

  20. Ultrasonic signal processing and tissue characterization

    NASA Astrophysics Data System (ADS)

    Mu, Zhiping

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

  1. 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

  2. Correlation analysis of electromyogram signals for multiuser myoelectric interfaces.

    PubMed

    Khushaba, Rami N

    2014-07-01

    An inability to adapt myoelectric interfaces to a novel user's unique style of hand motion, or even to adapt to the motion style of an opposite limb upon which the interface is trained, are important factors inhibiting the practical application of myoelectric interfaces. This is mainly attributed to the individual differences in the exhibited electromyogram (EMG) signals generated by the muscles of different limbs. We propose in this paper a multiuser myoelectric interface which easily adapts to novel users and maintains good movement recognition performance. The main contribution is a framework for implementing style-independent feature transformation by using canonical correlation analysis (CCA) in which different users' data is projected onto a unified-style space. The proposed idea is summarized into three steps: 1) train a myoelectric pattern classifier on the set of style-independent features extracted from multiple users using the proposed CCA-based mapping; 2) create a new set of features describing the movements of a novel user during a quick calibration session; and 3) project the novel user's features onto a lower dimensional unified-style space with features maximally correlated with training data and classify accordingly. The proposed method has been validated on a set of eight intact-limbed subjects, left-and-right handed, performing ten classes of bilateral synchronous fingers movements with four electrodes on each forearm. The method was able to overcome individual differences through the style-independent framework with accuracies of > 83% across multiple users. Testing was also performed on a set of ten intact-limbed and six below-elbow amputee subjects as they performed finger and thumb movements. The proposed framework allowed us to train the classifier on a normal subject's data while subsequently testing it on an amputee's data after calibration with a performance of > 82% on average across all amputees. PMID:24760933

  3. 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.

  4. 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.

  5. Quantum optical signal processing in diamond

    E-print Network

    Fisher, Kent A G; Maclean, Jean-Phillipe W; Bustard, Philip J; Resch, Kevin J; Sussman, Benjamin J

    2015-01-01

    Controlling the properties of single photons is essential for a wide array of emerging optical quantum technologies spanning quantum sensing, quantum computing, and quantum communications. Essential components for these technologies include single photon sources, quantum memories, waveguides, and detectors. The ideal spectral operating parameters (wavelength and bandwidth) of these components are rarely similar; thus, frequency conversion and spectral control are key enabling steps for component hybridization. Here we perform signal processing of single photons by coherently manipulating their spectra via a modified quantum memory. We store 723.5 nm photons, with 4.1 nm bandwidth, in a room-temperature diamond crystal; upon retrieval we demonstrate centre frequency tunability over 4.2 times the input bandwidth, and bandwidth modulation between 0.5 to 1.9 times the input bandwidth. Our results demonstrate the potential for diamond, and Raman memories in general, to be an integrated platform for photon storage ...

  6. Quantum optical signal processing in diamond

    E-print Network

    Kent A. G. Fisher; Duncan. G. England; Jean-Philippe W. MacLean; Philip J. Bustard; Kevin J. Resch; Benjamin J. Sussman

    2015-09-18

    Controlling the properties of single photons is essential for a wide array of emerging optical quantum technologies spanning quantum sensing, quantum computing, and quantum communications. Essential components for these technologies include single photon sources, quantum memories, waveguides, and detectors. The ideal spectral operating parameters (wavelength and bandwidth) of these components are rarely similar; thus, frequency conversion and spectral control are key enabling steps for component hybridization. Here we perform signal processing of single photons by coherently manipulating their spectra via a modified quantum memory. We store 723.5 nm photons, with 4.1 nm bandwidth, in a room-temperature diamond crystal; upon retrieval we demonstrate centre frequency tunability over 4.2 times the input bandwidth, and bandwidth modulation between 0.5 to 1.9 times the input bandwidth. Our results demonstrate the potential for diamond, and Raman memories in general, to be an integrated platform for photon storage and spectral conversion.

  7. Meteor radar signal processing and error analysis

    NASA Astrophysics Data System (ADS)

    Kang, Chunmei

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

  8. 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.

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

    PubMed

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

    2014-07-01

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

  10. Integrated signal processing, data association, and tracking

    NASA Astrophysics Data System (ADS)

    Isaac, Atef

    This thesis discusses four techniques to successfully track multiple closely-spaced and unresolved targets using monopulse radar measurements. It explores statistical estimation techniques based on the maximum likelihood criterion and Gibbs sampling, and addresses concerns about the accuracy of the measurements delivered thereby. In particular, the Gibbs approach can deliver joint measurements (and the associated covariances) from both targets, and it is therefore natural to consider a joint single filter. The ideas are compared; and amongst the various strategies discussed, a particle filter that approximates the targets' states' conditional pdf, bypassing the measurement extraction stage, and operating directly on the monopulse sum/difference data, i.e., without measurement extraction proves to be best. With successful tracking of those targets being achieved with the aid of nonlinear particle filters, the problem of detecting a target spawn will be tackled. Particle filters will be employed as nonlinear tracking filters to approximate the posterior probability densities of the targets' states under different hypotheses of the number of targets, which in turn can be used to evaluate the likelihood ratio between two different hypotheses at subsequent time steps. Ultimately, a quickest detection procedure based on sequential processing of the likelihood ratios will be used to decide on a change in the underlying target model as an indication of a newly spawning target. Radar signal processing, data association and target tracking are handled simultaneously.

  11. Isospin equilibration in multi-fragmentation processes and dynamical correlations

    E-print Network

    M. Papa; G. Giuliani

    2009-05-27

    The asymptotic time derivative of the total dipole signal is proposed as an useful observable to study Isospin equilibration phenomenon in multi-fragmentation processes. The study proceeds through the investigation of the $^{40}Cl+^{28}Si$ system at 40 MeV/nucleon by means of semiclassical microscopic many-body calculations based on the CoMD-II model. In particular, the study has been developed to describe charge/mass equilibration processes involving the gas and liquid "phases" of the total system formed during the early stage of a collision. Through the investigation of dynamical many-body correlations, it is also shown how the proposed observable is rather sensitive to different parameterizations of the isospin dependent interaction.

  12. Pedagogical reforms of digital signal processing education

    NASA Astrophysics Data System (ADS)

    Christensen, Michael

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

  13. Neural correlates of implicit and explicit combinatorial semantic processing

    PubMed Central

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

    2010-01-01

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

  14. Wavelets in signal detection and identification comparative signal processing technology evaluation

    NASA Astrophysics Data System (ADS)

    Raghaven, Raghu

    1994-12-01

    The Wavelet in Signal Detection and Identification: Comparative Signal Processing Technology Evaluation Program has been conducted by Lockheed Missiles and Space Company to develop wavelet based signal detection and classification techniques and compare them to Fourier time-frequency methods. The problem domain is submarine detection and identification using transient passive sonar signals. These nontraditional signals are critical in solving current antisubmarine warfare (ASW) problems which include ultra-quiet nuclear submarines and third world diesel submarines operating on batteries in shallow water.

  15. 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

  16. Spatial acoustic signal processing for immersive communication

    NASA Astrophysics Data System (ADS)

    Atkins, Joshua

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

  17. 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

  18. All GaAs signal processing architecture

    SciTech Connect

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

    1987-09-01

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

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

    E-print Network

    Papanicolaou, George C.

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

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

    SciTech Connect

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

    2003-01-01

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

  1. Abstract--Electroencephalogram signals (EEG), also known as brainwaves, provide rich information about the brain processes,

    E-print Network

    Wilamowski, Bogdan Maciej

    about the brain processes, once that they result from the electrical activity of millions of neurons beneath the skull. By finding correlation between EEG patterns and certain brain processes a new neural network to classify signals. I. INTRODUCTION The mammalian brain, and especially the human

  2. 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.

  3. 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 approach to overcoming the difficulties in large-sensor surveillance, and we illustrate promising performance results with simulated surveillance data. The third topic of this dissertation deals with distributed target detection in SN using Scan Statistics. We introduce a sequential procedure to detect a target with distributed sensors in a two dimensional region. The detection is carried out in a mobile fusion center which successively counts the number of binary decisions reported by local sensors lying inside its moving field of view. This is a two-dimensional scan statistic an emerging tool from the statistics field that has been applied to a variety of anomaly detection problems such as of epidemics or computer intrusion, but that seems to be unfamiliar to the signal processing community. We show that an optimal size of the field of view exists. We compare the sequential two-dimensional scan statistic test and two other tests. We also present results for system level detection. In the last topic we study a Repeated Significance Test (RST) with applications to sequential detection in SN. We introduce a randomly truncated sequential hypothesis test. Using the framework of a RST, we study a sequential test with truncation time based on a random stopping time. Using the Functional Central Limit Theorem (FCLT) for a sequence of statistics, we derive a general result that can be employed in developing a repeated significance test with random sample size. We present effective methods for evaluating accurate approximations for the probability of type I error and the power function. Numerical results are presented to evaluate the accuracy of these approximations. We apply the proposed test to a decentralized sequential detection in sensor networks (SN) with communication constraints. Finally a sequential detection problem with measurements at random times is investigated.

  4. 2004 IEEEWorkshop on Machine Learning for Signal Processing RECURSIVE PRINCIPALCOMPONENTS

    E-print Network

    Slatton, Clint

    2004 IEEEWorkshop on Machine Learning for Signal Processing RECURSIVE PRINCIPALCOMPONENTS ANALYSIS their true values. The performance is compared with traditional methods like Sanger and APEX algorithm

  5. The neural correlates of intentional and incidental self processing.

    PubMed

    Kircher, Tilo T J; Brammer, M; Bullmore, Edward; Simmons, A; Bartels, M; David, Anthony S

    2002-01-01

    The neuroscientific study of the 'Self' is just beginning to emerge. We used functional Magnetic Resonance Imaging (fMRI) to investigate cerebral activation while subjects processed words describing personality traits and physical features, in two experiments with contrasting designs: incidental and intentional. In the first experiment (intentional self processing), subjects were presented with personality trait adjectives and made judgements as to their self descriptiveness (versus non self descriptiveness). In the second experiment (incidental self processing), subjects categorised words according to whether they described physical versus psychological attributes, while unaware that the words had been arranged in blocks according to self descriptiveness. The subjects had previously rated all words for self descriptiveness 6 weeks prior to the scanning session. A reaction time advantage was present in both experiments for self descriptive trait words, suggesting a facilitation effect. Common areas of activation for the two experiments included the left superior parietal lobe, with adjacent regions of the lateral prefrontal cortex also active in both experiments. Differential signal changes were present in the left precuneus for the intentional and the right middle temporal gyrus for the incidental experiment. The results suggest that self processing involves distinct processes and can occur on more than one cognitive level with corresponding functional neuroanatomic correlates in areas previously implicated in the awareness of one's own state. PMID:11792407

  6. Signal processing and display for electrochemical data

    NASA Technical Reports Server (NTRS)

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

    1977-01-01

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

  7. 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.

  8. IEEE TRANSACTIONS ON SIGNAL PROCESSING 1 A Theory for Sampling Signals from

    E-print Network

    Do, Minh N.

    IEEE TRANSACTIONS ON SIGNAL PROCESSING 1 A Theory for Sampling Signals from a Union of Subspaces Yue M. Lu and Minh N. Do Abstract--One of the fundamental assumptions in traditional sampling theorems is that the signals to be sampled come from a single vector space (e.g. bandlimited functions). However, in many cases

  9. Development of an Ontology-Directed Signal Processing Toolbox

    SciTech Connect

    Stephen W. Lang

    2011-05-27

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

  10. Evaluation of laser Doppler flowmetry system with fast signal processing using an autoregressive process model

    NASA Astrophysics Data System (ADS)

    Elter, Peter; Stork, Wilhelm; Mueller-Glaser, Klaus-Dieter; Lutter, Norbert O.

    1999-05-01

    This report describes the evaluation of a noninvasive laser Doppler system comprising a sensor, a digital signal processor (DSP) unit and a visualizing PC for continuous blood flow measurements. The first weighted moment of the power spectrum density of the laser Doppler sensor signal is a linear measure for blood flow. In order to estimate the power spectrum densities in real time, a first order autoregressive process model was developed. Due to this very fast signal processing, the system allows measurements both in microcirculation and of higher blood flows in larger vessels with a signal bandwidth of up to 200 kHz, e.g. in superficial arteries. Since the analytical dependency of blood flow and first spectral moment is only valid for tissue perfusion, Monte Carlo simulations were performed to evaluate this dependency also for higher blood flow velocities in larger vessels. A multilayered, semi- infinite tissue model essentially comprising epidermis, dermis and a blood vessel with a parabolic profile of constant blood flow was used varying different parameter like vessel diameter and skin thickness. Furthermore, model measurements were performed using a Delrine slab with a drilling through which constant flow of whole blood was provided. Both the Monte Carlo simulations and model measurements prove very high linear correlations between the calculated spectral moments and flow velocities.

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

    E-print Network

    Social Signal Processing: Understanding Nonverbal Communication in Social Interactions Alessandro Processing, human-human communication, nonverbal behavior, social interactions. ACM Classification Keywords A in human sciences have shown that nonverbal communication is the main channel through which we express

  12. Stochastic Modeling of Correlation Radiometer Signals Brynmor Davis

    E-print Network

    ) where {·} denotes the Fourier transform. Appropriate interpretation of the spectral functions SP (), SQ, the Fourier transform of the corresponding temporal-correlation function, i.e. SF G() = {E[F(t)G (t - )]}, (2

  13. 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.

  14. Digital signal processing based on inverse scattering transform

    E-print Network

    Turitsyn, Sergei K.

    codes: (060.2330) Fiber optics communications; (060.1660) Coherent communications; (070.4340) Nonlinear of advanced modulation formats [1] and digital signal processing (DSP) for coher- ent communications (see, e, we illustrate the possibility of a new approach to digital signal processing in coherent optical

  15. A SIMD Vectorizing Compiler for Digital Signal Processing Algorithms

    E-print Network

    Franchetti, Franz

    A SIMD Vectorizing Compiler for Digital Signal Processing Algorithms£ Franz Franchetti Applied enhanced with short vector instructions for digital signal processing (DSP) transforms, such as the fast automatically gen- erated code is competitive with the hand-coded Intel Math Kernel Library. 1. Introduction

  16. Digital Signal Processing Department of Electrical and Computer Engineering

    E-print Network

    Saskatchewan, University of

    EE 880.3 Digital Signal Processing Department of Electrical and Computer Engineering Winter 2015, Applications of signal processing in communication systems: -Block transmission of data, zero prefix, cyclic behaviour is an important part of engineering practice. Each professional engineering association has a Code

  17. ECE Lecture Notes: Matrix Computations for Signal Processing

    E-print Network

    Ma, Wing-Kin "Ken"

    ECE Lecture Notes: Matrix Computations for Signal Processing James P. Reilly c Department, we discuss the fundamentals of eigenvalues and eigenvectors, then go on to covariance matrices in the field of signal processing. 2.1 Eigenvalues and Eigenvectors Suppose we have a matrix A: A = 4 1 1 4 (1

  18. Edinburgh Research Explorer Designer cell signal processing circuits for biotechnology

    E-print Network

    Maizels, Rick

    Edinburgh Research Explorer Designer cell signal processing circuits for biotechnology Citation for published version: Bradley, R & Wang, B 2015, 'Designer cell signal processing circuits for biotechnology' New Biotechnology, vol 32, no. 6, pp. 635-643., 10.1016/j.nbt.2014.12.009 Digital Object Identifier

  19. Signal Processing Group Prof. Dr. Simon Doclo

    E-print Network

    systems (mobile phone, voice-controlled systems) · Research, development and implementation of signal-constrained wireless link (e.g. distributed beamforming, compression) ­ Hearing aids with open fitting and microphone number of small, low-power microphones with wireless communication capability improvement in performance

  20. Noninvasive BCIs: Multiway Signal-Processing

    E-print Network

    Zhang, Liqing

    communication channels for severely handicapped people using their brain signals, recent efforts also have been to handicapped and elderly people. Several potential applications of BCI hold promise for rehabilitation chronic pain, and overcom- ing movement disabilities due to stroke. BCI can expand possibilities

  1. Anti-correlated Networks, Global Signal Regression, and the Effects of Caffeine in Resting-State Functional MRI

    PubMed Central

    Wong, Chi Wah; Olafsson, Valur; Tal, Omer; Liu, Thomas T.

    2012-01-01

    Resting-state functional connectivity magnetic resonance imaging is proving to be an essential tool for the characterization of functional networks in the brain. Two of the major networks that have been identified are the default mode network (DMN) and the task positive network (TPN). Although prior work indicates that these two networks are anti-correlated, the findings are controversial because the anti-correlations are often found only after the application of a pre-processing step, known as global signal regression, that can produce artifactual anti-correlations. In this paper, we show that, for subjects studied in an eyes-closed rest state, caffeine can significantly enhance the detection of anti-correlations between the DMN and TPN without the need for global signal regression. In line with these findings, we find that caffeine also leads to widespread decreases in connectivity and global signal amplitude. Using a recently introduced geometric model of global signal effects, we demonstrate that these decreases are consistent with the removal of an additive global signal confound. In contrast to the effects observed in the eyes-closed rest state, caffeine did not lead to significant changes in global functional connectivity in the eyes-open rest state. PMID:22743194

  2. Neural Correlates of Cognitive Processes LIDA Module

    E-print Network

    Memphis, University of

    orbitofrontal cortex/ventral striatum Keri 2004 Slipnet emotion nodes PAM-Romantic love brainstem right ventral olfaction and emotion nodes PAM-Olfactory reward & punishment signals Mushroom body neurons & dorsal paired medial neurons Keene et al. 2006. Slipnet emotion nodes PAM-Emotions amygdala and orbito-frontal cortex

  3. Quantifying time-varying coordination of multimodal speech signals using correlation map analysis.

    PubMed

    Barbosa, Adriano Vilela; Déchaine, Rose-Marie; Vatikiotis-Bateson, Eric; Yehia, Hani Camille

    2012-03-01

    This paper demonstrates an algorithm for computing the instantaneous correlation coefficient between two signals. The algorithm is the computational engine for analyzing the time-varying coordination between signals, which is called correlation map analysis (CMA). Correlation is computed around any pair of points in the two input signals. Thus, coordination can be assessed across a continuous range of temporal offsets and be detected even when changing over time due to temporal fluctuations. The correlation algorithm has two major features: (i) it is structurally similar to a tunable filter, requiring only one parameter to set its cutoff frequency (and sensitivity), (ii) it can be applied either uni-directionally (computing correlation based only on previous samples) or bi-directionally (computing correlation based on both previous and future samples). Computing instantaneous correlation for a range of time offsets between two signals produces a 2D correlation map, in which correlation is characterized as a function of time and temporal offset. Graphic visualization of the correlation map provides rapid assessment of how correspondence patterns progress through time. The utility of the algorithm and of CMA are exemplified using the spatial and temporal coordination of various audible and visible components associated with linguistic performance. PMID:22423712

  4. Statistical Measures of Planck Scale Signal Correlations in Interferometers

    E-print Network

    Hogan, Craig J

    2015-01-01

    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. 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 ...

  5. INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING Int. J. Adapt. Control Signal Process. 2012; 26:739756

    E-print Network

    Liberzon, Daniel

    INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING Int. J. Adapt. Control Signal with an estimator-based switching logic to select the active controller at every time. For static quantizers, we Process. 2012; 26:739­756 Published online 28 March 2012 in Wiley Online Library (wileyonlinelibrary

  6. W.A. SERDIJN: "A CLASSIFICATION OF ELECTRONIC SIGNAL-PROCESSING FUNCTIONS" 1 A classification of electronic signal-processing

    E-print Network

    Serdijn, Wouter A.

    pair and the current mirror, are presented. Some books additionally give some examples of electronicW.A. SERDIJN: "A CLASSIFICATION OF ELECTRONIC SIGNAL-PROCESSING FUNCTIONS" 1 A classification of electronic signal-processing functions Wouter A. Serdijn Delft University of Technology, Faculty

  7. Simulation of circuits adapted to signal processing

    NASA Astrophysics Data System (ADS)

    Guennouni, Jamal

    1989-02-01

    Simulation tools developed to study integrated circuits to be used in a voice synthesizer/analyzer are described. These tools allow a signal processor to obtain the functional specifications of the circuit needed for a specified application. These tools are also able to validate circuit choices at an algorithmic level and permit temporal analysis of a circuit from the very beginning of the conception phase. The practical applications of these tools are outlined.

  8. 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

  9. 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.

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

    E-print Network

    Xue, Zhenyu; Vlachos, Pavlos P

    2014-01-01

    In particle image velocimetry (PIV) the measurement signal is contained in the recorded intensity of the particle image pattern superimposed on a variety of noise sources. The signal-to-noise-ratio (SNR) strength governs the resulting PIV cross correlation and ultimately the accuracy and uncertainty of the resulting PIV measurement. Hence we posit that correlation SNR metrics calculated from the correlation plane can be used to quantify the quality of the correlation and the resulting uncertainty of an individual measurement. In this paper we present a framework for evaluating the correlation SNR using a set of different metrics, which in turn are used to develop models for uncertainty estimation. The SNR metrics and corresponding models presented herein are expanded to be applicable to both standard and filtered correlations. In addition, the notion of a valid measurement is redefined with respect to the correlation peak width in order to be consistent with uncertainty quantification principles and distinct ...

  11. MODELLING OF COMPLEX SIGNALS USING GAUSSIAN PROCESSES

    E-print Network

    Tobar, Felipe; Turner, Richard E.

    2015-01-01

    processes,” in Neural Networks and Machine Learning, C. M. Bishop, Ed. Springer, 1998, vol. 168 of NATO ASI Series, pp. 133–165. [17] N. Haji Ghassemi and M. Deisenroth, “Analytic long-term forecasting with periodic Gaussian processes,” in Proc. of AIS- TATS...

  12. Signal Processing and Electronic Noise in LZ

    E-print Network

    Khaitan, Dev Ashish

    2015-01-01

    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 $\\pm$ 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 $\\pm$ 0.02 ADCC (46 $\\pm$ 2$\\mu$V). A test facility...

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

    E-print Network

    Stanford University

    Correlation of GPS signal fades due to ionospheric scintillation for aviation applications Jiwon (GPS) signal fading due to strong ionospheric scintillation is a major concern for GPS- guided aviation in equatorial areas during high solar activity. A GPS aviation receiver may lose carrier tracking lock under

  14. FOURIER-BASED METHOD FOR ESTIMATING SIGNAL PERTURBATIONS IN LINEARLY-CORRELATED NOISE

    E-print Network

    Gorodnitsky, Irina

    1 FOURIER-BASED METHOD FOR ESTIMATING SIGNAL PERTURBATIONS IN LINEARLY-CORRELATED NOISE Irina the true signal )(tx from )(* tx . Let's denote the coefficients of the respective Fourier decomposition = = , where indicates the chosen frequency resolution of the Fourier decomposition. The DC-term exist, Eq. (2

  15. TWO-DIMENSIONAL COMPRESSION OF SURFACE ELECTROMYOGRAPHIC SIGNALS USING COLUMN-CORRELATION SORTING AND IMAGE ENCODERS

    E-print Network

    Carvalho, João Luiz

    :7, 1151­70, 2000. [15] Richardson, H.264 and MPEG-4 Video Compression: Video Coding for NextTWO-DIMENSIONAL COMPRESSION OF SURFACE ELECTROMYOGRAPHIC SIGNALS USING COLUMN-CORRELATION SORTING different approaches have been proposed for compression of electromyographic signals, including DPCM [3

  16. Modeling and Generation of Space-Time Correlated Signals for Sensor Network Fields

    E-print Network

    Rossi, Michele

    state, thus saving energy. The spatial correlation can instead be exploited in the deployment phase of as a representative node for other sensors in its neighborhood. [3] seeks to minimize the energy consumption of WSNs signals in order to achieve good performance in terms of energy savings and improved signal reconstruction

  17. Development of signal processing methods for imaging buried pipes

    SciTech Connect

    Michiguchi, Y.; Hiramoto, K.; Nishi, M.; Takahashi, F.; Ohtaka, T.; Okada, M.

    1987-01-01

    A new imaging technique for subsurface radars is described for reconstructing clear images of buried pipes in soil. The method developed has two signal processing stages; preprocessing and aperture synthesis. The preprocessing extracts signals scattered from the pipes by reducing clutter noise. The synthetic-aperture processing analyzes only the scattered signals derived by the first stage and reconstructs high-quality images in a short processing time. The imaging technique developed was successfully applied to the imaging of actual buried metallic pipes. It was experimentally confirmed that the new imaging method was capable of reconstructing clear images in a short time without losing image quality.

  18. SAR image statistics and adaptive signal processing for change detection

    NASA Astrophysics Data System (ADS)

    Vu, Viet T.; Machado, Renato; Pettersson, Mats I.; Dammert, Patrik; Hellsten, Hans

    2015-05-01

    The paper represents investigations on SAR image statistics and adaptive signal processing for change detection. The investigations show that the amplitude distributions of SAR images with possibly detected changes, that is retrieved with a linear subtraction operator, can approximately be represented by the probability density function of the Gaussian or normal distribution. This allows emerging the idea to use the available adaptive signal processing techniques for change detection. The experiments indicate the promising change detection results obtained with an adaptive line enhancer, one of the adaptive signal processing technique. The experiments are conducted on the data collected by CARABAS, a UWB low frequency SAR system.

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

    DOEpatents

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

    2013-11-19

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

  20. 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.

  1. A nonlinear optoelectronic filter for electronic signal processing

    E-print Network

    Ram, Rajeev J.

    the filter (Fig. 1b). This filter differs from conventional microwave-photonic (MWP) filters6A nonlinear optoelectronic filter for electronic signal processing William Loh1,2 , Siva of this microwave-photonic link also enable the manipulation of RF signals beyond what is possible in conventional

  2. SAMPLING THEORY IN SIGNAL AND IMAGE PROCESSING # 2003 SAMPLING PUBLISHING

    E-print Network

    Teschke, Gerd

    SAMPLING THEORY IN SIGNAL AND IMAGE PROCESSING c # 2003 SAMPLING PUBLISHING Vol. 3, No. 2, May 2004, Sobolev embedding op­ erator, Tikhonov regularization 2000 AMS Mathematics Subject Classification --- 65J the observation is a noisy and blurred version of the true signal or image. In order to extract the underlying

  3. Forensically Determining the Order of Signal Processing Operations

    E-print Network

    Liu, K. J. Ray

    Forensically Determining the Order of Signal Processing Operations Matthew C. Stamm #1 , Xiaoyu ChuMaryland, College Park, MD, USA 2 cxygrace@umd . com, 3 kj rl iu@umd . edu Abstract-Currently, many forensic manipulated a signal. In this paper, we propose a new forensic detection framework that can be used determine

  4. Research study: Severe storms Doppler lidar signal processing

    NASA Technical Reports Server (NTRS)

    Lee, R. W.

    1982-01-01

    Four tasks related to the signal processing aspects of the severe-storms Doppler lidar program are discussed. The development of algorithms for windfield retrieval from Doppler lidar measurements are discussed. Signal processor installation on a CV-990 aircraft is discussed.

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

    E-print Network

    Said, Maya Rida, 1976-

    2005-01-01

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

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

    E-print Network

    Advanced Turbulence Measurements and Signal Processing for Hydropower Flow Characterization and flow characterization within full scale conventional hydropower systems, at marine and hydrokinetic. These measurements are critical for turbine inflow characterization, hydrokinetic energy resource assessment, turbine

  7. Signal processing techniques for synchronization of wireless sensor networks

    NASA Astrophysics Data System (ADS)

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

    2010-11-01

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

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

    NASA Technical Reports Server (NTRS)

    Thomas, J. B.

    1988-01-01

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

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

    NASA Technical Reports Server (NTRS)

    Hong, Yie-Ming

    1973-01-01

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

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

    NASA Technical Reports Server (NTRS)

    Downie, John D.

    1995-01-01

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

  11. All-optical signal processing using dynamic Brillouin gratings.

    PubMed

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

    2013-01-01

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

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

    PubMed Central

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

    2006-01-01

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

  13. Simplified signal processing for an airborne CO2 Doppler lidar

    NASA Technical Reports Server (NTRS)

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

    1992-01-01

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

  14. Signal-processing theory for the TurboRogue receiver

    NASA Technical Reports Server (NTRS)

    Thomas, J. B.

    1995-01-01

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

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

    DOEpatents

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

    2009-04-14

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

  16. 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.,…

  17. Biomedical signal acquisition, processing and transmission using smartphone

    NASA Astrophysics Data System (ADS)

    Roncagliolo, Pablo; Arredondo, Luis; González, Agustín

    2007-11-01

    This article describes technical aspects involved in the programming of a system of acquisition, processing and transmission of biomedical signals by using mobile devices. This task is aligned with the permanent development of new technologies for the diagnosis and sickness treatment, based on the feasibility of measuring continuously different variables as electrocardiographic signals, blood pressure, oxygen concentration, pulse or simply temperature. The contribution of this technology is settled on its portability and low cost, which allows its massive use. Specifically this work analyzes the feasibility of acquisition and the processing of signals from a standard smartphone. Work results allow to state that nowadays these equipments have enough processing capacity to execute signals acquisition systems. These systems along with external servers make it possible to imagine a near future where the possibility of making continuous measures of biomedical variables will not be restricted only to hospitals but will also begin to be more frequently used in the daily life and at home.

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

    PubMed

    Alter, Orly

    2007-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

  20. Optimal processing of Doppler signals in OCT

    NASA Astrophysics Data System (ADS)

    Walther, Julia; Kirsten, Lars; Koch, Edmund

    2015-07-01

    Besides structural imaging, OCT can be used to estimate axial velocities of the sample resolved in depth by Doppler processing. In Fourier domain OCT (FD-OCT), this is accomplished by measuring the phase difference (i.e. phase shift) between timely separated A-scans at the same depth. In most cases, these data are disturbed by noise caused by intrinsic noise of the OCT system, specified by the SNR, and decorrelation noise caused by the transversal movement of the optical beam relative to the sample. Since the first use of Doppler methods in OCT, many methods to reduce the phase shift noise by averaging have been presented. While all these methods use a fixed set of consecutive A-scans, the best method, exhibiting no bias and having the smallest standard deviation, was questionable. Recently, Doppler processing methods depending on the mentioned noise sources and delivering the most likely phase shift and thereby axial velocity became available. The relation of these methods to previously known methods like the Kasai estimator, maximum likelihood estimator (MLE) and joint spectral and time domain OCT (jSTdOCT) will be discussed.

  1. HYMOSS signal processing for pushbroom spectral imaging

    NASA Technical Reports Server (NTRS)

    Ludwig, David E.

    1991-01-01

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

  2. Principles of statistical radiophysics 2. Correlation theory of random processes.

    NASA Astrophysics Data System (ADS)

    Rytov, S. M.; Kravtsov, Yu. A.; Tatarskii, V. I.

    This book is an English translation of the Russian original "Vredenie y staticheskuyu radiofiziku II", 2nd revised edition, published by Nauka, Moscow 1976. For volume 1 see 44.003.123. Contents: 1. Fundamentals of correlation theory. 2. Applications of correlation theory. 3. Spectral theory of random actions on dynamic systems. 4. Certain kinds of nonstationary processes.

  3. Fast Computation of Local Correlation Coefficients on Graphics Processing Units

    E-print Network

    Pitsianis, Nikos P.

    Fast Computation of Local Correlation Coefficients on Graphics Processing Units Georgios and architectural means, for fast calcula- tion of local correlation coefficients, which is a basic image the use of multi-dimensional fast Fourier transforms, without losing or sacrificing local and non

  4. Expression profiles uncover the correlation of OPN signaling pathways with rat liver regeneration at cellular level.

    PubMed

    Wang, Gaiping; Li, Xiaofang; Chen, Shasha; Zhao, Weiming; Yang, Jing; Chang, Cuifang; Xu, Cunshuan

    2015-11-01

    Osteopontin (OPN) could participate in the occurrence of multiple liver diseases via promoting inflammation, cell activation, proliferation, and migration. However, the correlation of OPN with liver regeneration (LR) is poorly defined. Previous studies from us and others revealed that OPN was probably involved in the activation and proliferation of various hepatic cell types during LR. In this study, to further investigate the underlined mechanism of OPN in regulating LR, eight hepatic cell types were isolated and purified from rat regenerative livers at 10 time points. The gene expression profiles of above hepatic cells were assayed by Rat Genome 230 2.0 chips, and then IPA software was used to uncover the correlations of gene expression changes with physiological activities. The findings demonstrated that the majority of the OPN pathway-related genes were up-regulated in hepatocytes (HCs), pit cells (PCs), oval cells (OCs), and biliary epithelial cells (BECs) but down-regulated in other four cell types including sinusoidal endothelial cells (SECs), Kupffer cells (KCs), dendritic cells (DCs), and hepatic stellate cells (HSCs). Thereafter, functional enriched analysis by IPA indicated that OPN signaling pathway might promote cell proliferation, activation, migration, and inflammation in HCs, OCs, BECs, and PCs, and slightly boost proliferation and migration of SECs and KCs but inhibit inflammation response and chemotaxis in SECs and KCs and almost all physiological processes in DCs and HSCs. Morever, apoptosis, cell death, and necrosis were remarkably inhibited through JAK/STAT, ERK1/2, and NF-kB branches in almost every cell type. These above results suggest that OPN signaling pathway is closely related to HCs, OCs, BECs, and PCs but has less regulatory effect on SECs, KCs, HSCs, and DCs during rat LR. PMID:26269331

  5. An epidemic process mediated by a decaying diffusing signal

    NASA Astrophysics Data System (ADS)

    Faria, Fernando P.; Dickman, Ronald

    2012-06-01

    We study a stochastic epidemic model consisting of elements (organisms in a community or cells in tissue) with fixed positions, in which damage or disease is transmitted by diffusing agents ('signals') emitted by infected individuals. The signals decay as well as diffuse; since they are assumed to be produced in large numbers, the signal concentration is treated deterministically. The model, which includes four cellular states (susceptible, transformed, depleted, and removed), admits various interpretations: spread of an infection or infectious disease, or of damage in a tissue in which injured cells may themselves provoke further damage, and as a description of the so-called radiation-induced bystander effect, in which the signals are molecules capable of inducing cell damage and/or death in unirradiated cells. The model exhibits a continuous phase transition between spreading and nonspreading phases. We formulate two mean-field theory (MFT) descriptions of the model, one of which ignores correlations between the cellular state and the signal concentration, and another that treats such correlations in an approximate manner. Monte Carlo simulations of the spread of infection on the square lattice yield values for the critical exponents and the fractal dimension consistent with the dynamic percolation universality class.

  6. Visualizing confusion matrices for multidimensional signal detection correlational methods

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1980-01-01

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

  8. Advanced Signal Processing for Thermal Flaw Detection

    SciTech Connect

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

    2001-09-01

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

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

    E-print Network

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

    2002-03-14

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

  10. Signal processing applied to photothermal techniques for materials characterization

    NASA Technical Reports Server (NTRS)

    Rooney, James A.

    1989-01-01

    There is a need to make noncontact measurements of material characteristics in the microgravity environment. Photothermal and photoacoustics techniques offer one approach for attaining this capability since lasers can be used to generate the required thermal or acoustic signals. The perturbations in the materials that can be used for characterization can be detected by optical reflectance, infrared detection or laser detection of photoacoustics. However, some of these laser techniques have disadvantages of either high energy pulsed excitation or low signal-to-noise ratio. Alternative signal processing techniques that have been developed can be applied to photothermal or photoacoustic instrumentation. One fully coherent spread spectrum signal processing technique is called time delay spectrometry (TDS). With TDS the system is excited using a combined frequency-time domain by employing a linear frequency sweep excitation function. The processed received signal can provide either frequency, phase or improved time resolution. This signal processing technique was shown to outperform other time selective techniques with respect to noise rejection and was recently applied to photothermal instrumentation. The technique yields the mathematical equivalent of pulses yet the input irradiances are orders of magnitude less than pulses with the concomitant reduction in perturbation of the sample and can increase the capability of photothermal methods for materials characterization.

  11. Signal Processing in the Workplace Daniel Gatica-Perez

    E-print Network

    Signal Processing in the Workplace Daniel Gatica-Perez According to the U.S. Bureau of Labor Statistics, during 2013 employed Americans "worked an average of 7.6 hours on the days they worked", and "83 percent did some or all of their work at their workplace" [1]. Understanding processes in the workplace

  12. Relationships between digital signal processing and control and estimation theory

    NASA Technical Reports Server (NTRS)

    Willsky, A. S.

    1978-01-01

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

  13. Optimal and adaptive methods of processing hydroacoustic signals (review)

    NASA Astrophysics Data System (ADS)

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

    2014-09-01

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

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

    SciTech Connect

    Dodge, D A

    2010-11-16

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  16. Integrated Optics for Planar imaging and Optical Signal Processing

    NASA Astrophysics Data System (ADS)

    Song, Qi

    Silicon photonics is a subject of growing interest with the potential of delivering planar electro-optical devices with chip scale integration. Silicon-on-insulator (SOI) technology has provided a marvelous platform for photonics industry because of its advantages in integration capability in CMOS circuit and countless nonlinearity applications in optical signal processing. This thesis is focused on the investigation of planar imaging techniques on SOI platform and potential applications in ultra-fast optical signal processing. In the first part, a general review and background introduction about integrated photonics circuit and planar imaging technique are provided. In chapter 2, planar imaging platform is realized by a silicon photodiode on SOI chip. Silicon photodiode on waveguide provides a high numerical aperture for an imaging transceiver pixel. An erbium doped Y2O3 particle is excited by 1550nm Laser and the fluorescent image is obtained with assistance of the scanning system. Fluorescence image is reconstructed by using image de-convolution technique. Under photovoltaic mode, we use an on-chip photodiode and an external PIN photodiode to realize similar resolution as 5?m. In chapter 3, a time stretching technique is developed to a spatial domain to realize a 2D imaging system as an ultrafast imaging tool. The system is evaluated based on theoretical calculation. The experimental results are shown for a verification of system capability to imaging a micron size particle or a finger print. Meanwhile, dynamic information for a moving object is also achieved by correlation algorithm. In chapter 4, the optical leaky wave antenna based on SOI waveguide has been utilized for imaging applications and extensive numerical studied has been conducted. and the theoretical explanation is supported by leaky wave theory. The highly directive radiation has been obtained from the broadside with 15.7 dB directivity and a 3dB beam width of ?Ø 3dB ? 1.65° in free space environment when ? -1 = 2.409 × 105/m, ?=4.576 ×103/m. At the end, electronics beam-steering principle has been studied and the comprehensive model has been built to explain carrier transformation behavior in a PIN junction as individual silicon perturbation. Results show that 1019/cm3 is possible obtained with electron injection mechanism. Although the radiation modulation based on carrier injection of 1019/cm3 gives 0.5dB variation, resonant structure, such as Fabry Perrot Cavity, can be integrated with LOWAs to enhance modulation effect.

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

    NASA Technical Reports Server (NTRS)

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

    2000-01-01

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

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

    PubMed Central

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

    2015-01-01

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

  19. Matched field signal processing in underwater sound channels (Review)

    NASA Astrophysics Data System (ADS)

    Sazontov, A. G.; Malekhanov, A. I.

    2015-03-01

    The state of the art of matched field hydroacoustic signal processing is described from the viewpoint of estimating the signal parameters in adaptive antenna arrays. The focus is on methods for solving the problem of source localization in an oceanic waveguide under mismatching effects of different nature, caused by disagreement between the received acoustic field and its model. Different approaches to increase the stability of the algorithms for source position estimation are discussed, which allows an increase in their efficiency in natural conditions.

  20. Optimal discrete wavelet design for cardiac signal processing.

    PubMed

    H Karel, J; M Peeters, R; Westra, R; S Moermans, K; P Haddad, S; Serdijn, W

    2005-01-01

    The question of designing the best wavelet for a given signal is discussed from the perspective of orthogonal filter banks. Two performance criteria are proposed to measure the quality of a wavelet, based on the principle of maximization of variance. The method is illustrated and evaluated by means of a worked example from biomedicine in the area of cardiac signal processing. The experimental results show the potential of the approach. PMID:17282815

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

    NASA Technical Reports Server (NTRS)

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

    1985-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1985-01-01

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

  3. Ultrahigh dispersion of broadband microwave signals by incoherent photonic processing.

    PubMed

    Park, Yongwoo; Azaña, José

    2010-07-01

    We propose and demonstrate a fiber-optic incoherent signal processing scheme to achieve extraordinary dispersion amounts on arbitrary microwave signals with bandwidths over tens of GHz. Using this new scheme, we experimentally achieve microwave dispersion values approaching 24 ns/GHz (equivalent to the dispersion induced by a section of standard single-mode fiber with a length of approximately 185,000 km). The scheme is used for real-time Fourier transformation (linear frequency-to-time mapping) of nanosecond-long microwave signals, including a square-like waveform, a sinusoidal pulse and a double pulse waveform, with bandwidths over 20 GHz. PMID:20639961

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

    SciTech Connect

    Li, Xuefeng; Cao, Guangzhan; Liu, Hongjun

    2014-04-15

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

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

    PubMed Central

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

    2014-01-01

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

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

    PubMed

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

    2014-05-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-10-01

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

  8. Naam TUD-onderdeel wijzigen in masterFaculty EEMCS One track of activities centers around acoustical signal processing, signal

    E-print Network

    Langendoen, Koen

    , array signal processing (utilizing multiple antennas) for radar and radio astronomy, biomedical communication, cognitive radio, radio astronomy and computational image formation, RFID, signal processing Underwater comm. UWB Positioning, synchronization Biomedical Radio Astronomy Cognitive Radio Sensor Networks

  9. Parallel Signal Processing and System Simulation using aCe

    NASA Technical Reports Server (NTRS)

    Dorband, John E.; Aburdene, Maurice F.

    2003-01-01

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

  10. Distributed Signal Processing for Wireless EEG Sensor Networks.

    PubMed

    Bertrand, Alexander

    2015-11-01

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

  11. Single photon laser altimeter simulator and statistical signal processing

    NASA Astrophysics Data System (ADS)

    Vacek, Michael; Prochazka, Ivan

    2013-05-01

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

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

    E-print Network

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

    2011-01-01

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

  13. Diffraction tomographic signal processing algorithms for tunnel detection

    SciTech Connect

    Witten, A.J.

    1993-08-01

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

  14. Hybrid signal processing in voltammetric determination of chromium(VI).

    PubMed

    Jakubowska, Ma?gorzata

    2010-04-15

    This study presents different hybrid signal processing algorithms which are useful in the interpretation of voltammetric signals recorded on mercury film electrodes for the determination of Cr(VI). Because of the complex character of the distortions (random, fast increasing, nonlinear, background noise and other perturbations) the application of a complex numerical procedure is necessary. In this work different variants of hybrid algorithms are utilized: adaptive degree polynomial filter, baseline generation and subtraction, signals ratio method, orthogonal signal correction and continuous wavelet transformation with dedicated mother wavelet. The operation and effectiveness of proposed procedures were tested by the determination of very low concentrations of Cr(VI) in synthetic and river water samples. PMID:20004057

  15. Analysis of signal processing techniques in pulsed thermography

    NASA Astrophysics Data System (ADS)

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

    2013-05-01

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

  16. Information content of signals using correlation function expansions of the entropy Phil Attard

    E-print Network

    Attard, Phil

    School of Chemistry F11, University of Sydney, Sydney, New South Wales 2006, Australia Owen G. Jepps and Stjepan Marcelja Department of Applied Mathematics, Research School of Physical Sciences and Engineering expansion is restricted to weakly correlated signals, whereas the truncated Markov expansion is uniformly

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

    ERIC Educational Resources Information Center

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

    2006-01-01

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

  18. Optical signal processing of a distributed fiber optical force sensor

    NASA Astrophysics Data System (ADS)

    Li, Zhigao; Zhou, Jian; Pan, Yingjun; Huang, Shanglian

    1993-09-01

    For the distributed fiber optical force sensor based on the principle of modecoupling of polarization-maintaining fiber and that of optical path compensation in the interference of quasi-monochromatic light, it is very important to process the weak optical signal from the sensing fiber. The paper analyzes the characteristics of the optical signal and suggests a Mach- Zehnder interferometer which includes an acouto-optical modulator and a polarized beam splitter to realize the polarization heterodyne interference. The method elimilates the iiifluences of light source fluctuation and back ground and cuts down the loss of the signal processing, so that it improves S/N ratio. The experiments coinicde well with the analysis.

  19. Smart signal processing for an evolving electric grid

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  20. Parallel Processing of Broad-Band PPM Signals

    NASA Technical Reports Server (NTRS)

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

    2010-01-01

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

  1. Social Signal Processing in Companion Systems -Challenges Ahead

    E-print Network

    emotional, nonverbal communication skills and empathy. One of the main challenges is to equip. In communication processes nonverbal social sig- naling conveys determination, interest, relatedness, etc. Due role that verbal communication plays in isolation and in conjunction with nonverbal signals in nat

  2. ULTRASONIC SIGNAL PROCESSING AND PATTERN RECONGITION IN EVALUATING

    E-print Network

    Saniie, Jafar

    ULTRASONIC SIGNAL PROCESSING AND PATTERN RECONGITION IN EVALUATING THE MICROSTRUCTURE OF MATERIALS. 1 Importa^nceof Grainsin Materials I.2 UltrasonicGrain SizeCharacterization 1. 3 Brief Introduction the Specimenwith Average Grain Sizeof 50pr,m,Measuredby Using 5 MHz Aero-tech Gamma Transducer 1.5 1

  3. SAMPLING THEORY IN SIGNAL AND IMAGE PROCESSING # 2004 SAMPLING PUBLISHING

    E-print Network

    Teschke, Gerd

    SAMPLING THEORY IN SIGNAL AND IMAGE PROCESSING c # 2004 SAMPLING PUBLISHING Vol. 3, No. 3, Sept and phrases : Parameter rule, Sobolev embedding op­ erator, Tikhonov regularization, Statistical noise model 2000 AMS Mathematics Subject Classification --- 65C20, 65J10, 65J20, 65J22, 94A12, 94A20 1 Introduction

  4. Signal processing underlying extrinsic control of stem cell fate

    E-print Network

    Zandstra, Peter W.

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

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

    ERIC Educational Resources Information Center

    Miller, Billy K.; And Others

    1983-01-01

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

  6. Adventures in Radio Astronomy Instrumentation and Signal Processing

    E-print Network

    Masci, Frank

    Adventures in Radio Astronomy Instrumentation and Signal Processing by Peter Leonard Mc has helped to validate the approach to developing radio astronomy instruments that CASPER advocates. 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2 Background 7 2.1 An Engineer's View of Radio Astronomy and Instrumentation . . . . 7 2.2 Single

  7. EURASIP Journal on Applied Signal Processing Multimedia over IP

    E-print Network

    Kuo, C.-C. "Jay"

    : Zixiang Xiong, Mihaela van der Schaar, Jie Chen, Eckehard Steinbach, C.-C. Jay Kuo, and Ming-Ting Sun #12.-C. Jay Kuo, and Ming-Ting Sun EURASIP Journal on Applied Signal Processing #12;Copyright © 2004 Hindawi, Korea Xiaodong Wang, USA Touradj Ebrahimi, Switzerland Y. Geoffrey Li, USA Douglas Williams, USA Sadaoki

  8. Maximum Likelihood Methods in Radar Array Signal Processing

    E-print Network

    Swindlehurst, A. Lee

    invariance principle, likelihood ratio detection test, maximum likelihood estimation, radar cross section radar cross section), direction of arrival (DOA), range, and Doppler frequency. Even when only a singleMaximum Likelihood Methods in Radar Array Signal Processing A. LEE SWINDLEHURST, MEMBER, IEEE

  9. Signal processing techniques for clutter filtering and wind shear detection

    NASA Technical Reports Server (NTRS)

    Baxa, Ernest G., Jr.; Deshpande, Manohar D

    1991-01-01

    An extended Prony algorithm applicable to signal processing techniques for clutter filtering and windshear detection is discussed. The algorithm is based upon modelling the radar return as a time series, and appears to offer potential for improving hazard factor estimates in the presence of strong clutter returns.

  10. Fiber optic displacement sensor and its signal processing

    NASA Astrophysics Data System (ADS)

    Wang, Guirong; Zheng, Shengxuan; Wang, TingYun; Chang, Danhua; Lu, Qizhu; Liu, Chengbin

    1996-09-01

    A low fineness fiber optic Fabry-Perot interferometric displacement sensor has been developed and tested. With using a high performance He-Ne laser, low noise photodetectors, low drift operational amplifiers, 6-pole Butterworth filters and perfect digital signal processing circuits, a 0.005 nm displacement resolution is obtained.

  11. Signal processing for the TOPAZ Time Projection Chamber

    SciTech Connect

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

    1987-02-01

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

  12. Opportunistic Strategies for Lightweight Signal Processing for Body Sensor Networks

    E-print Network

    for wearable signal processing, but it allows for opportunistic sensing strategies, in which many networks, opportunistic sensing, health monitoring, wearable computing, energy expenditure, physical of our BSN platform, which is now based on a smartphone running the Android operating system. We propose

  13. Robust Stimulus Encoding in Olfactory Processing: Hyperacuity and Ecient Signal

    E-print Network

    Pearce, Tim C.

    of Leicester, University Road LE1 7RH, United Kingdom. t.c.pearce@le.ac.uk 2 Institute of Neuroinformatics odour perception over time. Another factor of crucial importance when considering robust signal process of perception. Receptor adaptation or fatigue is a key factor here and is known to occur in ORNs

  14. Department of Electrical & Computer Engineering SIGNAL PROCESSING FOR COGNITIVE RADIOS

    E-print Network

    New Mexico, University of

    Department of Electrical & Computer Engineering SIGNAL PROCESSING FOR COGNITIVE RADIOS (A Fall 2015 as an evolution of software-defined radios (SDR), the Cognitive Radio technology is steadily evolving towards becoming the future of wireless communications. While SDR's can also be intelligent radios, what sets

  15. Survey Of Concurrent-Processors For Signal Processing Applications

    NASA Astrophysics Data System (ADS)

    Bond, J. Walter

    1980-12-01

    This paper summarizes a survey of concurrent-processing computer systems, particularly their descriptive differences and performance. The motivation is the high data processing rates required by ever-larger applications of infrared sensors and radar for data accumula-tion and the speed constraints of technology. The scope of the application and the technological limitations have caused consideration of alternative computer systems architectures for signal processing. In support of this, a survey was done of installations which are built and functioning, first to assess the architecture's application to signal processing, and second, to understand the difficulties inherent in developing an operational concurrent-processing computer system. The surveyed systems include C.mmp, Cm*, PLURIBUS, S-1, ILLIAC IV, STARAN, PEPE, CDC *100, TIASC, CRI - CR1, and the fault tolerant systems JPL-STAR and SRI-Sift. Some systems have been excluded from this paper because they either are not completed to an operational stage or are classified. In this investigation of system architectural issues for signal processing applications, it became evident that no effective systems characterizations for concurrent processors exist. Furthermore, performance measures for these systems are awkward and poorly related to the characterizations. The performance mea-sures thus need refinement. A descriptor is proposed which contains the elements of data flow, control and reliability and to which the performance measures can be properly related.

  16. Epileptic Seizure Prediction by Exploiting Spatiotemporal Relationship of EEG Signals Using Phase Correlation.

    PubMed

    Parvez, Mohammad Zavid; Paul, Manoranjan

    2016-01-01

    Automated seizure prediction has a potential in epilepsy monitoring, diagnosis, and rehabilitation. Electroencephalogram (EEG) is widely used for seizure detection and prediction. This paper proposes a new seizure prediction approach based on spatiotemporal relationship of EEG signals using phase correlation. This measures the relative change between current and reference vectors of EEG signals which can be used to identify preictal/ictal (before the actual seizure onset/ actual seizure period) and interictal (period between adjacent seizures) EEG signals to predict the seizure. The experiments show that the proposed method is less sensitive to artifacts and provides higher prediction accuracy (i.e., 91.95%) and lower number of false alarms compared to the state-of-the-art methods using intracranial EEG signals in different brain locations of 21 patients from a benchmark data set. PMID:26208360

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

    NASA Astrophysics Data System (ADS)

    Lee, Jounghun; Hoyle, Fiona

    2015-04-01

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

  18. Seismic signal processing optimized for a specific source and receiver

    SciTech Connect

    Stearns, S.D.

    1990-04-01

    A seismic signal processing procedure is designed so that its performance is optimized for a specific seismic array looking for explosions at a specific teleseismic location. In this report we first describe the processing procedure, which essentially estimates beamformer signal power as a function of time in a specified frequency band. Then we calibrate the procedure for the Norwegian Regional Seismic array (NRSA) in terms of equivalent body magnitude'' (emb) level versus signal power using US Department of Interior/Geological Survey (USGS) epicenter data from documented explosions at the USSR Semipalatinsk test area in Eastern Kazakh. Finally, we test the performance of the procedure on actual NRSA data and estimate that explosions above approximately mb 4.0 at Semipalatinsk correspond with an event rate in the emb signal on the order of one to ten events per hour. We conclude that, to detect and analyze events around the clock at levels below mb 4.0, an automatic event locator must be used to process the output of the procedure described here. 8 refs., 19 figs., 1 tab.

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

    NASA Astrophysics Data System (ADS)

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

    2015-07-01

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

  20. Method of vibration signal processing for interferometric optical fiber sensor

    NASA Astrophysics Data System (ADS)

    Cao, Zhengyuan; Feng, Ping; Feng, Ruhua; Gao, Jianxin; Zhao, Hong

    2001-10-01

    The method of vibration signal processing for interferometric optical fiber sensor is presented in this paper. For stable vibration, the method of frequency spectra analysis is used. For random vibration, using the system of fiber optic sensor in special coherence combined digital image processing setup and recording to moved number and direction of interferometric fringe and physical formula, collecting and processing image signal of vibration state is presented and professional software is studied and stress-time curve under random vibration state is measured after stress-time curve and vibration frequency for stable vibration were measured where they correspond with theory solution. This research provides a kind of new method for vibration monitoring of structure engineering.

  1. Modern Techniques in Acoustical Signal and Image Processing

    SciTech Connect

    Candy, J V

    2002-04-04

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

  2. Process-control in laser welding utilising optical signal oscillations

    SciTech Connect

    Haran, F.M.; Hand, D.P.; Jones, J.D.C.

    1996-12-31

    The authors describe an optical sensor for process monitoring of Nd:YAG laser welding. This sensor detects the broadband radiation produced by the welding process, dividing it into broad spectral bands (designated as UV/visible and IR). Fourier analysis is used to investigate an oscillatory intensity modulation of the optical signals, believed to arise from a combination of keyhole and weld pool oscillations. The spectral content of the oscillations may be used to detect a fully open welding keyhole, and determine work-piece thickness in this welding regime. These oscillations have also been utilized in the construction of a seam tracking system which allows the authors to follow the seam of a lap-weld. Additional signal processing also allows optimum positioning of the laser spot.

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

    PubMed

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

    2014-09-01

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

  4. Detecting a stochastic background of gravitational radiation: Signal processing strategies and sensitivities

    E-print Network

    Bruce Allen; Joseph D. Romano

    1997-10-27

    We analyze the signal processing required for the optimal detection of a stochastic background of gravitational radiation using laser interferometric detectors. Starting with basic assumptions about the statistical properties of a stochastic gravity-wave background, we derive expressions for the optimal filter function and signal-to-noise ratio for the cross-correlation of the outputs of two gravity-wave detectors. Sensitivity levels required for detection are then calculated. Issues related to: (i) calculating the signal-to-noise ratio for arbitrarily large stochastic backgrounds, (ii) performing the data analysis in the presence of nonstationary detector noise, (iii) combining data from multiple detector pairs to increase the sensitivity of a stochastic background search, (iv) correlating the outputs of 4 or more detectors, and (v) allowing for the possibility of correlated noise in the outputs of two detectors are discussed. We briefly describe a computer simulation which mimics the generation and detection of a simulated stochastic gravity-wave signal in the presence of simulated detector noise. Numerous graphs and tables of numerical data for the five major interferometers (LIGO-WA, LIGO-LA, VIRGO, GEO-600, and TAMA-300) are also given. The treatment given in this paper should be accessible to both theorists involved in data analysis and experimentalists involved in detector design and data acquisition.

  5. Automatic post-processing of correlation-plane imagery

    NASA Astrophysics Data System (ADS)

    Booth, Joseph J.

    1995-03-01

    The Weapons Sciences Directorate has dedicated many years of research to the development of optical correlators for applications in automatic target tracking and recognition. A great deal of effort has been directed toward the implementation of compact optical systems, optimal filter technologies, and high frame rate modulators. This effort follows general trends in the industry to improve the quality of the correlation plane. However, relatively little attention has been directed toward automating the analysis of images obtained at the correlator's output. The existence of a reliable post processing scheme is a prerequisite to the construction of a fully automatic correlation system. The design, construction and programming of a hardware post processor has recently been completed, and preliminary tests of the device have been successful.

  6. Correlation between muscular and nerve signals responsible for hand grasping in non-human primates.

    PubMed

    Sheshadri, Swathi; Kortelainen, Jukka; Nag, Sudip; Ng, Kian Ann; Bazley, Faith A; Michoud, Frederic; Patil, Anoop; Orellana, Josue; Libedinsky, Camilo; Lahiri, Amitabha; Chan, Louiza; Chng, Keefe; Cutrone, Annarita; Bossi, Silvia; Thakor, Nitish V; Delgado-Martinez, Ignacio; Yen, Shih-Cheng

    2014-01-01

    Neuroprosthetic devices that interface with the nervous system to restore functional motor activity offer a viable alternative to nerve regeneration, especially in proximal nerve injuries like brachial plexus injuries where muscle atrophy may set in before nerve re-innervation occurs. Prior studies have used control signals from muscle or cortical activity. However, nerve signals are preferred in many cases since they permit more natural and precise control when compared to muscle activity, and can be accessed with much lower risk than cortical activity. Identification of nerve signals that control the appropriate muscles is essential for the development of such a `bionic link'. Here we examine the correlation between muscle and nerve signals responsible for hand grasping in the M. fascicularis. Simultaneous recordings were performed using a 4-channel thin-film longitudinal intra-fascicular electrode (tf-LIFE) and 9 bipolar endomysial muscle electrodes while the animal performed grasping movements. We were able to identify a high degree of correlation (r > 0.6) between nerve signals from the median nerve and movement-dependent muscle activity from the flexor muscles of the forearm, with a delay that corresponded to 25 m/s nerve conduction velocity. The phase of the flexion could be identified using a wavelet approximation of the ENG. This result confirms this approach for a future neuroprosthetic device for the treatment of peripheral nerve injuries. PMID:25570451

  7. Dynamic submicroscopic signaling zones revealed by pair correlation tracking and localization microscopy.

    PubMed

    You, Changjiang; Richter, Christian P; Löchte, Sara; Wilmes, Stephan; Piehler, Jacob

    2014-09-01

    Unraveling the spatiotemporal organization of signaling complexes within the context of plasma membrane nanodomains has remained a highly challenging task. Here, we have applied super-resolution image correlation based on tracking and localization microscopy (TALM) for probing transient confinement as well as ligand binding and intracellular effector recruitment of the type I interferon (IFN) receptor in the plasma membrane of live cells. Ligand and receptor were labeled with monofunctional quantum dots, thus allowing long-term tracking with very high spatial and temporal resolution without an artificial receptor cross-linking at the cell surface. Dual-color TALM was employed for visualizing protein-protein interactions involved in IFN signaling at both sides of the plasma membrane with high spatial and temporal resolution. By pair correlation analyses based on time-lapse TALM images (pcTALM), complex assembly within dynamic submicroscopic zones was identified. Strikingly, recruitment of the IFN effector protein signal transducer and activator of transcription 2 (STAT2) into these dynamic signaling zones could be observed. The results suggest that confined diffusion zones in the plasma membrane are employed as transient platforms for the assembly of signaling complexes. PMID:25148216

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

    NASA Astrophysics Data System (ADS)

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

    2012-02-01

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

  9. Analysis of Wide-Band Signals Using Wavelet Array Processing

    NASA Astrophysics Data System (ADS)

    Nisii, V.; Saccorotti, G.

    2005-12-01

    Wavelets transforms allow for precise time-frequency localization in the analysis of non-stationary signals. In wavelet analysis the trade-off between frequency bandwidth and time duration, also known as Heisenberg inequality, is by-passed using a fully scalable modulated window which solves the signal-cutting problem of Windowed Fourier Transform. We propose a new seismic array data processing procedure capable of displaying the localized spatial coherence of the signal in both the time- and frequency-domain, in turn deriving the propagation parameters of the most coherent signals crossing the array. The procedure consists in: a) Wavelet coherence analysis for each station pair of the instruments array, aimed at retrieving the frequency- and time-localisation of coherent signals. To this purpose, we use the normalised wavelet cross- power spectrum, smoothed along the time and scale domains. We calculate different coherence spectra adopting smoothing windows of increasing lengths; a final, robust estimate of the time-frequency localisation of spatially-coherent signals is eventually retrieved from the stack of the individual coherence distribution. This step allows for a quick and reliable signal discrimination: wave groups propagating across the network will manifest as high-coherence patches spanning the corresponding time-scale region. b) Once the signals have been localised in the time and frequency domain,their propagation parameters are estimated using a modified MUSIC (MUltiple SIgnal Characterization) algorithm. We select the MUSIC approach as it demonstrated superior performances in the case of low SNR signals, more plane waves contemporaneously impinging at the array and closely separated sources. The narrow-band Coherent Signal Subspace technique is applied to the complex Continuous Wavelet Transform of multichannel data for improving the singularity of the estimated cross-covariance matrix and the accuracy of the estimated signal eigenvectors. Using synthetic multichannel data generated for different signal types, the resolution in time-frequency-slowness domains is estimated by a direct comparision with the Windowed Fourier Transform MUSIC algorithm. The main advantages of our Wavelet Transform MUSIC algorithm (WTM) consists in: a) The simplicity of the procedure, as different frequency bands are processed at once without sacrifying time resolution; b) Its ability to selectively process only those data windows which depict significant coherence throughout the network, thus ensuring the physical meaning of the solution. We applied this metodology to the study of the wavefield characteristic of seismo-volcanic activity recorded by a dense array of short-period seismometers deployed at Stromboli volcano during its 2002-2003 eruption. WTM gives precise descriptions of the distribution in time and frequency of the different wavefield components, in turn providing precise estimates of the corresponding wavevectors. These achievements represent a crucial step toward a better understanding of the seismic wavefields associated with volcanic activity.

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

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

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

  11. Synthetic aperture radar signal processing on the MPP

    NASA Technical Reports Server (NTRS)

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

    1987-01-01

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

  12. Neural Correlates of Bridging Inferences and Coherence Processing

    ERIC Educational Resources Information Center

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

    2012-01-01

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

  13. Neural Correlates of Sublexical Processing in Phonological Working Memory

    ERIC Educational Resources Information Center

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

    2011-01-01

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

  14. Physical characteristics of diblock polyacetylene copolymers: processability-conductivity correlation

    SciTech Connect

    Aldissi, M.; Hou, M.; Farrell, J.

    1986-01-01

    The physical properties of polyacetylene diblock copolymers containing polystyrene (PS) or polyisoprene (PI) blocks of various compositions are studied using electron spin resonance, resonance Raman scattering, and room temperature conductivity measurements. This study is performed to investigate the processability-conductivity correlation in these materials and their viability as conducting systems.

  15. Signal Processing in Periodically Forced Gradient Frequency Neural Networks

    PubMed Central

    Kim, Ji Chul; Large, Edward W.

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  17. Digital signal processing algorithms for automatic voice recognition

    NASA Astrophysics Data System (ADS)

    Botros, Nazeih M.

    1987-11-01

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

  18. Digital signal processing algorithms for automatic voice recognition

    NASA Technical Reports Server (NTRS)

    Botros, Nazeih M.

    1987-01-01

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

  19. Deterring watermark collusion attacks using signal processing techniques

    NASA Astrophysics Data System (ADS)

    Lemma, Aweke N.; van der Veen, Michiel

    2007-02-01

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

  20. Nonlinear signal processing of electroencephalograms for automated sleep monitoring

    NASA Astrophysics Data System (ADS)

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

    2005-02-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-07-01

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

  2. UniBoard: generic hardware for radio astronomy signal processing

    NASA Astrophysics Data System (ADS)

    Hargreaves, J. E.

    2012-09-01

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

  3. Signal Processing 86 (2006) 760775 Kalman filtering for self-similar processes

    E-print Network

    Yazici, Birsen

    2006-01-01

    Signal Processing 86 (2006) 760­775 Kalman filtering for self-similar processes Birsen Yazicia develop a state space representation and Kalman filtering method for self-similar processes. Key. The system and measurement models for the proposed Kalman filter are defined as t_xðtÞ ¼ tH AtÀH xðtÞ þ t

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

    NASA Technical Reports Server (NTRS)

    1999-01-01

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

  5. Signal processing methodologies for an acoustic fetal heart rate monitor

    NASA Technical Reports Server (NTRS)

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

    1992-01-01

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

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

    SciTech Connect

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

    2006-04-15

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

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

    PubMed Central

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

    2013-01-01

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

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

    PubMed

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

    2013-07-01

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

  9. Three-way noiseless signal splitting in a parametric amplifier with quantum correlation

    E-print Network

    Nannan Liu; Jiamin Li; Xiaoying Li; Z. Y. Ou

    2015-12-04

    We demonstrate that a phase-insensitive parametric amplifier, coupled to a quantum correlated source, can be used as a quantum information tap for noiseless three-way signal splitting. We find that the output signals are amplified noiselessly in two of the three output ports while the other can more or less keep its original input size without adding noise. This scheme is able to cascade and scales up for efficient information distribution in an optical network. Furthermore, we find this scheme satisfies the criteria for a non-ideal quantum non-demolition (QND) measurement and thus can serve as a QND measurement device. With two readouts correlated to the input, we find this scheme also satisfies the criterion for sequential QND measurement.

  10. Flash Signal Processing and NAND/ReRAM SSD

    NASA Astrophysics Data System (ADS)

    Takeuchi, K.

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

  11. Entropy bounds for quantum processes with initial correlations

    NASA Astrophysics Data System (ADS)

    Vinjanampathy, Sai; Modi, Kavan

    2015-11-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

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

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

    SciTech Connect

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

    2005-04-09

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

  14. Nonlinear fiber applications for ultrafast all-optical signal processing

    NASA Astrophysics Data System (ADS)

    Kravtsov, Konstantin

    In the present dissertation different aspects of all-optical signal processing, enabled by the use of nonlinear fibers, are studied. In particular, we focus on applications of a novel heavily GeO2-doped (HD) nonlinear fiber, that appears to be superior to many other types of nonlinear fibers because of its high nonlinearity and suitability for the use in nonlinear optical loop mirrors (NOLMs). Different functions, such as all-optical switching, thresholding, and wavelength conversion, are demonstrated with the HD fibers in the NOLM configuration. These basic functions are later used for realization of ultrafast time-domain demultiplexers, clock recovery, detectors of short pulses in stealth communications, and primitive elements for analog computations. Another important technology that benefits from the use of nonlinear fiber-based signal processing is optical code-division multiple access (CDMA). It is shown in both theory and experiment that all-optical thresholding is a unique way of improving existing detection methods for optical CDMA. Also, it is the way of implementation of true asynchronous optical spread-spectrum networks, which allows full realization of optical CDMA potential. Some aspects of quantum signal processing and manipulation of quantum states are also studied in this work. It is shown that propagation and collisions of Thirring solitons lead to a substantial squeezing of quantum states, which may find applications for generation of squeezed light.

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

    NASA Astrophysics Data System (ADS)

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

    2014-03-01

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

  16. Nonlinear signal processing using index calculus DBNS arithmetic

    NASA Astrophysics Data System (ADS)

    Muscedere, Roberto; Jullien, Graham A.; Dimitrov, Vassil S.; Miller, W. C.

    2000-11-01

    This paper discusses the use of a recently introduced index calculus Double-Base Number System (IDBNS) for representing and processing numbers for non-linear digital signal processing; the target application is a digital hearing aid processor. The IDBNS representation uses 2 orthogonal bases (2 and 3) to represent real numbers with arbitrary precision. By restricting the number of digits to one or two, It is possible to efficiently represent the real number using the indices of the bases rather than the distribution of the digits. In this paper we discuss the use of the two-digit form of this representation (2-IDBNS) to efficiently perform arithmetic associated with the non-linear processing required to correct the usual forms of hearing loss in a digital hearing aid. The non-linear processing takes the form of dynamic range compression as a function of frequency band. Currently developed digital hearing instrument processors require large dynamic range representations (20 - 24 bits) in order to accurately generate the dynamic range compression associated with typical hearing loss. We show that the natural non-linear representation afforded by the IDBNS provides both a more efficient signal representation and a more efficient technique for processing the dynamic range compression. We pay particular attention to a novel technique of converting from a linear binary input directly to the 2-IDBNS representation using an observation of partial cyclic repetition in the indices along with near unity approximants.

  17. Silicon Microring Resonator-Based Reconfigurable Optical Lattice Filter for On-Chip Optical Signal Processing

    E-print Network

    Yoo, S. J. Ben

    in laser radar (LADAR), electronic warfare (EW), free space optical (FSO) communications, synthetic-bandwidth signals at low power consumption. While electronics offer flexible and diverse signal processing capabilities, all-optical signal processing independently or in conjunction with electronic signal processing

  18. Two-point correlation properties of stochastic splitting processes.

    PubMed

    Gabrielli, Andrea; Joyce, Michael

    2008-03-01

    We study how the two-point density correlation properties of a point particle distribution are modified when each particle is divided, by a stochastic process, into an equal number of identical "daughter" particles. We consider generically that there may be nontrivial correlations in the displacement fields describing the positions of the different daughters of the same "mother" particle and then treat separately the cases in which there are, or are not, correlations also between the displacements of daughters belonging to different mothers. For both cases exact formulas are derived relating the structure factor (power spectrum) of the daughter distribution to that of the mothers. An application of these results is that they give explicit algorithms for generating, starting from regular lattice arrays, stochastic particle distributions with an arbitrarily high degree of large-scale uniformity. Such distributions are of interest, in particular, in the context of studies of self-gravitating systems in cosmology. PMID:18517361

  19. Knowledge-based signal processing for radar ESM systems

    NASA Astrophysics Data System (ADS)

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

    1990-10-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2010-12-01

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

  1. Micro-emboli detection: an ultrasound Doppler signal processing viewpoint.

    PubMed

    Girault, J M; Kouamé, D; Ouahabi, A; Patat, F

    2000-11-01

    Several studies have been carried out in the last twenty years on the characterization and detection of cerebral artery emboli. From the detection point of view, the existing methods are largely based on the classical Fourier analysis of which the well known limitations provide poor accuracy. This paper first recalls existing methods based on Fourier, Wigner-Ville and wavelet approaches. It then presents new emboli detection methods based on parametric signal processing approaches. The basic idea of these parametric methods is to compare the Doppler embolic signal to its autoregressive model. The detection principle consists in constructing a decision information which contains the signature of the micro-embolus being sought. The detection is finally evaluated using receiver operating characteristic (ROC) curves. Comparison between the new methods and classical approaches is performed using a realistic embolic signal simulation. Furthermore, to validate our theoretical study, we tested our new algorithms using in vivo signals. This comparison shows the significant inaccuracy of existing methods to detect micro-emboli. PMID:11077736

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

    NASA Astrophysics Data System (ADS)

    Nguyen, Lam

    2014-05-01

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

  3. Lack of measurement independence can simulate quantum correlations even when signaling can not

    NASA Astrophysics Data System (ADS)

    Banik, Manik

    2013-09-01

    In the Bell scenario, any nonlocal correlation shared between two spatially separated parties can be modeled deterministically either by allowing communications between the two parties or by restricting their free will in choosing the measurement settings. Recently, the Bell scenario has been generalized into a “semiquantum” scenario where external quantum inputs are provided to the parties. We show that in the semiquantum scenario, entangled states produce correlations whose deterministic explanation is possible only if measurement independence is reduced. Thus in simulating quantum correlation the semiquantum scenario reveals a qualitative distinction between signaling and measurement dependence which is absent in the Bell scenario. We further show that such distinction is not observed in the “steering-game” scenario, a special case of the semiquantum scenario.

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

    NASA Astrophysics Data System (ADS)

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

    2015-09-01

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

  5. Angiogenic and signalling proteins correlate with sensitivity to sequential treatment in renal cell cancer

    PubMed Central

    Rosa, R; Damiano, V; Nappi, L; Formisano, L; Massari, F; Scarpa, A; Martignoni, G; Bianco, R; Tortora, G

    2013-01-01

    Background: We aimed to study key signalling proteins involved in angiogenesis and proliferation on the response to inhibitors of tyrosine kinases and mammalian target of rapamycin in first- and in second-line treatment of renal cell carcinoma (RCC). Methods: In a panel of human RCC tumours, in vitro and in nude mice, we evaluated the effect of sunitinib, sorafenib and everolimus, alone and in sequence, on tumour growth and expression of signalling proteins involved in proliferation and resistance to treatment. Results: We demonstrated that, as single agents, sunitinib, sorafenib and everolimus share similar activity in inhibiting cell proliferation, signal transduction and vascular endothelial growth factor (VEGF) secretion in different RCC models, both in vitro and in tumour xenografts. Pre-treatment with sunitinib reduced the response to subsequent sunitinib and sorafenib but not to everolimus. Inability by sunitinib to persistently inhibit HIF-1, VEGF and pMAPK anticipated treatment resistance in xenografted tumours. After first-line sunitinib, second-line treatment with everolimus was more effective than either sorafenib or rechallenge with sunitinib in interfering with signalling proteins, VEGF and interleukin-8, translating into a significant advantage in tumour growth inhibition and mice survival. Conclusion: We demonstrated that a panel of angiogenic and signalling proteins can correlate with the onset of resistance to sunitinib and the activity of everolimus in second line. PMID:23839492

  6. Manganese-mediated MRI signals correlate with functional ?-cell mass during diabetes progression.

    PubMed

    Meyer, Anke; Stolz, Katharina; Dreher, Wolfgang; Bergemann, Jennifer; Holebasavanahalli Thimmashetty, Vani; Lueschen, Navina; Azizi, Zahra; Khobragade, Vrushali; Maedler, Kathrin; Kuestermann, Ekkehard

    2015-06-01

    Diabetes diagnostic therapy and research would strongly benefit from noninvasive accurate imaging of the functional ?-cells in the pancreas. Here, we developed an analysis of functional ?-cell mass (BCM) by measuring manganese (Mn(2+)) uptake kinetics into glucose-stimulated ?-cells by T1-weighted in vivo Mn(2+)-mediated MRI (MnMRI) in C57Bl/6J mice. Weekly MRI analysis during the diabetes progression in mice fed a high-fat/high-sucrose diet (HFD) showed increased Mn(2+)-signals in the pancreas of the HFD-fed mice during the compensation phase, when glucose tolerance and glucose-stimulated insulin secretion (GSIS) were improved and BCM was increased compared with normal diet-fed mice. The increased signal was only transient; from the 4th week on, MRI signals decreased significantly in the HFD group, and the reduced MRI signal in HFD mice persisted over the whole 12-week experimental period, which again correlated with both impaired glucose tolerance and GSIS, although BCM remained unchanged. Rapid and significantly decreased MRI signals were confirmed in diabetic mice after streptozotocin (STZ) injection. No long-term effects of Mn(2+) on glucose tolerance were observed. Our optimized MnMRI protocol fulfills the requirements of noninvasive MRI analysis and detects already small changes in the functional BCM. PMID:25804940

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

    PubMed

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

    2015-04-01

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

  8. Correlation technique for the compensation of diffraction widening of optical reference signals.

    PubMed

    Sáez-Landete, José; Alonso, José; Sanchez-Brea, Luis Miguel; Morlanes, Tomás; Bernabeu, Eusebio

    2009-09-01

    Two-grating measurement systems are routinely employed for high-resolution measurements of angular and linear displacement. Usually, these systems incorporate zero reference codes (ZRCs) to obtain a zero reference signal (ZRS), which is used as a stage-homing signal. This signal provides absolute information of the position to the otherwise relative information provided by the two-grating incremental subsystems. A zero reference signal is commonly obtained illuminating the superposition of two identical pseudorandom codes and registering the transmitted light by means of a photodiode. To increase the resolution of the system, a reduction of the grating period and the ZRC widths is required. Due to this reduction, the diffractive effects produce a widening of the ZRS and, in turn, a loss of the measuring accuracy. In this work, we propose a method to narrow the distorted signal obtained with a Lau-based encoder, reinstating the accuracy of the ZRS. The method consists of the inclusion of a correlation mask on the detector. A theoretical model to design the mask has been developed, and experimental results have been obtained that validate the proposed technique. PMID:19721672

  9. Biophoton signal transmission and processing in the brain.

    PubMed

    Tang, Rendong; Dai, Jiapei

    2014-10-01

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

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

    PubMed

    Planat, Michel; Rosu, Haret; Perrine, Serge

    2002-11-01

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

  11. Ramanujan sums for signal processing of low frequency noise

    E-print Network

    M. Planat; H. C. Rosu; S. Perrine

    2002-09-01

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

  12. Multiplexed interferometric fiber-optic sensors with digital signal processing

    NASA Astrophysics Data System (ADS)

    Sadkowski, Roberto; Lee, Chung E.; Taylor, Henry F.

    1995-09-01

    A microcontroller-based digital signal processing system developed for use with fiber-optic sensors for measuring pressure in internal combustion engines is described. A single distributed feedback laser source provides optical power for four interferometric sensors. The laser current is repetitively modulated so that its optical frequency is nearly a linear function of time over most of a cycle. The interferometer phase shift is proportional to the elapsed time from the initiation of a sawtooth until the sensor output signal level crosses a threshold value proportional to the laser output power. This elapsed time, assumed to vary linearly with the combustion chamber pressure, is determined by the use of a digital timer-counter. The system has been used with fiber Fabry-Perot interferometer transducers for in-cylinder pressure measurement on a four-cylinder gasoline-powered engine.

  13. Gallium arsenide enhances digital signal processing in electronic warfare

    NASA Astrophysics Data System (ADS)

    Hoffman, B.; Apte, D.

    1985-07-01

    The higher electron mobility and velocity of GaAs digital signal processing IC devices for electronic warfare (EW) allow operation times that are several times faster than those of ICs based on silicon. Particular benefits are foreseen for the response time and broadband capability of ECM systems. Many data manipulation methods can be implemented in emitter-coupled logic (ECL) GaAs devices, and digital GaAs RF memories are noted to show great promise for improved ECM system performance while encompassing microwave frequency and chirp signal synthesis, repeater jamming, and multiple false target generation. EW digital frequency synthesizers are especially in need of GaAS IC technology, since bandwidth and resolution have been limited by ECL technology to about 250 MHz.

  14. Information processing and signal integration in bacterial quorum sensing

    NASA Astrophysics Data System (ADS)

    Mehta, Pankaj

    2009-03-01

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

  15. The Open Host Network Packet Process Correlator for Windows

    Energy Science and Technology Software Center (ESTSC)

    2014-06-17

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

  16. Anomalous diffusion for a correlated process with long jumps

    NASA Astrophysics Data System (ADS)

    Srokowski, Tomasz

    2011-09-01

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

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

    NASA Astrophysics Data System (ADS)

    Si, Qian

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

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

    NASA Technical Reports Server (NTRS)

    Frehlich, Rod

    1993-01-01

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

  19. A Random Walk into Optical Signal Processing and Integrated Optofluidics

    NASA Astrophysics Data System (ADS)

    Baylor, Martha-Elizabeth

    2013-04-01

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

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

    SciTech Connect

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

    2010-09-01

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

  1. DSPSR: Digital Signal Processing Software for Pulsar Astronomy

    NASA Astrophysics Data System (ADS)

    van Straten, W.; Bailes, M.

    2010-10-01

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

  2. Integrated circuits for accurate linear analogue electric signal processing

    NASA Astrophysics Data System (ADS)

    Huijsing, J. H.

    1981-11-01

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

  3. Improved effectiveness of GPS RAIM through ridge regression signal processing

    NASA Technical Reports Server (NTRS)

    Kelly, Robert J.; Van Graas, Frank; Kuhl, Mark R.

    1989-01-01

    A measurement processing method has been developed which markedly improves the GPS Receiver Autonomous Integrity Monitoring (RAIM) software-based algorithm system's effectiveness in detecting satellite signal failures. Detection is via the consistency of a redundant set of pseudorange measurements. When five satellites are in view, five different subsolutions can be calculated; the integrity alarm is triggered on the basis of subsolution comparisons. Because a poor distribution of the satellites also causes RAIM subsolution scattering, a methodology for selecting the covariance matrix is presented which incorporates ridge regression into a Kalman filter.

  4. Application of Bayesian recursive estimation for seismic signal processing

    NASA Astrophysics Data System (ADS)

    Baziw, Erick

    2007-12-01

    Bayesian recursive estimation (BRE) requires that the posterior density function be estimated so that conditional mean estimates of desired parameters or states can be obtained. BRE has been referred to as a complete solution to the estimation problem since the posterior density function embodies all available statistical information (i.e., prior, likelihood and evidence). Until recent advances in BRE, most applications required that the system and measurement equations be linear, and that the process and measurement noise be Gaussian and white. A Kalman filter, KF, (closed form solution to the BRE) could be applied to systems that met these conditions. Previous applications of the KF to solve seismic signal processing problems (e.g., deconvolution) have had very limited success and acceptability in the geophysics signal processing community due to the restrictive nature of the KF. The recently new BRE development of sequential Monte Carlo (SMC) techniques for numerically solving non-stationary and non-linear problems has generated considerable interest and active research within the last decade. This thesis focuses upon the implementation of SMC techniques (e.g., particle filtering) for solving seismic signal processing problems. All the associated filters of BRE (hidden Markov model filter, KF, particle filter, Rao-Blackwellised particle filter, and jump Markov systems) and a new and highly robust and unique model of the seismic source wavelet are implemented in two innovative algorithms for solving the important problems of passive seismic event detection and blind seismic deconvolution. A ground-breaking concept in blind seismic deconvolution referred to as principle phase decomposition (PPD) is outlined and evaluated in this thesis. The PPD technique estimates and separates overlapping source wavelets instead of estimating high bandwidth reflection coefficients. It is shown that one can then easily generate reflection coefficients from the separated source wavelets. In this thesis many advantages of the PPD are outlined. Simulated seismogram data with low signal-to-noise ratios is blindly deconvolved where non-stationary, mixed-phase, and zero-phase source wavelets are present. I believe that there are currently no existing blind seismic deconvolution techniques which could obtain comparable performance results of the PPD technique. The work in this thesis has resulted in three IEEE publications and one peer reviewed conference publication.

  5. Signal transduction and information processing in mammalian taste buds

    PubMed Central

    2013-01-01

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

  6. Social signal processing for studying parent–infant interaction

    PubMed Central

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

    2014-01-01

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

  7. Social signal processing for studying parent-infant interaction.

    PubMed

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

    2014-01-01

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

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

    PubMed Central

    Chettoor, Antony M.; Evans, Matthew M. S.

    2015-01-01

    The plant life cycle alternates between two genetically active generations: the diploid sporophyte and the haploid gametophyte. In angiosperms the gametophytes are sexually dimorphic and consist of only a few cells. The female gametophyte, or embryo sac, is comprised of four cell types: two synergids, an egg cell, a central cell, and a variable number of antipodal cells. In some species the antipodal cells are indistinct and fail to proliferate, so many aspects of antipodal cell function and development have been unclear. In maize and many other grasses, the antipodal cells proliferate to produce a highly distinct cluster at the chalazal end of the embryo sac that persists at the apex of the endosperm after fertilization. The antipodal cells are a site of auxin accumulation in the maize embryo sac. Analysis of different families of genes involved in auxin biosynthesis, distribution, and signaling for expression in the embryo sac demonstrates that all steps are expressed within the embryo sac. In contrast to auxin signaling, cytokinin signaling is absent in the embryo sac and instead occurs adjacent to but outside of the antipodal cells. Mutant analysis shows a correlation between a loss of auxin signaling and a loss of proliferation of the antipodal cells. The leaf polarity mutant Laxmidrib1 causes a lack of antipodal cell proliferation coupled with a loss of DR5 and PIN1a expression in the antipodal cells. PMID:25859254

  9. Information processing correlates of a size-contrast illusion.

    PubMed

    Gold, Jason M

    2014-01-01

    Perception is often influenced by context. A well-known class of perceptual context effects is perceptual contrast illusions, in which proximate stimulus regions interact to alter the perception of various stimulus attributes, such as perceived brightness, color and size. Although the phenomenal reality of contrast effects is well documented, in many cases the connection between these illusions and how information is processed by perceptual systems is not well understood. Here, we use noise as a tool to explore the information processing correlates of one such contrast effect: the Ebbinghaus-Titchener size-contrast illusion. In this illusion, the perceived size of a central dot is significantly altered by the sizes of a set of surrounding dots, such that the presence of larger surrounding dots tends to reduce the perceived size of the central dot (and vise versa). In our experiments, we first replicated previous results that have demonstrated the subjective reality of the Ebbinghaus-Titchener illusion. We then used visual noise in a detection task to probe the manner in which observers processed information when experiencing the illusion. By correlating the noise with observers' classification decisions, we found that the sizes of the surrounding contextual elements had a direct influence on the relative weight observers assigned to regions within and surrounding the central element. Specifically, observers assigned relatively more weight to the surrounding region and less weight to the central region in the presence of smaller surrounding contextual elements. These results offer new insights into the connection between the subjective experience of size-contrast illusions and their associated information processing correlates. PMID:24600430

  10. Large-Array Signal Processing for Deep-Space Applications

    NASA Astrophysics Data System (ADS)

    Lee, C. H.; Vilnrotter, V.; Satorius, E.; Ye, Z.; Fort, D.; Cheung, K.-M.

    2002-04-01

    This article develops the mathematical models needed to describe the key issues in using an array of antennas for receiving spacecraft signals for DSN applications. The detrimental effects of nearby interfering sources, such as other spacecraft transmissions or natural radio sources within the array's field of view, on signal-to noise ratio (SNR) are determined, atmospheric effects relevant to the arraying problem developed, and two classes of algorithms (multiple signal classification (MUSIC) plus beam forming, and an eigen-based solution) capable of phasing up the array with maximized SNR in the presence of realistic disturbances are evaluated. It is shown that, when convolutionally encoded binary-phase shift keying (BPSK) data modulation is employed on the spacecraft signal, previously developed data pre-processing techniques that partially reconstruct the carrier can be of great benefit to array performance, particularly when strong interfering sources are present. Since this article is concerned mainly with demonstrating the required capabilities for operation under realistic conditions, no attempt has been made to reduce algorithm complexity; the design and evaluation of less complex algorithms with similar capabilities will be addressed in a future article. The performances of the candidate algorithms discussed in this article have been evaluated in terms of the number of symbols needed to achieve a given level of combining loss for different numbers of array elements, and compared on this common basis. It is shown that even the best algorithm requires approximately 25,000 symbols to achieve a combining loss of less than 0.5 dB when 128 antenna elements are employed, but generally 50,000 or more symbols are needed. This is not a serious impediment to successful arraying with high data-rate transmission, but may be of some concern with missions exploring near the edge of our solar system or beyond, where lower data rates may be required.

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

    PubMed

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

    2014-01-01

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

  12. Gravity Influences Top-Down Signals in Visual Processing

    PubMed Central

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

    2014-01-01

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

  13. Neuroanatomical correlates of processing in visual and visuospatial working memory.

    PubMed

    Suchan, Boris

    2008-03-01

    Working memory is traditionally seen as being organised in a modular way with a central executive orchestrating at least two slave systems (phonological loop and visuospatial sketch pad). Neuroanatomical correlates of the visual and visuospatial subsystems and the central executive are discussed in this article. A series of experiments are presented yielding evidence for a differentiation into active and passive processing in working memory as well as their neuroanatomical correlates in the prefrontal cortex. Data, yielding evidence for an interaction and separation of visual and visuospatial working memory are presented and discussed. Further results are presented which suggest a convergence of these two systems with increasing working memory demands. The discussed findings will give new insight in the organisation of visual and visuospatial working memory on the anatomical level. PMID:17909873

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

    SciTech Connect

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

    1996-05-01

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

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

    NASA Astrophysics Data System (ADS)

    Wu, Zheng

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

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

    NASA Astrophysics Data System (ADS)

    Yonak, Serdar Hakki

    2000-09-01

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

  17. Guest Editorial: Two-Dimensional Optical Signal Processing

    NASA Astrophysics Data System (ADS)

    Kooij, Theo; Ludman, Jacques E.; Stilwell, P. D., Jr.

    1982-10-01

    When some optical processing systems firms proposed to the Defense Advanced Research Project Agency (DARPA) and the U.S. Navy some years ago that they could beat the ILLIAC-IV-that venerable supercomputer, which until recently was the world's largest by at least a factor of 100, it sounded too good to be true. But they were right, and they did not even have to try hard. The problem was a two-dimensional (2-D) processing task of generating ambiguity surfaces to test whether two received signals came from a common origin, with unknown time and Doppler shifts. The ILLIAC, going all out as an in-line processor for the Acoustic Research Center near San Francisco, California, could just make a handful of such surfaces per second; the optical processors made hundreds, literally sucking their digital inputs dry.

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

    NASA Astrophysics Data System (ADS)

    Ramanathan, Ravishankar; Horodecki, Pawe?

    2014-11-01

    The phenomenon of monogamy of Bell inequality violations is interesting both from the fundamental perspective as well as in cryptographic applications such as the extraction of randomness and secret bits. In this article, we derive new and stronger monogamy relations for violations of Bell inequalities in general no-signaling theories. These relations are applicable to the class of binary output correlation inequalities known as xor games, and to free unique games. In many instances of interest, we show that the derived relation provides a significant strengthening over previously known results. Our result connects, for the first time, the property of monogamy with that crucial part of the Bell expression that is necessary for revealing a contradiction with local realistic predictions, thus shifting the paradigm in the field of monogamy of correlations.

  19. Strong monogamies of no-signaling violations for bipartite correlation bell inequalities.

    PubMed

    Ramanathan, Ravishankar; Horodecki, Pawe?

    2014-11-21

    The phenomenon of monogamy of Bell inequality violations is interesting both from the fundamental perspective as well as in cryptographic applications such as the extraction of randomness and secret bits. In this article, we derive new and stronger monogamy relations for violations of Bell inequalities in general no-signaling theories. These relations are applicable to the class of binary output correlation inequalities known as XOR games, and to free unique games. In many instances of interest, we show that the derived relation provides a significant strengthening over previously known results. Our result connects, for the first time, the property of monogamy with that crucial part of the Bell expression that is necessary for revealing a contradiction with local realistic predictions, thus shifting the paradigm in the field of monogamy of correlations. PMID:25479479

  20. Increasing signal processing sophistication in the calculation of the respiratory modulation of the photoplethysmogram (DPOP).

    PubMed

    Addison, Paul S; Wang, Rui; Uribe, Alberto A; Bergese, Sergio D

    2015-06-01

    DPOP (?POP or Delta-POP) is a non-invasive parameter which measures the strength of respiratory modulations present in the pulse oximetry photoplethysmogram (pleth) waveform. It has been proposed as a non-invasive surrogate parameter for pulse pressure variation (PPV) used in the prediction of the response to volume expansion in hypovolemic patients. Many groups have reported on the DPOP parameter and its correlation with PPV using various semi-automated algorithmic implementations. The study reported here demonstrates the performance gains made by adding increasingly sophisticated signal processing components to a fully automated DPOP algorithm. A DPOP algorithm was coded and its performance systematically enhanced through a series of code module alterations and additions. Each algorithm iteration was tested on data from 20 mechanically ventilated OR patients. Correlation coefficients and ROC curve statistics were computed at each stage. For the purposes of the analysis we split the data into a manually selected 'stable' region subset of the data containing relatively noise free segments and a 'global' set incorporating the whole data record. Performance gains were measured in terms of correlation against PPV measurements in OR patients undergoing controlled mechanical ventilation. Through increasingly advanced pre-processing and post-processing enhancements to the algorithm, the correlation coefficient between DPOP and PPV improved from a baseline value of R = 0.347 to R = 0.852 for the stable data set, and, correspondingly, R = 0.225 to R = 0.728 for the more challenging global data set. Marked gains in algorithm performance are achievable for manually selected stable regions of the signals using relatively simple algorithm enhancements. Significant additional algorithm enhancements, including a correction for low perfusion values, were required before similar gains were realised for the more challenging global data set. PMID:25209132

  1. Non-linear signal processing in digital hearing aids.

    PubMed

    Lunner, T; Hellgren, J; Arlinger, S; Elberling, C

    1998-01-01

    Three different non-linear digital signal processing algorithms were developed; LinEar, DynEar and RangeEar. All three provided individual frequency shaping via a seven-band low-power filterbank and compression in two channels. RangeEar and DynEar used wide dynamic range syllabic compression in the low-frequency (LF) channel, while LinEar used compression limiting. In the high-frequency (HF) channel, RangeEar used a slow-acting automatic volume control, while DynEar and LinEar used compression limiting. Wearable digital signal processing-based experimental instruments were used to evaluate the fitting algorithms under real world conditions with experienced hearing aid users. Evaluation included laboratory testing of speech recognition in noise and questionnaires on sound quality ratings. Results did not indicate one general good-for-all algorithm, but different algorithms resulting in preference and performance depending on the hearing loss configuration. Preference for any of the new algorithms could be predicted based on auditory dynamic range measurements. It was hypothesized that the different preferences were affected by different susceptibility to masking of HF sounds by amplified LF sounds. PMID:10209776

  2. Signal processing algorithms on parallel architectures: A performance update

    SciTech Connect

    Rover, D.; Tsai, V.; Chow, Yin-Shan; Gustafson, J.

    1991-02-01

    The Burg algorithm is a widely applied and extensively studied signal processing procedure having a structure typical of a class of important batch signal processing algorithms. Its implementation and performance on four different parallel machines were reported in the 1990 Journal of Parallel and Distributed Computing Special Issue on Massively Parallel Computation. The machines were: the Intel iPSC/2, the Denelcor HEP, the NASA/Goodyear MPP, and the Cray X-MP/48. The objective of the work reported here was to extend that study to two new parallel machines: the nCUBE 2 and the MasPar MP-1. These computers are related to the distributed memory systems above (i.e., the iPSC and the MPP, respectively), but use newer technology. In addition to achieving significant performance gains on the new machines compared to machines in the same architectural class, we found that the original study underestimated the scaleability of the algorithm. That is, the algorithm maps efficiently to small-scale as well as large-scale computers, including both SIMD and MIMD distributed memory systems. Improvements in the parallel algorithm are highlighted. Of special import is the use of appropriate performance metrics and performance visualization to characterize the parallelism of the algorithm and lend insight toward understanding and evaluating its performance. 14 refs., 9 figs.

  3. Peta-Flop Real Time Radio Astronomy Signal Processing Instrumentation and the CASPER Collaboration

    NASA Astrophysics Data System (ADS)

    Werthimer, Dan

    2014-04-01

    I will briefly describe next generation radio telescopes, such as HERA and the Square Kilometer Array (SKA), which will require 1E15 to 1E17 operations per second of real time processing. I'll present some of the new architectures we've used to develop a variety of heterogeneous FPGA-GPU-CPU based signal processing systems for such telescopes, including spectrometers, correlators, and beam formers. I will also describe the CASPER collaboration, which has developed architectures, open source programming tools, libraries and reference designs that make it relatively easy to develop a variety of scalable, upgradeable, fault tolerant, low power, real time digital signal processing instrumentation. CASPER utilizes commercial 10Gbit and 40 Gbit ethernet switches to interconnect open source general purpose field programmable gate array (FPGA) boards with GPUs and software modules. CASPER collaborators at hundreds of universities, government labs and observatories have used these techniques to rapidly develop and deploy a variety of correlators, beamformers, spectrometers, pulsar/transient machines, and VLBI instrumentation. CASPER instrumentation is also utilized in physics, medicine, genomics and engineering. Open source source hardware, software, libraries, tools, tutorials, reference designs, information about workshops, and how to join the collaboration are available at http://casper.berkeley.edu

  4. Electrophysiological correlates of the BOLD signal for EEG-informed fMRI

    PubMed Central

    Murta, Teresa; Leite, Marco; Carmichael, David W; Figueiredo, Patrícia; Lemieux, Louis

    2015-01-01

    Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are important tools in cognitive and clinical neuroscience. Combined EEG–fMRI has been shown to help to characterise brain networks involved in epileptic activity, as well as in different sensory, motor and cognitive functions. A good understanding of the electrophysiological correlates of the blood oxygen level-dependent (BOLD) signal is necessary to interpret fMRI maps, particularly when obtained in combination with EEG. We review the current understanding of electrophysiological–haemodynamic correlates, during different types of brain activity. We start by describing the basic mechanisms underlying EEG and BOLD signals and proceed by reviewing EEG-informed fMRI studies using fMRI to map specific EEG phenomena over the entire brain (EEG–fMRI mapping), or exploring a range of EEG-derived quantities to determine which best explain colocalised BOLD fluctuations (local EEG–fMRI coupling). While reviewing studies of different forms of brain activity (epileptic and nonepileptic spontaneous activity; cognitive, sensory and motor functions), a significant attention is given to epilepsy because the investigation of its haemodynamic correlates is the most common application of EEG-informed fMRI. Our review is focused on EEG-informed fMRI, an asymmetric approach of data integration. We give special attention to the invasiveness of electrophysiological measurements and the simultaneity of multimodal acquisitions because these methodological aspects determine the nature of the conclusions that can be drawn from EEG-informed fMRI studies. We emphasise the advantages of, and need for, simultaneous intracranial EEG–fMRI studies in humans, which recently became available and hold great potential to improve our understanding of the electrophysiological correlates of BOLD fluctuations. PMID:25277370

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

    NASA Astrophysics Data System (ADS)

    Teich, Malvin C.

    1998-03-01

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

  6. An information processing method for acoustic emission signal inspired from musical staff

    NASA Astrophysics Data System (ADS)

    Zheng, Wei; Wu, Chunxian

    2016-01-01

    This study proposes a musical-staff-inspired signal processing method for standard description expressions for discrete signals and describing the integrated characteristics of acoustic emission (AE) signals. The method maps various AE signals with complex environments into the normalized musical space. Four new indexes are proposed to comprehensively describe the signal. Several key features, such as contour, amplitude, and signal changing rate, are quantitatively expressed in a normalized musical space. The processed information requires only a small storage space to maintain high fidelity. The method is illustrated by using experiments on sandstones and computed tomography (CT) scanning to determine its validity for AE signal processing.

  7. Neural pulse frequency modulation of an exponentially correlated Gaussian process

    NASA Technical Reports Server (NTRS)

    Hutchinson, C. E.; Chon, Y.-T.

    1976-01-01

    The effect of NPFM (Neural Pulse Frequency Modulation) on a stationary Gaussian input, namely an exponentially correlated Gaussian input, is investigated with special emphasis on the determination of the average number of pulses in unit time, known also as the average frequency of pulse occurrence. For some classes of stationary input processes where the formulation of the appropriate multidimensional Markov diffusion model of the input-plus-NPFM system is possible, the average impulse frequency may be obtained by a generalization of the approach adopted. The results are approximate and numerical, but are in close agreement with Monte Carlo computer simulation results.

  8. Advanced Signal Processing for High Temperatures Health Monitoring of Condensed Water Height in Steam Pipes

    NASA Technical Reports Server (NTRS)

    Lih, Shyh-Shiuh; Bar-Cohen, Yoseph; Lee, Hyeong Jae; Takano, Nobuyuki; Bao, Xiaoqi

    2013-01-01

    An advanced signal processing methodology is being developed to monitor the height of condensed water thru the wall of a steel pipe while operating at temperatures as high as 250deg. Using existing techniques, previous study indicated that, when the water height is low or there is disturbance in the environment, the predicted water height may not be accurate. In recent years, the use of the autocorrelation and envelope techniques in the signal processing has been demonstrated to be a very useful tool for practical applications. In this paper, various signal processing techniques including the auto correlation, Hilbert transform, and the Shannon Energy Envelope methods were studied and implemented to determine the water height in the steam pipe. The results have shown that the developed method provides a good capability for monitoring the height in the regular conditions. An alternative solution for shallow water or no water conditions based on a developed hybrid method based on Hilbert transform (HT) with a high pass filter and using the optimized windowing technique is suggested. Further development of the reported methods would provide a powerful tool for the identification of the disturbances of water height inside the pipe.

  9. Correlation study between contamination and signal degradation in single-mode APC connectors

    NASA Astrophysics Data System (ADS)

    Lytle, Steve; Brown, Matt; Berdinskikh, Tatiana; Wilson, Douglas H.; Fisher, David; Huang, Sun-Yuan; Hughes, Mike; Mitcheltree, Tom; Roche, Brian J.

    2009-06-01

    This paper summarizes the correlation study between contamination and scratches on singlemode APC connectors and signal degradation; leading to an Acceptance Criteria Matrix. The study is a continuation of International Electronics Manufacturing Initiative (iNEMI) research on development of cleanliness specification for singlemode angled physical contact (SM-APC) connectors. Twenty-five APC SC connectors on one-meter patch cords were used for this study. The Design of the Experiment (DoE) was a multi-step process that involved: (1) inspecting, cleaning and inspecting connectors being tested (devices under test, or DUTs) and launch connectors; (2) making multiple matings and dematings of each DUT, in a pristine state, with a reference connector, and recording Return Loss (RL) data after each cycle; (3) manually applying dust to the cleaned end-faces of the DUTs; then (4) mating contaminated DUTs with clean reference connectors at least five times, taking RL measurements after each mating and saving fiber end-face images for both connectors. It was shown that connectors with the contamination at the core (9um diameter) demonstrated a dramatic decrease in average RL of 14.2 dB. In comparison, the samples with contamination on the cladding and clear core demonstrated a negligible change in RL of 0.15 dB. For highly contaminated samples in the cladding layer, we found the changes of RL to be about 5-6 dB. Further investigation established that particle migration during successive matings also occurs on the ferrule within the contact zone (approximately <250 ?m in diameter). Polishing scratches had no impact on RL of APC connectors. Based on the experimental data described in this paper, an inspection criteria matrix is proposed for SM-APC connectors including the zone definitions and number of allowable defects (contamination and scratches) for each zone. The recommendations on pass/fail criteria have been provided to the IEC (International Electrotechnical Committee). It is expected IEC-61300-3-25, which contains these criteria, will publish in 2009.

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

    E-print Network

    Andrea Gabrielli; Michael Joyce

    2007-11-02

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

  11. Processing of multiport CCD video signals at very high frame rates

    SciTech Connect

    Turko, B.T.; Yates, G.J.; King, N.S.P.

    1995-12-31

    Rates exceeding 1,000 frames/s can be achieved with multiport CCD state-of-art video sensors. In order to provide sufficient spatial resolution, sensor configurations of 512 x 512 pixels are typical. Image area is divided into segments with individual video ports. Each port includes a photocharge sensitive amplifier, typically comprising sample/hold and charge reset circuits. Some amplifiers are even provided with a double correlated sample circuit for improving the signal/noise ratio. Frame rates are proportional to the number of ports, since the individual sensor segments are run in parallel. Unfortunately, the amount of external circuitry required for signal processing increases accordingly. 16-port sensors are a quite common configuration. Cameras with even higher number of ports are prohibitively expensive. Therefore, in order to achieve very high frame readout rates with a moderate number of ports, the sensor`s charge transport clock frequencies must be increased to the limit. Horizontal charge transfer frequencies exceeding 30 MHz have been achieved. The quality of the video signal deteriorates with frequency due to bandwidth limitation of the photocharge detecting amplifier. Its sample/hold and double correlated sample circuits are useless at such rates. Methods and circuits for the processing of video signals under such conditions are described. The circuits include wide bandwidth video buffer amplifiers/level translator/line drivers, fast peak stretchers, 10-bit resolution (or more) A/D converters and fiber optic data links to a remote mass digital data storage and processors. Also, the circuits must satisfy a number of practical conditions (size, power dissipation, cost) in order to make such camera useful in applications where space is limited and multiple head high frame rate cameras are required.

  12. Session : NEWCOM Session on the Advanced Signal Processing Algorithms for Wireless Communications ( II ) (SPECIAL

    E-print Network

    Spagnolini, Umberto

    Session : NEWCOM Session on the Advanced Signal Processing Algorithms for Wireless Communications University, Turkey) Back Menu Next #12;Session : NEWCOM Session on the Advanced Signal Processing Algorithms of Technology, Turkey) Back Menu Next #12;Session : NEWCOM Session on the Advanced Signal Processing Algorithms

  13. ENG EC516 Digital Signal Processing 2008-2009 Catalog Data

    E-print Network

    ; cepstral analysis and deconvolution; parametric signal modeling; multidimensional signal processing Array Processing Course Outcomes mapped to Program Outcomes: Program: a b c d e f g h i j k Course: 1ENG EC516 Digital Signal Processing 2008-2009 Catalog Data ENG EC 516 Prereq: ENG EC 416, ENG EC

  14. An Enhanced Signal Processing Strategy For Fetal Heart Rate Detection Charles Brewton

    E-print Network

    Zahorian, Stephen A.

    ABSTRACT An Enhanced Signal Processing Strategy For Fetal Heart Rate Detection Charles Brewton Old the signal processing strategy for an acoustic fetal heart rate monitor. The theory, implementation, and testing of several possible signal processing strategies for fetal heart rate detection are presented

  15. Information processing and signal integration in bacterial quorum sensing

    E-print Network

    Mehta, Pankaj

    for analyzing signal integration on the basis of information theory and use it to analyze quorum sensing in V: biophysics; information theory; quorum sensing; signal integration; signal transduction This is an open for understanding signal integration based on information theory (Shannon, 1948) and we use it to study information

  16. Single sensor processing to obtain high resolution color component signals

    NASA Technical Reports Server (NTRS)

    Glenn, William E. (Inventor)

    2010-01-01

    A method for generating color video signals representative of color images of a scene includes the following steps: focusing light from the scene on an electronic image sensor via a filter having a tri-color filter pattern; producing, from outputs of the sensor, first and second relatively low resolution luminance signals; producing, from outputs of the sensor, a relatively high resolution luminance signal; producing, from a ratio of the relatively high resolution luminance signal to the first relatively low resolution luminance signal, a high band luminance component signal; producing, from outputs of the sensor, relatively low resolution color component signals; and combining each of the relatively low resolution color component signals with the high band luminance component signal to obtain relatively high resolution color component signals.

  17. Signal Processing Methods for Liquid Rocket Engine Combustion Stability Assessments

    NASA Technical Reports Server (NTRS)

    Kenny, R. Jeremy; Lee, Erik; Hulka, James R.; Casiano, Matthew

    2011-01-01

    The J2X Gas Generator engine design specifications include dynamic, spontaneous, and broadband combustion stability requirements. These requirements are verified empirically based high frequency chamber pressure measurements and analyses. Dynamic stability is determined with the dynamic pressure response due to an artificial perturbation of the combustion chamber pressure (bomb testing), and spontaneous and broadband stability are determined from the dynamic pressure responses during steady operation starting at specified power levels. J2X Workhorse Gas Generator testing included bomb tests with multiple hardware configurations and operating conditions, including a configuration used explicitly for engine verification test series. This work covers signal processing techniques developed at Marshall Space Flight Center (MSFC) to help assess engine design stability requirements. Dynamic stability assessments were performed following both the CPIA 655 guidelines and a MSFC in-house developed statistical-based approach. The statistical approach was developed to better verify when the dynamic pressure amplitudes corresponding to a particular frequency returned back to pre-bomb characteristics. This was accomplished by first determining the statistical characteristics of the pre-bomb dynamic levels. The pre-bomb statistical characterization provided 95% coverage bounds; these bounds were used as a quantitative measure to determine when the post-bomb signal returned to pre-bomb conditions. The time for post-bomb levels to acceptably return to pre-bomb levels was compared to the dominant frequency-dependent time recommended by CPIA 655. Results for multiple test configurations, including stable and unstable configurations, were reviewed. Spontaneous stability was assessed using two processes: 1) characterization of the ratio of the peak response amplitudes to the excited chamber acoustic mode amplitudes and 2) characterization of the variability of the peak response's frequency over the test duration. This characterization process assists in evaluating the discreteness of a signal as well as the stability of the chamber response. Broadband stability was assessed using a running root-mean-square evaluation. These techniques were also employed, in a comparative analysis, on available Fastrac data, and these results are presented here.

  18. Correlation between light scattering signal and tissue reversibility in rat brain exposed to hypoxia

    NASA Astrophysics Data System (ADS)

    Kawauchi, Satoko; Sato, Shunichi; Uozumi, Yoichi; Nawashiro, Hiroshi; Ishihara, Miya; Kikuchi, Makoto

    2010-02-01

    Light scattering signal is a potential indicator of tissue viability in brain because cellular and subcellular structural integrity should be associated with cell viability in brain tissue. We previously performed multiwavelength diffuse reflectance measurement for a rat global ischemic brain model and observed a unique triphasic change in light scattering at a certain time after oxygen and glucose deprivation. This triphasic scattering change (TSC) was shown to precede cerebral ATP exhaustion, suggesting that loss of brain tissue viability can be predicted by detecting scattering signal. In the present study, we examined correlation between light scattering signal and tissue reversibility in rat brain in vivo. We performed transcranial diffuse reflectance measurement for rat brain; under spontaneous respiration, hypoxia was induced for the rat by nitrogen gas inhalation and reoxygenation was started at various time points. We observed a TSC, which started at 140 +/- 15 s after starting nitrogen gas inhalation (mean +/- SD, n=8). When reoxygenation was started before the TSC, all rats survived (n=7), while no rats survived when reoxygenation was started after the TSC (n=8). When reoxygenation was started during the TSC, rats survived probabilistically (n=31). Disability of motor function was not observed for the survived rats. These results indicate that TSC can be used as an indicator of loss of tissue reversibility in brains, providing useful information on the critical time zone for treatment to rescue the brain.

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

    SciTech Connect

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

    1995-02-22

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

  20. Temporally selective processing of communication signals by auditory midbrain neurons

    PubMed Central

    Christensen-Dalsgaard, Jakob; Kelley, Darcy B.

    2011-01-01

    Perception of the temporal structure of acoustic signals contributes critically to vocal signaling. In the aquatic clawed frog Xenopus laevis, calls differ primarily in the temporal parameter of click rate, which conveys sexual identity and reproductive state. We show here that an ensemble of auditory neurons in the laminar nucleus of the torus semicircularis (TS) of X. laevis specializes in encoding vocalization click rates. We recorded single TS units while pure tones, natural calls, and synthetic clicks were presented directly to the tympanum via a vibration-stimulation probe. Synthesized click rates ranged from 4 to 50 Hz, the rate at which the clicks begin to overlap. Frequency selectivity and temporal processing were characterized using response-intensity curves, temporal-discharge patterns, and autocorrelations of reduplicated responses to click trains. Characteristic frequencies ranged from 140 to 3,250 Hz, with minimum thresholds of ?90 dB re 1 mm/s at 500 Hz and ?76 dB at 1,100 Hz near the dominant frequency of female clicks. Unlike units in the auditory nerve and dorsal medullary nucleus, most toral units respond selectively to the behaviorally relevant temporal feature of the rate of clicks in calls. The majority of neurons (85%) were selective for click rates, and this selectivity remained unchanged over sound levels 10 to 20 dB above threshold. Selective neurons give phasic, tonic, or adapting responses to tone bursts and click trains. Some algorithms that could compute temporally selective receptive fields are described. PMID:21289132

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

    NASA Astrophysics Data System (ADS)

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

    2015-10-01

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

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

    PubMed Central

    Grimaldi, Giuliana; Manto, Mario

    2010-01-01

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

  3. Holographic storage scheme based on digital signal processing

    NASA Astrophysics Data System (ADS)

    Jia, Kebin; Yang, Dapeng; Dun, Shubo; Tao, Shiquan; Qin, Mingyan

    2003-10-01

    In this paper, a holographic storage scheme for multimedia data storage and retrieval based on the digital signal processing (DSP) is designed. A communication model for holographic storage system is obtained on the analogy of traditional communication system. Many characteristics of holographic storage are embodied in the communication model. Then some new methods of DSP including two-dimensional (2-D) shifting interleaving, encoding and decoding of modulation-array (MA) code and method of soft-decision, etc. are proposed and employed in the system. From the results of experiments it can be seen that those measures can effectively reduce the influence of noise. A segment of multimedia data, including video and audio data, is retrieved successfully after holographic storage by using those techniques.

  4. On adaptive robustness approach to Anti-Jam signal processing

    NASA Astrophysics Data System (ADS)

    Poberezhskiy, Y. S.; Poberezhskiy, G. Y.

    An effective approach to exploiting statistical differences between desired and jamming signals named adaptive robustness is proposed and analyzed in this paper. It combines conventional Bayesian, adaptive, and robust approaches that are complementary to each other. This combining strengthens the advantages and mitigates the drawbacks of the conventional approaches. Adaptive robustness is equally applicable to both jammers and their victim systems. The capabilities required for realization of adaptive robustness in jammers and victim systems are determined. The employment of a specific nonlinear robust algorithm for anti-jam (AJ) processing is described and analyzed. Its effectiveness in practical situations has been proven analytically and confirmed by simulation. Since adaptive robustness can be used by both sides in electronic warfare, it is more advantageous for the fastest and most intelligent side. Many results obtained and discussed in this paper are also applicable to commercial applications such as communications in unregulated or poorly regulated frequency ranges and systems with cognitive capabilities.

  5. Digital Signal Processing for the Event Horizon Telescope

    NASA Astrophysics Data System (ADS)

    Weintroub, Jonathan

    2015-08-01

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

  6. Attosecond metrology: from electron capture to future signal processing

    NASA Astrophysics Data System (ADS)

    Krausz, Ferenc; Stockman, Mark I.

    2014-03-01

    The accurate measurement of time lies at the heart of experimental science, and is relevant to everyday life. Extending chronoscopy to ever shorter timescales has been the key to gaining real-time insights into microscopic phenomena, ranging from vital biological processes to the dynamics underlying high technologies. The generation of isolated attosecond pulses in 2001 allowed the fastest of all motions outside the nucleus -- electron dynamics in atomic systems -- to be captured. Attosecond metrology has provided access to several hitherto immeasurably fast electron phenomena in atoms, molecules and solids. The fundamental importance of electron processes for the physical and life sciences, technology and medicine has rendered the young field of attosecond science one of the most dynamically expanding research fields of the new millennium. Here, we review the basic concepts underlying attosecond measurement and control techniques. Among their many potential applications, we focus on the exploration of the fundamental speed limit of electronic signal processing. This endeavour relies on ultimate-speed electron metrology, as provided by attosecond technology.

  7. A nonlinear optoelectronic filter for electronic signal processing.

    PubMed

    Loh, William; Yegnanarayanan, Siva; Ram, Rajeev J; Juodawlkis, Paul W

    2014-01-01

    The conversion of electrical signals into modulated optical waves and back into electrical signals provides the capacity for low-loss radio-frequency (RF) signal transfer over optical fiber. Here, we show that the unique properties of this microwave-photonic link also enable the manipulation of RF signals beyond what is possible in conventional systems. We achieve these capabilities by realizing a novel nonlinear filter, which acts to suppress a stronger RF signal in the presence of a weaker signal independent of their separation in frequency. Using this filter, we demonstrate a relative suppression of 56 dB for a stronger signal having a 1-GHz center frequency, uncovering the presence of otherwise undetectable weaker signals located as close as 3.5 Hz away. The capabilities of the optoelectronic filter break the conventional limits of signal detection, opening up new possibilities for radar and communication systems, and for the field of precision frequency metrology. PMID:24402418

  8. A nonlinear optoelectronic filter for electronic signal processing

    PubMed Central

    Loh, William; Yegnanarayanan, Siva; Ram, Rajeev J.; Juodawlkis, Paul W.

    2014-01-01

    The conversion of electrical signals into modulated optical waves and back into electrical signals provides the capacity for low-loss radio-frequency (RF) signal transfer over optical fiber. Here, we show that the unique properties of this microwave-photonic link also enable the manipulation of RF signals beyond what is possible in conventional systems. We achieve these capabilities by realizing a novel nonlinear filter, which acts to suppress a stronger RF signal in the presence of a weaker signal independent of their separation in frequency. Using this filter, we demonstrate a relative suppression of 56?dB for a stronger signal having a 1-GHz center frequency, uncovering the presence of otherwise undetectable weaker signals located as close as 3.5?Hz away. The capabilities of the optoelectronic filter break the conventional limits of signal detection, opening up new possibilities for radar and communication systems, and for the field of precision frequency metrology. PMID:24402418

  9. A nonlinear optoelectronic filter for electronic signal processing

    NASA Astrophysics Data System (ADS)

    Loh, William; Yegnanarayanan, Siva; Ram, Rajeev J.; Juodawlkis, Paul W.

    2014-01-01

    The conversion of electrical signals into modulated optical waves and back into electrical signals provides the capacity for low-loss radio-frequency (RF) signal transfer over optical fiber. Here, we show that the unique properties of this microwave-photonic link also enable the manipulation of RF signals beyond what is possible in conventional systems. We achieve these capabilities by realizing a novel nonlinear filter, which acts to suppress a stronger RF signal in the presence of a weaker signal independent of their separation in frequency. Using this filter, we demonstrate a relative suppression of 56 dB for a stronger signal having a 1-GHz center frequency, uncovering the presence of otherwise undetectable weaker signals located as close as 3.5 Hz away. The capabilities of the optoelectronic filter break the conventional limits of signal detection, opening up new possibilities for radar and communication systems, and for the field of precision frequency metrology.

  10. Optical hybrid analog-digital signal processing based on spike processing in neurons

    NASA Astrophysics Data System (ADS)

    Fok, Mable P.; Tian, Yue; Rosenbluth, David; Deng, Yanhua; Prucnal, Paul R.

    2011-09-01

    Spike processing is one kind of hybrid analog-digital signal processing, which has the efficiency of analog processing and the robustness to noise of digital processing. When instantiated with optics, a hybrid analog-digital processing primitive has the potential to be scalable, computationally powerful, and have high operation bandwidth. These devices open up a range of processing applications for which electronic processing is too slow. Our approach is based on a hybrid analog/digital computational primitive that elegantly implements the functionality of an integrate-and-fire neuron using a Ge-doped non-linear optical fiber and off-the-shelf semiconductor devices. In this paper, we introduce our photonic neuron architecture and demonstrate the feasibility of implementing simple photonic neuromorphic circuits, including the auditory localization algorithm of the barn owl, which is useful for LIDAR localization, and the crayfish tail-flip escape response.

  11. Correlative intravital imaging of cGMP signals and vasodilation in mice

    PubMed Central

    Thunemann, Martin; Schmidt, Kjestine; de Wit, Cor; Han, Xiaoxing; Jain, Rakesh K.; Fukumura, Dai; Feil, Robert

    2014-01-01

    Cyclic guanosine monophosphate (cGMP) is an important signaling molecule and drug target in the cardiovascular system. It is well known that stimulation of the vascular nitric oxide (NO)-cGMP pathway results in vasodilation. However, the spatiotemporal dynamics of cGMP signals themselves and the cGMP concentrations within specific cardiovascular cell types in health, disease, and during pharmacotherapy with cGMP-elevating drugs are largely unknown. To facilitate the analysis of cGMP signaling in vivo, we have generated transgenic mice that express fluorescence resonance energy transfer (FRET)-based cGMP sensor proteins. Here, we describe two models of intravital FRET/cGMP imaging in the vasculature of cGMP sensor mice: (1) epifluorescence-based ratio imaging in resistance-type vessels of the cremaster muscle and (2) ratio imaging by multiphoton microscopy within the walls of subcutaneous blood vessels accessed through a dorsal skinfold chamber. Both methods allow simultaneous monitoring of NO-induced cGMP transients and vasodilation in living mice. Detailed protocols of all steps necessary to perform and evaluate intravital imaging experiments of the vasculature of anesthetized mice including surgery, imaging, and data evaluation are provided. An image segmentation approach is described to estimate FRET/cGMP changes within moving structures such as the vessel wall during vasodilation. The methods presented herein should be useful to visualize cGMP or other biochemical signals that are detectable with FRET-based biosensors, such as cyclic adenosine monophosphate or Ca2+, and to correlate them with respective vascular responses. With further refinement and combination of transgenic mouse models and intravital imaging technologies, we envision an exciting future, in which we are able to “watch” biochemistry, (patho-)physiology, and pharmacotherapy in the context of a living mammalian organism. PMID:25352809

  12. Study of cross-correlation signals in a data-driven approach for damage classification in aircraft wings

    NASA Astrophysics Data System (ADS)

    Camacho-Navarro, Jhonatan; Ruiz, Magda; Villamizar, Rodolfo; Mujica, Luis; Güemes, Alfredo; González-Requema, Ignacio

    2015-07-01

    This paper discusses, experimental results of classifying several mass adding in a wing aircraft structure, using cross-correlated piezoelectric signals, represented by principal components. Piezoelectric signals are applied and recorded at specific points of the structure under analysis. Then, statistical features are obtained by means of principal component analysis to the correlation between excitation and response signals. Unsupervised learning is implemented to the reduced feature space, in order to identify clusters of damaged cases. The main result of this paper is the advantage resulting from using cross-correlated signals, evaluated through the performance of clustering indexes. Experimental data are collected from two test structures: i.) A turbine blade of a commercial aircraft and ii.) The skin panel of the torsion box of a wing. Damages are induced adding masses at different locations of the wing section surface. The results obtained show the effectiveness of the methodology to distinguish between different damage cases.

  13. IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 52, NO. 7, JULY 2004 1891 A Blind Particle Filtering Detector of Signals

    E-print Network

    ´, Senior Member, IEEE Abstract--A new particle filtering detector (PFD) is proposed for blind signal detection, least mean square, particle filtering detector, recursive least square. I. INTRODUCTIONIEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 52, NO. 7, JULY 2004 1891 A Blind Particle Filtering

  14. Exploration, processing and visualization of physiological signals from the ICU

    E-print Network

    Renjifo, Carlos A

    2005-01-01

    This report studies physiological signals measured from patients in the Intensive Care Unit (ICU). The signals explored include heart rate, arterial blood pressure, pulmonary artery pressure, and central venous pressure ...

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

    E-print Network

    Xie, Yao

    For MIMO Radar Petre Stoica, Fellow, IEEE, Jian Li, Fellow, IEEE, and Yao Xie, Student Member, IEEE Abstract--A multiple-input multiple-output (MIMO) radar system, unlike a standard phased-array radar, can the cross-correlation of the signals reflected back to the radar by the targets of interest. In this paper

  16. Playback of beyond high definition video signal in holographic data storage system with wavefront compensation and parallel signal processing

    NASA Astrophysics Data System (ADS)

    Muroi, Tetsuhiko; Kinoshita, Nobuhiro; Ishii, Norihiko; Kamijo, Koji; Kikuchi, Hiroshi

    2014-09-01

    We have developed a holographic data storage system that can demonstrate real-time playback of beyond high definition video signals. In the proposed system, to increase the data-transfer rate of the reproduced data, we focused on improving the SNR of the reproduced data and on improving the signal processing speed, which the SNR of the reproduced data has a significant effect on. One of the factors that deteriorate the SNR is shrinkage in the medium. This shrinkage distorts recorded holograms and degrades the quality of the reproduced data. We investigated wavefront compensation as a means to improve the SNR of reproduced data degraded by hologram distortion and found that controlling the defocus component of the reference beam is effective. We have also been developing parallel signal processing to increase the data-transfer rate. We placed three GPUs in the signal processing unit: one for the reproduced data detection from the reconstructed image and two for the LDPC decoding for error correction of the reproduced data. The LDPC decoding required a lot more time than the data detection, so we designed a signal processing in which detected data in the GPU for the data detection were sent to the two GPUs for the LDPC decoding alternatively. We implemented wavefront compensation for the defocus component and developed parallel signal processing with three GPUs for our holographic data storage system. Using this system, we demonstrated real-time playback of beyond high definition video signals with 50 Mbps.

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

    PubMed Central

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

    2013-01-01

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

  18. Differential auditory signal processing in an animal model

    NASA Astrophysics Data System (ADS)

    Lim, Dukhwan; Kim, Chongsun; Chang, Sun O.

    2002-05-01

    Auditory evoked responses were collected in male zebra finches (Poephila guttata) to objectively determine differential frequency selectivity. First, the mating call of the animal was recorded and analyzed for its frequency components through the customized program. Then, auditory brainstem responses and cortical responses of each anesthetized animal were routinely recorded in response to tone bursts of 1-8 kHz derived from the corresponding mating call spectrum. From the results, most mating calls showed relatively consistent spectral structures. The upper limit of the spectrum was well under 10 kHz. The peak energy bands were concentrated in the region less than 5 kHz. The assessment of auditory brainstem responses and cortical evoked potentials showed differential selectivity with a series of characteristic scales. This system appears to be an excellent model to investigate complex sound processing and related language behaviors. These data could also be used in designing effective signal processing strategies in auditory rehabilitation devices such as hearing aids and cochlear implants. [Work supported by Brain Science & Engineering Program from Korean Ministry of Science and Technology.

  19. Optimal Signal Processing of Frequency-Stepped CW Radar Data

    NASA Technical Reports Server (NTRS)

    Ybarra, Gary A.; Wu, Shawkang M.; Bilbro, Griff L.; Ardalan, Sasan H.; Hearn, Chase P.; Neece, Robert T.

    1995-01-01

    An optimal signal processing algorithm is derived for estimating the time delay and amplitude of each scatterer reflection using a frequency-stepped CW system. The channel is assumed to be composed of abrupt changes in the reflection coefficient profile. The optimization technique is intended to maximize the target range resolution achievable from any set of frequency-stepped CW radar measurements made in such an environment. The algorithm is composed of an iterative two-step procedure. First, the amplitudes of the echoes are optimized by solving an overdetermined least squares set of equations. Then, a nonlinear objective function is scanned in an organized fashion to find its global minimum. The result is a set of echo strengths and time delay estimates. Although this paper addresses the specific problem of resolving the time delay between the first two echoes, the derivation is general in the number of echoes. Performance of the optimization approach is illustrated using measured data obtained from an HP-X510 network analyzer. It is demonstrated that the optimization approach offers a significant resolution enhancement over the standard processing approach that employs an IFFT. Degradation in the performance of the algorithm due to suboptimal model order selection and the effects of additive white Gaussion noise are addressed.

  20. Optimal Signal Processing of Frequency-Stepped CW Radar Data

    NASA Technical Reports Server (NTRS)

    Ybarra, Gary A.; Wu, Shawkang M.; Bilbro, Griff L.; Ardalan, Sasan H.; Hearn, Chase P.; Neece, Robert T.

    1995-01-01

    An optimal signal processing algorithm is derived for estimating the time delay and amplitude of each scatterer reflection using a frequency-stepped CW system. The channel is assumed to be composed of abrupt changes in the reflection coefficient profile. The optimization technique is intended to maximize the target range resolution achievable from any set of frequency-stepped CW radar measurements made in such an environment. The algorithm is composed of an iterative two-step procedure. First, the amplitudes of the echoes are optimized by solving an overdetermined least squares set of equations. Then, a nonlinear objective function is scanned in an organized fashion to find its global minimum. The result is a set of echo strengths and time delay estimates. Although this paper addresses the specific problem of resolving the time delay between the two echoes, the derivation is general in the number of echoes. Performance of the optimization approach is illustrated using measured data obtained from an HP-851O network analyzer. It is demonstrated that the optimization approach offers a significant resolution enhancement over the standard processing approach that employs an IFFT. Degradation in the performance of the algorithm due to suboptimal model order selection and the effects of additive white Gaussion noise are addressed.

  1. Correlations between the Signal Complexity of Cerebral and Cardiac Electrical Activity: A Multiscale Entropy Analysis

    PubMed Central

    Lin, Pei-Feng; Lo, Men-Tzung; Tsao, Jenho; Chang, Yi-Chung; Lin, Chen; Ho, Yi-Lwun

    2014-01-01

    The heart begins to beat before the brain is formed. Whether conventional hierarchical central commands sent by the brain to the heart alone explain all the interplay between these two organs should be reconsidered. Here, we demonstrate correlations between the signal complexity of brain and cardiac activity. Eighty-seven geriatric outpatients with healthy hearts and varied cognitive abilities each provided a 24-hour electrocardiography (ECG) and a 19-channel eye-closed routine electroencephalography (EEG). Multiscale entropy (MSE) analysis was applied to three epochs (resting-awake state, photic stimulation of fast frequencies (fast-PS), and photic stimulation of slow frequencies (slow-PS)) of EEG in the 1–58 Hz frequency range, and three RR interval (RRI) time series (awake-state, sleep and that concomitant with the EEG) for each subject. The low-to-high frequency power (LF/HF) ratio of RRI was calculated to represent sympatho-vagal balance. With statistics after Bonferroni corrections, we found that: (a) the summed MSE value on coarse scales of the awake RRI (scales 11–20, RRI-MSE-coarse) were inversely correlated with the summed MSE value on coarse scales of the resting-awake EEG (scales 6–20, EEG-MSE-coarse) at Fp2, C4, T6 and T4; (b) the awake RRI-MSE-coarse was inversely correlated with the fast-PS EEG-MSE-coarse at O1, O2 and C4; (c) the sleep RRI-MSE-coarse was inversely correlated with the slow-PS EEG-MSE-coarse at Fp2; (d) the RRI-MSE-coarse and LF/HF ratio of the awake RRI were correlated positively to each other; (e) the EEG-MSE-coarse at F8 was proportional to the cognitive test score; (f) the results conform to the cholinergic hypothesis which states that cognitive impairment causes reduction in vagal cardiac modulation; (g) fast-PS significantly lowered the EEG-MSE-coarse globally. Whether these heart-brain correlations could be fully explained by the central autonomic network is unknown and needs further exploration. PMID:24498375

  2. Correlations between the signal complexity of cerebral and cardiac electrical activity: a multiscale entropy analysis.

    PubMed

    Lin, Pei-Feng; Lo, Men-Tzung; Tsao, Jenho; Chang, Yi-Chung; Lin, Chen; Ho, Yi-Lwun

    2014-01-01

    The heart begins to beat before the brain is formed. Whether conventional hierarchical central commands sent by the brain to the heart alone explain all the interplay between these two organs should be reconsidered. Here, we demonstrate correlations between the signal complexity of brain and cardiac activity. Eighty-seven geriatric outpatients with healthy hearts and varied cognitive abilities each provided a 24-hour electrocardiography (ECG) and a 19-channel eye-closed routine electroencephalography (EEG). Multiscale entropy (MSE) analysis was applied to three epochs (resting-awake state, photic stimulation of fast frequencies (fast-PS), and photic stimulation of slow frequencies (slow-PS)) of EEG in the 1-58 Hz frequency range, and three RR interval (RRI) time series (awake-state, sleep and that concomitant with the EEG) for each subject. The low-to-high frequency power (LF/HF) ratio of RRI was calculated to represent sympatho-vagal balance. With statistics after Bonferroni corrections, we found that: (a) the summed MSE value on coarse scales of the awake RRI (scales 11-20, RRI-MSE-coarse) were inversely correlated with the summed MSE value on coarse scales of the resting-awake EEG (scales 6-20, EEG-MSE-coarse) at Fp2, C4, T6 and T4; (b) the awake RRI-MSE-coarse was inversely correlated with the fast-PS EEG-MSE-coarse at O1, O2 and C4; (c) the sleep RRI-MSE-coarse was inversely correlated with the slow-PS EEG-MSE-coarse at Fp2; (d) the RRI-MSE-coarse and LF/HF ratio of the awake RRI were correlated positively to each other; (e) the EEG-MSE-coarse at F8 was proportional to the cognitive test score; (f) the results conform to the cholinergic hypothesis which states that cognitive impairment causes reduction in vagal cardiac modulation; (g) fast-PS significantly lowered the EEG-MSE-coarse globally. Whether these heart-brain correlations could be fully explained by the central autonomic network is unknown and needs further exploration. PMID:24498375

  3. Monitoring and predicting cognitive state and performance via physiological correlates of neuronal signals.

    PubMed

    Russo, Michael B; Stetz, Melba C; Thomas, Maria L

    2005-07-01

    Judgment, decision making, and situational awareness are higher-order mental abilities critically important to operational cognitive performance. Higher-order mental abilities rely on intact functioning of multiple brain regions, including the prefrontal, thalamus, and parietal areas. Real-time monitoring of individuals for cognitive performance capacity via an approach based on sampling multiple neurophysiologic signals and integrating those signals with performance prediction models potentially provides a method of supporting warfighters' and commanders' decision making and other operationally relevant mental processes and is consistent with the goals of augmented cognition. Cognitive neurophysiological assessments that directly measure brain function and subsequent cognition include positron emission tomography, functional magnetic resonance imaging, mass spectroscopy, near-infrared spectroscopy, magnetoencephalography, and electroencephalography (EEG); however, most direct measures are not practical to use in operational environments. More practical, albeit indirect measures that are generated by, but removed from the actual neural sources, are movement activity, oculometrics, heart rate, and voice stress signals. The goal of the papers in this section is to describe advances in selected direct and indirect cognitive neurophysiologic monitoring techniques as applied for the ultimate purpose of preventing operational performance failures. These papers present data acquired in a wide variety of environments, including laboratory, simulator, and clinical arenas. The papers discuss cognitive neurophysiologic measures such as digital signal processing wrist-mounted actigraphy; oculometrics including blinks, saccadic eye movements, pupillary movements, the pupil light reflex; and high-frequency EEG. These neurophysiological indices are related to cognitive performance as measured through standard test batteries and simulators with conditions including sleep loss, time on task, and aviation flight-induced fatigue. PMID:16018331

  4. Clay content evaluation in soils through GPR signal processing

    NASA Astrophysics Data System (ADS)

    Tosti, Fabio; Patriarca, Claudio; Slob, Evert; Benedetto, Andrea; Lambot, Sébastien

    2013-10-01

    The mechanical behavior of soils is partly affected by their clay content, which arises some important issues in many fields of employment, such as civil and environmental engineering, geology, and agriculture. This work focuses on pavement engineering, although the method applies to other fields of interest. Clay content in bearing courses of road pavement frequently causes damages and defects (e.g., cracks, deformations, and ruts). Therefore, the road safety and operability decreases, directly affecting the increase of expected accidents. In this study, different ground-penetrating radar (GPR) methods and techniques were used to non-destructively investigate the clay content in sub-asphalt compacted soils. Experimental layout provided the use of typical road materials, employed for road bearing courses construction. Three types of soils classified by the American Association of State Highway and Transportation Officials (AASHTO) as A1, A2, and A3 were used and adequately compacted in electrically and hydraulically isolated test boxes. Percentages of bentonite clay were gradually added, ranging from 2% to 25% by weight. Analyses were carried out for each clay content using two different GPR instruments. A pulse radar with ground-coupled antennae at 500 MHz centre frequency and a vector network analyzer spanning the 1-3 GHz frequency range were used. Signals were processed in both time and frequency domains, and the consistency of results was validated by the Rayleigh scattering method, the full-waveform inversion, and the signal picking techniques. Promising results were obtained for the detection of clay content affecting the bearing capacity of sub-asphalt layers.

  5. Implementation of Hearing Aid Signal Processing Algorithms on the TI DHP-100 Platform

    E-print Network

    Chamberlain, Roger

    Implementation of Hearing Aid Signal Processing Algorithms on the TI DHP-100 Platform Roger D, "Implementation of Hearing Aid Signal Processing Algorithms on the TI DHP-100 Platform," in Proc. of 37th Asilomar Conf. on Signals, Systems and Computers, November 2003. BECS Technology, Inc. and Hearing Emulations

  6. PROCESSING OF SONAR SIGNALS USING NEURAL NETWORKS FOR ROBUST TARGET DIFFERENTIATION

    E-print Network

    Barshan, Billur

    PROCESSING OF SONAR SIGNALS USING NEURAL NETWORKS FOR ROBUST TARGET DIFFERENTIATION Birsel Ayrulu ABSTRACT This study investigates the processing of sonar signals using neural networks for robust di is of interest for intel- ligent systems. Amplitude and time-of- ight TOF patterns of sonar signals acquired from

  7. Impact of Architecture Extensions for Media Signal Processing on Data-Path Organization

    E-print Network

    Oklobdzija, Vojin G.

    in consumer electronic products, such as personal digital assistants, cellular phones, video games, digital of multiple data types, including digital videos, digital audio, computer arithmetic, text and graphics. Media processing of audio and video signals. Real-time signal processing of audio/video signals is necessary

  8. header for SPIE use Computer Arithmetic for the Processing of Media Signals

    E-print Network

    Oklobdzija, Vojin G.

    in consumer electronic products, such as personal digital assistants, cellular phones, video games, digital of multiple data types, including digital videos, digital audio, computer arithmetic, text and graphics. Media processing of audio and video signals. Real-time signal processing of audio/video signals is necessary

  9. Power Signal Processing: A New Perspective for Power Analysis and Optimization

    E-print Network

    Zhong, Lin

    or distributed signals. A component can be a gate, ALU, processor core, or even an entire chip on a printed-circuit board. Then, we explore advanced signal processing and pattern analysis techniques to study the powerPower Signal Processing: A New Perspective for Power Analysis and Optimization Quming Zhou, Lin

  10. Chatter, process damping, and chip segmentation in turning: A signal processing approach

    NASA Astrophysics Data System (ADS)

    Taylor, Christopher M.; Turner, Sam; Sims, Neil D.

    2010-11-01

    An increasing number of aerospace components are manufactured from titanium and nickel alloys that are difficult to machine due to their thermal and mechanical properties. This limits the metal removal rates that can be achieved from the production process. However, under these machining conditions the phenomenon of process damping can be exploited to help avoid self-excited vibrations known as regenerative chatter. This means that greater widths of cut can be taken so as to increase the metal removal rate, and hence offset the cutting speed restrictions that are imposed by the thermo-mechanical properties of the material. However, there is little or no consensus as to the underlying mechanisms that cause process damping. The present study investigates two process damping mechanisms that have previously been proposed in the machining literature: the tool flank/workpiece interference effect, and the short regenerative effect. A signal processing procedure is employed to identify flank/workpiece interference from experimental data. Meanwhile, the short regenerative model is solved using a new frequency domain approach that yields additional insight into its stabilising effect. However, analysis and signal processing of the experimentally obtained data reveals that neither of these models can fully explain the increases in stability that are observed in practice. Meanwhile, chip segmentation effects were observed in a number of measurements, and it is suggested that segmentation could play an important role in the process-damped chatter stability of these materials.

  11. A Preferential Design Approach for Energy-Efficient and Robust Implantable Neural Signal Processing Hardware

    E-print Network

    Bhunia, Swarup

    -voltage, robust and area-efficient implementation using nanoscale process technology. The basic idea is to isolate-electrode array and analog signal conditioning and transceiver electronics. A recently proposed neural signal

  12. Neural correlates of impaired emotion processing in manifest Huntington's disease.

    PubMed

    Dogan, Imis; Saß, Christian; Mirzazade, Shahram; Kleiman, Alexandra; Werner, Cornelius J; Pohl, Anna; Schiefer, Johannes; Binkofski, Ferdinand; Schulz, Jörg B; Shah, N Jon; Reetz, Kathrin

    2014-05-01

    The complex phenotype of Huntington's disease (HD) encompasses motor, psychiatric and cognitive dysfunctions, including early impairments in emotion recognition. In this first functional magnetic resonance imaging study, we investigated emotion-processing deficits in 14 manifest HD patients and matched controls. An emotion recognition task comprised short video clips displaying one of six basic facial expressions (sadness, happiness, disgust, fear, anger and neutral). Structural changes between patients and controls were assessed by means of voxel-based morphometry. Along with deficient recognition of negative emotions, patients exhibited predominantly lower neural response to stimuli of negative valences in the amygdala, hippocampus, striatum, insula, cingulate and prefrontal cortices, as well as in sensorimotor, temporal and visual areas. Most of the observed reduced activity patterns could not be explained merely by regional volume loss. Reduced activity in the thalamus during fear correlated with lower thalamic volumes. During the processing of sadness, patients exhibited enhanced amygdala and hippocampal activity along with reduced recruitment of the medial prefrontal cortex. Higher amygdala activity was related to more pronounced amygdala atrophy and disease burden. Overall, the observed emotion-related dysfunctions in the context of structural neurodegeneration suggest both disruptions of striatal-thalamo-cortical loops and potential compensation mechanism with greater disease severity in manifest HD. PMID:23482620

  13. The expression of Wnt-1 inducible signaling pathway protein-2 in astrocytoma: Correlation between pathological grade and clinical outcome

    PubMed Central

    XIAO, GELEI; TANG, ZHI; YUAN, XIANRUI; YUAN, JIAN; ZHAO, JIE; ZHANG, ZHIPING; HE, ZHENGWEN; LIU, JINGPING

    2015-01-01

    Wnt-1 inducible signaling pathway protein-2 (WISP-2) is a member of the CCN family, which is critical for the control of cell morphology, motion, adhesion and other processes involved in tumorigenesis. The expression pattern and clinical significance of WISP-2 in astrocytomas remains unclear. In this study, reverse transcription-polymerase chain reaction was performed to systematically investigate the expression of WISP-2 in 47 astrocytoma tissues of different pathological grades and 10 normal brain tissues. The mRNA expression levels of WISP-2 in the astrocytoma tissues were observed to be significantly higher than those in the normal brain tissues. Furthermore, the upregulation of WISP-2 was found to be associated with astrocytomas of higher pathological grades. Subsequently, 154 astrocytoma and 15 normal brain tissues were analyzed using immunohistochemistry and similar results were obtained. Univariate and multivariate survival analyses were used to determine the correlations between WISP-2 expression and overall survival (OS) and progression-free survival (PFS). The results indicated that the expression of WISP-2 was found to negatively correlate with patient PFS and OS. These results demonstrated that the WISP-2 protein is involved in the pathogenesis and progression of human astrocytomas and may serve as a malignant biomarker of this disease. PMID:25435966

  14. Programmable rate modem utilizing digital signal processing techniques

    NASA Technical Reports Server (NTRS)

    Bunya, George K.; Wallace, Robert L.

    1989-01-01

    The engineering development study to follow was written to address the need for a Programmable Rate Digital Satellite Modem capable of supporting both burst and continuous transmission modes with either binary phase shift keying (BPSK) or quadrature phase shift keying (QPSK) modulation. The preferred implementation technique is an all digital one which utilizes as much digital signal processing (DSP) as possible. Here design tradeoffs in each portion of the modulator and demodulator subsystem are outlined, and viable circuit approaches which are easily repeatable, have low implementation losses and have low production costs are identified. The research involved for this study was divided into nine technical papers, each addressing a significant region of concern in a variable rate modem design. Trivial portions and basic support logic designs surrounding the nine major modem blocks were omitted. In brief, the nine topic areas were: (1) Transmit Data Filtering; (2) Transmit Clock Generation; (3) Carrier Synthesizer; (4) Receive AGC; (5) Receive Data Filtering; (6) RF Oscillator Phase Noise; (7) Receive Carrier Selectivity; (8) Carrier Recovery; and (9) Timing Recovery.

  15. Protein import into plant mitochondria: signals, machinery, processing, and regulation.

    PubMed

    Murcha, Monika W; Kmiec, Beata; Kubiszewski-Jakubiak, Szymon; Teixeira, Pedro F; Glaser, Elzbieta; Whelan, James

    2014-12-01

    The majority of more than 1000 proteins present in mitochondria are imported from nuclear-encoded, cytosolically synthesized precursor proteins. This impressive feat of transport and sorting is achieved by the combined action of targeting signals on mitochondrial proteins and the mitochondrial protein import apparatus. The mitochondrial protein import apparatus is composed of a number of multi-subunit protein complexes that recognize, translocate, and assemble mitochondrial proteins into functional complexes. While the core subunits involved in mitochondrial protein import are well conserved across wide phylogenetic gaps, the accessory subunits of these complexes differ in identity and/or function when plants are compared with Saccharomyces cerevisiae (yeast), the model system for mitochondrial protein import. These differences include distinct protein import receptors in plants, different mechanistic operation of the intermembrane protein import system, the location and activity of peptidases, the function of inner-membrane translocases in linking the outer and inner membrane, and the association/regulation of mitochondrial protein import complexes with components of the respiratory chain. Additionally, plant mitochondria share proteins with plastids, i.e. dual-targeted proteins. Also, the developmental and cell-specific nature of mitochondrial biogenesis is an aspect not observed in single-celled systems that is readily apparent in studies in plants. This means that plants provide a valuable model system to study the various regulatory processes associated with protein import and mitochondrial biogenesis. PMID:25324401

  16. The analog signal processing board for the HEAT telescopes

    NASA Astrophysics Data System (ADS)

    Ambrosio, M.; Aramo, C.; Boiano, A.; Cilmo, M.; D'Urso, D.; Guarino, F.; Mangone, C.; Valore, L.; Yushkov, A.

    2011-12-01

    The aim of the Pierre Auger Observatory is to measure with high statistics the flux, the arrival directions and the mass composition of cosmic rays at the highest energies. Since 2009, the Auger Collaboration has added three new High Elevation Auger Telescopes (HEAT) along with a new 25 km 2 infill array in the field of view of the new telescopes. These enhancements have lowered the energy threshold of the Observatory by about an order of magnitude. In combination with the existing telescopes in Coihueco the vertical field of view is extended to about 60°, allowing the measurement of nearby air showers arising from primaries with energies as low as 2×10 17 eV. In this paper we describe the new front-end analog board developed to process the signals generated by the photomultipliers of the HEAT telescopes. Eighty analog boards have been produced, fully characterized and tested. The main characteristics of the electronic circuits and the circuit parameters are illustrated.

  17. Cryogenic loss monitors with FPGA TDC signal processing

    SciTech Connect

    Warner, A.; Wu, J.; /Fermilab

    2011-09-01

    Radiation hard helium gas ionization chambers capable of operating in vacuum at temperatures ranging from 5K to 350K have been designed, fabricated and tested and will be used inside the cryostats at Fermilab's Superconducting Radiofrequency beam test facility. The chamber vessels are made of stainless steel and all materials used including seals are known to be radiation hard and suitable for operation at 5K. The chambers are designed to measure radiation up to 30 kRad/hr with sensitivity of approximately 1.9 pA/(Rad/hr). The signal current is measured with a recycling integrator current-to-frequency converter to achieve a required measurement capability for low current and a wide dynamic range. A novel scheme of using an FPGA-based time-to-digital converter (TDC) to measure time intervals between pulses output from the recycling integrator is employed to ensure a fast beam loss response along with a current measurement resolution better than 10-bit. This paper will describe the results obtained and highlight the processing techniques used.

  18. Signal Processing for a Lunar Array: Minimizing Power Consumption

    NASA Technical Reports Server (NTRS)

    D'Addario, Larry; Simmons, Samuel

    2011-01-01

    Motivation for the study is: (1) Lunar Radio Array for low frequency, high redshift Dark Ages/Epoch of Reionization observations (z =6-50, f=30-200 MHz) (2) High precision cosmological measurements of 21 cm H I line fluctuations (3) Probe universe before first star formation and provide information about the Intergalactic Medium and evolution of large scale structures (5) Does the current cosmological model accurately describe the Universe before reionization? Lunar Radio Array is for (1) Radio interferometer based on the far side of the moon (1a) Necessary for precision measurements, (1b) Shielding from earth-based and solar RFI (12) No permanent ionosphere, (2) Minimum collecting area of approximately 1 square km and brightness sensitivity 10 mK (3)Several technologies must be developed before deployment The power needed to process signals from a large array of nonsteerable elements is not prohibitive, even for the Moon, and even in current technology. Two different concepts have been proposed: (1) Dark Ages Radio Interferometer (DALI) (2)( Lunar Array for Radio Cosmology (LARC)

  19. Material and process optimization of correlated electron random access memories

    NASA Astrophysics Data System (ADS)

    Celinska, Jolanta; McWilliams, Christopher; Paz de Araujo, Carlos; Xue, Kan-Hao

    2011-05-01

    A method of making transition metal oxide materials that result in resistive switching properties stable over time and temperature is described. We have developed an ultra low temperature (?450°C) process for carbonyl ligand modified NiO thin films based on the chemical solution deposition (CSD) for correlated electron random access memory (CeRAM) applications. CeRAMs form the general class of devices that use the electron-electron interaction as the primary mode of operation. These devices are fabricated in the conductive state (born-ON), thus, they do not require electroforming to enter the variable resistance state. Several process parameters such as film stoichiometry, thickness, annealing temperature and ambient have been investigated to optimize CeRAMs properties. We present the coordination number `fine tuning' in NiO ultra thin films via carbonyl ligand doping that regulate the number of oxygen vacancies and the surface excess of metal ions. CeRAMs contrary to just standard NiO based resistive memories use the pure Mott-like charge transfer insulator in which an abrupt metal to insulator transition is the dominant mechanism without the aid of charge trapping vacancies. In our films the effect of the oxygen vacancies are canceled due to the stabilizing effect of the carbonyl based extrinsic ligand. In this paper, detailed process sequence and the extrinsic ligand doping scheme is described in some length. It is shown that complexes formed by the introduction of the extrinsic ligand promote Ni2+ ions to enter the disproportionation reaction Ni2+ + Ni2+?Ni1+ + Ni3+ which is considered to be responsible for the memory mechanism.

  20. Detection and Processing Techniques of FECG Signal for Fetal Monitoring

    PubMed Central

    2009-01-01

    Fetal electrocardiogram (FECG) signal contains potentially precise information that could assist clinicians in making more appropriate and timely decisions during labor. The ultimate reason for the interest in FECG signal analysis is in clinical diagnosis and biomedical applications. The extraction and detection of the FECG signal from composite abdominal signals with powerful and advance methodologies are becoming very important requirements in fetal monitoring. The purpose of this review paper is to illustrate the various methodologies and developed algorithms on FECG signal detection and analysis to provide efficient and effective ways of understanding the FECG signal and its nature for fetal monitoring. A comparative study has been carried out to show the performance and accuracy of various methods of FECG signal analysis for fetal monitoring. Finally, this paper further focused some of the hardware implementations using electrical signals for monitoring the fetal heart rate. This paper opens up a passage for researchers, physicians, and end users to advocate an excellent understanding of FECG signal and its analysis procedures for fetal heart rate monitoring system. PMID:19495912

  1. Signal processing and statistical descriptive reanalysis of steady state chute-flow experiments

    NASA Astrophysics Data System (ADS)

    truong, hoan; eckert, nicolas; keylock, chris; naaim, mohamed; bellot, hervé

    2014-05-01

    An accurate knowledge of snow rheology is needed for the mitigation against avalanche hazard. Indeed snow avalanches have a significant impact on the livelihoods and economies of alpine communities. To do so, 60 small-scale in-situ flow experiments were performed with various slopes, temperatures and flow depths. The investigation of these data previously seemed to show the dense flow of dry snow may be composed of two layers; a sheared basal layer made of single snow grains and a less sheared upper layer made of large aggregates. These outcomes were mainly based on the mean velocity profile of the flow and on interpretation in terms of rheological behavior of granular materials and snow microstructure [Pierre G. Rognon et al., 2007]. Here, the main objective remains the same, but the rheological and physical viewpoints are put aside to extract as much information contained in the data as possible various using signal processing methods and descriptive statistics methods as the maximum overlap discrete wavelet transform (MODWT), transfer entropy (TE) and maximum cross-correlation (MCC). Specifically, we aim at the improving the velocity estimations as function of the depth particularly the velocity fluctuations around the mean profile to better document the behavior of dense dry snow flows during a steady and uniform chute regime. The data are composed of pairs of voltage signals (right and left), which makes that the velocity is known indirectly only. The MCC method is classically used to determine the time lag between both signals. Previously, the MCC method that showed the mean velocity profile may be fitted by a simple bilinear function [Pierre G. Rognon et al., 2007], but no interesting temporal dynamics could be highlighted. Hence, a new process method was developed to provide velocity series with much better temporal resolution. The process is mainly made of a MODWT-based denoising method and the choice of window size for correlation. The results prove to be good enough in term of reasonable variability and measurement numbers. A statistical descriptive analysis of the velocity results shows a disagreement with the previous outcomes. Indeed, the clustering method and the empirical probability distribution functions show that the vertical velocity profile may reflect three different behaviors, possibly corresponding to three layers and/or to transient flow layers. These flow layers are located at different heights depending on initial conditions of flow experiments (temperature, slope and depth). Keywords: Maximum cross correlation, MODWT, probability distribution function

  2. Quantitative confocal fluorescence microscopy of dynamic processes by multifocal fluorescence correlation spectroscopy

    NASA Astrophysics Data System (ADS)

    Krmpot, Aleksandar J.; Nikoli?, Stanko N.; Vitali, Marco; Papadopoulos, Dimitrios K.; Oasa, Sho; Thyberg, Per; Tisa, Simone; Kinjo, Masataka; Nilsson, Lennart; Gehring, Walter J.; Terenius, Lars; Rigler, Rudolf; Vukojevic, Vladana

    2015-07-01

    Quantitative confocal fluorescence microscopy imaging without scanning is developed for the study of fast dynamical processes. The method relies on the use of massively parallel Fluorescence Correlation Spectroscopy (mpFCS). Simultaneous excitation of fluorescent molecules across the specimen is achieved by passing a single laser beam through a Diffractive Optical Element (DOE) to generate a quadratic illumination matrix of 32×32 light sources. Fluorescence from 1024 illuminated spots is detected in a confocal arrangement by a matching matrix detector consisting of the same number of single-photon avalanche photodiodes (SPADs). Software was developed for data acquisition and fast autoand cross-correlation analysis by parallel signal processing using a Graphic Processing Unit (GPU). Instrumental performance was assessed using a conventional single-beam FCS instrument as a reference. Versatility of the approach for application in biomedical research was evaluated using ex vivo salivary glands from Drosophila third instar larvae expressing a fluorescently-tagged transcription factor Sex Combs Reduced (Scr) and live PC12 cells stably expressing the fluorescently tagged mu-opioid receptor (MOPeGFP). We show that quantitative mapping of local concentration and mobility of transcription factor molecules across the specimen can be achieved using this approach, which paves the way for future quantitative characterization of dynamical reaction-diffusion landscapes across live cells/tissue with a submillisecond temporal resolution (presently 21 ?s/frame) and single-molecule sensitivity.

  3. Correlation analysis of laser Doppler flowmetry signals: a potential non-invasive tool to assess microcirculatory changes in diabetes mellitus.

    PubMed

    Lal, Cerine; Unni, Sujatha Narayanan

    2015-06-01

    Measurement and analysis of microcirculation is vital in assessing local and systemic tissue health. Changes in microvascular perfusion if detected can provide information on the development of various related diseases. Laser Doppler blood flowmetry (LDF) provides a non-invasive real-time measurement of cutaneous blood perfusion. LDF signals possess fractal nature that represents the correlation in the successive signal elements. Changes in the correlation of flow and its associated parameters could be used as a tool in differentiating the ailments at different stages or assessing the treatment effectiveness of a particular ailment. Spectral domain analysis of LDF signals reveals five characteristic frequency peaks corresponding to local and central regulatory mechanisms of the human body, namely metabolic, neurogenic, myogenic, respiration, and heart rate. This paper investigates the changes in the fractal nature and constituent frequency bands of laser Doppler signals in diabetic and healthy control subjects acquired from the glabrous skin of the foot so as to provide an assessment of microcirculatory dynamics. As a pilot study, it was attempted on a set of healthy control and diabetic volunteers, and the obtained results indicate that fractal nature of LDF signals is less in diabetic subjects compared to the healthy control. The wavelet analysis carried out on the set of signals reveals the dynamics of blood flow which may have led to the difference in correlation results. PMID:25752769

  4. Design and implementation of a hybrid circuit system for micro sensor signal processing

    NASA Astrophysics Data System (ADS)

    Zhuping, Wang; Jing, Chen; Ruqing, Liu

    2011-04-01

    This paper covers a micro sensor analog signal processing circuit system (MASPS) chip with low power and a digital signal processing circuit board implementation including hardware connection and software design. Attention has been paid to incorporate the MASPS chip into the digital circuit board. The ultimate aim is to form a hybrid circuit used for mixed-signal processing, which can be applied to a micro sensor flow monitoring system.

  5. SU-E-J-253: Evaluation of 4DCT Images with Correlation of RPM Signals to Tumor Motion for Respiratory-Gated Radiotherapy

    SciTech Connect

    Lee, TK; Ewald, A; Schultz, T; Park, SY

    2014-06-01

    Purpose: The amplitudes of lung tumor target motion and RPM signals are different from each other. Also, RPM system does not have in-depth RPM signal analysis tool. We have developed an algorithm that analyzes RPM signals for its stability as well as correlativity to the tumor motion. Methods: We used a Philips Big Bore CT scanner with a Varian Real-Time Position Management™ (RPM) system attached. 4DCT images were reviewed and tumor motion amplitudes of full breathing in superior-inferior, anterior-posterior, and left-right directions were measured. RPM signals were analyzed with the algorithm developed with Matlab. Average signal period, amplitude and statistical stability of the full breathing pattern as well as the pattern around full expiration were calculated. RPM signal amplitudes were normalized to measured tumor motion amplitudes so that selected gating phases (30%–70% or 40%–60%) allow tumor motion under 5.0mm. Results: Twelve patient cases were analyzed in this study with GTV sizes ranged from 1.0cm to 3.0cm diameter. The periods and amplitudes of RPM signal ranged from 3.1seconds to 6.5seconds and from 0.2cm to 1.7cm, respectively. RPM signals were most stable at full expiration. The standard deviation of the RPM signal peaks at full expiration was <0.11cm, and that of gated amplitudes was <0.25cm. Tumor motion amplitudes were primary in superior-inferior direction and minor (<=0.2cm) in other directions on all analyzed cases, ranged from 0.2cm to 2.5cm. The amplitudes increases with the tumor located toward the diaphragm. The gated phases were selected so that the average gated tumor motion amplitude as well as that plus deviation became under 0.5cm in superior-inferior direction. Conclusion: We were able to determine the respiratory-gated phases in RPM signals employing measured tumor motion amplitudes as well as developed RPM signal analyzer through correlation process. The RPM signal amplitudes do not represent tumor motion because of its location.

  6. High-resolution correlation

    NASA Astrophysics Data System (ADS)

    Nelson, D. J.

    2007-09-01

    In the basic correlation process a sequence of time-lag-indexed correlation coefficients are computed as the inner or dot product of segments of two signals. The time-lag(s) for which the magnitude of the correlation coefficient sequence is maximized is the estimated relative time delay of the two signals. For discrete sampled signals, the delay estimated in this manner is quantized with the same relative accuracy as the clock used in sampling the signals. In addition, the correlation coefficients are real if the input signals are real. There have been many methods proposed to estimate signal delay to more accuracy than the sample interval of the digitizer clock, with some success. These methods include interpolation of the correlation coefficients, estimation of the signal delay from the group delay function, and beam forming techniques, such as the MUSIC algorithm. For spectral estimation, techniques based on phase differentiation have been popular, but these techniques have apparently not been applied to the correlation problem . We propose a phase based delay estimation method (PBDEM) based on the phase of the correlation function that provides a significant improvement of the accuracy of time delay estimation. In the process, the standard correlation function is first calculated. A time lag error function is then calculated from the correlation phase and is used to interpolate the correlation function. The signal delay is shown to be accurately estimated as the zero crossing of the correlation phase near the index of the peak correlation magnitude. This process is nearly as fast as the conventional correlation function on which it is based. For real valued signals, a simple modification is provided, which results in the same correlation accuracy as is obtained for complex valued signals.

  7. Signal processing for order 10 pm accuracy displacement metrology in real-world scientific applications

    NASA Technical Reports Server (NTRS)

    Halverson, Peter G.; Loya, Frank M.

    2004-01-01

    This paper describes heterodyne displacement metrology gauge signal processing methods that achieve satisfactory robustness against low signal strength and spurious signals, and good long-term stability. We have a proven displacement-measuring approach that is useful not only to space-optical projects at JPL, but also to the wider field of distance measurements.

  8. Parallelisation of Digital Signal Processing in Uniform and Reconfigurable Filter Banks for Satellite Communications

    E-print Network

    Göckler, Heinz G.

    of wide-band FDM-signals in conjunction with beam switching on-board a satellite. For this application and remultiplexing of (ultra-)wide-band FDM- signals require high end sample rates that, often, range beyond technological limit (e.g. > 1GHz). A remedy is to process the signals at a lower rate in a parallel manner

  9. Higgs boson production at hadron colliders: Signal and background processes

    SciTech Connect

    David Rainwater; Michael Spira; Dieter Zeppenfeld

    2004-01-12

    We review the theoretical status of signal and background calculations for Higgs boson production at hadron colliders. Particular emphasis is given to missing NLO results, which will play a crucial role for the Tevatron and the LHC.

  10. Signal processing and decision making in single cells

    E-print Network

    Mettetal, Jerome Thomas, II

    2008-01-01

    Cells are not simple passive observers oblivious to their environment, but sense and adapt to environmental changes in order to thrive. In addition to sensing the presence of signals in the environment, cells can extract ...

  11. Low cost analog signal processing for massive radio telescope arrays

    E-print Network

    Kunz, Eben A

    2012-01-01

    Measurement and analysis of redshifted 21cm hydrogen emissions is a developing technique for studying the early universe. The primary time of interest corresponds to a signal in the the 100-200MHz frequency band. The ...

  12. Measuring Postural Stability: Strategies For Signal Acquisition And Processing

    NASA Astrophysics Data System (ADS)

    Riedel, Susan A.; Harris, Gerald F.

    1987-01-01

    A balance platform was used to collect postural stability data from 60 children, approximately half of whom have been diagnosed with cerebral palsy. The data was examined with respect to its frequency content, resulting in an improved strategy for frequency estimation. With a reliable assessment of the frequency domain characteristics, the signal stationarity could then be examined. Significant differences in signal stationarity were observed when the epoch length was changed, as well as between the normal and cerebral palsy populations.

  13. Method And Aparatus For Improving Resolution In Spectrometers Processing Output Steps From Non-Ideal Signal Sources

    DOEpatents

    Warburton, William K. (1300 Mills St., Menlo Park, CA 94025); Momayezi, Michael (San Francisco, CA)

    2003-07-01

    A method and apparatus for processing step-like output signals generated by non-ideal, nominally single-pole ("N-1P") devices responding to possibly time-varying, pulse-like input signals of finite duration, wherein the goal is to recover the integrated areas of the input signals. Particular applications include processing step-like signals generated by detector systems in response to absorbed radiation or particles and, more particularly, to digitally processing such step-like signals in high resolution, high rate gamma ray (.gamma.-ray) spectrometers with resistive feedback preamplifiers connected to large volume germanium detectors. Superconducting bolometers can be similarly treated. The method comprises attaching a set of one or more filters to the device's (e.g., preamplifier's) output, capturing a correlated multiple output sample from the filter set in response to a detected event, and forming a weighted sum of the sample values to accurately recover the total area (e.g., charge) of the detected event.

  14. Multiple functional ECG signal is processing for wearable applications of long-term cardiac monitoring.

    PubMed

    Liu, Xin; Zheng, Yuanjin; Phyu, Myint Wai; Zhao, Bin; Je, Minkyu; Yuan, Xiaojun

    2011-02-01

    In this paper, an integrated electrocardiogram (ECG) signal-processing scheme is proposed. Using a systematic wavelet transform algorithm, this signal-processing scheme can realize multiple functions in real time, including baseline-drift removal, noise suppression, QRS detection, heart beat rate prediction and classification, and clean ECG reconstruction. Utilizing the novel low-cost hardware architecture, the proposed ECG signal-processing scheme is implemented in application-specific integrated circuits with 0.18 ? m CMOS technology. This ECG signal-processor chip achieves low area and power consumptions, and is highly suitable for wearable applications of long-term cardiac monitoring. PMID:20679025

  15. The cross correlation between the 21-cm radiation and the CMB lensing field: a new cosmological signal

    SciTech Connect

    Vallinotto, Alberto

    2011-01-01

    The measurement of Baryon Acoustic Oscillations through the 21-cm intensity mapping technique at redshift z {<=} 4 has the potential to tightly constrain the evolution of dark energy. Crucial to this experimental effort is the determination of the biasing relation connecting fluctuations in the density of neutral hydrogen (HI) with the ones of the underlying dark matter field. In this work I show how the HI bias relevant to these 21-cm intensity mapping experiments can successfully be measured by cross-correlating their signal with the lensing signal obtained from CMB observations. In particular I show that combining CMB lensing maps from Planck with 21-cm field measurements carried out with an instrument similar to the Cylindrical Radio Telescope, this cross-correlation signal can be detected with a signal-to-noise (S/N) ratio of more than 5. Breaking down the signal arising from different redshift bins of thickness {Delta}z = 0.1, this signal leads to constraining the large scale neutral hydrogen bias and its evolution to 4{sigma} level.

  16. Signal Processing of MEMS Gyroscope Arrays to Improve Accuracy Using a 1st Order Markov for Rate Signal Modeling

    PubMed Central

    Jiang, Chengyu; Xue, Liang; Chang, Honglong; Yuan, Guangmin; Yuan, Weizheng

    2012-01-01

    This paper presents a signal processing technique to improve angular rate accuracy of the gyroscope by combining the outputs of an array of MEMS gyroscope. A mathematical model for the accuracy improvement was described and a Kalman filter (KF) was designed to obtain optimal rate estimates. Especially, the rate signal was modeled by a first-order Markov process instead of a random walk to improve overall performance. The accuracy of the combined rate signal and affecting factors were analyzed using a steady-state covariance. A system comprising a six-gyroscope array was developed to test the presented KF. Experimental tests proved that the presented model was effective at improving the gyroscope accuracy. The experimental results indicated that six identical gyroscopes with an ARW noise of 6.2 °/?h and a bias drift of 54.14 °/h could be combined into a rate signal with an ARW noise of 1.8 °/?h and a bias drift of 16.3 °/h, while the estimated rate signal by the random walk model has an ARW noise of 2.4 °/?h and a bias drift of 20.6 °/h. It revealed that both models could improve the angular rate accuracy and have a similar performance in static condition. In dynamic condition, the test results showed that the first-order Markov process model could reduce the dynamic errors 20% more than the random walk model. PMID:22438734

  17. On the Management of Latency in the Synthesis of RealTime Signal Processing Systems from

    E-print Network

    Goddard, Steve

    mobile satellite receiver application, and an acoustic signal processing application from the ALFS anti­submarine warfare system. This research is the first to model the execution of processing graphs with the real­ time

  18. Genetic Circuit Building Blocks for Cellular Computation, Communications, and Signal Processing

    E-print Network

    Batzoglou, Serafim

    Genetic Circuit Building Blocks for Cellular Computation, Communications, and Signal Processing Ron library and a biocircuit design methodology for assembling these components into compound circuits, reliably produce the desired behavior. We use simulation tools to guide circuit design, a process

  19. Fourier analysis and signal processing by use of the Moebius inversion formula

    NASA Technical Reports Server (NTRS)

    Reed, Irving S.; Yu, Xiaoli; Shih, Ming-Tang; Tufts, Donald W.; Truong, T. K.

    1990-01-01

    A novel Fourier technique for digital signal processing is developed. This approach to Fourier analysis is based on the number-theoretic method of the Moebius inversion of series. The Fourier transform method developed is shown also to yield the convolution of two signals. A computer simulation shows that this method for finding Fourier coefficients is quite suitable for digital signal processing. It competes with the classical FFT (fast Fourier transform) approach in terms of accuracy, complexity, and speed.

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

    NASA Technical Reports Server (NTRS)

    Carden, F.

    1973-01-01

    Conventional analytical techniques used to determine and optimize phase-lock loop (PLL) characteristics are most often based on a model which is valid only if the intermediate frequency (IF) filter bandwidth is large compared to the PLL bandwidth and the phase error is small. An improved model (called the quasi-linear model) is developed which takes into account small IF filter bandwidths and nonlinear effects associated with large phase errors. By comparison of theoretical and experimental results it is demonstrated that the quasi-linear model accurately predicts PLL characteristics. This is true even for small IF filter bandwidths and large phase errors where the conventional model is invalid. The theoretical and experimental results are used to draw conclusions concerning threshold, multiplier output variance, phase error variance, output signal-to-noise ratio, and signal distortion. The relationship between these characteristics and IF filter bandwidth, modulating signal spectrum, and rms deviation is also determined.

  1. Silicon technology compatible photonic molecules for compact optical signal processing

    SciTech Connect

    Barea, Luis A. M. Vallini, Felipe; Jarschel, Paulo F.; Frateschi, Newton C.

    2013-11-11

    Photonic molecules (PMs) based on multiple inner coupled microring resonators allow to surpass the fundamental constraint between the total quality factor (Q{sub T}), free spectral range (FSR), and resonator size. In this work, we use a PM that presents doublets and triplets resonance splitting, all with high Q{sub T}. We demonstrate the use of the doublet splitting for 34.2?GHz signal extraction by filtering the sidebands of a modulated optical signal. We also demonstrate that very compact optical modulators operating 2.75 times beyond its resonator linewidth limit may be obtained using the PM triplet splitting, with separation of ?55?GHz.

  2. Neural network post-processing of grayscale optical correlator

    NASA Technical Reports Server (NTRS)

    Lu, Thomas T; Hughlett, Casey L.; Zhoua, Hanying; Chao, Tien-Hsin; Hanan, Jay C.

    2005-01-01

    In this paper we present the use of a radial basis function neural network (RBFNN) as a post-processor to assist the optical correlator to identify the objects and to reject false alarms. Image plane features near the correlation peaks are extracted and fed to the neural network for analysis. The approach is capable of handling large number of object variations and filter sets. Preliminary experimental results are presented and the performance is analyzed.

  3. A STATISTICAL SIGNAL PROCESSING APPROACH TO IMAGE FUSION FOR CONCELED WEAPON DETECTION1

    E-print Network

    Blum, Rick

    A STATISTICAL SIGNAL PROCESSING APPROACH TO IMAGE FUSION FOR CONCELED WEAPON DETECTION1 J. Yang A statistical signal processing approach to multisensor image fusion is presented for concealed weapon detection weapon detection (CWD) applications [5,6]. 2. THE IMAGE FORMATION MODEL We model every coefficient

  4. A regression model with a hidden logistic process for signal parametrization

    E-print Network

    Chamroukhi, Faicel

    A regression model with a hidden logistic process for signal parametrization F. Chamroukhi1,2 , A simulated data and real data. 2 Regression model with a hidden logistic process 2.1 The global regression approach for signal parametrization, which consists of a specific regression model incorporating a discrete

  5. On signal/image processing for concealed weapon detection from stand-off range (Invited Paper)

    NASA Astrophysics Data System (ADS)

    Varshney, P. K.; Chen, H.; Rao, R. M.

    2005-05-01

    We present an overview of signal and image processing techniques developed for the concealed weapon detection (CWD) application. The signal/image processing chain is described and the tasks include image denoising and enhancement, image registration and fusion, object segmentation, shape description, and weapon recognition. Finally, a complete CWD example is presented for illustration.

  6. IEEE SIGNAL PROCESSING MAGAZINE [104] JULY 2005 [applications CORNER] Eli Saber, Sohail Dianat,

    E-print Network

    Li, Perry Y.

    , Lalit K. Mestha, and Perry Y. Li T he field of digital signal processing (DSP) has been advancing- photography, pattern and speech recognition, remote sensing, printing, and multimedia applications rely heav the signal processing audience to the uti- lization of DSP methods in digital printing systems, clearly

  7. Optical Signal Processing in All-Optical Packet Routing Systems S. J. Ben Yoo

    E-print Network

    Yoo, S. J. Ben

    Optical Signal Processing in All-Optical Packet Routing Systems S. J. Ben Yoo Department@ece.ucdavis.edu, Abstract: This paper discusses important signal processing functions in all-optical packet routing systems. We will pay special attention to all-optical time-to-live, optical performance monitoring, optical

  8. Guidelines for Affective Signal Processing (ASP): From Lab to Life Egon L. van den Broek

    E-print Network

    Theune, Mariët

    Guidelines for Affective Signal Processing (ASP): From Lab to Life Egon L. van den Broek Center, The Netherlands vandenbroek@acm.org Joris H. Janssen Dept. of Human Technology Interaction, Eindhoven University session: Guidelines for Affective Signal Processing (ASP): From lab to life. Although affect is embraced

  9. PetaOp/Second FPGA Signal Processing for SETI and Radio Astronomy

    E-print Network

    Zakhor, Avideh

    PetaOp/Second FPGA Signal Processing for SETI and Radio Astronomy Aaron Parsons1 , Donald Backer1), seeks to speed the development of radio astronomy signal process- ing instrumentation by designing: aparsons@astron.berkeley.edu 2 Xilinx Corporation Currently in radio astronomy, high-performance DSP in

  10. Lab 3--Signal Processing II PHYS 309 Name

    E-print Network

    Herman, Rhett

    the general reaction of each circuit to the frequencies. LCR series circuit LCR parallel circuit f (Hz) Vpp. The total impedance of a circuit is given by = + . R is the real, purely resistive part; and X is the imaginary part. The reactance X tells you how the circuit element reacts to the frequency = 2 of the signal

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

    E-print Network

    Fernandez, Thomas

    , the number of possible H values, which define a primary mask, is also limited. A secondary mask is defined applications one needs to intercept and classify pings of an unknown sonar in presence of unknown number, in ping interception and classification. Appearance of these signals in spectrograms depends

  12. STATISTICAL SIGNAL PROCESSING FOR AUTOMOTIVE SAFETY SYSTEMS Fredrik Gustafsson

    E-print Network

    Gustafsson, Fredrik

    to common shared computer hard- ware, sensors and actuators using central data buses. This paper overviews recent and future safety systems, and high- lights the big challenges for researchers in the signal pro in spectral analysis, non-uniform sampling, sys- tem identification, change detection, diagnosis and fault de

  13. Introduction to Digital Signal Processing ENG EC416 (Spring 2013)

    E-print Network

    to add/change class: Jan. 30, Last day to drop a course: without "W" ­ Feb. 21, with "W" ­ Mar. 29 of new textbook. Otherwise, a separate purchase of web access from Pearson is needed ($20 for students filters and spectral analyzers, and in their application to real signals (e.g., speech, music, images). o

  14. Wide-band array signal processing via spectral smoothing

    NASA Technical Reports Server (NTRS)

    Xu, Guanghan; Kailath, Thomas

    1989-01-01

    A novel algorithm for the estimation of direction-of-arrivals (DOA) of multiple wide-band sources via spectral smoothing is presented. The proposed algorithm does not require an initial DOA estimate or a specific signal model. The advantages of replacing the MUSIC search with an ESPRIT search are discussed.

  15. Evaluating Signal-Correlated Noise as a Control Task with Language-Related Gamma Activity on Electrocorticography

    PubMed Central

    Brown, Erik C.; Muzik, Otto; Rothermel, Robert; Juhász, Csaba; Shah, Aashit K.; Fuerst, Darren; Mittal, Sandeep; Sood, Sandeep; Asano, Eishi

    2014-01-01

    Objective Our recent electrocorticography (ECoG) study suggested reverse speech, a widely used control task, to be a poor control for non-language-related auditory activity. We hypothesized that this may be due to retained perception as a human voice. We report a follow-up ECoG study in which we contrast forward and reverse speech with a signal-correlated noise (SCN) control task that cannot be perceived as a human voice. Methods Ten patients were presented 90 audible stimuli, including 30 each of corresponding forward speech, reverse speech, and SCN trials, during ECoG recording with evaluation of gamma activity between 50–150 Hz. Results Sites of the lateral temporal gyri activated throughout speech stimuli were generally less activated by SCN, while some temporal sites seemed to process both human and non-human sounds. Reverse speech trials were associated with activities across the temporal lobe similar to those associated with forward speech. Conclusions Findings herein externally validate functional neuroimaging studies utilizing SCN as a control for non-language-specific auditory function. Our findings are consistent with the notion that stimuli perceived as originating from a human voice are poor controls for non-language auditory function. Significance Our findings have implications in functional neuroimaging research as well as improved clinical mapping of auditory functions. PMID:24412331

  16. A kind of integrated method discuss of fOG signal processing circuit

    NASA Astrophysics Data System (ADS)

    Lu, Jun; Pan, Xin; Ying, Jiaju; Liu, Jie

    2014-12-01

    In view of the circuit miniaturization need in project application of fiber optic gyroscope(FOG), a new integrated technical scheme adopting system in package(SIP) for signal processing circuit of FOG was put forward. At first, the principle on signal processing circuit of FOG was analyzed, and the technical scheme adopting SIP based on low-temperature co-fired substrate technology was presented according to circuit characteristic and actual condition. Secondly, under the prerequisite of the concept introduction of SIP and LTCC, the SIP prototype of signal processing circuit of FOG was trialed produced?and it passed through the debug test. This SIP modular is an overall circuit complete integrated the signal processing circuit of FOG, and only a potentiometer and EPROM do not case outside. The testing results indicate that SIP is a kind of feasible scheme that carries out miniaturization for signal processing circuit of FOG.

  17. EE 235 Lecture Notes Signal Analysis { First course in Signal Processing, Communications, Con-

    E-print Network

    Hochberg, Michael

    compression, CT, magnetic resonance imaging, modems, speech enhancement, MP3 encoding, coding a signal. Prediction { predict the future based on past trends { sales, stock market, inventory 4. Synthesizer independent variables (e.g. t 2 image, weather information, sales information, voltage

  18. Dynamic signal processing by ribozyme-mediated RNA circuits to control gene expression

    PubMed Central

    Shen, Shensi; Rodrigo, Guillermo; Prakash, Satya; Majer, Eszter; Landrain, Thomas E.; Kirov, Boris; Daròs, José-Antonio; Jaramillo, Alfonso

    2015-01-01

    Organisms have different circuitries that allow converting signal molecule levels to changes in gene expression. An important challenge in synthetic biology involves the de novo design of RNA modules enabling dynamic signal processing in live cells. This requires a scalable methodology for sensing, transmission, and actuation, which could be assembled into larger signaling networks. Here, we present a biochemical strategy to design RNA-mediated signal transduction cascades able to sense small molecules and small RNAs. We design switchable functional RNA domains by using strand-displacement techniques. We experimentally characterize the molecular mechanism underlying our synthetic RNA signaling cascades, show the ability to regulate gene expression with transduced RNA signals, and describe the signal processing response of our systems to periodic forcing in single live cells. The engineered systems integrate RNA–RNA interaction with available ribozyme and aptamer elements, providing new ways to engineer arbitrary complex gene circuits. PMID:25916845

  19. Acoustic Emission Signal Processing Technique to Characterize Reactor In-Pile Phenomena

    SciTech Connect

    Vivek Agarwal; Magdy Samy Tawfik; James A Smith

    2014-07-01

    Existing and developing advanced sensor technologies and instrumentation will allow non-intrusive in-pile measurement of temperature, extension, and fission gases when coupled with advanced signal processing algorithms. The transmitted measured sensor signals from inside to the outside of containment structure are corrupted by noise and are attenuated, thereby reducing the signal strength and signal-to-noise ratio. Identification and extraction of actual signal (representative of an in-pile phenomenon) is a challenging and complicated process. In this paper, empirical mode decomposition technique is proposed to reconstruct actual sensor signal by partially combining intrinsic mode functions. Reconstructed signal corresponds to phenomena and/or failure modes occurring inside the reactor. In addition, it allows accurate non-intrusive monitoring and trending of in-pile phenomena.

  20. Acoustic emission signal processing technique to characterize reactor in-pile phenomena

    SciTech Connect

    Agarwal, Vivek; Tawfik, Magdy S.; Smith, James A.

    2015-03-31

    Existing and developing advanced sensor technologies and instrumentation will allow non-intrusive in-pile measurement of temperature, extension, and fission gases when coupled with advanced signal processing algorithms. The transmitted measured sensor signals from inside to the outside of containment structure are corrupted by noise and are attenuated, thereby reducing the signal strength and the signal-to-noise ratio. Identification and extraction of actual signal (representative of an in-pile phenomenon) is a challenging and complicated process. In the paper, empirical mode decomposition technique is utilized to reconstruct actual sensor signal by partially combining intrinsic mode functions. Reconstructed signal will correspond to phenomena and/or failure modes occurring inside the reactor. In addition, it allows accurate non-intrusive monitoring and trending of in-pile phenomena.

  1. Auditory Signal Processing in Communication: Perception and Performance of Vocal Sounds

    PubMed Central

    Prather, Jonathan F.

    2013-01-01

    Learning and maintaining the sounds we use in vocal communication require accurate perception of the sounds we hear performed by others and feedback-dependent imitation of those sounds to produce our own vocalizations. Understanding how the central nervous system integrates auditory and vocal-motor information to enable communication is a fundamental goal of systems neuroscience, and insights into the mechanisms of those processes will profoundly enhance clinical therapies for communication disorders. Gaining the high-resolution insight necessary to define the circuits and cellular mechanisms underlying human vocal communication is presently impractical. Songbirds are the best animal model of human speech, and this review highlights recent insights into the neural basis of auditory perception and feedback-dependent imitation in those animals. Neural correlates of song perception are present in auditory areas, and those correlates are preserved in the auditory responses of downstream neurons that are also active when the bird sings. Initial tests indicate that singing-related activity in those downstream neurons is associated with vocal-motor performance as opposed to the bird simply hearing itself sing. Therefore, action potentials related to auditory perception and action potentials related to vocal performance are co-localized in individual neurons. Conceptual models of song learning involve comparison of vocal commands and the associated auditory feedback to compute an error signal that is used to guide refinement of subsequent song performances, yet the sites of that comparison remain unknown. Convergence of sensory and motor activity onto individual neurons points to a possible mechanism through which auditory and vocal-motor signals may be linked to enable learning and maintenance of the sounds used in vocal communication. PMID:23827717

  2. Auditory signal processing in communication: perception and performance of vocal sounds.

    PubMed

    Prather, Jonathan F

    2013-11-01

    Learning and maintaining the sounds we use in vocal communication require accurate perception of the sounds we hear performed by others and feedback-dependent imitation of those sounds to produce our own vocalizations. Understanding how the central nervous system integrates auditory and vocal-motor information to enable communication is a fundamental goal of systems neuroscience, and insights into the mechanisms of those processes will profoundly enhance clinical therapies for communication disorders. Gaining the high-resolution insight necessary to define the circuits and cellular mechanisms underlying human vocal communication is presently impractical. Songbirds are the best animal model of human speech, and this review highlights recent insights into the neural basis of auditory perception and feedback-dependent imitation in those animals. Neural correlates of song perception are present in auditory areas, and those correlates are preserved in the auditory responses of downstream neurons that are also active when the bird sings. Initial tests indicate that singing-related activity in those downstream neurons is associated with vocal-motor performance as opposed to the bird simply hearing itself sing. Therefore, action potentials related to auditory perception and action potentials related to vocal performance are co-localized in individual neurons. Conceptual models of song learning involve comparison of vocal commands and the associated auditory feedback to compute an error signal that is used to guide refinement of subsequent song performances, yet the sites of that comparison remain unknown. Convergence of sensory and motor activity onto individual neurons points to a possible mechanism through which auditory and vocal-motor signals may be linked to enable learning and maintenance of the sounds used in vocal communication. This article is part of a Special Issue entitled "Communication Sounds and the Brain: New Directions and Perspectives". PMID:23827717

  3. 7/24/13 Signal Processing Society www.signalprocessingsociety.org/uploads/email/JSTSP_SI_SPSG.html 1/2

    E-print Network

    Qiu, Robert Caiming

    , statistical signal processing, signal representation and data compression, machine learning, optimization Society www.signalprocessingsociety.org/uploads/email/SPM_SI_big_data.html 1/2 P lease click here if you SIGNAL PROCESSING MAGAZINE Special Issue on Signal Processing for Big Data Aims and Scope We live

  4. Selection on signal–reward correlation: limits and opportunities to the evolution of deceit in Turnera ulmifolia L.

    PubMed

    Benitez-Vieyra, S; Ordano, M; Fornoni, J; Boege, K; Domínguez, C A

    2010-12-01

    Because pollinators are unable to directly assess the amount of rewards offered by flowers, they rely on the information provided by advertising floral traits. Thus, having a lower intra-individual correlation between signal and reward (signal accuracy) than other plants in the population provides the opportunity to reduce investment in rewards and cheat pollinators. However, pollinators' cognitive capacities can impose a limit to the evolution of this plant cheating strategy if they can punish those plants with low signal accuracy. In this study, we examined the opportunity for cheating in the perennial weed Turnera ulmifolia L. evaluating the selective value of signal accuracy, floral display and reward production in a natural population. We found that plant reproductive success was positively related to signal accuracy and floral display, but not to nectar production. The intensity of selection on floral display was more than three times higher than on signal accuracy. The pattern of selection indicated that pollinators can select for signal accuracy provided by plants and suggests that learning abilities of pollinators can limit the evolution of deceptive strategies in T. ulmifolia. PMID:21121090

  5. Paradoxical correlation between signal in functional magnetic resonance imaging and deoxygenated haemoglobin content in capillaries: a new theoretical explanation

    NASA Astrophysics Data System (ADS)

    Yamamoto, Toru; Kato, Toshinori

    2002-04-01

    Signal increases in functional magnetic resonance imaging (fMRI) are believed to be a result of decreased paramagnetic deoxygenated haemoglobin (deoxyHb) content in the neural activation area. However, discrepancies in this canonical blood oxygenation level dependent (BOLD) theory have been pointed out in studies using optical techniques, which directly measure haemoglobin changes. To explain the discrepancies, we developed a new theory bridging magnetic resonance (MR) signal and haemoglobin changes. We focused on capillary influences, which have been neglected in most previous fMRI studies and performed a combined fMRI and near-infrared spectroscopy (NIRS) study using a language task. Paradoxically, both the MR signal and deoxyHb content increased in Broca's area. On the other hand, fMRI activation in the auditory area near large veins correlated with a mirror-image decrease in deoxyHb and increase in oxygenated haemoglobin (oxyHb), in agreement with canonical BOLD theory. All fMRI signal changes correlated consistently with changes in oxyHb, the diamagnetism of which is insensitive to MR. We concluded that the discrepancy with the canonical BOLD theory is caused by the fact that the BOLD theory ignores the effect of the capillaries. Our theory explains the paradoxical phenomena of the oxyHb and deoxyHb contributions to the MR signal and gives a new insight into the precise haemodynamics of activation by analysing fMRI and NIRS data.

  6. Processing of Signals from Fiber Bragg Gratings Using Unbalanced Interferometers

    NASA Technical Reports Server (NTRS)

    Adamovsky, Grigory; Juergens, Jeff; Floyd, Bertram

    2005-01-01

    Fiber Bragg gratings (FBG) have become preferred sensory structures in fiber optic sensing system. High sensitivity, embedability, and multiplexing capabilities make FBGs superior to other sensor configurations. The main feature of FBGs is that they respond in the wavelength domain with the wavelength of the returned signal as the indicator of the measured parameter. The wavelength is then converted to optical intensity by a photodetector to detect corresponding changes in intensity. This wavelength-to-intensity conversion is a crucial part in any FBG-based sensing system. Among the various types of wavelength-to-intensity converters, unbalanced interferometers are especially attractive because of their small weight and volume, lack of moving parts, easy integration, and good stability. In this paper we investigate the applicability of unbalanced interferometers to analyze signals reflected from Bragg gratings. Analytical and experimental data are presented.

  7. Signal processing with neural networks: throwing off the yoke of linearity

    NASA Astrophysics Data System (ADS)

    Hecht-Nielsen, Robert

    1991-11-01

    During the 1930s and 1940s Norbert Wiener and others invented the core concepts of linear signal processing. These ideas quickly became popular and played a significant role in the Allies' victory in World War II. During and after the war, linear signal processing theory was greatly expanded and began to take on the character of an imposing monolith. By the mid- 1940s, Wiener (and others, such as Dennis Gabor) came to recognize that linear signal processing theory, while interesting and very useful, was only a piece of a much larger picture. In 1946 and 1958 Gabor and Wiener, respectively, attempted to address the whole picture. While they were not completely successful, they did implicitly set an agenda for a more general approach to signal processing. Although a few others have, from time to time, addressed this agenda; in terms of the signal processing community as a whole it still remains lost in the shadow of the ever-growing monolith of linear signal processing theory. The thesis of this paper is that it is now time to get on with the Wiener and Gabor agenda. It is time to make general signal processing the mainstream focus of the subject. It is argued here that the best way to do this is to abandon the transfer function/Fourier analysis/z-transform approach of the current linear signal processing regime and replace it with a much more natural intellectual framework for general signal processing--the framework offered by neurocomputing. A potential benefit of this refocusing of the field is that the detailed engineering might soon be left to machines, while human technologists will be able to concentrate on the art of signal sculpting.

  8. Feature extraction and signal processing for nylon DNA microarrays

    PubMed Central

    Lopez, F; Rougemont, J; Loriod, B; Bourgeois, A; Loï, L; Bertucci, F; Hingamp, P; Houlgatte, R; Granjeaud, S

    2004-01-01

    Background High-density DNA microarrays require automatic feature extraction methodologies and softwares. These can be a potential source of non-reproducibility of gene expression measurements. Variation in feature location or in signal integration methodology may be a significant contribution to the observed variance in gene expression levels. Results We explore sources of variability in feature extraction from DNA microarrays on Nylon membrane with radioactive detection. We introduce a mathematical model of the signal emission and derive methods for correcting biases such as overshining, saturation or variation in probe amount. We also provide a quality metric which can be used qualitatively to flag weak or untrusted signals or quantitatively to modulate the weight of each experiment or gene in higher level analyses (clustering or discriminant analysis). Conclusions Our novel feature extraction methodology, based on a mathematical model of the radioactive emission, reduces variability due to saturation, neighbourhood effects and variable probe amount. Furthermore, we provide a fully automatic feature extraction software, BZScan, which implements the algorithms described in this paper. PMID:15222896

  9. SCOPE: IEEE Signal Processing Magazine publishes tutorial-style articles on signal processing research and applications, as well as columns and forums of interest to the signal processing community. Coverage ranges from fundamental principles to practical

    E-print Network

    Nehorai, Arye

    DIVERSITY IN RADAR SIGNAL PROCESSING Robert Calderbank, Stephen D. Howard, and Bill Moran [VOLUME 26 NUMBER, Douglas Cochran, and Muralidhar Rangaswamy 65 LESSONS FOR RADAR Michele Vespe, Gareth Jones, and Chris J José Moura 140 APPLICATIONS CORNER Cognitive Radios for Spectrum Sharing Anant Sahai, Shridhar Mubaraq

  10. To appear in Proc. the 1997 IEEE Workshop on Nonlinear Signal and Image Processing, Michigan, September, 1997. ON-LINE BLIND SIGNAL EXTRACTION METHODS EXPLOITING A PRIORI

    E-print Network

    Cichocki, Andrzej

    To appear in Proc. the 1997 IEEE Workshop on Nonlinear Signal and Image Processing, Michigan, September, 1997. ON-LINE BLIND SIGNAL EXTRACTION METHODS EXPLOITING A PRIORI KNOWLEDGE OF THE PREVIOUSLY EXTRACTED SIGNALS Andrzej CICHOCKIy, Ruck THAWONMASy3 , and Shun-ichi AMARIy yBrain Information Processing

  11. Laser Doppler Blood Flow Imaging Using a CMOS Imaging Sensor with On-Chip Signal Processing

    PubMed Central

    He, Diwei; Nguyen, Hoang C.; Hayes-Gill, Barrie R.; Zhu, Yiqun; Crowe, John A.; Gill, Cally; Clough, Geraldine F.; Morgan, Stephen P.

    2013-01-01

    The first fully integrated 2D CMOS imaging sensor with on-chip signal processing for applications in laser Doppler blood flow (LDBF) imaging has been designed and tested. To obtain a space efficient design over 64 × 64 pixels means that standard processing electronics used off-chip cannot be implemented. Therefore the analog signal processing at each pixel is a tailored design for LDBF signals with balanced optimization for signal-to-noise ratio and silicon area. This custom made sensor offers key advantages over conventional sensors, viz. the analog signal processing at the pixel level carries out signal normalization; the AC amplification in combination with an anti-aliasing filter allows analog-to-digital conversion with a low number of bits; low resource implementation of the digital processor enables on-chip processing and the data bottleneck that exists between the detector and processing electronics has been overcome. The sensor demonstrates good agreement with simulation at each design stage. The measured optical performance of the sensor is demonstrated using modulated light signals and in vivo blood flow experiments. Images showing blood flow changes with arterial occlusion and an inflammatory response to a histamine skin-prick demonstrate that the sensor array is capable of detecting blood flow signals from tissue. PMID:24051525

  12. Dielectric properties of Granodiorite partially saturated with water and its correlation to the detection of seismic electric signals

    E-print Network

    Papathanassiou, A N; Grammatikakis, J

    2011-01-01

    Transient electric signals emitted prior to earthquake occurrence are recorded at certain sites in the Earth's crust termed sensitive. These field observations enforce the laboratory investigation of the dielectric response of rocks forming these localities. The dielectric relaxation of granodiorite rock coming from such a sensitive locality (Keratea, Greece) reveals, through complex impedance spectroscopy, that the activation volume for relaxation of this rock is negative which so far has been reported only rarely. This result, however, supports a theoretical model on the pre-seismic electric signals and is likely to be correlated with the sensitivity of the site and hence with the selectivity.

  13. Research on signal-processing supercomputers. Final technical report, September 1985-September 1986

    SciTech Connect

    Kung, H.T.

    1988-09-01

    Signal processing is an area where the required computational bandwidth in an application can be unbounded. Applications such as radar, sonar and communications already call for signal-processing systems capable of delivering billions or tens of billions of operations per second. In developing a new signal processor to meet these requirements, it is essential to understand the underlying computational models. An ad-hoc processor development effort that is unclear on the computational models will likely be wasteful and unable to meet the long-term performance goal. Fortunately, because the control in signal processing is typically data-independent, computational models in this area can be relatively simple. Based on the study performed under this contract, this report describes some important computational models for parallel signal processing, and illustrates how the Warp machine developed by Carnegie Mellon supports these models. (jes)

  14. Punch stretching process monitoring using acoustic emission signal analysis. II - Application of frequency domain deconvolution

    NASA Technical Reports Server (NTRS)

    Liang, Steven Y.; Dornfeld, David A.; Nickerson, Jackson A.

    1987-01-01

    The coloring effect on the acoustic emission signal due to the frequency response of the data acquisition/processing instrumentation may bias the interpretation of AE signal characteristics. In this paper, a frequency domain deconvolution technique, which involves the identification of the instrumentation transfer functions and multiplication of the AE signal spectrum by the inverse of these system functions, has been carried out. In this way, the change in AE signal characteristics can be better interpreted as the result of the change in only the states of the process. Punch stretching process was used as an example to demonstrate the application of the technique. Results showed that, through the deconvolution, the frequency characteristics of AE signals generated during the stretching became more distinctive and can be more effectively used as tools for process monitoring.

  15. A regression model with a hidden logistic process for signal parametrization

    E-print Network

    Chamroukhi, Faicel

    A regression model with a hidden logistic process for signal parametrization F. Chamroukhi, A. Samé 2009 6 / 21 #12;The proposed regression approach A regression model with a hidden logistic process A regression model with a hidden logistic process The proposed regression based on hidden process approach

  16. DEVELOPMENT OF SIGNAL PROCESSING TOOLS AND HARDWARE FOR PIEZOELECTRIC SENSOR DIAGNOSTIC PROCESSES

    SciTech Connect

    OVERLY, TIMOTHY G.; PARK, GYUHAE; FARRAR, CHARLES R.

    2007-02-09

    This paper presents a piezoelectric sensor diagnostic and validation procedure that performs in -situ monitoring of the operational status of piezoelectric (PZT) sensor/actuator arrays used in structural health monitoring (SHM) applications. The validation of the proper function of a sensor/actuator array during operation, is a critical component to a complete and robust SHM system, especially with the large number of active sensors typically involved. The method of this technique used to obtain the health of the PZT transducers is to track their capacitive value, this value manifests in the imaginary part of measured electrical admittance. Degradation of the mechanical/electric properties of a PZT sensor/actuator as well as bonding defects between a PZT patch and a host structure can be identified with the proposed procedure. However, it was found that temperature variations and changes in sensor boundary conditions manifest themselves in similar ways in the measured electrical admittances. Therefore, they examined the effects of temperature variation and sensor boundary conditions on the sensor diagnostic process. The objective of this study is to quantify and classify several key characteristics of temperature change and to develop efficient signal processing techniques to account for those variations in the sensor diagnostis process. In addition, they developed hardware capable of making the necessary measurements to perform the sensor diagnostics and to make impedance-based SHM measurements. The paper concludes with experimental results to demonstrate the effectiveness of the proposed technique.

  17. A user's guide for the signal processing software for image and speech compression developed in the Communications and Signal Processing Laboratory (CSPL), version 1

    NASA Technical Reports Server (NTRS)

    Kumar, P.; Lin, F. Y.; Vaishampayan, V.; Farvardin, N.

    1986-01-01

    A complete documentation of the software developed in the Communication and Signal Processing Laboratory (CSPL) during the period of July 1985 to March 1986 is provided. Utility programs and subroutines that were developed for a user-friendly image and speech processing environment are described. Additional programs for data compression of image and speech type signals are included. Also, programs for the zero-memory and block transform quantization in the presence of channel noise are described. Finally, several routines for simulating the perfromance of image compression algorithms are included.

  18. Earthquake early warning system using real-time signal processing

    SciTech Connect

    Leach, R.R. Jr.; Dowla, F.U.

    1996-02-01

    An earthquake warning system has been developed to provide a time series profile from which vital parameters such as the time until strong shaking begins, the intensity of the shaking, and the duration of the shaking, can be derived. Interaction of different types of ground motion and changes in the elastic properties of geological media throughout the propagation path result in a highly nonlinear function. We use neural networks to model these nonlinearities and develop learning techniques for the analysis of temporal precursors occurring in the emerging earthquake seismic signal. The warning system is designed to analyze the first-arrival from the three components of an earthquake signal and instantaneously provide a profile of impending ground motion, in as little as 0.3 sec after first ground motion is felt at the sensors. For each new data sample, at a rate of 25 samples per second, the complete profile of the earthquake is updated. The profile consists of a magnitude-related estimate as well as an estimate of the envelope of the complete earthquake signal. The envelope provides estimates of damage parameters, such as time until peak ground acceleration (PGA) and duration. The neural network based system is trained using seismogram data from more than 400 earthquakes recorded in southern California. The system has been implemented in hardware using silicon accelerometers and a standard microprocessor. The proposed warning units can be used for site-specific applications, distributed networks, or to enhance existing distributed networks. By producing accurate, and informative warnings, the system has the potential to significantly minimize the hazards of catastrophic ground motion. Detailed system design and performance issues, including error measurement in a simple warning scenario are discussed in detail.

  19. 4D time-frequency representation for binaural speech signal processing

    NASA Astrophysics Data System (ADS)

    Mikhael, Raed; Szu, Harold H.

    2006-04-01

    Hearing is the ability to detect and process auditory information produced by the vibrating hair cilia residing in the corti of the ears to the auditory cortex of the brain via the auditory nerve. The primary and secondary corti of the brain interact with one another to distinguish and correlate the received information by distinguishing the varying spectrum of arriving frequencies. Binaural hearing is nature's way of employing the power inherent in working in pairs to process information, enhance sound perception, and reduce undesired noise. One ear might play a prominent role in sound recognition, while the other reinforces their perceived mutual information. Developing binaural hearing aid devices can be crucial in emulating the working powers of two ears and may be a step closer to significantly alleviating hearing loss of the inner ear. This can be accomplished by combining current speech research to already existing technologies such as RF communication between PDAs and Bluetooth. Ear Level Instrument (ELI) developed by Micro-tech Hearing Instruments and Starkey Laboratories is a good example of a digital bi-directional signal communicating between a PDA/mobile phone and Bluetooth. The agreement and disagreement of arriving auditory information to the Bluetooth device can be classified as sound and noise, respectively. Finding common features of arriving sound using a four coordinate system for sound analysis (four dimensional time-frequency representation), noise can be greatly reduced and hearing aids would become more efficient. Techniques developed by Szu within an Artificial Neural Network (ANN), Blind Source Separation (BSS), Adaptive Wavelets Transform (AWT), and Independent Component Analysis (ICA) hold many possibilities to the improvement of acoustic segmentation of phoneme, all of which will be discussed in this paper. Transmitted and perceived acoustic speech signal will improve, as the binaural hearing aid will emulate two ears in sound localization, speech understanding in noisy environment, and loudness differentiation.

  20. Low Bandwidth Vocoding using EM Sensor and Acoustic Signal Processing

    SciTech Connect

    Ng, L C; Holzrichter, J F; Larson, P E

    2001-10-25

    Low-power EM radar-like sensors have made it possible to measure properties of the human speech production system in real-time, without acoustic interference [1]. By combining these data with the corresponding acoustic signal, we've demonstrated an almost 10-fold bandwidth reduction in speech compression, compared to a standard 2.4 kbps LPC10 protocol used in the STU-III (Secure Terminal Unit, third generation) telephone. This paper describes a potential EM sensor/acoustic based vocoder implementation.

  1. Speaker verification using combined acoustic and EM sensor signal processing

    SciTech Connect

    Ng, L C; Gable, T J; Holzrichter, J F

    2000-11-10

    Low Power EM radar-like sensors have made it possible to measure properties of the human speech production system in real-time, without acoustic interference. This greatly enhances the quality and quantity of information for many speech related applications. See Holzrichter, Burnett, Ng, and Lea, J. Acoustic. SOC. Am . 103 ( 1) 622 (1998). By combining the Glottal-EM-Sensor (GEMS) with the Acoustic-signals, we've demonstrated an almost 10 fold reduction in error rates from a speaker verification system experiment under a moderate noisy environment (-10dB).

  2. Temporal signal processing of dolphin biosonar echoes from salmon prey.

    PubMed

    Au, Whitlow W L; Ou, Hui Helen

    2014-08-01

    Killer whales project short broadband biosonar clicks. The broadband nature of the clicks provides good temporal resolution of echo highlights and allows for the discriminations of salmon prey. The echoes contain many highlights as the signals reflect off different surfaces and parts of the fish body and swim bladder. The temporal characteristics of echoes from salmon are highly aspect dependent and six temporal parameters were used in a support vector machine to discriminate between species. Results suggest that killer whales can classify salmon based on their echoes and provide some insight as to which features might enable the classification. PMID:25096148

  3. Variation in opsin genes correlates with signalling ecology in North American fireflies.

    PubMed

    Sander, S E; Hall, D W

    2015-09-01

    Genes underlying signal reception should evolve to maximize signal detection in a particular environment. In animals, opsins, the protein component of visual pigments, are predicted to evolve according to this expectation. Fireflies are known for their bioluminescent mating signals. The eyes of nocturnal species are expected to maximize the detection of conspecific signal colours emitted in the typical low-light environment. This is not expected for species that have transitioned to diurnal activity in bright daytime environments. Here, we test the hypothesis that opsin gene sequence plays a role in modifying firefly eye spectral sensitivity. We use genome and transcriptome sequencing in four firefly species, transcriptome sequencing in six additional species and targeted gene sequencing in 28 other species to identify all opsin genes present in North American fireflies and to elucidate amino acid sites under positive selection. We also determine whether amino acid substitutions in opsins are linked to evolutionary changes in signal mode, signal colour and light environment. We find only two opsins, one long wavelength and one ultraviolet, in all firefly species and identify 25 candidate sites that may be involved in determining spectral sensitivity. In addition, we find elevated rates of evolution at transitions to diurnal activity, and changes in selective constraint on long wavelength opsin associated with changes in light environment. Our results suggest that changes in eye spectral sensitivity are at least partially due to opsin sequence. Fireflies continue to be a promising system in which to investigate the evolution of signals, receptors and signalling environments. PMID:26289828

  4. Neuronal correlates of a preference for leading signals in the synchronizing bushcricket Mecopoda elongata (Orthoptera, Tettigoniidae).

    PubMed

    Siegert, M E; Römer, H; Hashim, R; Hartbauer, M

    2011-12-01

    Acoustically interacting males of the tropical katydid Mecopoda elongata synchronize their chirps imperfectly, so that one male calls consistently earlier in time than the other. In choice situations, females prefer the leader signal, and it has been suggested that a neuronal mechanism based on directional hearing may be responsible for the asymmetric, stronger representation of the leader signal in receivers. Here, we investigated the potential mechanism in a pair of interneurons (TN1 neuron) of the afferent auditory pathway, known for its contralateral inhibitory input in directional hearing. In this interneuron, conspecific signals are reliably encoded under natural conditions, despite high background noise levels. Unilateral presentations of a conspecific chirp elicited a TN1 response where each suprathreshold syllable in the chirp was reliably copied in a phase-locked fashion. Two identical chirps broadcast with a 180 deg spatial separation resulted in a strong suppression of the response to the follower signal, when the time delay was 20 ms or more. Muting the ear on the leader side fully restored the response to the follower signal compared with unilateral controls. Time-intensity trading experiments, in which the disadvantage of the follower signal was traded against higher sound pressure levels, demonstrated the dominating influence of signal timing on the TN1 response, and this was especially pronounced at higher sound levels of the leader. These results support the hypothesis that the female preference for leader signals in M. elongata is the outcome of a sensory mechanism that originally evolved for directional hearing. PMID:22071183

  5. Neuronal correlates of a preference for leading signals in the synchronizing bushcricket Mecopoda elongata (Orthoptera, Tettigoniidae)

    PubMed Central

    Siegert, M. E.; Römer, H.; Hashim, R.; Hartbauer, M.

    2011-01-01

    SUMMARY Acoustically interacting males of the tropical katydid Mecopoda elongata synchronize their chirps imperfectly, so that one male calls consistently earlier in time than the other. In choice situations, females prefer the leader signal, and it has been suggested that a neuronal mechanism based on directional hearing may be responsible for the asymmetric, stronger representation of the leader signal in receivers. Here, we investigated the potential mechanism in a pair of interneurons (TN1 neuron) of the afferent auditory pathway, known for its contralateral inhibitory input in directional hearing. In this interneuron, conspecific signals are reliably encoded under natural conditions, despite high background noise levels. Unilateral presentations of a conspecific chirp elicited a TN1 response where each suprathreshold syllable in the chirp was reliably copied in a phase-locked fashion. Two identical chirps broadcast with a 180 deg spatial separation resulted in a strong suppression of the response to the follower signal, when the time delay was 20 ms or more. Muting the ear on the leader side fully restored the response to the follower signal compared with unilateral controls. Time–intensity trading experiments, in which the disadvantage of the follower signal was traded against higher sound pressure levels, demonstrated the dominating influence of signal timing on the TN1 response, and this was especially pronounced at higher sound levels of the leader. These results support the hypothesis that the female preference for leader signals in M. elongata is the outcome of a sensory mechanism that originally evolved for directional hearing. PMID:22071183

  6. IEEE SIGNAL PROCESSING MAGAZINE6 September 2004 leadership reflections

    E-print Network

    Nehorai, Arye

    in the Northeast were looking for more minority candidates and changing from single-sex to coed. Many of my to teach and getting to work with out- standing technical people. The job I took was in image processing Research was only one of two places that could process images digitally and, at least this time, I saw

  7. Correlation of SO2 Gas Emissions, Seismicity and Thermal Signals at Santiaguito, Guatemala

    NASA Astrophysics Data System (ADS)

    Branan, Y. K.; Watson, I.; Harris, A. J.; Rose, W.; Bluth, G. J.; Chigna, G.; Mota, M.

    2003-12-01

    With vertical explosions occurring approximately every 40-50 minutes, the Santiaguito dome at Santa Maria Volcano is an ideal system for examining short-term data patterns. A 3-week long field experiment was performed in January 2003 at the Santiaguito Volcano Observatory in order to record high temporal resolution measurements of volcanic activity. We collected digital seismic data from a single vertical component seismometer located approximately 4 km southeast of the active Caliente vent. A portable infrared thermal monitoring unit was deployed daily to record the temperature of the plume as it left the vent at an acquisition rate of 300 measurements per minute. A miniature ultraviolet spectrometer (MUSE) was also deployed daily to measure the SO2 gas emissions just above the vent. This instrument is based on the differential optical absorption spectroscopy (DOAS) technique and allowed for continuous readings at a rate of 36 measurements per minute from approximately 6.5 km south of the Caliente vent. At abstract time, the seismic data is not analyzed, but there is a strong correlation between the SO2 emission and thermal data showing that the expulsed gas heats the dome extensively as it is emitted, with a possibility of different signatures indicating certain types of activity such as pyroclastic flows. It is expected that, with the addition of seismic data and the application of analysis of periodicity using Fourier Transforms, the data will elucidate conduit processes, providing additional vital constraints to sub-surface models.

  8. Toward lightweight biometric signal processing for wearable devices.

    PubMed

    Francescon, Roberto; Hooshmand, Mohsen; Gadaleta, Matteo; Grisan, Enrico; Seung Keun Yoon; Rossi, Michele

    2015-08-01

    Wearable devices are becoming a natural and economic means to gather biometric data from end users. The massive amount of information that they will provide, unimaginable until a few years ago, owns an immense potential for applications such as continuous monitoring for personalized healthcare and use within fitness applications. Wearables are however heavily constrained in terms of amount of memory, transmission capability and energy reserve. This calls for dedicated, lightweight but still effective algorithms for data management. This paper is centered around lossy data compression techniques, whose aim is to minimize the amount of information that is to be stored on their onboard memory and subsequently transmitted over wireless interfaces. Specifically, we analyze selected compression techniques for biometric signals, quantifying their complexity (energy consumption) and compression performance. Hence, we propose a new class of codebook-based (CB) compression algorithms, designed to be energy efficient, online and amenable to any type of signal exhibiting recurrent patterns. Finally, the performance of the selected and the new algorithm is assessed, underlining the advantages offered by CB schemes in terms of memory savings and classification algorithms. PMID:26737218

  9. Design of a dataway processor for a parallel image signal processing system

    NASA Astrophysics Data System (ADS)

    Nomura, Mitsuru; Fujii, Tetsuro; Ono, Sadayasu

    1995-04-01

    Recently, demands for high-speed signal processing have been increasing especially in the field of image data compression, computer graphics, and medical imaging. To achieve sufficient power for real-time image processing, we have been developing parallel signal-processing systems. This paper describes a communication processor called 'dataway processor' designed for a new scalable parallel signal-processing system. The processor has six high-speed communication links (Dataways), a data-packet routing controller, a RISC CORE, and a DMA controller. Each communication link operates at 8-bit parallel in a full duplex mode at 50 MHz. Moreover, data routing, DMA, and CORE operations are processed in parallel. Therefore, sufficient throughput is available for high-speed digital video signals. The processor is designed in a top- down fashion using a CAD system called 'PARTHENON.' The hardware is fabricated using 0.5-micrometers CMOS technology, and its hardware is about 200 K gates.

  10. H CANYON PROCESSING IN CORRELATION WITH FH ANALYTICAL LABS

    SciTech Connect

    Weinheimer, E.

    2012-08-06

    Management of radioactive chemical waste can be a complicated business. H Canyon and F/H Analytical Labs are two facilities present at the Savannah River Site in Aiken, SC that are at the forefront. In fact H Canyon is the only large-scale radiochemical processing facility in the United States and this processing is only enhanced by the aid given from F/H Analytical Labs. As H Canyon processes incoming materials, F/H Labs provide support through a variety of chemical analyses. Necessary checks of the chemical makeup, processing, and accountability of the samples taken from H Canyon process tanks are performed at the labs along with further checks on waste leaving the canyon after processing. Used nuclear material taken in by the canyon is actually not waste. Only a small portion of the radioactive material itself is actually consumed in nuclear reactors. As a result various radioactive elements such as Uranium, Plutonium and Neptunium are commonly found in waste and may be useful to recover. Specific processing is needed to allow for separation of these products from the waste. This is H Canyon's specialty. Furthermore, H Canyon has the capacity to initiate the process for weapons-grade nuclear material to be converted into nuclear fuel. This is one of the main campaigns being set up for the fall of 2012. Once usable material is separated and purified of impurities such as fission products, it can be converted to an oxide and ultimately turned into commercial fuel. The processing of weapons-grade material for commercial fuel is important in the necessary disposition of plutonium. Another processing campaign to start in the fall in H Canyon involves the reprocessing of used nuclear fuel for disposal in improved containment units. The importance of this campaign involves the proper disposal of nuclear waste in order to ensure the safety and well-being of future generations and the environment. As processing proceeds in the fall, H Canyon will have a substantial number of samples being sent to F/H Labs. All analyses of these samples are imperative to safe and efficient processing. The important campaigns to occur would be impossible without feedback from analyses such as chemical makeup of solutions, concentrations of dissolution acids and nuclear material, as well as nuclear isotopic data. The necessity of analysis for radiochemical processing is evident. Processing devoid of F/H Lab's feedback would go against the ideals of a safety-conscious and highly accomplished processing facility such as H Canyon.

  11. Low-Pass Parabolic FFT Filter for Airborne and Satellite Lidar Signal Processing

    PubMed Central

    Jiao, Zhongke; Liu, Bo; Liu, Enhai; Yue, Yongjian

    2015-01-01

    In order to reduce random errors of the lidar signal inversion, a low-pass parabolic fast Fourier transform filter (PFFTF) was introduced for noise elimination. A compact airborne Raman lidar system was studied, which applied PFFTF to process lidar signals. Mathematics and simulations of PFFTF along with low pass filters, sliding mean filter (SMF), median filter (MF), empirical mode decomposition (EMD) and wavelet transform (WT) were studied, and the practical engineering value of PFFTF for lidar signal processing has been verified. The method has been tested on real lidar signal from Wyoming Cloud Lidar (WCL). Results show that PFFTF has advantages over the other methods. It keeps the high frequency components well and reduces much of the random noise simultaneously for lidar signal processing. PMID:26473881

  12. Neural Correlates of Individual Differences in Strategic Retrieval Processing

    ERIC Educational Resources Information Center

    Bridger, Emma K.; Herron, Jane E.; Elward, Rachael L.; Wilding, Edward L.

    2009-01-01

    Processes engaged when information is encoded into memory are an important determinant of whether that information will be recovered subsequently. Also influential, however, are processes engaged at the time of retrieval, and these were investigated here by using event-related potentials (ERPs) to measure a specific class of retrieval operations.…

  13. Nuclear Correlations and the r Process A. Arcones*

    E-print Network

    Bertsch George F.

    of a weakened pairing field in the Hartree-Fock-Bogoliubov (HFB) treatment of nuclei near the dripline on the synthesis of heavy elements by the r process. As calculated by Delaroche et al. [Phys. Rev. C 81, 014303 the calculated abundances before the third r-process peak (at mass number A % 195), where the abundances are low

  14. The neural correlates of emotion processing in juvenile offenders.

    PubMed

    Pincham, Hannah L; Bryce, Donna; Pasco Fearon, R M

    2015-11-01

    Individuals with severe antisocial behaviour often demonstrate abnormalities or difficulties in emotion processing. Antisocial behaviour typically onsets before adulthood and is reflected in antisocial individuals at the biological level. We therefore conducted a brain-based study of emotion processing in juvenile offenders. Male adolescent offenders and age-matched non-offenders passively viewed emotional images whilst their brain activity was recorded using electroencephalography. The early posterior negativity (EPN) and the late positive potential (LPP) components were used as indices of emotion processing. For both juvenile offenders and non-offenders, the EPN differentiated unpleasant images from other image types, suggesting that early perceptual processing was not impaired in the offender group. In line with normal emotion processing, the LPP was significantly enhanced following unpleasant images for non-offenders. However, for juvenile offenders, the LPP did not differ across image categories, indicative of deficient emotional processing. The findings indicated that this brain-based hypo-reactivity occurred during a late stage of cognitive processing and was not a consequence of atypical early visual attention or perception. This study is the first to show attenuated emotion processing in juvenile offenders at the neural level. Overall, these results have the potential to inform interventions for juvenile offending. PMID:25440113

  15. Correlation of neural responses in the cochlear nucleus with low-frequency noise amplitude modulation of a tonal signal

    NASA Astrophysics Data System (ADS)

    Bibikov, N. G.

    2014-09-01

    The responses of single neurons of the cochlear nucleus of a grass frog to long tonal signals amplitude-modulated by repeat intervals of low-frequency noise have been studied. The carrier frequency always corresponded to the characteristic frequency of the studied cell (a range of 0.2 kHz-2 kHz); the modulated signal was noise in the ranges 0-15 Hz, 0-50 Hz, or 0-150 Hz. We obtained the correlation functions of the cyclic histogram reflecting the change in probability of a neuron pulse discharge (spike) during the modulation period with the shape of the signal envelope in the same period. The form of the obtained correlation functions usually does not change qualitatively with a change in carrier level or modulation depth; however, this could essentially depend of the frequency component of the modulating function. In the majority of cases, comparison of the cyclic histogram of the reaction with only the current amplitude value does not adequately reveal the signal's time features that determine the reaction of a neuron. The response is also determined by the other sound features, primarily by the rate of the change in amplitude. The studied neurons differed among themselves, both in preference toward a certain range of modulated frequencies and in the features of the envelope that caused the cell's response.

  16. Reliable and Efficient Parallel Processing Algorithms and Architectures for Modern Signal Processing. Ph.D. Thesis

    NASA Technical Reports Server (NTRS)

    Liu, Kuojuey Ray

    1990-01-01

    Least-squares (LS) estimations and spectral decomposition algorithms constitute the heart of modern signal processing and communication problems. Implementations of recursive LS and spectral decomposition algorithms onto parallel processing architectures such as systolic arrays with efficient fault-tolerant schemes are the major concerns of this dissertation. There are four major results in this dissertation. First, we propose the systolic block Householder transformation with application to the recursive least-squares minimization. It is successfully implemented on a systolic array with a two-level pipelined implementation at the vector level as well as at the word level. Second, a real-time algorithm-based concurrent error detection scheme based on the residual method is proposed for the QRD RLS systolic array. The fault diagnosis, order degraded reconfiguration, and performance analysis are also considered. Third, the dynamic range, stability, error detection capability under finite-precision implementation, order degraded performance, and residual estimation under faulty situations for the QRD RLS systolic array are studied in details. Finally, we propose the use of multi-phase systolic algorithms for spectral decomposition based on the QR algorithm. Two systolic architectures, one based on triangular array and another based on rectangular array, are presented for the multiphase operations with fault-tolerant considerations. Eigenvectors and singular vectors can be easily obtained by using the multi-pase operations. Performance issues are also considered.

  17. Resolving the range ambiguity in OFDR using digital signal processing

    NASA Astrophysics Data System (ADS)

    Riesen, Nicolas; T-Y Lam, Timothy; Chow, Jong H.

    2014-12-01

    A digitally range-gated variant of optical frequency domain reflectometry is demonstrated which overcomes the beat note ambiguity when sensing beyond a single frequency sweep. The range-gating is achieved using a spread spectrum technique involving time-stamping of the optical signal using high-frequency pseudorandom phase modulation. The reflections from different sections of fiber can then be isolated in the time domain by digitally inverting the phase modulation using appropriately-delayed copies of the pseudorandom noise code. Since the technique overcomes the range ambiguity in OFDR, it permits high sweep repetition rates without sacrificing range, thus allowing for high-bandwidth sensing over long lengths of fiber. This is demonstrated for the case of quasi-distributed sensing.

  18. Decision Processes in Discrimination: Fundamental Misrepresentations of Signal Detection Theory

    NASA Technical Reports Server (NTRS)

    Balakrishnan, J. D.

    1998-01-01

    In the first part of this article, I describe a new approach to studying decision making in discrimination tasks that does not depend on the technical assumptions of signal detection theory (e.g., normality of the encoding distributions). Applying these new distribution-free tests to data from three experiments, I show that base rate and payoff manipulations had substantial effects on the participants' encoding distributions but no effect on their decision rules, which were uniformly unbiased in equal and unequal base rate conditions and in symmetric and asymmetric payoff conditions. In the second part of the article, I show that this seemingly paradoxical result is readily explained by the sequential sampling models of discrimination. I then propose a new, "model-free" test for response bias that seems to more properly identify both the nature and direction of the biases induced by the classical bias manipulations.

  19. Neurophysiological Correlates of Configural Face Processing in Schizotypy

    PubMed Central

    Batty, Rachel A.; Francis, Andrew J. P.; Innes-Brown, Hamish; Joshua, Nicole R.; Rossell, Susan L.

    2014-01-01

    Background: Face processing impairment in schizophrenia appears to be underpinned by poor configural (as opposed to feature-based) processing; however, few studies have sought to characterize this impairment electrophysiologically. Given the sensitivity of event-related potentials to antipsychotic medications, and the potential for neurophysiological abnormalities to serve as vulnerability markers for schizophrenia, a handful of studies have investigated early visual P100 and face-selective N170 in “at risk” populations. However, this is the first known neurophysiological investigation of configural face processing in a non-clinical schizotypal sample. Methods: Using stimuli designed to engage configural processing in face perception (upright and inverted Mooney and photographic faces), P100 and N170 components were recorded in healthy individuals characterized by high (N?=?14) and low (N?=?14) schizotypal traits according to the Oxford–Liverpool Inventory of Feelings and Experiences. Results: High schizotypes showed significantly reduced N170 amplitudes to inverted photographic faces. Typical N170 latency and amplitude inversion effects (delayed and enhanced N170 to inverted relative to upright photographic faces, and enhanced amplitude to upright versus inverted Mooney faces), were demonstrated by low, but not high, schizotypes. No group differences were shown for P100 analyses. Conclusions: The findings suggest that neurophysiological deficits in processing facial configurations (N170) are apparent in schizotypy, while the early sensory processing (P100) of faces appears intact. This work adds to the mounting evidence for analogous neural processing anomalies at the healthy end of the psychosis continuum. PMID:25161628

  20. IEEE SIGNAL PROCESSING LETTERS, VOL. 16, NO. 9, SEPTEMBER 2009 739 Robust and Consistent Sampling

    E-print Network

    Eldar, Yonina

    IEEE SIGNAL PROCESSING LETTERS, VOL. 16, NO. 9, SEPTEMBER 2009 739 Robust and Consistent Sampling Tsvi G. Dvorkind and Yonina C. Eldar, Senior Member, IEEE Abstract--We address a sampling problem in which the goal is to approximate a signal from its nonideal (generalized) samples. The reconstruction

  1. EURASIP SIGNAL PROCESSING 1 Design of Digital Systems for Arbitrary Sampling

    E-print Network

    Göckler, Heinz G.

    EURASIP SIGNAL PROCESSING 1 Design of Digital Systems for Arbitrary Sampling Rate Conversion Gennaro Evangelista Abstract-- The conversion of digital signals from a given sampling rate to a second, arbitrary sampling rate, with both sam- pling rates derived from independent clock generators, is revisited

  2. Towards neuromote: a single-chip, 100-channel, neural-signal acquisition, processing, and telemetry device.

    PubMed

    Farshchi, Shahin; Markovic, Dejan; Pamarti, Sudhakar; Razavi, Behzad; Judy, Jack W

    2007-01-01

    This paper investigates the design of a single-chip, 100-channel wireless neural-signal acquisition, processing, and communications device. Design approaches for realizing front-end neural-signal amplifier, data conversion, microprocessor, and transceiver circuitry have been outlined. PMID:18001983

  3. Role for G Protein G## Isoform Specificity in Synaptic Signal Processing: A Computational Study

    E-print Network

    Role for G Protein G## Isoform Specificity in Synaptic Signal Processing: A Computational Study for G protein G## isoform specificity in synaptic signal pro­ cessing: A computational study. J the functional impact of G protein--mediated presynaptic autoin­ hibition on synaptic filtering properties

  4. SIGNAL PROCESSING FOR HEARING AND SPEECH SCIENCES SLHS 605 -SPRING 2014

    E-print Network

    Heinz, Michael G.

    SIGNAL PROCESSING FOR HEARING AND SPEECH SCIENCES SLHS 605 - SPRING 2014 Time: Monday 1:30-4:20pm-6627 Email: mheinz@purdue.edu Office Hours: TBD Required Text: Signals and Systems for Speech and Hearing (2 to hearing and speech sciences. Topics include: Introduction to MATLAB, time and frequency domain

  5. A Cochlear Implant Signal Processing Lab: Exploration of a Problem-Based Learning Exercise

    ERIC Educational Resources Information Center

    Bhatti, P. T.; McClellan, J. H.

    2011-01-01

    This paper presents an introductory signal processing laboratory and examines this laboratory exercise in the context of problem-based learning (PBL). Centered in a real-world application, a cochlear implant, the exercise challenged students to demonstrate a working software-based signal processor. Partnering in groups of two or three, second-year…

  6. Power Signal Processing: A New Perspective for Power Analysis and Optimization

    E-print Network

    Mohanram, Kartik

    . A component can be a gate, ALU, processor core, or even an entire chip on a printed- circuit board. BasedPower Signal Processing: A New Perspective for Power Analysis and Optimization Quming Zhou, Lin analysis and opti- mization of modern systems, we propose to treat power as a signal and leverage the rich

  7. SAMPLING THEORY IN SIGNAL AND IMAGE PROCESSING c 2011 SAMPLING PUBLISHING

    E-print Network

    Bidegaray, Brigitte

    SAMPLING THEORY IN SIGNAL AND IMAGE PROCESSING c 2011 SAMPLING PUBLISHING Vol. 10, No. 1-2, 2011 theory, which fixes the sampling frequency at least twice the input signal frequency bandwidth. It has.Fesquet@imag.fr Abstract We propose a filtering technique which takes advantage of a specific non-uniform sampling scheme

  8. Signal Processing Techniques for a Planetary Subsurface Radar Onboard Satellite

    NASA Astrophysics Data System (ADS)

    Yagitani, S.; Ishikawa, T.; Nagano, I.; Kojima, H.; Matsumoto, H.

    2001-12-01

    We are developing a satellite-borne HF ( ~ 10 MHz) radar system to be used to investigate planetary subsurface layered structures. Before deciding the design of a high-performance subsurface radar system, in this study we calculate the propagation and reflection characteristics of various HF radar pulses through subsurface layer models, in order to examine the wave forms and frequencies of the radar pulses suitable to discriminate and pick up weak subsurface echoes buried in stronger surface reflection and scattering echoes. In the numerical calculations the wave form of a transmitted radar pulse is first Fourier-transformed into a number of elementary plane waves having different frequencies, for each of which the propagation and reflection characteristics through subsurface layer models are calculated by a full wave analysis. Then the wave form of the reflected radar echo is constructed by synthesizing all of the elementary plane waves. As the transmitted pulses, we use several different types of wave form modulation to realize the radar pulse compression to improve the signal-to-noise (S/N) ratio and time resolution of the subsurface echoes: the linear FM chirp (conventional), the M (maximal-length) sequence and the complementary sequences. We will discuss the characteristics of these pulse compression techniques, such as the improvement in the S/N ratio and the time resolution to identify the subsurface echoes. We will also present the possibility of applying the Multiple Signal Classification (MUSIC) method to further improve both the S/N ratio and time resolution to extract the weaker subsurface echoes.

  9. DETECTION OF SIGNALS FROM COSMIC REIONIZATION USING RADIO INTERFEROMETRIC SIGNAL PROCESSING

    SciTech Connect

    Datta, A.; Bhatnagar, S.; Carilli, C. L.

    2009-10-01

    Observations of the H I 21 cm transition line promises to be an important probe into the cosmic dark ages and epoch of reionization. One of the challenges for the detection of this signal is the accuracy of the foreground source removal. This paper investigates the extragalactic point source contamination and how accurately the bright sources (approx>1 Jy) should be removed in order to reach the desired rms noise and be able to detect the 21 cm transition line. Here, we consider position and flux errors in the global sky model for these bright sources as well as the frequency independent residual calibration errors. The synthesized beam is the only frequency dependent term included here. This work determines the level of accuracy for the calibration and source removal schemes and puts forward constraints for the design of the cosmic reionization data reduction scheme for the upcoming low frequency arrays such as, Murchison Widefield Array, Precision Array to Probe Epoch of Reionization, etc. We show that in order to detect the reionization signal the bright sources need to be removed from the data sets with a positional accuracy of approx0.1 arcsec. Our results also demonstrate that the efficient foreground source removal strategies can only tolerate a frequency independent antenna based mean residual calibration error of approx<0.2% in amplitude or approx<0.{sup 0}2 in phase, if they are constant over each days of observations (6 hr). In future papers, we will extend this analysis to the power-spectral domain and also include the frequency-dependent calibration errors and direction-dependent errors (ionosphere, primary beam, etc.).

  10. Parallel digital signal processing (DSP) vehicle controller for automated vehicles

    NASA Astrophysics Data System (ADS)

    Perelli, Fabio; Rajagopalan, Ramesh

    1997-01-01

    This paper presents the design and implementation of a high performance vehicle controller based on parallel digital processing systems for automated vehicles. From the literature it has been observed that one of the main limiting factors of most automated vehicles rests on the available computing power. Most systems employ camera vision for guidance purposes. In some cases other sensors are used in combination with camera vision. The amount of information that has to be processed can overwhelm many processors. Solutions so far involved distributed processing, massively parallel processors, dedicated processors and mini computers. In most cases, these systems use specially designed processors, lacking standard interfacing, and as a result proprietary interface cards have to be built. This paper takes the alternate approach of designing a high performance controller using the parallel DSP systems, namely, the TMS320C40 processors with 275 MIPS and 50 MFLOPS. This controller processes data from a CCD camera which is focused onto a road segment containing a line that has suitable contrast with the road surface. The DSP based controller in a PC environment. Carries out the task of high level control while the low level servo control is assigned to dedicated motion controllers communicating with the DSP based controller through the PC bus. Results of image processing and timing requirements for various topologies are detailed.

  11. Bioelectrical signal processing in cardiac and neurological applications and electromyography: physiology, engineering, and noninvasive applications

    PubMed Central

    Valentinuzzi, Max E

    2007-01-01

    The present article reviews two recent books dealing with rather closely related subjects; in fact, they tend to complement and supplement reciprocally. Obviously, the electromyogram is a bioelectrical signal that often is mathematically manipulated in different ways to better extract its information. Moreover, its correlation with other bioelectric variables may become necessary.

  12. Neural correlates of response inhibition in children with attention-deficit/hyperactivity disorder: A controlled version of the stop-signal task.

    PubMed

    Janssen, Tieme W P; Heslenfeld, Dirk J; van Mourik, Rosa; Logan, Gordon D; Oosterlaan, Jaap

    2015-08-30

    The stop-signal task has been used extensively to investigate the neural correlates of inhibition deficits in children with ADHD. However, previous findings of atypical brain activation during the stop-signal task in children with ADHD may be confounded with attentional processes, precluding strong conclusions on the nature of these deficits. In addition, there are recent concerns on the construct validity of the SSRT metric. The aim of this study was to control for confounding factors and improve the specificity of the stop-signal task to investigate inhibition mechanisms in children with ADHD. FMRI was used to measure inhibition related brain activation in 17 typically developing children (TD) and 21 children with ADHD, using a highly controlled version of the stop-signal task. Successful inhibition trials were contrasted with control trials that were comparable in frequency, visual presentation and absence of motor response. We found reduced brain activation in children with ADHD in key inhibition areas, including the right inferior frontal gyrus/insula, and anterior cingulate/dorsal medial prefrontal cortex. Using a more stringent controlled design, this study replicated and specified previous findings of atypical brain activation in ADHD during motor response inhibition. PMID:26195296

  13. Lab 3: Simulation of Earthquake Response of Buildings CEE370 Sensors, Electrical Circuits, and Signal Processing

    E-print Network

    Lynch, Jerome P.

    Lab 3: Simulation of Earthquake Response of Buildings CEE370 ­ Sensors, Electrical Circuits, and Signal Processing Lab 3: Simulation of Earthquake Response of Buildings #12;Lab 3: Simulation of Earthquake Response of Buildings CEE370 ­ Sensors, Electrical Circuits

  14. Signal processing and transduction in plant cells: the end of the beginning? 

    E-print Network

    Gilroy, Simon; Trewavas, Anthony J

    Plants have a very different lifestyle to animals, and one might expect that unique molecules and processes would underpin plant-cell signal transduction. But, with a few notable exceptions, the list is remarkably ...

  15. Likelihood and Bayesian signal processing methods for the analysis of auditory neural and behavioral data

    E-print Network

    Dreyer, Anna Alexandra

    2008-01-01

    Developing a consensus on how to model neural and behavioral responses and to quantify important response properties is a challenging signal processing problem because models do not always adequately capture the data and ...

  16. Signal Processing Variables for Optimization of Flaw Detection in Composites Using Ultrasonic Guided Wave Scanning

    NASA Technical Reports Server (NTRS)

    Roth, Don J.; Cosgriff, Laura M.; Martin, Richard E.; Teemer, LeTarrie

    2004-01-01

    This study analyzes the effect of signal processing variables on the ability of the ultrasonic guided wave scan method at NASA Glenn Research Center to distinguish various flaw conditions in ceramic matrix composites samples. In the ultrasonic guided wave scan method, several time- and frequency-domain parameters are calculated from the ultrasonic guided wave signal at each scan location to form images. The parameters include power spectral density, centroid mean time, total energy (zeroth moment), centroid frequency, and ultrasonic decay rate. A number of signal processing variables are available to the user when calculating these parameters. These signal processing variables include 1) the time portion of the time-domain waveform processed, 2) integration type for the properties requiring integrations, 3) bounded versus unbounded integrations, 4) power spectral density window type, 5) and the number of time segments chosen if using the short-time fourier transform to calculate ultrasonic decay rate. Flaw conditions examined included delamination, cracking, and density variation.

  17. On the Management of Latency in the Synthesis of Real-Time Signal Processing Systems from

    E-print Network

    Jeffay, Kevin

    the literature and industry: a synthetic aperture radar application, an INMARSAT mobile satellite receiver application, and an acoustic signal processing application from the ALFS anti-submarine warfare system

  18. On the Management of Latency in the Synthesis of RealTime Signal Processing Systems from

    E-print Network

    Goddard, Steve

    application, an INMARSAT mobile satellite receiver application, and an acoustic signal processing application from the ALFS anti­submarine warfare system. This research is the first to model the execution

  19. Digital signal processing techniques for optical coherence tomography : OCT and OCT image enhancement

    E-print Network

    Adler, Desmond Christopher, 1978-

    2004-01-01

    Digital signal processing (DSP) techniques were developed to improve the flexibility, functionality, and image quality of ultrahigh resolution optical coherence tomography (OCT) systems. To reduce the dependence of OCT ...

  20. Want to find how the Brain is "illusioned"? Signal/Image processing summer internship position.

    E-print Network

    Salvaggio, Carl

    Want to find how the Brain is "illusioned"? Signal/Image processing summer internship position/junior) or a graduate student (first year) seeking a summer internship/graduate project topic. Qualifications