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. SAR image enhancement via post-correlation signal processing

    NASA Technical Reports Server (NTRS)

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

    1984-01-01

    Seventeen interpreters ranked sets of computer-generated radar imagery to assess the value of post-correlation processing on the interpretability of SAR (synthetic aperture radar) imagery. The post-correlation processing evaluated amounts to a nonlinear mapping of the signal exiting a digital correlator and allows full use of signal bandwidth for improving the spatial resolution or for noise reduction. The results indicate that it is reasonable to hypothesize an optimal SAR presentation format for specific applications even though this study was too limited to be specific.

  4. 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.

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

    SciTech Connect

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

    2006-08-30

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

  6. 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

  7. 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.

  8. 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.

  9. 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.

  10. 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

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

    PubMed

    Ataie, Vahid; Papen, George

    2011-02-01

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

  12. Advanced signal processing

    NASA Astrophysics Data System (ADS)

    Creasey, D. J.

    1985-12-01

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

  13. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2006-06-01

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

  15. 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

  16. 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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

    We report a high-resolution optical refractometer based on the long-period grating Michelson interferometer. The interferometer phase shift depends on the refractive index that surrounds the fiber probe. A cross-correlation signal-processing method is used to demodulate the interferometer phase shift. Experimental results show that a resolution of 3×10-6 refractive index unit (RIU) can be obtained using this cross-correlation signal processing method. In addition, a measurement sensitivity up to 3×103 deg/RIU is showed as the surrounding refractive index changing from 1.33 to 1.42. Such high-resolution and low-cost optical refractometers would find more applications in chemical or biochemical sensing fields.

  18. 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.

  19. Microwave photonic signal processing.

    PubMed

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

    2013-09-23

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

  20. Telemetry Ranging: Signal Processing

    NASA Astrophysics Data System (ADS)

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

    2016-02-01

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

  1. Optical signal processing

    NASA Astrophysics Data System (ADS)

    Vanderlugt, A.

    1993-07-01

    A quasi-realtime adaptive processing system was used to correct the multipath distortion found in wideband digital radios. The measured power spectral density of the input signal was used to adaptively select one of eight equalization filters which reduce the residual distortion to less than 3.6 dB even for the most severe channel distortion. A related adaptive system was used for signal excision in which we removed narrowband interference from wideband signals with minimum signal distortion. An 8x8 acousto-optic switch in a multimode fiber-optic system was built. Insertion loss is approximately 2-4 dB, signal-to-crosstalk ratio is better than 25 dB, and the reconfiguration time is 880 nsec. Short pulses were detected by using the Fresnel transform. Pulses as short as the theoretical limit of 20 nanoseconds were detected for this system, and separated by as little as 60 nanoseconds or by as much as 17 nanoseconds. All possible acousto-optic scanning configurations were considered and classified into four basic types. A consistent set of design relationships for each of the scanning configurations was developed and presented in both tabular and graphic forms from which a preliminary design is obtained.

  2. Digital signal processing

    NASA Astrophysics Data System (ADS)

    Meyer, G.

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

  3. 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.

  4. [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.

  5. Signal and Image Processing Operations

    Energy Science and Technology Software Center (ESTSC)

    1995-05-10

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

  6. Signal processing in SETI

    NASA Technical Reports Server (NTRS)

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

    1985-01-01

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

  7. 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.

  8. 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

  9. 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

  10. 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.

  11. 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.

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

    NASA Astrophysics Data System (ADS)

    Mejía-Uriarte, E. V.; Navarrete, M.; Villagrán-Muniz, M.

    2004-09-01

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

  13. 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.

  14. 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

  15. Wave-based signal processing

    NASA Astrophysics Data System (ADS)

    McClure, Mark Richard

    The efficacy of imbedding knowledge of wave-scattering phenomenology into the processing of remote-sensing data is examined. In particular, the processing of radar and sonar phase history and synthetic-aperture imagery is considered. Algorithms are developed for effecting signal denoising, feature extraction (for use in target identification/classification) and detection. Three classes of algorithms are presented: (1) superresolution, (2) adaptive-signal decomposition, and (3) template matching. A superresolution signal-processing algorithm is used for the identification of wavefronts from the fields scattered from several canonical targets. Particular wave objects that are examined are single and multiple edge diffraction, scattering from flat and curved surfaces, cone diffraction, and creeping waves. General properties of superresolution processing of such data--independent of the particular algorithm used--are assessed through examination of the Cramer-Rao bounds. The method of matching pursuits is used to effect data-adaptive signal decomposition. This algorithm utilizes a nonlinear iterative procedure to project a given waveform onto a particular dictionary. For scattering problems, the most appropriate dictionary is composed of waveobjects consistent with the underlying wave phenomenology. A signal scattered from most targets of interest can be decomposed in terms of wavefronts, resonances, and chirps--and each of these subclasses can be further subdivided based on characteristic wave physics. Here the efficacy of applying the method of matching pursuits with a wave-based dictionary is examined, for the processing of scattering data. Detection test statistics are derived based on matching-pursuits results from each dictionary separately as well as with the cumulative results from multiple dictionaries. Examples are presented using measured data, for wideband, time-domain acoustic scattering from a submerged elastic shell. Finally, a full-wave electromagnetic-scattering model is utilized to effect a landmine detector via a multiresolution template-matching-like algorithm. Detection is performed on fully polarimetric ultra-wideband (50-1200 MHz) synthetic aperture radar (SAR) imagery. Multiresolution template matching is effected via discrete-wavelet transform (DWT) of the SAR imagery and the parametric target-signatures (templates). Detector results are presented and compared with those obtained using alternative techniques.

  16. Signal processing in eukaryotic chemotaxis

    NASA Astrophysics Data System (ADS)

    Segota, Igor; Rachakonda, Archana; Franck, Carl

    2013-03-01

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

  17. Nuclear sensor signal processing circuit

    DOEpatents

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

    2007-02-20

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

  18. Hot topics: Signal processing in acoustics

    NASA Astrophysics Data System (ADS)

    Gaumond, Charles F.

    2005-09-01

    Signal processing in acoustics is a multidisciplinary group of people that work in many areas of acoustics. We have chosen two areas that have shown exciting new applications of signal processing to acoustics or have shown exciting and important results from the use of signal processing. In this session, two hot topics are shown: the use of noiselike acoustic fields to determine sound propagation structure and the use of localization to determine animal behaviors. The first topic shows the application of correlation on geo-acoustic fields to determine the Greens function for propagation through the Earth. These results can then be further used to solve geo-acoustic inverse problems. The first topic also shows the application of correlation using oceanic noise fields to determine the Greens function through the ocean. These results also have utility for oceanic inverse problems. The second topic shows exciting results from the detection, localization, and tracking of marine mammals by two different groups. Results from detection and localization of bullfrogs are shown, too. Each of these studies contributed to the knowledge of animal behavior. [Work supported by ONR.

  19. Advanced detectors and signal processing

    NASA Technical Reports Server (NTRS)

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

    1986-01-01

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

  20. 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.

  1. All-optical implementation of signal processing functions

    NASA Astrophysics Data System (ADS)

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

    2015-01-01

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

  2. Synthetic aperture radar signal processing: Trends and technologies

    NASA Technical Reports Server (NTRS)

    Curlander, John C.

    1993-01-01

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

  3. Principal Component Analysis in ECG Signal Processing

    NASA Astrophysics Data System (ADS)

    Castells, Francisco; Laguna, Pablo; Sörnmo, Leif; Bollmann, Andreas; Roig, José Millet

    2007-12-01

    This paper reviews the current status of principal component analysis in the area of ECG signal processing. The fundamentals of PCA are briefly described and the relationship between PCA and Karhunen-Loève transform is explained. Aspects on PCA related to data with temporal and spatial correlations are considered as adaptive estimation of principal components is. Several ECG applications are reviewed where PCA techniques have been successfully employed, including data compression, ST-T segment analysis for the detection of myocardial ischemia and abnormalities in ventricular repolarization, extraction of atrial fibrillatory waves for detailed characterization of atrial fibrillation, and analysis of body surface potential maps.

  4. Signal Processing Techniques for Robust Speech Recognition

    NASA Astrophysics Data System (ADS)

    Asano, Futoshi

    In this paper, signal processing techniques which can be applied to automatic speech recognition to improve its robustness are reviewed. The choice of signal processing techniques is strongly dependent on the scenario of the applications. The analysis of scenario and the choice of suitable signal processing techniques are shown through two examples.

  5. Early anti-correlated BOLD signal changes of physiologic origin

    PubMed Central

    Bright, Molly G.; Bianciardi, Marta; de Zwart, Jacco A.; Murphy, Kevin; Duyn, Jeff H.

    2014-01-01

    Negative BOLD signals that are synchronous with resting state fluctuations have been observed in large vessels in the cortical sulci and surrounding the ventricles. In this study, we investigated the origin of these negative BOLD signals by applying a Cued Deep Breathing (CDB) task to create transient hypocapnia and a resultant global fMRI signal decrease. We hypothesized that a global stimulus would amplify the effect in large vessels and that using a global negative (vasoconstrictive) stimulus would test whether these voxels exhibit either inherently negative or simply anti-correlated BOLD responses. Significantly anti-correlated, but positive, BOLD signal changes during respiratory challenges were identified in voxels primarily located near edges of brain spaces containing CSF. These positive BOLD responses occurred earlier than the negative CDB response across most of gray matter voxels. These findings confirm earlier suggestions that in some brain regions, local, fractional changes in CSF volume may overwhelm BOLD-related signal changes, leading to signal anti-correlation. We show that regions with CDB anti-correlated signals coincide with most, but not all, of the regions with negative BOLD signal changes observed during a visual and motor stimulus task. Thus, the addition of a physiological challenge to fMRI experiments can help identify which negative BOLD signals are passive physiological anti-correlations and which may have a putative neuronal origin. PMID:24211818

  6. 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.

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

    NASA Technical Reports Server (NTRS)

    Prokop, Norman; Krasowski, Michael

    2013-01-01

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

  8. 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.

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

    PubMed

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

    2015-07-01

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

  10. 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.

  11. 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.

  12. Robot Gripper With Signal Processing

    NASA Technical Reports Server (NTRS)

    Killion, Richard R.

    1988-01-01

    Single-chip computer and sensor-circuit chips preprocess sensor data. Self-contained circuitry combines sensor signals for serial digital transmission. Gripping surfaces crossed with grooves for grasping differently shaped objects. Gripper cavities house sensors and preprocessing circuitry. Sensors and preprocessing circuitry in robot gripper reduce amount of data being transmitted between robot controller and gripper. Placement in gripper reduces signal delays and vulnerability to electromagnetic interference.

  13. Process Dissociation and Mixture Signal Detection Theory

    ERIC Educational Resources Information Center

    DeCarlo, Lawrence T.

    2008-01-01

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

  14. A coherent nonlinear optical signal induced by electron correlations

    PubMed Central

    Mukamel, Shaul; Oszwa?dowski, Rafa?; Yang, Lijun

    2010-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2011-10-01

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

  16. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  18. Electronic warfare channelizer signal processing algorithms

    NASA Astrophysics Data System (ADS)

    Wood, Jerry B.; Daugherty, Gregory K.

    1995-06-01

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

  19. 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.

  20. 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.

  1. Hybrid image and signal processing

    SciTech Connect

    Casasent, D.P.; Tescher, A.G.

    1988-01-01

    Topics presented in these proceedings include: optical processors, bimodal optical computers, systems for geophysical diffraction tomography, parallel image processing, optical image processors, processor arrays, hypercube multiprocessors, border finding in cardiac digital x-ray images, and analysis of ultrasound image sequences by concurrent processing.

  2. 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.

  3. 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.

  4. Signal processing of infrared imaging system

    NASA Astrophysics Data System (ADS)

    Li, Layuan

    1986-01-01

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

  5. 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.

  6. ECG signal processing using multiresolution analysis.

    PubMed

    Boutaa, M; Bereksi-Reguig, F; Debbal, S M A

    2008-01-01

    In this paper, multiresolution analysis using wavelets is discussed and evaluated in ECG signal processing. The approach we developed for processing the ECG signals uses two steps. In the first step, we implement an algorithm based on multiresolution analysis using discrete wavelet transform for denoising the ECG signals. The results we obtained on MIT-BIH ECG signals show good performance in denoising ECG signals. In the second step, multiresolution analysis is applied for QRS complex detection. It is shown that with such analysis, the QRS complex can be distinguished from high P or T waves, baseline drift and artefacts. The results we obtained on ECG signals from the MIT-BIH database show a detection rate of QRS complexes above 99.8% (sensitivity=99.88% and predictivity=99.89%), and a total detection failure of 0.24%. PMID:18608790

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

    PubMed

    Rodrigues, Francisco Aparecido; da Fontoura Costa, Luciano

    2009-01-01

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

  8. Optical Profilometers Using Adaptive Signal Processing

    NASA Technical Reports Server (NTRS)

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

    2006-01-01

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

  9. Surface Electromyography Signal Processing and Classification Techniques

    PubMed Central

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

    2013-01-01

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

  10. Optical signal processing: Musical score for optical signals

    NASA Astrophysics Data System (ADS)

    Testorf, Markus

    2012-07-01

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

  11. Digital signal processing in microwave radiometers

    NASA Technical Reports Server (NTRS)

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

    1980-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-10-01

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

  13. 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

  14. Modeling signalized intersection safety with corridor-level spatial correlations.

    PubMed

    Guo, Feng; Wang, Xuesong; Abdel-Aty, Mohamed A

    2010-01-01

    Intersections in close spatial proximity along a corridor should be considered as correlated due to interacted traffic flows as well as similar road design and environmental characteristics. It is critical to incorporate this spatial correlation for assessing the true safety impacts of risk factors. In this paper, several Bayesian models were developed to model the crash data from 170 signalized intersections in the state of Florida. The safety impacts of risk factors such as geometric design features, traffic control, and traffic flow characteristics were evaluated. The Poisson and Negative Binomial Bayesian models with non-informative priors were fitted but the focus is to incorporate spatial correlations among intersections. Two alternative models were proposed to capture this correlation: (1) a mixed effect model in which the corridor-level correlation is incorporated through a corridor-specific random effect and (2) a conditional autoregressive model in which the magnitude of correlations is determined by spatial distances among intersections. The models were compared using the Deviance Information Criterion. The results indicate that the Poisson spatial model provides the best model fitting. Analysis of the posterior distributions of model parameters indicated that the size of intersection, the traffic conditions by turning movement, and the coordination of signal phase have significant impacts on intersection safety. PMID:19887148

  15. 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)

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

    PubMed Central

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

    2014-01-01

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

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

    PubMed

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

    2014-01-01

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

  18. 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

  19. 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.

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

    SciTech Connect

    Katz, R.A.

    1996-10-01

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

  1. Process Correlation Analysis Model for Process Improvement Identification

    PubMed Central

    Park, Sooyong

    2014-01-01

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

  2. 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.}

  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. Bacteriorhodopsin Film For Processing SAR Signals

    NASA Technical Reports Server (NTRS)

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

    1992-01-01

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

  6. 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

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

    NASA Technical Reports Server (NTRS)

    Kishoni, Doron; Pietsch, Benjamin E.

    1990-01-01

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

  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. Signal/noise enhancement strategies for stochastically estimated correlation functions

    NASA Astrophysics Data System (ADS)

    Detmold, William; Endres, Michael G.

    2014-08-01

    We develop strategies for enhancing the signal/noise ratio for stochastically sampled correlation functions. The techniques are general and offer a wide range of applicability. We demonstrate the potential of the approach with a generic two-state system and then explore the practical applicability of the method for single hadron correlators in lattice quantum chromodynamics. In the latter case, we determine the ground state energies of the pion, proton, and delta baryon, as well as the ground and first excited state energy of the rho meson using matrices of correlators computed on an exemplary ensemble of anisotropic gauge configurations. In the majority of cases, we find a modest reduction in the statistical uncertainties on extracted energies compared to conventional variational techniques. However, in the case of the delta baryon, we achieve a factor of 3 reduction in statistical uncertainties. The variety of outcomes achieved for single hadron correlators illustrates an inherent dependence of the method on the properties of the system under consideration and the operator basis from which the correlators are constructed.

  11. Stimulus Contrast and Retinogeniculate Signal Processing.

    PubMed

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

    2016-01-01

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

  12. Stimulus Contrast and Retinogeniculate Signal Processing

    PubMed Central

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

    2016-01-01

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

  13. 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.

  14. Surveillance of industrial processes with correlated parameters

    DOEpatents

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

    1996-12-17

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

  15. Applied digital signal processing systems for vortex flowmeter with digital signal processing.

    PubMed

    Xu, Ke-Jun; Zhu, Zhi-Hai; Zhou, Yang; Wang, Xiao-Fen; Liu, San-Shan; Huang, Yun-Zhi; Chen, Zhi-Yuan

    2009-02-01

    The spectral analysis is combined with digital filter to process the vortex sensor signal for reducing the effect of disturbance at low frequency from pipe vibrations and increasing the turndown ratio. Using digital signal processing chip, two kinds of digital signal processing systems are developed to implement these algorithms. One is an integrative system, and the other is a separated system. A limiting amplifier is designed in the input analog condition circuit to adapt large amplitude variation of sensor signal. Some technique measures are taken to improve the accuracy of the output pulse, speed up the response time of the meter, and reduce the fluctuation of the output signal. The experimental results demonstrate the validity of the digital signal processing systems. PMID:19256675

  16. 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.

  17. 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…

  18. 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.

  19. VLIW architectures for video signal processing

    NASA Astrophysics Data System (ADS)

    Wolf, Wayne H.

    1998-03-01

    This paper surveys the state-of-the-art in very long instruction word (VLIW) architectures for video signal processing (VSP). Several factors make VLIW and video a good match, including the large amounts of data parallelism in video programs and the ability to implement VLIW VSPs on a single chip. The paper first introduces the canonical VLIW architecture, then considers several alternative architectural approaches for video processing, and finally discusses some VLIW VSP architectures in more detail.

  20. 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.

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

    SciTech Connect

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

    2007-03-21

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

  2. 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.

  3. An ultrasonic device for signal processing

    NASA Astrophysics Data System (ADS)

    Kulakov, S. V.; Leks, A. G.; Semenov, S. P.; Ulyanov, G. K.

    1985-11-01

    The invention concerns the field of radioengineering and can be used in analog processors of the signals of phased antenna arrays. There are familiar devices for processing the signals of phased antenna arrays. However these are large in size, structurally complicated, and contain expensive parts. In the proposed device, for the purpose of simplification and cheapening the design and reducing the dimensions, the counting system is in the form of a receiving acoustical array, the elements of which are hooked up to a television-type indicator.

  4. 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.

  5. 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.

  6. 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.

  7. Neural Correlates of Subliminal Language Processing

    PubMed Central

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

    2015-01-01

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

  8. 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.

  9. 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.

  10. 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.

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

    PubMed Central

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

    2012-01-01

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

  12. 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.

  13. 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.

  14. Digital signal processing for beam position feedback

    SciTech Connect

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

    1992-04-01

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

  15. Digital signal processing in acoustics. I

    NASA Astrophysics Data System (ADS)

    Davies, H.; McNeil, D. J.

    1985-11-01

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

  16. 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.

  17. 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.

  18. 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

  19. 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.

  20. 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.

  1. Radar transponder apparatus and signal processing technique

    SciTech Connect

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

    1994-12-31

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

  2. Radar transponder apparatus and signal processing technique

    DOEpatents

    Axline, Jr., Robert M.; Sloan, George R.; Spalding, Richard E.

    1996-01-01

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

  3. 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.

  4. 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.

  5. 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.

  6. Investigating signaling processes in membrane trafficking.

    PubMed

    Sharpe, Laura J; Brown, Andrew J

    2015-01-01

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

  7. 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.

  8. Discrete-time signal processing with DNA.

    PubMed

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

    2013-05-17

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

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

    NASA Technical Reports Server (NTRS)

    Berner, Stephan; DeLeon, Phillip

    1999-01-01

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

  10. 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.

  11. Efficient audio signal processing for embedded systems

    NASA Astrophysics Data System (ADS)

    Chiu, Leung Kin

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

  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. 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.

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

    PubMed

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

    2015-09-01

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

  15. 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.

  16. GLAST Burst Monitor Signal Processing System

    SciTech Connect

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

    2007-07-12

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

  17. GLAST Burst Monitor Signal Processing System

    NASA Astrophysics Data System (ADS)

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

    2007-07-01

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

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

    PubMed

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

    2014-01-01

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

  19. Writer Identification Using Inexpensive Signal Processing Techniques

    NASA Astrophysics Data System (ADS)

    Mokhov, Serguei A.; Song, Miao; Suen, Ching Y.

    We propose to use novel and classical audio and text signal-processing and otherwise techniques for “inexpensive” fast writer identification tasks of scanned hand-written documents “visually”. The “inexpensive” refers to the efficiency of the identification process in terms of CPU cycles while preserving decent accuracy for preliminary identification. This is a comparative study of multiple algorithm combinations in a pattern recognition pipeline implemented in Java around an open-source Modular Audio Recognition Framework (MARF) that can do a lot more beyond audio. We present our preliminary experimental findings in such an identification task. We simulate “visual” identification by “looking” at the hand-written document as a whole rather than trying to extract fine-grained features out of it prior classification.

  20. Computational problems and signal processing in SETI

    NASA Technical Reports Server (NTRS)

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

    1991-01-01

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

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

    NASA Technical Reports Server (NTRS)

    Tsai, C. S.

    1984-01-01

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

  2. 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.

  3. 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.

  4. 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.

  5. Active voltammetric microsensors with neural signal processing.

    SciTech Connect

    Vogt, M. C.

    1998-12-11

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

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

    NASA Astrophysics Data System (ADS)

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

    2011-06-01

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

  7. Parallel Processing with Digital Signal Processing Hardware and Software

    NASA Technical Reports Server (NTRS)

    Swenson, Cory V.

    1995-01-01

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

  8. 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

  9. 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.

  10. Neural correlates of abstract verb processing.

    PubMed

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

    2011-01-01

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

  11. 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.

  12. Signal processing for a vestibular neurostimulator.

    PubMed

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

    2010-01-01

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

  13. 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.

  14. Exponential signal synthesis in digital pulse processing

    NASA Astrophysics Data System (ADS)

    Jordanov, Valentin T.

    2012-04-01

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

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

    PubMed Central

    Deschamps, Isabelle; Hasson, Uri; Tremblay, Pascale

    2016-01-01

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

  16. 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.

  17. 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.

  18. Automated Processing of Two-Dimensional Correlation Spectra

    NASA Astrophysics Data System (ADS)

    Sengstschmid, Helmut; Sterk, Heinz; Freeman, Ray

    1998-04-01

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

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

    PubMed Central

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

    2013-01-01

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

  20. Interactions between visceral afferent signaling and stimulus processing

    PubMed Central

    Critchley, Hugo D.; Garfinkel, Sarah N.

    2015-01-01

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

  1. 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.

  2. 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.

  3. Optimal signal processing for continuous qubit readout

    NASA Astrophysics Data System (ADS)

    Ng, Shilin; Tsang, Mankei

    2014-08-01

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

  4. Integrated optical signal processing with magnetostatic waves

    NASA Technical Reports Server (NTRS)

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

    1984-01-01

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

  5. 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

  6. 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.

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

    DOEpatents

    Fu, Chi Yung; Petrich, Loren I.

    2004-07-13

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

  8. 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.

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

    PubMed Central

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

    2009-01-01

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

  10. MR imaging in thyroid disorders: correlation of signal intensity with Graves disease activity.

    PubMed

    Charkes, N D; Maurer, A H; Siegel, J A; Radecki, P D; Malmud, L S

    1987-08-01

    Thirty-six patients with a variety of thyroid disorders and eight healthy subjects were studied with T1- and T2-weighted magnetic resonance (MR) imaging. Solid benign nodules, malignant tumors, and inflammatory conditions were not distinguishable by thyroidal MR signal intensity, but almost all patients with Graves disease had a moderate to marked diffuse increase in signal intensity at both settings. Quantitative evaluation showed that in these patients, the thyroid-muscle signal intensity contrast ratio was linearly related to both the serum thyroxine (T4) level and the 24-hour radioactive iodine uptake. In three patients treated with iodine 131, this contrast ratio rose or fell in parallel with the serum T4 level and 24-hour radioactive iodine uptake. Either parenchymal changes or increased vascularity in Graves disease, or both, could produce these findings. In patients without Graves disease, signal intensity was not correlated with serum T4 levels. These findings suggest that MR signal intensity may reflect the activity of the stimulatory process in Graves disease and may therefore be a useful measure of thyroid function in this disorder, with both diagnostic and prognostic value. PMID:3602391

  11. 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.

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

    PubMed

    Zhou, Wei-Xing

    2008-06-01

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

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

    NASA Astrophysics Data System (ADS)

    Zhou, Wei-Xing

    2008-06-01

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

  14. Neural mechanisms of spatiotemporal signal processing

    NASA Astrophysics Data System (ADS)

    Khanbabaie Shoub, Shaban (Reza)

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

  15. 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.

  16. Microwave signal processing with photorefractive dynamic holography

    NASA Astrophysics Data System (ADS)

    Fotheringham, Edeline B.

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

  17. 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.

  18. Pathologic correlates of incidental MRI white matter signal hyperintensities.

    PubMed

    Fazekas, F; Kleinert, R; Offenbacher, H; Schmidt, R; Kleinert, G; Payer, F; Radner, H; Lechner, H

    1993-09-01

    We related the histopathologic changes associated with incidental white matter signal hyperintensities on MRIs from 11 elderly patients (age range, 52 to 82 years) to a descriptive classification for such abnormalities. Punctate, early confluent, and confluent white matter hyperintensities corresponded to increasing severity of ischemic tissue damage, ranging from mild perivascular alterations to large areas with variable loss of fibers, multiple small cavitations, and marked arteriolosclerosis. Microcystic infarcts and patchy rarefaction of myelin were also characteristic for irregular periventricular high signal intensity. Hyperintense periventricular caps and a smooth halo, however, were of nonischemic origin and constituted areas of demyelination associated with subependymal gliosis and discontinuity of the ependymal lining. Based on these findings, our classification appears to reflect both the different etiologies and severities of incidental MRI signal abnormalities, if it is modified to treat irregular periventricular and confluent deep white matter hyperintensities together. PMID:8414012

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

    NASA Astrophysics Data System (ADS)

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

    2013-05-01

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

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

    NASA Astrophysics Data System (ADS)

    Chung, Kil Woo

    2011-12-01

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

  1. Statistical measures of Planck scale signal correlations in interferometers

    SciTech Connect

    Hogan, Craig J.; Kwon, Ohkyung

    2015-06-22

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

  2. Local quantum measurement and no-signaling imply quantum correlations.

    PubMed

    Barnum, H; Beigi, S; Boixo, S; Elliott, M B; Wehner, S

    2010-04-01

    We show that, assuming that quantum mechanics holds locally, the finite speed of information is the principle that limits all possible correlations between distant parties to be quantum mechanical as well. Local quantum mechanics means that a Hilbert space is assigned to each party, and then all local positive-operator-valued measurements are (in principle) available; however, the joint system is not necessarily described by a Hilbert space. In particular, we do not assume the tensor product formalism between the joint systems. Our result shows that if any experiment would give nonlocal correlations beyond quantum mechanics, quantum theory would be invalidated even locally. PMID:20481921

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

    NASA Astrophysics Data System (ADS)

    Scipioni, A.; Rischette, P.

    2012-07-01

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

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

    PubMed

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

    2013-02-25

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

  5. Optimizing signal and image processing applications using Intel libraries

    NASA Astrophysics Data System (ADS)

    Landré, Jérôme; Truchetet, Frédéric

    2007-01-01

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

  6. Electrophysiological Correlates of Second Language Processing

    ERIC Educational Resources Information Center

    Mueller, Jutta L.

    2005-01-01

    The aim of this article is to provide a selective review of event-related potential (ERP) research on second language processing. As ERPs have been used in the investigation of a variety of linguistic domains, the reported studies cover different paradigms assessing processing mechanisms in the second language at various levels, ranging from…

  7. 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.

  8. Photonic signal processing using acousto-optic effects

    NASA Astrophysics Data System (ADS)

    Widjaja, Joewono

    2015-07-01

    Acousto-optic effects have been used to perform computationally extensive signal and image processing. The paper first discusses spatial modulation of light by using the acousto-optic modulator. Following this, applications of the acoustooptic modulator to time signal analysis are presented, with the emphasis on the Fourier spectrum analysis and joint timefrequency signal representation.

  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. Nonlinear filtering for robust signal processing

    SciTech Connect

    Palmieri, F.

    1987-01-01

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

  11. Artificial intelligence applied to process signal analysis

    NASA Technical Reports Server (NTRS)

    Corsberg, Dan

    1988-01-01

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

  12. Fluctuations and correlations as a signal of deconfinement

    SciTech Connect

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

    2012-06-15

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

  13. Electrophysiological Correlates of Stimulus Equivalence Processes

    ERIC Educational Resources Information Center

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

    2009-01-01

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

  14. Time delays in correlated photoemission processes

    NASA Astrophysics Data System (ADS)

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

    2015-09-01

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

  15. 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.

  16. 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

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

    NASA Astrophysics Data System (ADS)

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

    2015-11-01

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

  18. Signal processing at the Poker Flat MST radar

    NASA Technical Reports Server (NTRS)

    Carter, D. A.

    1983-01-01

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

  19. 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.

  20. Signal processing for an infrared array detector

    NASA Astrophysics Data System (ADS)

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

    1989-09-01

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

  1. Processing electrophysiological signals for the monitoring of alertness

    NASA Technical Reports Server (NTRS)

    Lai, D. C.

    1974-01-01

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

  2. 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

  3. 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

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

    PubMed

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

    2011-08-01

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

  5. Mixed-correlated ARFIMA processes for power-law cross-correlations

    NASA Astrophysics Data System (ADS)

    Kristoufek, Ladislav

    2013-12-01

    We introduce a general framework of the Mixed-correlated ARFIMA (MC-ARFIMA) processes which allows for various specifications of univariate and bivariate long-term memory. Apart from a standard case when H={1}/{2}(Hx+Hy), MC-ARFIMA also allows for processes with H<{1}/{2}(Hx+Hy) but also for long-range correlated processes which are either short-range cross-correlated or simply correlated. The major contribution of MC-ARFIMA lies in the fact that the processes have well-defined asymptotic properties for Hx, Hy and H, which are derived in the paper, so that the processes can be used in simulation studies comparing various estimators of the bivariate Hurst exponent H. Moreover, the framework allows for modeling of processes which are found to have H<{1}/{2}(Hx+Hy).

  6. Signal detection for uniform renewal processes

    NASA Astrophysics Data System (ADS)

    Choi, Y.; Bell, C. B.; Ahmad, R.; Park, C. J.

    1983-06-01

    Detection problems for renewal processes are represented in the formats of GOF(goodness-of-fit), 2 sample; and GOF with nuisance parameter problems. The techniques are all based on the minimal sufficient statistic or its orthogonal complement. The statistics employed are, for the most part, that of Kolmogoroy, and its modification by Lilliefors and Srinivasan. Each technique is illustrated by a numerical example.

  7. 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.

  8. Grating geophone signal processing based on wavelet transform

    NASA Astrophysics Data System (ADS)

    Li, Shuqing; Zhang, Huan; Tao, Zhifei

    2008-12-01

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

  9. Auxiliary signal processing system for a multiparameter radar

    NASA Technical Reports Server (NTRS)

    Chandrasekar, V.; Gray, G. R.; Caylor, I. J.

    1993-01-01

    The design of an auxiliary signal processor for a multiparameter radar is described with emphasis on low cost, quick development, and minimum disruption of radar operations. The processor is based around a low-cost digital signal processor card and personal computer controller. With the use of such a concept, an auxiliary processor was implemented for the NCAR CP-2 radar during a 1991 summer field campaign and allowed measurement of additional polarimetric parameters, namely, the differential phase and the copolar cross correlation. Sample data are presented from both the auxiliary and existing radar signal processors.

  10. 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.

  11. Preliminary development of digital signal processing in microwave radiometers

    NASA Technical Reports Server (NTRS)

    Stanley, W. D.

    1980-01-01

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

  12. Processing of physiological signals in automotive research.

    PubMed

    Dambier, Michael; Altmüller, Tobias; Ladstätter, Ulrich

    2006-12-01

    The development of innovative driver assistance systems requires the evaluation of the predisposed hypotheses such as acceptance and driving safety. For this purpose, the conduction of experiments with end-users as subjects is necessary. Analysis and evaluation are based on the recording of numerous sensor values and system variables. Video, gaze and physiological data are recorded for the analysis of gaze distraction and emotional reactions of subjects to system behaviour. In this paper, a modular data streaming and processing architecture is suggested and a concept for this architecture is defined for consistent data evaluation, which integrates off-the-shelf products for data analysis and evaluation. PMID:17155867

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

    NASA Astrophysics Data System (ADS)

    Downie, John D.

    1995-07-01

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

  14. 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.

  15. Synthetic aperture focusing technique signal processing

    NASA Astrophysics Data System (ADS)

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

    1986-06-01

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

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

    PubMed Central

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

    2007-01-01

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

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

    PubMed

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

    2012-01-01

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

  18. 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.

  19. 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.

  20. 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.

  1. Optical architectures for digital signal processing

    SciTech Connect

    Antony, S.

    1988-01-01

    Optical computing can be defined as the representation of information by photons and the use of optical devices for the parallel processing of one-dimensional or multidimensional data. Optical implementation requires significant advances in devices, identification of a suitable number system and encoding scheme to represent the data, and development of architectures and algorithms that can utilize the unique properties of optics. The modified signed-digit (MDS) representation employed in the design of the architectures developed in this dissertation fully exploits the parallelism of optics. MSD representation satisfies the requirements of totally parallel addition/subtraction using modular or identical units and allows the addition/subtraction of any two numbers in two successive steps. Since MSD representation possesses many advantages over the binary- and residue-number systems, MSD is identified as a more suitable number system for optical implementations. The MSD digits are coded using three linear states of polarization. The two arithmetic units - and the adder and the multiplier - are developed to form the basic building blocks of an optical computer. All the designs presented here are based on the principle of symbolic substitution.

  2. 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.

  3. 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.

  4. 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.

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

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

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

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

    PubMed

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

    2012-01-01

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

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

    NASA Technical Reports Server (NTRS)

    Willsky, A. S.

    1978-01-01

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

  8. Hybrid digital signal processing and neural networks applications in PWRs

    SciTech Connect

    Eryurek, E.; Upadhyaya, B.R.; Kavaklioglu, K.

    1991-01-01

    Signal validation and plant subsystem tracking in power and process industries require the prediction of one or more state variables. Both heteroassociative and auotassociative neural networks were applied for characterizing relationships among sets of signals. A multi-layer neural network paradigm was applied for sensor and process monitoring in a Pressurized Water Reactor (PWR). This nonlinear interpolation technique was found to be very effective for these applications.

  9. Hybrid digital signal processing and neural networks applications in PWRs

    SciTech Connect

    Eryurek, E.; Upadhyaya, B.R.; Kavaklioglu, K.

    1991-12-31

    Signal validation and plant subsystem tracking in power and process industries require the prediction of one or more state variables. Both heteroassociative and auotassociative neural networks were applied for characterizing relationships among sets of signals. A multi-layer neural network paradigm was applied for sensor and process monitoring in a Pressurized Water Reactor (PWR). This nonlinear interpolation technique was found to be very effective for these applications.

  10. Microscopic realization of cross-correlated noise processes.

    PubMed

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

    2010-06-01

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

  11. Increased basal intracellular signaling patterns do not correlate with JAK2 genotype in human myeloproliferative neoplasms.

    PubMed

    Anand, Shubha; Stedham, Frances; Gudgin, Emma; Campbell, Peter; Beer, Philip; Green, Anthony R; Huntly, Brian J P

    2011-08-11

    Myeloproliferative neoplasms (MPNs) are associated with recurrent activating mutations of signaling proteins such as Janus kinase 2 (JAK2). However, the actual downstream signaling events and how these alter myeloid homeostasis are poorly understood. We developed an assay to measure basal levels of phosphorylated signaling intermediates by flow cytometry during myeloid differentiation in MPN patients. Our study provides the first systematic demonstration of specific signaling events and their comparison with disease phenotype and JAK2 mutation status. We demonstrate increased basal signaling in MPN patients, which occurs in both early and later stages of myeloid differentiation. In addition, the pattern of signaling is not correlated with JAK2 mutation status and signaling intensity is poorly correlated with mutant JAK2 allele burden. In contrast, signaling differences are detected between different MPN disease phenotypes. Finally, we demonstrate that signaling can be inhibited by a JAK2-selective small molecule, but that this inhibition is not JAK2 V617F specific, because MPN patients with mutant JAK2, wild-type JAK2, and control patients were inhibited to a similar degree. Our data suggest that, in addition to JAK2 mutations, other factors contribute significantly to the MPN phenotype, results that are relevant to both the pathogenesis and therapy of MPN. PMID:21653937

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

    NASA Astrophysics Data System (ADS)

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

    2013-06-01

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

  13. 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

  14. Signal processing challenges for single-trial analysis of simultaneous EEG/fMRI.

    PubMed

    Sajda, Paul

    2009-01-01

    A relatively new neuroimaging modality is simultaneous EEG and fMRI. Though such a multi-modal acquisition is attractive given that it can exploit the temporal resolution of EEG and spatial resolution of fMRI, it comes with unique signal processing and pattern classification challenges. In this paper I will review some our work at developing signal processing and pattern recognition for analysis of simultaneous EEG and fMRI, with a focus on those algorithms enabling a single-trial analysis of the neural signal. In general, these algorithms exploit the multivariate nature of the EEG, removing MR induced artifacts and classifying event-related signals that then can be correlated with the BOLD signal to yield specific fMRI activations. PMID:19965105

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

    NASA Astrophysics Data System (ADS)

    Langel, Robert A.

    1995-10-01

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

  16. 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.

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

    DOEpatents

    Fu, Chi Yung; Petrich, Loren

    2009-04-14

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

  18. Removing Background Noise with Phased Array Signal Processing

    NASA Technical Reports Server (NTRS)

    Podboy, Gary; Stephens, David

    2015-01-01

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

  19. Signal processing in optical coherence tomography for aerospace material characterization

    NASA Astrophysics Data System (ADS)

    Liu, Ping; Groves, Roger M.; Benedictus, Rinze

    2013-03-01

    Based on a customized time-domain optical coherence tomography (OCT) system, a series of signal processing approaches have been designed and reviewed. To improve demodulation accuracy and image quality, demodulation approaches such as median filter, Hilbert transform, and envelope detector were investigated with simulated as well as experimental data. Without noise, the Hilbert transform has the best performance, but after considering the narrow-band noise in the modulated signal, the envelope detector was selected as the ideal demodulation technique. To reduce noise and enhance image contrast, digital signal processing techniques such as a bandpass filtering and two-dimensional median filtering were applied before and after the demodulation, respectively. Finally with integration of the customized OCT setup and designed signal processing algorithms, aerospace materials, such as polymer coatings and glass-fiber composites, were successfully characterized. The cross-sectional images obtained clearly show the microstructures of the materials.

  20. 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

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. online Surveillance of Industrial Processes with Correlated Parameters

    Energy Science and Technology Software Center (ESTSC)

    1996-12-18

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

  6. Analog signal processing for low-power sensor systems

    NASA Astrophysics Data System (ADS)

    Hasler, Paul

    2006-05-01

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

  7. 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

  8. 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

  9. Tunable signal processing in synthetic MAP kinase cascades

    PubMed Central

    O'Shaughnessy, Ellen C.; Palani, Santhosh; Collins, James J.; Sarkar, Casim A.

    2010-01-01

    SUMMARY The flexibility of MAPK cascade responses enables regulation of a vast array of cell-fate decisions, but elucidating the mechanisms underlying this plasticity is difficult in endogenous signaling networks. We constructed insulated mammalian MAPK cascades in yeast to explore how intrinsic and extrinsic perturbations affect the flexibility of these synthetic signaling modules. Contrary to biphasic dependence on scaffold concentration, we observe monotonic decreases in signal strength as scaffold concentration increases. We find augmenting the concentration of sequential kinases can enhance ultrasensitivity and lower the activation threshold. Further, integrating negative regulation and concentration variation can decouple ultrasensitivity and threshold from the strength of the response. Computational analyses show that cascading can generate ultrasensitivity and that natural cascades with different kinase concentrations are innately biased toward their distinct activation profiles. This work demonstrates that tunable signal processing is inherent to minimal MAPK modules and elucidates principles for rational design of synthetic signaling systems. PMID:21215374

  10. 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.

  11. A signal processing unit for IR detector arrays

    NASA Astrophysics Data System (ADS)

    McEwen, R. K.

    The signal processing unit for IR detector arrays here presented overcomes processing speed and adequate grey scale resolution problems by performing the necessary nonuniformity processing in the analog, rather than the digital, domain. The fixed pattern noise is thereby removed while the signal remains in the analog domain; the data rate in question is in excess of those currently achievable by 12-bit monolithic or hybrid air data computers. This compact system is recommended for such large array applications as homing missiles, where higher frame rates are required.

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

    PubMed

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

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Matsushima, Kyoji

    2015-09-01

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

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  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. Digital signal processing for fiber-optic thermometers

    SciTech Connect

    Fernicola, V.; Crovini, L.

    1994-12-31

    A digital signal processing scheme for measurement of exponentially-decaying signals, such as those found in fluorescence, lifetime-based, fiber-optic sensors, is proposed. The instrument uses a modified digital phase-sensitive-detection technique with the phase locked to a fixed value and the modulation period tracking the measured lifetime. Typical resolution of the system is 0.05% for slow decay (>500 {mu}s) and 0.1% for fast decay.

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

    PubMed

    Kroth, J; Yoneda, D; Hammond, A

    1998-12-01

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

  2. 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

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

    PubMed Central

    Zhang, Yanyan; Wang, Jue

    2014-01-01

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

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

    PubMed Central

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

    2008-01-01

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

  5. Research on mud pulse signal data processing in MWD

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  6. 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.

  7. Digital processing of RF signals from optical frequency combs

    NASA Astrophysics Data System (ADS)

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

    2013-01-01

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

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

    PubMed

    Volman, Vladislav; Levine, Herbert

    2009-09-01

    We study the characteristics of weak signal detection by a recurrent neuronal network with plastic synaptic coupling. It is shown that in the presence of an asynchronous component in synaptic transmission, the network acquires selectivity with respect to the frequency of weak periodic stimuli. For nonperiodic frequency-modulated stimuli, the response is quantified by the mutual information between input (signal) and output (network's activity) and is optimized by synaptic depression. Introducing correlations in signal structure resulted in the decrease in input-output mutual information. Our results suggest that in neural systems with plastic connectivity, information is not merely carried passively by the signal; rather, the information content of the signal itself might determine the mode of its processing by a local neuronal circuit. PMID:19791987

  9. Detectors and signal processing for high-energy physics

    SciTech Connect

    Rehak, P.

    1981-01-01

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

  10. 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).

  11. Analysis of Low Probability of Intercept (LPI) Radar Signals Using Cyclostationary Processing

    NASA Astrophysics Data System (ADS)

    Lime, Antonio F., Jr.

    2002-09-01

    LPI (Low Probability of Intercept) radar is a class of radar systems that possess certain performance characteristics that make them nearly undetectable by today's digital intercept receivers. This presents a significant tactical problem in the battle space. To detect these types of radar, new digital receivers that use sophisticated signal processing techniques are required This thesis investigates the use of cyclostationary processing to extract the modulation parameters from a variety of continuous-wave (CW) low-probability-of-intercept (LPI) radar waveforms. The cyclostationary detection techniques described exploit the fact that digital signals vary in time with single or multiple periodicities, because they have spectral correlation, namely, non-zero correlation between certain frequency components, at certain frequency shifts. The use of cyclostationary signal processing in a non-cooperative intercept receiver can help identify the particular emitter and can help develop electronic attacks. LPI CW waveforms examined include Frank codes, polyphase codes (Pt through P4), Frequency Modulated CW (FMCW), Costas frequencies as well as several frequency-shift-keying/phase-shift-keying (FSK/PSK) waveforms. It is shown that for signal-to-noise ratios of OdB and -6 dB, the cyclostationary signal processing can extract the modulation parameters necessary in order to distinguish among the various types of LPI modulations.

  12. 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.

  13. Remote laser interferometer with pseudo-heterodyne signal processing

    NASA Astrophysics Data System (ADS)

    Liokumovich, Leonid B.; Markov, Sergey I.

    2000-11-01

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

  14. Distributed Signal Processing for Wireless EEG Sensor Networks.

    PubMed

    Bertrand, Alexander

    2015-11-01

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

  15. 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…

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

    SciTech Connect

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

    1990-01-01

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

  17. Demystifying biomedical signals: a student centred approach to learning signal processing.

    PubMed

    Simpson, D M; De Stefano, A; Allen, R; Lutman, M E

    2005-09-01

    The processing and analysis of physiological signals has become firmly established in clinical medicine and biomedical research. Many of the users of this technology however do not come from an engineering or science background, and traditional approaches in teaching signal processing are thus not appropriate for them. We have therefore developed a series of modular courses that are aimed specifically at an audience with a background in medicine, health-care or the life-sciences. In these courses, we focus on the concepts, principles and rationale of applying signal processing methods, rather than the mathematical foundations of the techniques. Thus, we aim to remove some of the perceived 'mystery' often surrounding this subject. The very practical approach, with hands-on experience using the MATLAB software, has been well received, with strong evidence that students have learnt to apply their knowledge. This paper describes the learning and teaching approach taken, and some of the experience acquired. PMID:16046177

  18. Phosphorelays Provide Tunable Signal Processing Capabilities for the Cell

    PubMed Central

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

    2013-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Marco, Santiago

    2011-09-01

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

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

    PubMed

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

    2015-08-01

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

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

    PubMed Central

    Kudla, Jörg; Batistič, Oliver; Hashimoto, Kenji

    2010-01-01

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

  2. ISLE (Image and Signal Lisp Environment): A functional language interface for signal and image processing

    SciTech Connect

    Azevedo, S.G.; Fitch, J.P.

    1987-05-01

    Conventional software interfaces which utilize imperative computer commands or menu interactions are often restrictive environments when used for researching new algorithms or analyzing processed experimental data. We found this to be true with current signal processing software (SIG). Existing ''functional language'' interfaces provide features such as command nesting for a more natural interaction with the data. The Image and Signal Lisp Environment (ISLE) will be discussed as an example of an interpreted functional language interface based on Common LISP. Additional benefits include multidimensional and multiple data-type independence through dispatching functions, dynamic loading of new functions, and connections to artificial intelligence software.

  3. ISLE (Image and Signal LISP Environment): A functional language interface for signal and image processing

    SciTech Connect

    Azevedo, S.G.; Fitch, J.P.

    1987-10-21

    Conventional software interfaces that use imperative computer commands or menu interactions are often restrictive environments when used for researching new algorithms or analyzing processed experimental data. We found this to be true with current signal-processing software (SIG). As an alternative, ''functional language'' interfaces provide features such as command nesting for a more natural interaction with the data. The Image and Signal LISP Environment (ISLE) is an example of an interpreted functional language interface based on common LISP. Advantages of ISLE include multidimensional and multiple data-type independence through dispatching functions, dynamic loading of new functions, and connections to artificial intelligence (AI) software. 10 refs.

  4. 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

  5. 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.

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

    NASA Astrophysics Data System (ADS)

    Terrillon, Jean-Christophe

    1995-11-01

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

  7. Parallel-Processing Software for Correlating Stereo Images

    NASA Technical Reports Server (NTRS)

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

    2007-01-01

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

  8. 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…

  9. 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…

  10. 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…

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

    PubMed

    Coatrieux, Jean-Louis

    2002-01-01

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

  12. 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.

  13. SoC-based architecture for biomedical signal processing.

    PubMed

    Gutierrez-Rivas, R; Hernandez, A; Garcia, J J; Marnane, W

    2015-08-01

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

  14. 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.

  15. 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

  16. 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.

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

    NASA Technical Reports Server (NTRS)

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

    1973-01-01

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

  18. 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.

  19. 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).

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

    NASA Astrophysics Data System (ADS)

    Chitgarha, Mohammad Reza

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

  1. Continuous monitoring of watershed signals: Disentangling compounded processes

    NASA Astrophysics Data System (ADS)

    McGlynn, B. L.; Seybold, E. C.; Zimmer, M. A.; Kaiser, K. E.; Mallard, J. M.; Bergstrom, A.; Jencso, K. G.; Nippgen, F.

    2014-12-01

    Matching observation and process time scales is critical for uncovering and quantifying ecosystem processes and developing new understanding of key drivers of observed behavior. Fortunately, real-time monitoring of hydrological and biogeochemical signals across watershed and stream systems is becoming more common. Unfortunately, disentangling compounded biological and physical processes operating and transported across often asynchronous time scales presents new challenges for realizing the potential of real-time sensor technology. Here we focus on challenges to interpreting in-stream observations as well as opportunities to use these emerging technologies to gain new insight into system behavior through enhanced observational networks and analysis that can reduce equifinality in process attribution of observed signals.

  2. 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)

  3. Optical Design and Signal Processing for Edge Detection

    NASA Technical Reports Server (NTRS)

    Huck, Friedrich O.; Stacy, Kathryn

    1987-01-01

    Properly combining optical design with 3-by-3 element mask reduces number of required computations by factor of as much as 100. Spatial and spatial-frequency responses obtained in system of combination of optical design and signal-processing algorithm. Closely approximate difference-of-Gaussian-function response.

  4. 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.

  5. 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.

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

    PubMed

    Konstantinides, K; Rasure, J R

    1994-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    1996-11-01

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

  8. Passive impacts localization based on dispersion compensation and cross-correlated signals wavelet analysis

    NASA Astrophysics Data System (ADS)

    Perelli, Alessandro; De Marchi, Luca; Marzani, Alessandro; Speciale, Nicolò

    2012-05-01

    A method for impact location in plate-like structures with a passive sensors network is proposed. The approach is based on guided waves dispersion compensation joint with a distance-frequency analysis obtained through a wavelet basis of cross-correlated signals. In passive monitoring techniques the knowledge of the time of impact is not given; despite this limit, the proposed dispersion compensation procedure is useful as it removes in the group delay of the acquired signals the dependence on the travelled distance. By cross-correlating the signals related to the same event acquired by different sensors, the time difference of arrival is estimated. To reduce the interference due to the edge reflections and the own plate echoes, the cross-correlating signal is decomposed by a suitable orthogonal basis and the magnitude of the Continous Wavelet Transform is used to obtain the difference in travelled distances and to locate the wave source via hyperbolic positioning. The proposed procedure is tested with a passive network of three/four piezo-sensors located symmetrically and asymmetrically with respect to the plate edges. The experimentally results are close to those theoretically predicted by Cramèr-Rao bound.

  9. Advanced signal processing methods for pulsed laser vibrometry.

    PubMed

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

    2010-07-10

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

  10. Neural predictive error signal correlates with depressive illness severity in a game paradigm.

    PubMed

    Steele, J D; Meyer, M; Ebmeier, K P

    2004-09-01

    Considerable experimental evidence supports the existence of predictive error signals in various brain regions during associative learning in animals and humans. These regions include the prefrontal cortex, temporal lobe, cerebellum and monoamine systems. Various quantitative theories have been developed to describe behaviour during learning, including Rescorla-Wagner, Temporal Difference and Kalman filter models. These theories may also account for neural error signals. Reviews of imaging studies of depressive illness have consistently implicated the prefrontal and temporal lobes as having abnormal function, and sometimes structure, whilst the monoamine systems are directly influenced by antidepressant medication. It was hypothesised that such abnormalities may be associated with a dysfunction of associative learning that would be reflected by different predictive error signals in depressed patients when compared with healthy controls. This was tested with 30 subjects, 15 with a major depressive illness, using a gambling paradigm and fMRI. Consistent with the hypothesis, depressed patients differed from controls in having an increased error signal. Additionally, for some brain regions, the magnitude of the error signal correlated with Hamilton depression rating of illness severity. Structural equation modelling was used to investigate hypothesised change in effective connectivity between prespecified regions of interest in the limbic and paralimbic system. Again, differences were found that in some cases correlated with illness severity. These results are discussed in the context of quantitative theories of brain function, clinical features of depressive illness and treatments. PMID:15325374

  11. 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.

  12. 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.

  13. Quantum process estimation via generic two-body correlations

    NASA Astrophysics Data System (ADS)

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

    2010-03-01

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

  14. Electrophysiological correlates of aesthetic music processing: comparing experts with laypersons.

    PubMed

    Müller, Mira; Höfel, Lea; Brattico, Elvira; Jacobsen, Thomas

    2009-07-01

    We analyzed the processes of making aesthetic judgments of music, focusing on the differences between music experts and laypersons. Sixteen students of musicology and 16 control subjects (also students) judged the aesthetic value as well as the harmonic correctness of chord sequences. Event-related potential (ERP) data indicate differences between experts and laypersons in making aesthetic judgments at three different processing stages. Additionally, effects of expertise on ERP components that have previously been proven to be sensitive to musical training were replicated. The study thus provides insights into the effects of musical expertise on neural correlates of aesthetic music processing. PMID:19673807

  15. 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.

  16. Array Signal Processing and Spatial Spectral Estimation Using Data Transformation

    NASA Astrophysics Data System (ADS)

    Hong, Wooyoung

    Array signal processing is concerned with the detection and the estimation of signals and their parameters from data collected by spatially distributed sensors or antennas. Interest in array signal processing comes from the numerous applications--sonar, radar, radio astronomy, tomography and seismic exploration, etc. One of the important issues in array signal processing is that of finding the location of a number of sources. In particular, many eigen -decomposition based high resolution methods have been proposed in the past for the estimation of the directions of closely spaced sources using a uniform linear array under the assumption of narrow band sources. However, those techniques do not perform as well with special array geometry such as circular arrays. It is shown here that for plane waves, a circular array which consists of M identical sensors uniformly distributed around a circle of radius R is equivalent to a uniform linear array and that the improvement in performance can be obtained by using any eigenstructure technique with a proposed data transformation rather than the array data directly. Furthermore, when the sources to be localized are wideband, several algorithms to deal with wideband sources require pre-estimates. An efficient algorithm using the data transformation (focusing operation) is proposed which does not require a priori knowledge of source locations and minimizes the average of the squared norm of focusing error over the angles of interest. Simulation results are discussed that compare the performance of several well known algorithms, including MUSIC, ROOT-MUSIC, MIN-NORM, and ESPRIT.

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

    NASA Astrophysics Data System (ADS)

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

    2015-11-01

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

  18. Signaling-mediated Regulation of MicroRNA Processing

    PubMed Central

    Shen, Jia; Hung, Mien-Chie

    2015-01-01

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

  19. 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.

  20. 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

  1. 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.

  2. 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.

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

    PubMed

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

    2015-10-01

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

  4. 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

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

    NASA Astrophysics Data System (ADS)

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

    2006-04-01

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

  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. Gender differences in the neural correlates of response inhibition during a stop signal task.

    PubMed

    Li, Chiang-Shan Ray; Huang, Cong; Constable, R Todd; Sinha, Rajita

    2006-10-01

    We used functional magnetic resonance imaging to examine gender differences in the neural correlates of response inhibition during a stop signal task. The task has a frequent "go" signal to set up a pre-potent response tendency and a less frequent "stop" signal for subjects to withhold their response. A contrast in brain activation was made between successful and failed inhibitions for individual subjects. We compared 20 men and 20 women matched in age and years of education and in stop signal performance, with stop success rate, post-error slowing and task-related frustration ratings as covariates. The results showed greater activation in men, compared to women, in a wide array of cortical and subcortical areas, including the globus pallidus and motor thalamus during stop signal inhibition. In contrast, no brain regions demonstrated greater activation in women, even at a lower statistical threshold. Moreover, while men activated the medial superior frontal and anterior cingulate cortices, women activated the caudate tail to mediate response inhibition. These results extended gender differences in regional brain activation to response inhibition during a cognitive motor task. Men activated the motor circuitry while women appeared to involve visual association or habit learning during stop signal performance. PMID:16806976

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

    NASA Astrophysics Data System (ADS)

    Knurenko, Stanislav; Petrov, Igor

    2015-08-01

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

  9. 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.

  10. 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.

  11. Signal Processing in Periodically Forced Gradient Frequency Neural Networks

    PubMed Central

    Kim, Ji Chul; Large, Edward W.

    2015-01-01

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

  12. Signal Processing in Periodically Forced Gradient Frequency Neural Networks.

    PubMed

    Kim, Ji Chul; Large, Edward W

    2015-01-01

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

  13. 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.

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

    PubMed

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

    2009-01-01

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

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

    PubMed

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

    2014-03-28

    Nanopore-based sequencing has demonstrated a significant potential for the development of fast, accurate, and cost-efficient fingerprinting techniques for next generation molecular detection and sequencing. We propose a specific multilayered graphene-based nanopore device architecture for the recognition of single biomolecules. Molecular detection and analysis can be accomplished through the detection of transverse currents as the molecule or DNA base translocates through the nanopore. To increase the overall signal-to-noise ratio and the accuracy, we implement a new 'multi-point cross-correlation' technique for identification of DNA bases or other molecules on the single molecular level. We demonstrate that the cross-correlations between each nanopore will greatly enhance the transverse current signal for each molecule. We implement first-principles transport calculations for DNA bases surveyed across a multilayered graphene nanopore system to illustrate the advantages of the proposed geometry. A time-series analysis of the cross-correlation functions illustrates the potential of this method for enhancing the signal-to-noise ratio. This work constitutes a significant step forward in facilitating fingerprinting of single biomolecules using solid state technology. PMID:24577191

  16. 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.

  17. Biological signal processing with a genetic toggle switch.

    PubMed

    Hillenbrand, Patrick; Fritz, Georg; Gerland, Ulrich

    2013-01-01

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

  18. 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.

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

    PubMed

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

    2012-12-17

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

  20. 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

  1. The Open Host Network Packet Process Correlator for Windows

    SciTech Connect

    2014-06-17

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

  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. 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.

  4. Signal processing for Internet video streaming: a review

    NASA Astrophysics Data System (ADS)

    Lu, Jian

    2000-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-02-01

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

  7. 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.

  8. 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.

  9. Programmable rate modem utilizing digital signal processing techniques

    NASA Technical Reports Server (NTRS)

    Naveh, Arad

    1992-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Edmondson, Richard; Rodgers, Michael

    2008-04-01

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

  11. 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.

  12. Biomedical signal processing using a new class of wavelets

    NASA Astrophysics Data System (ADS)

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

    2000-04-01

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

  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. Signal Processing Effects for Ultrasonic Guided Wave Scanning of Composites

    NASA Astrophysics Data System (ADS)

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

    2005-04-01

    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.

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

    SciTech Connect

    Lapedes, A.; Farber, R.

    1987-06-01

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

  16. Digital signal processing in AFM topography and recognition imaging

    NASA Astrophysics Data System (ADS)

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

    2005-10-01

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

  17. 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

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

    NASA Astrophysics Data System (ADS)

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

    2010-12-01

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

  19. A Signal Processing Analysis of Purkinje Cells in vitro

    PubMed Central

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

    2010-01-01

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

  20. 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.

  1. 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.

  2. Information processing correlates of a size-contrast illusion

    PubMed Central

    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

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

    PubMed

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

    2016-01-29

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

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

    NASA Astrophysics Data System (ADS)

    Luk, Franklin T.

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

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

    NASA Astrophysics Data System (ADS)

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

    2005-10-01

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

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

    PubMed

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

    2015-08-30

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

  7. 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.

  8. 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

  9. Information processing and signal integration in bacterial quorum sensing

    NASA Astrophysics Data System (ADS)

    Mehta, Pankaj

    2009-03-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-03-01

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

  11. 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.

  12. 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.

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

    PubMed

    Patek, D R; Tompkins, W J

    1980-12-01

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

  14. 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

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

    PubMed

    Chettoor, Antony M; Evans, Matthew M S

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Cappellini, V.; Constantinides, A. G.

    1984-09-01

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

  17. 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.

  18. Control mechanism to prevent correlated message arrivals from degrading signaling no. 7 network performance

    NASA Astrophysics Data System (ADS)

    Kosal, Haluk; Skoog, Ronald A.

    1994-04-01

    Signaling System No. 7 (SS7) is designed to provide a connection-less transfer of signaling messages of reasonable length. Customers having access to user signaling bearer capabilities as specified in the ANSI T1.623 and CCITT Q.931 standards can send bursts of correlated messages (e.g., by doing a file transfer that results in the segmentation of a block of data into a number of consecutive signaling messages) through SS7 networks. These message bursts with short interarrival times could have an adverse impact on the delay performance of the SS7 networks. A control mechanism, Credit Manager, is investigated in this paper to regulate incoming traffic to the SS7 network by imposing appropriate time separation between messages when the incoming stream is too bursty. The credit manager has a credit bank where credits accrue at a fixed rate up to a prespecified credit bank capacity. When a message arrives, the number of octets in that message is compared to the number of credits in the bank. If the number of credits is greater than or equal to the number of octets, then the message is accepted for transmission and the number of credits in the bank is decremented by the number of octets. If the number of credits is less than the number of octets, then the message is delayed until enough credits are accumulated. This paper presents simulation results showing delay performance of the SS7 ISUP and TCAP message traffic with a range of correlated message traffic, and control parameters of the credit manager (i.e., credit generation rate and bank capacity) are determined that ensure the traffic entering the SS7 network is acceptable. The results show that control parameters can be set so that for any incoming traffic stream there is no detrimental impact on the SS7 ISUP and TCAP message delay, and the credit manager accepts a wide range of traffic patterns without causing significant delay.

  19. Use of fuzzy logic in signal processing and validation

    SciTech Connect

    Heger, A.S.; Alang-Rashid, N.K. ); Holbert, K.E. )

    1993-01-01

    The advent of fuzzy logic technology has afforded another opportunity to reexamine the signal processing and validation process (SPV). The features offered by fuzzy logic can lend themselves to a more reliable and perhaps fault-tolerant approach to SPV. This is particularly attractive to complex system operations, where optimal control for safe operation depends on reliable input data. The reason for the use of fuzzy logic as the tool for SPV is its ability to transform information from the linguistic domain to a mathematical domain for processing and then transformation of its result back into the linguistic domain for presentation. To ensure the safe and optimal operation of a nuclear plant, for example, reliable and valid data must be available to the human and computer operators. Based on these input data, the operators determine the current state of the power plant and project corrective actions for future states. This determination is based on available data and the conceptual and mathematical models for the plant. A fault-tolerant SPV based on fuzzy logic can help the operators meet the objective of effective, efficient, and safe operation of the nuclear power plant. The ultimate product of this project will be a code that will assist plant operators in making informed decisions under uncertain conditions when conflicting signals may be present.

  20. 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.

  1. Silver Nanostructures for Fluorescence Correlation Spectroscopy: Reduced Volumes and Increased Signal Intensities

    PubMed Central

    Choudhury, Sharmistha Dutta; Ray, Krishanu; Lakowicz, Joseph R.

    2016-01-01

    Fluorescence correlation spectroscopy (FCS) is a widely used technique to investigate the interactions and dynamics of molecules, below micromolar concentrations. Silver nanostructure (AgNS) substrates can extend the applicability of FCS to higher concentrations, which is useful for many biologically relevant reactions. Additionally, these substrates can improve detection efficiency by increasing fluorescence signal intensities. The ease of preparation of the AgNS substrates in comparison to previously investigated materials prepared by top-down nanofabrication is expected to make them readily available and suitable for various FCS applications.

  2. 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

  3. 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.

  4. 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.

  5. 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.

  6. 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.

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

    SciTech Connect

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

    1997-03-01

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

  8. 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.

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

    SciTech Connect

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

    1988-02-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

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

    PubMed

    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

  12. Identification and utilization of arbitrary correlations in models of recombination signal sequences

    PubMed Central

    Cowell, Lindsay G; Davila, Marco; Kepler, Thomas B; Kelsoe, Garnett

    2002-01-01

    Background A significant challenge in bioinformatics is to develop methods for detecting and modeling patterns in variable DNA sequence sites, such as protein-binding sites in regulatory DNA. Current approaches sometimes perform poorly when positions in the site do not independently affect protein binding. We developed a statistical technique for modeling the correlation structure in variable DNA sequence sites. The method places no restrictions on the number of correlated positions or on their spatial relationship within the site. No prior empirical evidence for the correlation structure is necessary. Results We applied our method to the recombination signal sequences (RSS) that direct assembly of B-cell and T-cell antigen-receptor genes via V(D)J recombination. The technique is based on model selection by cross-validation and produces models that allow computation of an information score for any signal-length sequence. We also modeled RSS using order zero and order one Markov chains. The scores from all models are highly correlated with measured recombination efficiencies, but the models arising from our technique are better than the Markov models at discriminating RSS from non-RSS. Conclusions Our model-development procedure produces models that estimate well the recombinogenic potential of RSS and are better at RSS recognition than the order zero and order one Markov models. Our models are, therefore, valuable for studying the regulation of both physiologic and aberrant V(D)J recombination. The approach could be equally powerful for the study of promoter and enhancer elements, splice sites, and other DNA regulatory sites that are highly variable at the level of individual nucleotide positions. PMID:12537561

  13. 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

  14. 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

  15. 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

  16. 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.

  17. Optimal processing and the statistics of visual input signals

    NASA Astrophysics Data System (ADS)

    de Ruyter van Steveninck, Rob

    2008-03-01

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

  18. 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.

  19. 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

  20. 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

  1. 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.

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

    PubMed

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

    2015-01-01

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

  3. 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.

  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. Correlation functions and power spectra of Doppler response signals in ultrasonic medical applications.

    PubMed

    Skresanova, Iryna V; Barannik, Evgen A

    2012-07-01

    Ultrasound Doppler methods are widely used in clinical practice as prospective investigational tool to study the vascular system and soft biological tissues. Meanwhile, the most general relationship between the power Doppler spectra, spectral characteristics of the scattering fluctuations and the probing ultrasound field parameters for some clinical implementations are still unexplored. Based upon the continuum model of scattering inhomogeneities, a set of the closed-form expressions for the correlation functions and the spectra of Doppler response of soft tissues and blood have been derived. The influence of the correlation among inhomogeneities and the diffusion processes on the Doppler power spectra formed by stationary flows have been examined. Computer simulations of Doppler spectra were performed for different values of correlation radius and diffusion coefficient. With simulation results the effects of the correlation among inhomogeneities and the diffusion processes on the spectral width and mean frequency are established and discussed in respect to turbulent flows. Closed-form expressions for correlation functions and Doppler spectra for the vibrational sonoelastography technique for visualizing malignant tumors in tissues have been derived. Based on the peculiarities of the obtained Doppler spectra, it is shown that the differentiation of soft tissues with respect to the amplitude value of constrained oscillations is feasible. The expressions were derived for the cases of non-stationary accelerated blood movement. It has been found that the frequency dependence reveals solely at a finite time of observation and depends on the initial phase of the accelerated movement. PMID:22354019

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

    PubMed

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

    2011-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Boashash, Boualem; Boubchir, Larbi; Azemi, Ghasem

    2012-12-01

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

  8. 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.

  9. Monitoring Of Volcanic Processes Through Analysis Of Hydroacoustic Signals Originating From Monowai Seamount

    NASA Astrophysics Data System (ADS)

    Cook, K. E.; Bohnenstiehl, D. R.; Dziak, R. P.; Matsumoto, H.; Fowler, M. J.; Conder, J. A.; Wiens, D. A.

    2010-12-01

    Monowai seamount, located at 25.9S, 177.2E, is an extremely active subduction zone submarine volcanic center located on the southern end of the Kermadec arc. Between January 2009 and April 2010, underwater acoustic signals generated at Monowai were recorded by an array of autonomous moored hydrophones deployed within the Lau Basin, approximately 650 km to the north. The instruments sampled continuously at a rate of 250 Hz and were located at a depth of 1000 m below the sea surface, near the axis of the SOund Fixing And Ranging (SOFAR) channel. Nine distinct episodes of volcanic swarm activity were detected with up to hundreds of events per day during the periods between February 28-March 23, May 2-May 6, July 5-July 10, September 13-September 18, October 15-October 31, November 10-November 13, November 27-December 3, December 14-December 17, and April 10-April 15. To locate the source of the signals, hydroacoustic arrivals were combined with T-wave detections on seismic stations RAR (Rarotonga, Cook Islands) and PPTF (Papeete, Tahiti Island). The peak energy of the signals at each station was used as the arrival time to iterate a source location based on average acoustic velocities in the area. More than three stations were used to locate all selected signals within the periods of high activity. Signals originating from Monowai exhibit spectral energy of up to 60 Hz, with the dominant energy in the 1-10 Hz band. Signal durations extend for several minutes and commonly exhibit multiple peaks in the signal record, with the largest amplitudes often observed within the first 30%-40% of the signal. Waveform envelopes show a coherent pattern of arrivals across the array, which is used to further refine the source location coordinates. High correlation coefficients also are observed between events and provide evidence of repeatable eruptive processes occurring at Monowai.

  10. Developmental changes in the neural correlates of semantic processing.

    PubMed

    Chou, Tai-Li; Booth, James R; Burman, Douglas D; Bitan, Tali; Bigio, Jordan D; Lu, Dong; Cone, Nadia E

    2006-02-15

    Functional magnetic resonance imaging (fMRI) was used to explore the neural correlates of semantic judgments in the auditory modality in a group of 9- to 15-year-old children. Subjects were required to indicate if word pairs were related in meaning. Consistent with previous findings in adults, children showed activation in bilateral superior temporal gyri (BA 22) for recognizing spoken words as well as activations in bilateral inferior frontal gyri (BAs 47, 45) and left middle temporal gyrus (BA 21) for semantic processing. The neural substrates of semantic association and age differences were also investigated. Words with strong semantic association elicited significantly greater activation in the left inferior parietal lobule (BA 40), whereas words with weak semantic association elicited activation in left inferior frontal gyrus (BAs 47/45). Correlations with age were observed in the left middle temporal gyrus (BA 21) and the right inferior frontal gyrus (BA 47). The pattern of results for semantic association implies that the left inferior parietal lobule effectively integrates highly related semantic features and the left inferior frontal gyrus becomes more active for words that require a greater search for semantic associations. The developmental results suggest that older children recruit the right inferior frontal gyrus as they conduct a broader semantic search and the left middle temporal gyrus to provide more efficient access to semantic representations. PMID:16275017

  11. Electrophysiological correlates of emotional processing in sensation seeking.

    PubMed

    Zheng, Ya; Xu, Jing; Jia, Hongning; Tan, Fei; Chang, Yi; Zhou, Li; Shen, Huijuan; Qu, Benqing

    2011-09-01

    Previous studies have consistently reported a relationship between sensation seeking and emotional reactivity. However, little is known about the neural correlates and the time course of emotional processing in sensation seeking. The present study addressed these issues by recording event-related potentials (ERPs) during an emotional oddball task. Valence effect was significant at N2, P3 and LPP whereas arousal effect was significant at P3 and LPP. More importantly, low sensation seekers (LSSs) exhibited an increased emotional N2 whereas high sensation seekers (HSSs) showed an enhanced emotional P3. Furthermore, the arousal effect was similar across the two groups, but the valence effect at N2 stage was significant in LSSs instead of HSSs. These findings suggest that LSSs tend to show a more active general alerting system toward emotional stimuli, particularly for negative stimuli, whereas HSSs tend to display a stronger preference for intense stimulation irrespective of the emotional valence. PMID:21726599

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

    PubMed

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

    2010-10-01

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

  13. 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.

  14. 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

  15. Neural Correlates of Affect Processing and Aggression in Methamphetamine Dependence

    PubMed Central

    Payer, Doris E.; Lieberman, Matthew D.; London, Edythe D.

    2012-01-01

    Context Methamphetamine abuse is associated with high rates of aggression, but few studies have addressed the contributing neurobiological factors. Objective To quantify aggression, investigate function of the amygdala and prefrontal cortex, and assess relationships between brain function and behavior in methamphetamine-dependent individuals. Design In a case-control study, aggression and brain activation were compared between methamphetamine-dependent and control participants. Setting Participants were recruited from the general community to an academic research center. Participants Thirty-nine methamphetamine-dependent volunteers (16 women) who were abstinent for 7 to 10 days and 37 drug-free control volunteers (18 women) participated in the study; subsets completed self-report and behavioral measures. Functional magnetic resonance imaging (fMRI) was performed on 25 methamphetamine-dependent and 23 control participants. Main outcome measures We measured self-reported and perpetrated aggression, and self-reported alexithymia. Brain activation was assessed using fMRI during visual processing of facial affect (affect matching), and symbolic processing (affect labeling), the latter representing an incidental form of emotion regulation. Results Methamphetamine-dependent participants self-reported more aggression and alexithymia than control participants and escalated perpetrated aggression more following provocation. Alexithymia scores correlated with measures of aggression. During affect matching, fMRI showed no differences between groups in amygdala activation, but found lower activation in methamphetamine-dependent than control participants in bilateral ventral inferior frontal gyrus. During affect labeling, participants recruited dorsal inferior frontal gyrus and exhibited decreased amygdala activity, consistent with successful emotion regulation; there was no group difference in this effect. The magnitude of decrease in amygdala activity during affect labeling correlated inversely with self-reported aggression in control participants, and perpetrated aggression in all participants. Ventral inferior frontal gyrus activation correlated inversely with alexithymia in control participants. Conclusions Contrary to the hypotheses, methamphetamine-dependent individuals may successfully regulate emotions through incidental means (affect labeling). Instead, low ventral inferior frontal gyrus activity may contribute to heightened aggression by limiting emotional insight. PMID:21041607

  16. 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.

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

    PubMed Central

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

    2015-01-01

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

  18. Regulation of Amyloid Precursor Protein Processing by Serotonin Signaling

    PubMed Central

    Pimenova, Anna A.; Thathiah, Amantha; De Strooper, Bart; Tesseur, Ina

    2014-01-01

    Proteolytic processing of the amyloid precursor protein (APP) by the β- and γ-secretases releases the amyloid-β peptide (Aβ), which deposits in senile plaques and contributes to the etiology of Alzheimer's disease (AD). The α-secretase cleaves APP in the Aβ peptide sequence to generate soluble APPα (sAPPα). Upregulation of α-secretase activity through the 5-hydroxytryptamine 4 (5-HT4) receptor has been shown to reduce Aβ production, amyloid plaque load and to improve cognitive impairment in transgenic mouse models of AD. Consequently, activation of 5-HT4 receptors following agonist stimulation is considered to be a therapeutic strategy for AD treatment; however, the signaling cascade involved in 5-HT4 receptor-stimulated proteolysis of APP remains to be determined. Here we used chemical and siRNA inhibition to identify the proteins which mediate 5-HT4d receptor-stimulated α-secretase activity in the SH-SY5Y human neuronal cell line. We show that G protein and Src dependent activation of phospholipase C are required for α-secretase activity, while, unexpectedly, adenylyl cyclase and cAMP are not involved. Further elucidation of the signaling pathway indicates that inositol triphosphate phosphorylation and casein kinase 2 activation is also a prerequisite for α-secretase activity. Our findings provide a novel route to explore the treatment of AD through 5-HT4 receptor-induced α-secretase activation. PMID:24466315

  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. Superconductive circuits for on-FPA IR digital signal processing

    NASA Astrophysics Data System (ADS)

    Jensen, Arthur S.; Burnell, David M.

    1992-09-01

    Digital signal processing (DSP) on focal plane array (FPA) is attractive for large focal planes for reducing the amount of data output to no more than that which is of interest and for simplifying the IO to a simple digital bus. However, semiconductor circuits dissipate too much power for use on the FPA, overloading the cooling system capability, and requiring too much system cooling power for many applications. On the other hand, superconductive circuits (SC) offer an attractive alternative because they dissipate only about 0.1% the power of semiconductor circuits for an equivalent circuit function. SC 12 bit A/D converter and SC shift registers demonstrated in Nb at 4 K are readily convertible to NbN at 10 K. As the development of active devices in YBa(subscript 2)Cu(subscript 3)O(subscript 7) matures, these and a full complement of logic devices should be possible as high as 80 K. Scene signal and detector leakage current considerations require that long wavelength IR/FPA using quantum detectors must operate at cryogenic temperatures (< 80 K). It is no significant burden to use SC circuits at these cryogenic temperatures. SC circuits operate so much faster than semiconductor circuits and SC memory circuits are so relatively limited in size that DSP architecture has to be restructured. The derived benefit in terms of system capability will warrant this investment.

  1. The application of multi-dimensional access memories to radar signal processing systems

    NASA Astrophysics Data System (ADS)

    Hayes, David; Strawhorne, Bill

    1986-07-01

    A multi-dimensional access memory (MDAM) allows a word to be accessed from store either in the manner it was entered or as part of a bit slice of equally spaced or contiguous words. Conceptually, data may be regarded as being stored in an n dimensional hypercube of side length equal to the word length that usefully maps onto a wide range of signal processing operations, (e.g., FFTs, matrix inversion, multiple moments, distance metrics, sorts, searches and correlation decodes), when associated processing units that can carry out both bit parallel and bit serial arithmetic are used. The mapping of the natural multi-dimensionality of a signal processing task onto the MDAM structure is shown to be particularly useful when bit serial, word parallel processors are employed. In these circumstances the facilities of the MDAM make possible a range of useful operations that could only be implemented with great inefficiency using conventional memories. Furthermore, the MDAM considerably simplifies address generation for the I/O of real and complex words (e.g., the corner turn of incoming samples) while allowing useful permutations, such as barrel shifts, to be applied on each memory access for a insignificant cost in extra circuitry. Highly efficient and deeply pipelined, implementations of MDAM/processor structures are discussed that are particulary well suited to VLSI methodologies, in that very wide bandwidth interconnection networks of high complexity can be achieved at relatively low gate and pin counts. Thus, it is possible to form highly parallel multi-MDAM/processor structures that support very high levels of concurrency, identified as necessary for future radar signal processing systems. Moreover these structures translate over classes of operations that are not normally associated with each other. Consequently, these forms can be made extremely general and modular to produce powerful and compact processing kernels for programmable systems that embody high level signal processing constructs in their VLSI fabric and lead to high performance at the minimum silicon cost.

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

    NASA Astrophysics Data System (ADS)

    Langbein, J.

    2008-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Vardhan, Harsh; Roy Mahapatra, D.

    2012-04-01

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

  4. 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

  5. Digital Signal Processing System for Active Noise Reduction

    NASA Astrophysics Data System (ADS)

    Edmonson, William W.; Tucker, Jerry

    2002-12-01

    Over the years there has been a need to improve the comfort of passengers in flight. One avenue for increasing comfort is to reduce cabin noise that is attributed to the engine and the vibration of fuselage panels that radiate sound. High frequency noise can be abated using sound absorbing material. Though, for low frequency noise the sound absorption material would have to very thick, thereby reducing the cabin size. To reduce these low frequency disturbances, active noise control systems (ANC) is being developed that utilizes feedback for cancellation of the disturbance. The active noise control system must be small in size, be a low power device, and operate in real-time. It must also be numerically stable i.e. insensitive to temperature and pressure variations. The ANC system will be a module that consists of digital signal processor (DSP), analog-digital and digital-analog converters, power converters, an actuator and sensors. The DSP will implement the feedback control algorithm that controls the actuators. This module will be attached to panels on the inside of the fuselage for actively eliminating resonant modes of the structure caused by turbulent flow across the fuselage Skin. A hardware prototype of the ANC system must be able to eliminate broadband noise consisting of a bandwidth between 100 Hz and 1500 Hz, which requires a sample rate of 5000 Hz. The analog/digital converters output accuracy is 16 bits with a 2's-compliment format and a very short acquisition time. This will also yield the appropriate dynamic range. Similar specifications are required of the digital/analog converter. The processor section of the system integrates a digital signal processor (TI TMS320C33) with analog/digital (Burr-Brown ADS8320) and digital/analog signal (DAC853 1) converters. The converters with associated power conditioning circuitry and test points reside on a daughter board that sits on top of a Spectrum Digital evaluation module. This will have the ability to test different adaptive noise cancellation algorithms and provide an operational prototype to understand the behavior of the system under test. DSP software was required to interface the processor with the data converters using interrupt routines. The goal is to build a complete ANC system that can be placed on a flexible circuit with added memory circuitry that also contains the power supply, sensors and actuators. This work on the digital signal processing system for active noise reduction was completed in collaboration with another ASEE Fellow, Dr. Jerry Tucker from Virginia Commonwealth University, Richmond, VA.

  6. 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.

  7. Signal Processing Strategies for Cochlear Implants Using Current Steering

    NASA Astrophysics Data System (ADS)

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

    2009-12-01

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

  8. 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.

  9. Biomedical signal processing and modeling in cardiovascular systems.

    PubMed

    Baselli, Giuseppe; Caiani, Enrico; Porta, Alberto; Montano, Nicola; Signorini, Maria Gabriella; Cerutti, Sergio

    2002-01-01

    This article revisits the subject of short-term heart-rate and arterial-pressure variability from the perspective of model structures that can be useful in defining signal processing algorithms. We draw a general scheme of the oscillation sources and interactions that contribute to cardiovascular control mechanisms and highlight the elements that were considered in different modeling works. The origin, superposition, and interaction of respiratory high-frequency (HF) and vasomotor low-frequency (LF) rhythms is presented as the integration of supraspinal and spinal circuits, vasomotor activity, and pressure control loops. We analyze in detail the necessity of considering all relevant interactions for the algorithms designed to estimate the baroreflex sensitivity. We also pinpoint the components of cardiorespiratory coupling in relation to the analysis of data from the acoustic quantification of the left ventricular volume. Finally, we analyze the tendency to produce complex behaviors even in extremely simplified systems involving interactions between oscillatory mechanisms. PMID:12650286

  10. 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

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

    NASA Astrophysics Data System (ADS)

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

    2015-09-01

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

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

    SciTech Connect

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

    2006-01-15

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

  13. REVIEW ARTICLE: Spectrophotometric applications of digital signal processing

    NASA Astrophysics Data System (ADS)

    Morawski, Roman Z.

    2006-09-01

    Spectrophotometry is more and more often the method of choice not only in analysis of (bio)chemical substances, but also in the identification of physical properties of various objects and their classification. The applications of spectrophotometry include such diversified tasks as monitoring of optical telecommunications links, assessment of eating quality of food, forensic classification of papers, biometric identification of individuals, detection of insect infestation of seeds and classification of textiles. In all those applications, large numbers of data, generated by spectrophotometers, are processed by various digital means in order to extract measurement information. The main objective of this paper is to review the state-of-the-art methodology for digital signal processing (DSP) when applied to data provided by spectrophotometric transducers and spectrophotometers. First, a general methodology of DSP applications in spectrophotometry, based on DSP-oriented models of spectrophotometric data, is outlined. Then, the most important classes of DSP methods for processing spectrophotometric data—the methods for DSP-aided calibration of spectrophotometric instrumentation, the methods for the estimation of spectra on the basis of spectrophotometric data, the methods for the estimation of spectrum-related measurands on the basis of spectrophotometric data—are presented. Finally, the methods for preprocessing and postprocessing of spectrophotometric data are overviewed. Throughout the review, the applications of DSP are illustrated with numerous examples related to broadly understood spectrophotometry.

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

    NASA Astrophysics Data System (ADS)

    Krausz, Ferenc; Stockman, Mark I.

    2014-03-01

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

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

    PubMed Central

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

    2010-01-01

    The current study investigated the neural correlates that underlie the processing of ambiguous words and the potential effects of semantic competition on that processing. Participants performed speeded lexical decisions on semantically related and unrelated prime-target pairs presented in the auditory modality. The primes were either ambiguous words (e.g., ball) or unambiguous words (e.g., athlete), and targets were either semantically related to the dominant (i.e., most frequent) meaning of the ambiguous prime word (e.g., soccer) or to the subordinate (i.e., less frequent) meaning (e.g., dance). Results showed increased activation in the bilateral inferior frontal gyrus (IFG) for ambiguous related compared to unambiguous related stimulus pairs, demonstrating that prefrontal areas are activated even in an implicit task where participants are not required to explicitly analyze the semantic content of the stimuli and to make an overt selection of a particular meaning based on this analysis. Additionally, increased activation was found in the left IFG and the left cingulate gyrus for subordinate meaning compared to dominant meaning conditions, suggesting that additional resources are recruited in order to resolve increased competition demands in accessing the subordinate meaning of an ambiguous word. PMID:18702579

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

    SciTech Connect

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

    2015-10-15

    During the long course of evolution, nature has learnt how to exploit quantum effects. In fact, recent experiments reveal the existence of quantum processes whose coherence extends over unexpectedly long time and space ranges. In particular, photosynthetic processes in light-harvesting complexes display a typical oscillatory dynamics ascribed to quantum coherence. Here, we consider the simple model where a dimer made of two chromophores is strongly coupled with a quasi-resonant vibrational mode. We observe the occurrence of wide oscillations of genuine quantum correlations, between electronic excitations and the environment, represented by vibrational bosonic modes. Such a quantum dynamics has been unveiled through the calculation of the negativity of entanglement and the discord, indicators widely used in quantum information for quantifying the resources needed to realize quantum technologies. We also discuss the possibility of approximating additional weakly-coupled off-resonant vibrational modes, simulating the disturbances induced by the rest of the environment, by a single vibrational mode. Within this approximation, one can show that the off-resonant bath behaves like a classical source of noise.

  17. Improved Statistical Signal Processing of Nonstationary Random Processes Using Time-Warping

    NASA Astrophysics Data System (ADS)

    Wisdom, Scott Thomas

    A common assumption used in statistical signal processing of nonstationary random signals is that the signals are locally stationary. Using this assumption, data is segmented into short analysis frames, and processing is performed using these short frames. Short frames limit the amount of data available, which in turn limits the performance of statistical estimators. In this thesis, we propose a novel method that promises improved performance for a variety of statistical signal processing algorithms. This method proposes to estimate certain time-varying parameters of nonstationary signals and then use this estimated information to perform a time-warping of the data that compensates for the time-varying parameters. Since the time-warped data is more stationary, longer analysis frames may be used, which improves the performance of statistical estimators. We first examine the spectral statistics of two particular types of nonstationary random processes that are useful for modeling ship propeller noise and voiced speech. We examine the effect of time-varying frequency content on these spectral statistics, and in addition show that the cross-frequency spectral statistics of these signals contain significant additional information that is not usually exploited using a stationary assumption. This information, combined with our proposed method, promises improvements for a wide variety of applications in the future. We then describe and test an implementation of our time-warping method, the fan-chirp transform. We apply our method to two applications, detection of ship noise in a passive sonar application and joint denoising and dereverberation of speech. Our method yields improved results for both applications compared to conventional methods.

  18. 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.

  19. 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

  20. Deregulation of STING Signaling in Colorectal Carcinoma Constrains DNA Damage Responses and Correlates With Tumorigenesis.

    PubMed

    Xia, Tianli; Konno, Hiroyasu; Ahn, Jeonghyun; Barber, Glen N

    2016-01-12

    Stimulator of interferon genes (STING) has been shown to be critical for controlling antiviral responses as well as anti-tumor adaptive immunity, but little is known regarding its regulation in human tumors. Here, we report that STING signaling is recurrently suppressed in a wide variety of cancers, including colorectal carcinoma. Loss of STING signaling impeded DNA damage responses accountable for generating key cytokines that facilitate tissue repair and anti-tumor T cell priming, such as type I interferons (IFNs). Correspondingly, defective STING function was also highly predictive of effectual DNA-virus-mediated oncolytic activity. Thus, impaired STING responses may enable damaged cells to evade host immunosurveillance processes, although they provide a critical prognostic measurement that could help predict the outcome of effective oncoviral therapy. PMID:26748708

  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. 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

  3. 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.

  4. 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.

  5. 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.

  6. Neural correlates of sublexical processing in phonological working memory.

    PubMed

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

    2011-04-01

    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 responses to these manipulations under conditions of covert rehearsal (Experiment 1). A left-dominant network of temporal and motor cortex showed increased activity for longer items, with motor cortex only showing greater activity concomitant with adding consonant clusters. An individual-differences analysis revealed a significant positive relationship between activity in the angular gyrus and the hippocampus, and accuracy on pseudoword repetition. As models of pWM stipulate that its neural correlates should be activated during both perception and production/rehearsal [Buchsbaum, B. R., & D'Esposito, M. The search for the phonological store: From loop to convolution. Journal of Cognitive Neuroscience, 20, 762-778, 2008; Jacquemot, C., & Scott, S. K. What is the relationship between phonological short-term memory and speech processing? Trends in Cognitive Sciences, 10, 480-486, 2006; Baddeley, A. D., & Hitch, G. Working memory. In G. H. Bower (Ed.), The psychology of learning and motivation: Advances in research and theory (Vol. 8, pp. 47-89). New York: Academic Press, 1974], we further assessed the effects of the two factors in a separate passive listening experiment (Experiment 2). In this experiment, the effect of the number of syllables was concentrated in posterior-medial regions of the supratemporal plane bilaterally, although there was no evidence of a significant response to added clusters. Taken together, the results identify the planum temporale as a key region in pWM; within this region, representations are likely to take the form of auditory or audiomotor "templates" or "chunks" at the level of the syllable [Papoutsi, M., de Zwart, J. A., Jansma, J. M., Pickering, M. J., Bednar, J. A., & Horwitz, B. From phonemes to articulatory codes: an fMRI study of the role of Broca's area in speech production. Cerebral Cortex, 19, 2156-2165, 2009; Warren, J. E., Wise, R. J. S., & Warren, J. D. Sounds do-able: auditory-motor transformations and the posterior temporal plane. Trends in Neurosciences, 28, 636-643, 2005; Griffiths, T. D., & Warren, J. D. The planum temporale as a computational hub. Trends in Neurosciences, 25, 348-353, 2002], whereas more lateral structures on the STG may deal with phonetic analysis of the auditory input [Hickok, G. The functional neuroanatomy of language. Physics of Life Reviews, 6, 121-143, 2009]. PMID:20350182

  7. 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.

  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. 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.

  10. 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.

  11. 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.

  12. Correlation between Gene Variants, Signaling Pathways, and Efficacy of Chemotherapy Drugs against Colon Cancers

    PubMed Central

    Tripathi, Swarnendu; Belkacemi, Louiza; Cheung, Margaret S.; Bose, Rathindra N.

    2016-01-01

    Efficacies, toxicities, and resistance mechanisms of chemotherapy drugs, such as oxaliplatin and 5-fluorouracil (5-FU), vary widely among various categories and subcategories of colon cancers. By understanding the differences in the drug efficacy and resistance at the level of protein–protein networks, we identified the correlation between the drug activity of oxaliplatin/5-FU and gene variations from the US National Cancer Institute-60 human cancer cell lines. The activity of either of these drugs is correlated with specific amino acid variant(s) of KRAS and other genes from the signaling pathways of colon cancer progression. We also discovered that the activity of a non-DNA-binding novel platinum drug, phosphaplatin, is comparable with oxaliplatin and 5-FU when it was tested against colon cancer cell lines. Our strategy that combines the knowledge from pharmacogenomics across cell lines with the molecular information from specific cancer cells is beneficial for predicting the outcome of a possible combination therapy for personalized treatment. PMID:26819545

  13. Online Epileptic Seizure Prediction Using Wavelet-Based Bi-Phase Correlation of Electrical Signals Tomography.

    PubMed

    Vahabi, Zahra; Amirfattahi, Rasoul; Shayegh, Farzaneh; Ghassemi, Fahimeh

    2015-09-01

    Considerable efforts have been made in order to predict seizures. Among these methods, the ones that quantify synchronization between brain areas, are the most important methods. However, to date, a practically acceptable result has not been reported. In this paper, we use a synchronization measurement method that is derived according to the ability of bi-spectrum in determining the nonlinear properties of a system. In this method, first, temporal variation of the bi-spectrum of different channels of electro cardiography (ECoG) signals are obtained via an extended wavelet-based time-frequency analysis method; then, to compare different channels, the bi-phase correlation measure is introduced. Since, in this way, the temporal variation of the amount of nonlinear coupling between brain regions, which have not been considered yet, are taken into account, results are more reliable than the conventional phase-synchronization measures. It is shown that, for 21 patients of FSPEEG database, bi-phase correlation can discriminate the pre-ictal and ictal states, with very low false positive rates (FPRs) (average: 0.078/h) and high sensitivity (100%). However, the proposed seizure predictor still cannot significantly overcome the random predictor for all patients. PMID:26126613

  14. 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.

  15. Electrophysiological correlates of melodic processing in congenital amusia.

    PubMed

    Omigie, Diana; Pearce, Marcus T; Williamson, Victoria J; Stewart, Lauren

    2013-08-01

    Music listening involves using previously internalized regularities to process incoming musical structures. A condition known as congenital amusia is characterized by musical difficulties, notably in the detection of gross musical violations. However, there has been increasing evidence that individuals with the disorder show preserved musical ability when probed using implicit methods. To further characterize the degree to which amusic individuals show evidence of latent sensitivity to musical structure, particularly in the context of stimuli that are ecologically valid, electrophysiological recordings were taken from a sample of amusic and control participants as they listened to real melodies. To encourage them to pay attention to the music, participants were asked to detect occasional notes in a different timbre. Using a computational model of auditory expectation to identify points of varying levels of expectedness in these melodies (in units of information content (IC), a measure which has an inverse relationship with probability), ERP analysis investigated the extent to which the amusic brain differs from that of controls when processing notes of high IC (low probability) as compared to low IC ones (high probability). The data revealed a novel effect that was highly comparable in both groups: Notes with high IC reliably elicited a delayed P2 component relative to notes with low IC, suggesting that amusic individuals, like controls, found these notes more difficult to evaluate. However, notes with high IC were also characterized by an early frontal negativity in controls that was attenuated in amusic individuals. A correlation of this early negative effect with the ability to make accurate note expectedness judgments (previous data collected from a subset of the current sample) was shown to be present in typical individuals but compromised in individuals with amusia: a finding in line with evidence of a close relationship between the amplitude of such a response and explicit knowledge of musical deviance. PMID:23707539

  16. Neural Signaling of Food Healthiness Associated with Emotion Processing

    PubMed Central

    Herwig, Uwe; Dhum, Matthias; Hittmeyer, Anna; Opialla, Sarah; Scherpiet, Sigrid; Keller, Carmen; Brühl, Annette B.; Siegrist, Michael

    2016-01-01

    The ability to differentiate healthy from unhealthy foods is important in order to promote good health. Food, however, may have an emotional connotation, which could be inversely related to healthiness. The neurobiological background of differentiating healthy and unhealthy food and its relations to emotion processing are not yet well understood. We addressed the neural activations, particularly considering the single subject level, when one evaluates a food item to be of a higher, compared to a lower grade of healthiness with a particular view on emotion processing brain regions. Thirty-seven healthy subjects underwent functional magnetic resonance imaging while evaluating the healthiness of food presented as photographs with a subsequent rating on a visual analog scale. We compared individual evaluations of high and low healthiness of food items and also considered gender differences. We found increased activation when food was evaluated to be healthy in the left dorsolateral prefrontal cortex and precuneus in whole brain analyses. In ROI analyses, perceived and rated higher healthiness was associated with lower amygdala activity and higher ventral striatal and orbitofrontal cortex activity. Females exerted a higher activation in midbrain areas when rating food items as being healthy. Our results underline the close relationship between food and emotion processing, which makes sense considering evolutionary aspects. Actively evaluating and deciding whether food is healthy is accompanied by neural signaling associated with reward and self-relevance, which could promote salutary nutrition behavior. The involved brain regions may be amenable to mechanisms of emotion regulation in the context of psychotherapeutic regulation of food intake. PMID:26903859

  17. Neural Signaling of Food Healthiness Associated with Emotion Processing.

    PubMed

    Herwig, Uwe; Dhum, Matthias; Hittmeyer, Anna; Opialla, Sarah; Scherpiet, Sigrid; Keller, Carmen; Brühl, Annette B; Siegrist, Michael

    2016-01-01

    The ability to differentiate healthy from unhealthy foods is important in order to promote good health. Food, however, may have an emotional connotation, which could be inversely related to healthiness. The neurobiological background of differentiating healthy and unhealthy food and its relations to emotion processing are not yet well understood. We addressed the neural activations, particularly considering the single subject level, when one evaluates a food item to be of a higher, compared to a lower grade of healthiness with a particular view on emotion processing brain regions. Thirty-seven healthy subjects underwent functional magnetic resonance imaging while evaluating the healthiness of food presented as photographs with a subsequent rating on a visual analog scale. We compared individual evaluations of high and low healthiness of food items and also considered gender differences. We found increased activation when food was evaluated to be healthy in the left dorsolateral prefrontal cortex and precuneus in whole brain analyses. In ROI analyses, perceived and rated higher healthiness was associated with lower amygdala activity and higher ventral striatal and orbitofrontal cortex activity. Females exerted a higher activation in midbrain areas when rating food items as being healthy. Our results underline the close relationship between food and emotion processing, which makes sense considering evolutionary aspects. Actively evaluating and deciding whether food is healthy is accompanied by neural signaling associated with reward and self-relevance, which could promote salutary nutrition behavior. The involved brain regions may be amenable to mechanisms of emotion regulation in the context of psychotherapeutic regulation of food intake. PMID:26903859

  18. Memory Processes in the Response of Plants to Environmental Signals

    PubMed Central

    Tafforeau, M; Verdus, M C; Norris, V; Ripoll, C

    2006-01-01

    Plants are sensitive to stimuli from the environment (e.g., wind, rain, contact, pricking, wounding). They usually respond to such stimuli by metabolic or morphogenetic changes. Sometimes the information corresponding to a stimulus may be “stored” in the plant where it remains inactive until a second stimulus “recalls” this information and finally allows it to take effect. Two experimental systems have proved especially useful in unravelling the main features of these memory-like processes. In the system based on Bidens seedlings, an asymmetrical treatment (e.g., pricking, or gently rubbing one of the seedling cotyledons) causes the cotyledonary buds to grow asymmetrically after release of apical dominance by decapitation of the seedlings. This information may be stored within the seedlings, without taking effect, for at least two weeks; then the information may be recalled by subjecting the seedlings to a second, appropriate, treatment that permits transduction of the signal into the final response (differential growth of the buds). Whilst storage is an irreversible, all-or-nothing process, recall is sensitive to a number of factors, including the intensity of these factors, and can readily be enabled or disabled. In consequence, it is possible to recall the stored message several times successively. In the system based on flax seedlings, stimulation such as manipulation stimulus, drought, wind, cold shock and radiation from a GSM telephone or from a 105 GHz Gunn oscillator, has no apparent effect. If, however, the seedlings are subjected at the same time to transient calcium depletion, numerous epidermal meristems form in their hypocotyls. When the calcium depletion treatment is applied a few days after the mechanical treatment, the time taken for the meristems to appear is increased by a number of days exactly equal to that between the application of the mechanical treatment and the beginning of the calcium depletion treatment. This means that a meristem-production information corresponding to the stimulation treatment has been stored in the plants, without any apparent effect, until the calcium depletion treatment recalls this information to allow it to take effect. Gel electrophoresis has shown that a few protein spots are changed (pI shift, appearance or disappearance of a spot) as a consequence of the application of the treatments that store or recall a meristem-production signal in flax seedlings. A SIMS investigation has revealed that the pI shift of one of these spots is probably due to protein phosphorylation. Modifications of the proteome have also been observed in Arabidopsis seedlings subjected to stimuli such as cold shock or radiation from a GSM telephone. PMID:19521470

  19. Algorithms and architectures for adaptive least squares signal processing, with applications in magnetoencephalography

    SciTech Connect

    Lewis, P.S.

    1988-10-01

    Least squares techniques are widely used in adaptive signal processing. While algorithms based on least squares are robust and offer rapid convergence properties, they also tend to be complex and computationally intensive. To enable the use of least squares techniques in real-time applications, it is necessary to develop adaptive algorithms that are efficient and numerically stable, and can be readily implemented in hardware. The first part of this work presents a uniform development of general recursive least squares (RLS) algorithms, and multichannel least squares lattice (LSL) algorithms. RLS algorithms are developed for both direct estimators, in which a desired signal is present, and for mixed estimators, in which no desired signal is available, but the signal-to-data cross-correlation is known. In the second part of this work, new and more flexible techniques of mapping algorithms to array architectures are presented. These techniques, based on the synthesis and manipulation of locally recursive algorithms (LRAs), have evolved from existing data dependence graph-based approaches, but offer the increased flexibility needed to deal with the structural complexities of the RLS and LSL algorithms. Using these techniques, various array architectures are developed for each of the RLS and LSL algorithms and the associated space/time tradeoffs presented. In the final part of this work, the application of these algorithms is demonstrated by their employment in the enhancement of single-trial auditory evoked responses in magnetoencephalography. 118 refs., 49 figs., 36 tabs.

  20. 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.

  1. A new multi-channel real-time digital signal processing platform for acoustic signal processing and sensor response emulation

    NASA Astrophysics Data System (ADS)

    Gaydecki, P.

    2007-07-01

    In recent years, the DSP group at the University of Manchester has developed a range of DSP platforms for real-time filtering and processing of acoustic signals. A next generation system has now been designed, which incorporates a processor operating at 0.55 Giga MMACS, six input and eight output analogue channels, digital input/output in the form of S/PDIF and a USB interface. The software allows the user, with no knowledge of filter theory or programming, to design and run standard or completely arbitrary FIR, IIR and adaptive filters. Processing tasks may be described and linked using the graphical icon based interface. In addition, the system has the capability to emulate in real-time linear system behaviour such as sensors, instrument bodies, string vibrations, resonant spaces and electrical networks. Tests have confirmed a high degree of fidelity between the behaviour of the physical system and its digitally emulated counterpart. In addition to the supplied software, the user may also program the system using a variety of commercial packages via the JTAG interface.

  2. Gene microarrays in hippocampal aging: statistical profiling identifies novel processes correlated with cognitive impairment.

    PubMed

    Blalock, Eric M; Chen, Kuey-Chu; Sharrow, Keith; Herman, James P; Porter, Nada M; Foster, Thomas C; Landfield, Philip W

    2003-05-01

    Gene expression microarrays provide a powerful new tool for studying complex processes such as brain aging. However, inferences from microarray data are often hindered by multiple comparisons, small sample sizes, and uncertain relationships to functional endpoints. Here we sought gene expression correlates of aging-dependent cognitive decline, using statistical profiling of gene microarrays in well powered groups of young, mid-aged, and aged rats (n = 10 per group). Animals were trained on two memory tasks, and the hippocampal CA1 region of each was analyzed on an individual microarray (one chip per animal). Aging- and cognition-related genes were identified by testing each gene by ANOVA (for aging effects) and then by Pearson's test (correlating expression with memory). Genes identified by this algorithm were associated with several phenomena known to be aging-dependent, including inflammation, oxidative stress, altered protein processing, and decreased mitochondrial function, but also with multiple processes not previously linked to functional brain aging. These novel processes included downregulated early response signaling, biosynthesis and activity-regulated synaptogenesis, and upregulated myelin turnover, cholesterol synthesis, lipid and monoamine metabolism, iron utilization, structural reorganization, and intracellular Ca2+ release pathways. Multiple transcriptional regulators and cytokines also were identified. Although most gene expression changes began by mid-life, cognition was not clearly impaired until late life. Collectively, these results suggest a new integrative model of brain aging in which genomic alterations in early adulthood initiate interacting cascades of decreased signaling and synaptic plasticity in neurons, extracellular changes, and increased myelin turnover-fueled inflammation in glia that cumulatively induce aging-related cognitive impairment. PMID:12736351

  3. 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

  4. 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)

  5. Research on the signal processing technology of laser fuze

    NASA Astrophysics Data System (ADS)

    Gao, Jing; Deng, Jiahao; Cai, Kerong

    2011-06-01

    Laser fuze has been widely used in a variety of large-caliber ammunitions, such as missile, aerial bomb and rocket bomb, due to its typical advantages of proactivity in target detection, sharp directivity of probe field and strong antielectromagnetic interference ability. Recently a new kind of small laser fuze adapted to small-caliber ammunitions is being actively developed. Designed the mathematic model of the laser echo waveform based on Gauss beam and deduced time domain of echo impulse power with varied sharps of target (such as plane target, circle target and mutant target). Echo impulse waveform of laser fuse with the noise interference, such as sunlight and raindrop, also has been studied based on the modeling. The test experiments show that the system can detect weak laser echoed wave, distinguish target and interferences signal by amplifying, modulating and processing the echoed waveform, and detect vertical test board (gray iron) at 5m far away with no more than 90mA current. The test results in High overload conditions indicates that the prototyping can work normally and steadily in the whole trajectory.

  6. 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.

  7. 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.

  8. Magnetoencephalographic signals identify stages in real-life decision processes.

    PubMed

    Braeutigam, S; Stins, J F; Rose, S P; Swithenby, S J; Ambler, T

    2001-01-01

    We used magnetoencephalography (MEG) to study the dynamics of neural responses in eight subjects engaged in shopping for day-to-day items from supermarket shelves. This behavior not only has personal and economic importance but also provides an example of an experience that is both personal and shared between individuals. The shopping experience enables the exploration of neural mechanisms underlying choice based on complex memories. Choosing among different brands of closely related products activated a robust sequence of signals within the first second after the presentation of the choice images. This sequence engaged first the visual cortex (80-100 ms), then as the images were analyzed, predominantly the left temporal regions (310-340 ms). At longer latency, characteristic neural activation was found in motor speech areas (500-520 ms) for images requiring low salience choices with respect to previous (brand) memory, and in right parietal cortex for high salience choices (850-920 ms). We argue that the neural processes associated with the particular brand-choice stimulus can be separated into identifiable stages through observation of MEG responses and knowledge of functional anatomy. PMID:12018772

  9. Validation of a raw data-based synchronization signal (kymogram) for phase-correlated cardiac image reconstruction.

    PubMed

    Ertel, Dirk; Pflederer, Tobias; Achenbach, Stephan; Kachelriess, Marc; Steffen, Peter; Kalender, Willi A

    2008-02-01

    Phase-correlated reconstruction is commonly used in computed tomography (CT)-based cardiac imaging. Alternatively to the commonly used ECG, the raw data-based kymogram function can be used as a synchronization signal. We used raw data of 100 consecutive patient exams to compare the performance of kymogram function to the ECG signal. For objective validation the correlation of the ECG and the kymogram was assessed. Additionally, we performed a double-blinded comparison of ECG-based and kymogram-based phase-correlated images. The two synchronization signals showed good correlation indicated by a mean difference in the detected heart rate of negligible 0.2 bpm. The mean image quality score was 2.0 points for kymogram-correlated images and 2.3 points for ECG-correlated images, respectively (3: best; 0: worst). The kymogram and the ECG provided images adequate for diagnosis for 93 and 97 patients, respectively. For 50% of the datasets the kymogram provided an equivalent or even higher image quality compared with the ECG signal. We conclude that an acceptable image quality can be assured in most cases by the kymogram. Improvements of image quality by the kymogram function were observed in a noticeable number of cases. The kymogram can serve as a backup solution when an ECG is not available or lacking in quality. PMID:18008075

  10. Signal processing algorithms for staring single pixel hyperspectral sensors

    NASA Astrophysics Data System (ADS)

    Manolakis, Dimitris; Rossacci, Michael; O'Donnell, Erin; D'Amico, Francis M.

    2006-08-01

    Remote sensing of chemical warfare agents (CWA) with stand-off hyperspectral sensors has a wide range of civilian and military applications. These sensors exploit the spectral changes in the ambient photon flux produced thermal emission or absorption after passage through a region containing the CWA cloud. In this work we focus on (a) staring single-pixel sensors that sample their field of view at regular intervals of time to produce a time series of spectra and (b) scanning single or multiple pixel sensors that sample their FOV as they scan. The main objective of signal processing algorithms is to determine if and when a CWA enters the FOV of the sensor. We shall first develop and evaluate algorithms for staring sensors following two different approaches. First, we will assume that no threat information is available and we design an adaptive anomaly detection algorithm to detect a statistically-significant change in the observed spectrum. The algorithm processes the observed spectra sequentially-in-time, estimates adaptively the background, and checks whether the next spectrum differs significantly from the background based on the Mahalanobis distance or the distance from the background subspace. In the second approach, we will assume that we know the spectral signature of the CWA and develop sequential-in-time adaptive matched filter detectors. In both cases, we assume that the sensor starts its operation before the release of the CWA; otherwise, staring at a nearby CWA-free area is required for background estimation. Experimental evaluation and comparison of the proposed algorithms is accomplished using data from a long-wave infrared (LWIR) Fourier transform spectrometer.

  11. A New Digital Signal Processing Method for Spectrum Interference Monitoring

    NASA Astrophysics Data System (ADS)

    Angrisani, L.; Capriglione, D.; Ferrigno, L.; Miele, G.

    2011-01-01

    Frequency spectrum is a limited shared resource, nowadays interested by an ever growing number of different applications. Generally, the companies providing such services pay to the governments the right of using a limited portion of the spectrum, consequently they would be assured that the licensed radio spectrum resource is not interested by significant external interferences. At the same time, they have to guarantee that their devices make an efficient use of the spectrum and meet the electromagnetic compatibility regulations. Therefore the competent authorities are called to control the access to the spectrum adopting suitable management and monitoring policies, as well as the manufacturers have to periodically verify the correct working of their apparatuses. Several measurement solutions are present on the market. They generally refer to real-time spectrum analyzers and measurement receivers. Both of them are characterized by good metrological accuracies but show costs, dimensions and weights that make no possible a use "on the field". The paper presents a first step in realizing a digital signal processing based measurement instrument able to suitably accomplish for the above mentioned needs. In particular the attention has been given to the DSP based measurement section of the instrument. To these aims an innovative measurement method for spectrum monitoring and management is proposed in this paper. It performs an efficient sequential analysis based on a sample by sample digital processing. Three main issues are in particular pursued: (i) measurement performance comparable to that exhibited by other methods proposed in literature; (ii) fast measurement time, (iii) easy implementation on cost-effective measurement hardware.

  12. Signal Processor Development by Personnel of the JSC Signal Processing Section

    NASA Technical Reports Server (NTRS)

    Holland, S. Douglas

    1994-01-01

    The purpose of this paper is to describe systems and components of systems developed by personnel in the Signal Processing Section of the Tracking and Communications Division. The scope of this includes past developments which are in current use in NASA flight operations and future developments which are targeted for upcoming NASA applications. These projects specifically are: (1) NASA High Definition Television (HDTV) Project, (2) Video Codecs, (3) NASA Electronic Still Camera (ESC) Project, (4) Hercules Payload, (5) Ku-band Communications Adapter (KCA), (6) Windows Drivers for Satellite Interfacing to Commercial Equipment, and (7) Advanced Statistical Multiplexers. The methods used to determine what projects should be done in-house as opposed to which should not is based in NASA applications versus commercially available systems to meet those applications. If a commercial-off-the-shelf (COTS) component or system is available which meets the need, the first choice is to use COTS equipment. If it is not, and there is a NASA requirement, it is developed in-house. This results in technology which is being developed which otherwise was not available. Personnel involved in these projects have been contacted by many commercial companies interested in licensing or obtaining the NASA design.

  13. Statistical tests for power-law cross-correlated processes

    NASA Astrophysics Data System (ADS)

    Podobnik, Boris; Jiang, Zhi-Qiang; Zhou, Wei-Xing; Stanley, H. Eugene

    2011-12-01

    For stationary time series, the cross-covariance and the cross-correlation as functions of time lag n serve to quantify the similarity of two time series. The latter measure is also used to assess whether the cross-correlations are statistically significant. For nonstationary time series, the analogous measures are detrended cross-correlations analysis (DCCA) and the recently proposed detrended cross-correlation coefficient, ρDCCA(T,n), where T is the total length of the time series and n the window size. For ρDCCA(T,n), we numerically calculated the Cauchy inequality -1≤ρDCCA(T,n)≤1. Here we derive -1≤ρDCCA(T,n)≤1 for a standard variance-covariance approach and for a detrending approach. For overlapping windows, we find the range of ρDCCA within which the cross-correlations become statistically significant. For overlapping windows we numerically determine—and for nonoverlapping windows we derive—that the standard deviation of ρDCCA(T,n) tends with increasing T to 1/T. Using ρDCCA(T,n) we show that the Chinese financial market's tendency to follow the U.S. market is extremely weak. We also propose an additional statistical test that can be used to quantify the existence of cross-correlations between two power-law correlated time series.

  14. Tensor Decompositions for Signal Processing Applications: From two-way to multiway component analysis

    NASA Astrophysics Data System (ADS)

    Cichocki, Andrzej; Mandic, Danilo; De Lathauwer, Lieven; Zhou, Guoxu; Zhao, Qibin; Caiafa, Cesar; PHAN, HUY ANH

    2015-03-01

    The widespread use of multi-sensor technology and the emergence of big datasets has highlighted the limitations of standard flat-view matrix models and the necessity to move towards more versatile data analysis tools. We show that higher-order tensors (i.e., multiway arrays) enable such a fundamental paradigm shift towards models that are essentially polynomial and whose uniqueness, unlike the matrix methods, is guaranteed under verymild and natural conditions. Benefiting fromthe power ofmultilinear algebra as theirmathematical backbone, data analysis techniques using tensor decompositions are shown to have great flexibility in the choice of constraints that match data properties, and to find more general latent components in the data than matrix-based methods. A comprehensive introduction to tensor decompositions is provided from a signal processing perspective, starting from the algebraic foundations, via basic Canonical Polyadic and Tucker models, through to advanced cause-effect and multi-view data analysis schemes. We show that tensor decompositions enable natural generalizations of some commonly used signal processing paradigms, such as canonical correlation and subspace techniques, signal separation, linear regression, feature extraction and classification. We also cover computational aspects, and point out how ideas from compressed sensing and scientific computing may be used for addressing the otherwise unmanageable storage and manipulation problems associated with big datasets. The concepts are supported by illustrative real world case studies illuminating the benefits of the tensor framework, as efficient and promising tools for modern signal processing, data analysis and machine learning applications; these benefits also extend to vector/matrix data through tensorization. Keywords: ICA, NMF, CPD, Tucker decomposition, HOSVD, tensor networks, Tensor Train.

  15. Digital Signal Processing Techniques for the GIFTS SM EDU

    NASA Technical Reports Server (NTRS)

    Tian, Jialin; Reisse, Robert A.; Gazarik, Michael J.

    2007-01-01

    The Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) Sensor Module (SM) Engineering Demonstration Unit (EDU) is a high resolution spectral imager designed to measure infrared (IR) radiance using a Fourier transform spectrometer (FTS). The GIFTS instrument employs three Focal Plane Arrays (FPAs), which gather measurements across the long-wave IR (LWIR), short/mid-wave IR (SMWIR), and visible spectral bands. The raw interferogram measurements are radiometrically and spectrally calibrated to produce radiance spectra, which are further processed to obtain atmospheric profiles via retrieval algorithms. This paper describes several digital signal processing (DSP) techniques involved in the development of the calibration model. In the first stage, the measured raw interferograms must undergo a series of processing steps that include filtering, decimation, and detector nonlinearity correction. The digital filtering is achieved by employing a linear-phase even-length FIR complex filter that is designed based on the optimum equiripple criteria. Next, the detector nonlinearity effect is compensated for using a set of pre-determined detector response characteristics. In the next stage, a phase correction algorithm is applied to the decimated interferograms. This is accomplished by first estimating the phase function from the spectral phase response of the windowed interferogram, and then correcting the entire interferogram based on the estimated phase function. In the calibration stage, we first compute the spectral responsivity based on the previous results and the ideal Planck blackbody spectra at the given temperatures, from which, the calibrated ambient blackbody (ABB), hot blackbody (HBB), and scene spectra can be obtained. In the post-calibration stage, we estimate the Noise Equivalent Spectral Radiance (NESR) from the calibrated ABB and HBB spectra. The NESR is generally considered as a measure of the instrument noise performance, and can be estimated as the standard deviation of calibrated radiance spectra from multiple scans. To obtain an estimate of the FPA performance, we developed an efficient method of generating pixel performance assessments. In addition, a random pixel selection scheme is developed based on the pixel performance evaluation. This would allow us to perform the calibration procedures on a random pixel population that is a good statistical representation of the entire FPA. The design and implementation of each individual component will be discussed in details.

  16. Digital Signal Processing Techniques for the GIFTS SM EDU

    NASA Astrophysics Data System (ADS)

    Tian, J.; Reisse, R.; Gazarik, M.

    The Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) Sensor Module (SM) Engineering Demonstration Unit (EDU) is a high resolution spectral imager designed to measure infrared (IR) radiance using a Fourier transform spectrometer (FTS). The GIFTS instrument employs three Focal Plane Arrays (FPAs), which gather measurements across the long-wave IR (LWIR), short/mid-wave IR (SMWIR), and visible spectral bands. The raw interferogram measurements are radiometrically and spectrally calibrated to produce radiance spectra, which are further processed to obtain atmospheric profiles via retrieval algorithms. This paper describes several digital signal processing (DSP) techniques involved in the development of the calibration model. In the first stage, the measured raw interferograms must undergo a series of processing steps that include filtering, decimation, and detector nonlinearity correction. The digital filtering is achieved by employing a linear-phase even-length FIR complex filter that is designed based on the optimum equiripple criteria. Next, the detector nonlinearity effect is compensated for using a set of pre-determined detector response characteristics. In the next stage, a phase correction algorithm is applied to the decimated interferograms. This is accomplished by first estimating the phase function from the spectral phase response of the windowed interferogram, and then correcting the entire interferogram based on the estimated phase function. In the calibration stage, we first compute the spectral responsivity based on the previous results and the ideal Planck blackbody spectra at the given temperatures, from which, the calibrated ambient blackbody (ABB), hot blackbody (HBB), and scene spectra can be obtained. In the post-calibration stage, we estimate the Noise Equivalent Spectral Radiance (NESR) from the calibrated ABB and HBB spectra. The NESR is generally considered as a measure of the instrument noise performance, and can be estimated as the standard deviation of calibrated radiance spectra from multiple scans. To obtain an estimate of the FPA performance, we developed an efficient method of generating pixel performance assessments. In addition, a random pixel selection scheme is developed based on the pixel performance evaluation. This would allow us to perform the calibration procedures on a random pixel population that is a good statistical representation of the entire FPA. The design and implementation of each individual component will be discussed in details.

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

    NASA Astrophysics Data System (ADS)

    Krmpot, Aleksandar J.; Nikolić, 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 μs/frame) and single-molecule sensitivity.

  18. 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.

  19. Differential DNA damage signalling and apoptotic threshold correlate with mouse epiblast-specific hypersensitivity to radiation.

    PubMed

    Laurent, Audrey; Blasi, Francesco

    2015-11-01

    Between implantation and gastrulation, mouse pluripotent epiblast cells expand enormously in number and exhibit a remarkable hypersensitivity to DNA damage. Upon low-dose irradiation, they undergo mitotic arrest followed by p53-dependent apoptosis, whereas the other cell types simply arrest. This protective mechanism, active exclusively after E5.5 and lost during gastrulation, ensures the elimination of every mutated cell before its clonal expansion and is therefore expected to greatly increase fitness. We show that the insurgence of apoptosis relies on the epiblast-specific convergence of both increased DNA damage signalling and stronger pro-apoptotic balance. Although upstream Atm/Atr global activity and specific γH2AX phosphorylation are similar in all cell types of the embryo, 53BP1 recruitment at DNA breaks is immediately amplified only in epiblast cells after ionizing radiation. This correlates with rapid epiblast-specific activation of p53 and its transcriptional properties. Moreover, between E5.5 and E6.5 epiblast cells lower their apoptotic threshold by enhancing the expression of pro-apoptotic Bak and Bim and repressing the anti-apoptotic Bcl-xL. Thus, even after low-dose irradiation, the cytoplasmic priming of epiblast cells allows p53 to rapidly induce apoptosis via a partially transcription-independent mechanism. PMID:26395482

  20. In vitro and in vivo approaches to studying the bacterial signal peptide processing.

    PubMed

    Wang, Peng; Dalbey, Ross E

    2010-01-01

    Protein targeting in both eukaryotic and prokaryotic cells is often directed by a signal sequence located at the amino-terminus of the protein. In eukaryotes, proteins that are sorted into different compartments of the cell, such as endoplasmic reticulum, mitochondria, and chloroplast, require different signal sequences. In bacteria, proteins which are exported to the outer membrane or the periplasmic space are also guided by signal peptides. After the protein is translocated across the cytoplasmic membrane, the signal peptide is proteolytically removed by signal peptide cleavage. Here, in this chapter, we describe methods to study signal peptide processing in bacteria, including purification of signal peptidase and its substrates. We also describe the measurement of the catalytic constants of signal peptidases using an in vitro assay. In addition, we will present an in vivo assay using a temperature sensitive signal peptidase strain to determine which preproteins are processed by Signal peptidase 1. PMID:20419402

  1. Radar and communication band signal processing using time-integration processors

    NASA Astrophysics Data System (ADS)

    Berg, N. J.; Casseday, M. W.; Abramovitz, I. J.; Lee, J. N.

    1980-01-01

    A new architecture for performing time-integration correlation is described. The correlator uses a surface acoustic wave (SAW) delay line, and features the optical interference of two coherent light beams which have been Bragg-diffracted by SAW's propagating in the line. The time integration is performed by a photodiode array which detects the diffracted light. Time-bandwidth products exceeding one-million (50 MHz times 30 ms) have been achieved. This two-beam SAW acousto-optic time-integrating correlator has been used to detect a number of wideband spread-spectrum signals. It has several attributes which make it particularly well suited for use as a spread-spectrum signal processor. These include linearity of operation, large time aperture over which the correlation can be observed, and the ability to determine the center frequency and bandwidth of the signals. The suitability of this correlator for use as a signal processor in spread-spectrum systems is considered. In addition, a two-dimensional realization of this correlator is proposed for frequency scanning correlation. The use of this frequency scanning correlator as an LPI radar signal processor is discussed.

  2. 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.

  3. Roles of phosphotase 2A in nociceptive signal processing

    PubMed Central

    2013-01-01

    Multiple protein kinases affect the responses of dorsal horn neurons through phosphorylation of synaptic receptors and proteins involved in intracellular signal transduction pathways, and the consequences of this modulation may be spinal central sensitization. In contrast, the phosphatases catalyze an opposing reaction of de-phosphorylation, which may also modulate the functions of crucial proteins in signaling nociception. This is an important mechanism in the regulation of intracellular signal transduction pathways in nociceptive neurons. Accumulated evidence has shown that phosphatase 2A (PP2A), a serine/threonine specific phosphatase, is implicated in synaptic plasticity of the central nervous system and central sensitization of nociception. Therefore, targeting protein phosphotase 2A may provide an effective and novel strategy for the treatment of clinical pain. This review will characterize the structure and functional regulation of neuronal PP2A and bring together recent advances on the modulation of PP2A in targeted downstream substrates and relevant multiple nociceptive signaling molecules. PMID:24010880

  4. A CCD/CMOS process for integrated image acquisition and early vision signal processing

    NASA Astrophysics Data System (ADS)

    Keast, Craig L.; Sodini, Charles G.

    The development of technology which integrates a four phase, buried-channel CCD in an existing 1.75 micron CMOS process is described. The four phase clock is employed in the integrated early vision system to minimize process complexity. Signal corruption is minimized and lateral fringing fields are enhanced by burying the channel. The CMOS process for CCD enhancement is described, which highlights a new double-poly process and the buried channel, and the integration is outlined. The functionality and transfer efficiency of the process enhancement were appraised by measuring CCD shift registers at 100 kHz. CMOS measurement results are presented, which include threshold voltages, poly-to-poly capacitor voltage and temperature coefficients, and dark current. A CCD/CMOS processor is described which combines smoothing and segmentation operations. The integration of the CCD and the CMOS processes is found to function due to the enhancement-compatible design of the CMOS process and the thorough employment of CCD module baseline process steps.

  5. 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.

  6. A Research on the Relation Between the Integrated Three-Pulse Photon Echo Signal and the Correlation Function

    NASA Astrophysics Data System (ADS)

    Zhang, Zhonghua; Chen, Jia; Zhao, Yang; Xia, Yuangin

    2014-03-01

    The photon echo phenomenon has been described and proven with classical theory. In this paper, in order to calculate the three-pulse photon echo signal, we treat the vibration of material molecules as the model of the multimode Brownian oscillator (MBO). Using the correlation function, we can calculate the linear function, the time response function, and the third-order nonlinear polarization; then we can obtain the three-pulse photon echo signal. After that, we numerically simulate the three-pulse photon echo signal by changing the contribution ratios of these four kinds of vibration in the MBO model and setting the coherence time (t12) or the population time (t23) equal to zero. Finally, we analyze the result and find that these three laser pulses are not in time coincidence completely when the signal reaches a maximum. In addition, the location of the peak signal intensity will vary if the oscillating regime of the material molecules changes.

  7. Signal simulation and signal processing for multiple reference optical coherence tomography

    NASA Astrophysics Data System (ADS)

    Neuhaus, Kai; Subhash, Hrebesh; Dsouza, Roshan; Hogan, Josh; Wilson, Carol; Leahy, Martin

    2015-03-01

    The generation of a synthetic MR-OCT signal is presented and compared to a real acquired signal. Multiple reference optical coherence tomography (MR-OCT) is a novel time-domain interferometric system. The MR-OCT principle is adding a partial mirror to extend the axial scan range, which effectively extends the scan depth for imaging. The actuation of the scan mirror required for time-domain OCT, was demonstrated to operate with a low cost miniature voice coil, such as a speaker extracted from a smartphone or CD/DVD pick-up system. Building a compact and cost-effective optical imaging system will enable affordable medical diagnosis at low-resource setting applications. The partial mirror recirculates multiple reflections (orders) into the interferometric system and the increase of optical path delay does increase the beat frequency of the interference signal. The synthesis of such an interference signal using a numerical method is described in this manuscript.

  8. Neural Correlates for Numerical Processing in the Manual Mode

    ERIC Educational Resources Information Center

    Masataka, Nobuo; Ohnishi, Takashi; Imabayashi, Etsuko; Hirakata, Makiko; Matsuda, Hiroshi

    2006-01-01

    This paper reports a study designed to examine the neuronal correlates for comprehending the signs of American Sign Language representing numerals in deaf signers who acquired Japanese Sign Language as their first language. The participants were scanned by functional magnetic resonance imaging (fMRI) twice on the day of the experiment. The results…

  9. Processes of Sibling Influence in Adolescence: Individual and Family Correlates

    ERIC Educational Resources Information Center

    Whiteman, Shawn D.; Christiansen, Abigail

    2008-01-01

    This study examined the nature and correlates of adolescents' perceptions of sibling influence. Participants included 2 siblings (firstborn age M = 17.34; second-born age M = 14.76 years) from 191 maritally intact families. Adolescents' perceptions of sibling influence were measured via coded responses to open-ended questions about whether their…

  10. 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

  11. A processing circuit for overlapped pulse signals for a thermal neutron coincidence counter.

    PubMed

    Lee, Chul-Yong; Lee, Tae-Hoon; Kim, Ho-Dong

    2009-11-01

    We have developed a processing circuit for overlapped pulse signals. The overlapped pulse signals are generated when the pulse signals of a He-3 detector, by using a neutron coincidence counter, are connected to shift register coincidence electronics by an OR gate device. The developed circuit detects the overlapped pulse signals from among four input signals and produces new 50 ns pulse wide signals. We considered a case where two pulse signals are simultaneously overlapped among four signals. This circuit was tested with an ACP safeguards neutron counter (ASNC) for an advanced spent fuel conditioning process (ACP) and a (252)Cf neutron source at high rates. The loss rate of the output signal was reduced by 1.27% for singles and 4.75% for doubles when compared with the OR gate device. Also the variation for the triples was much bigger. PMID:19692251

  12. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2013-11-01

    Photonic molecules (PMs) based on multiple inner coupled microring resonators allow to surpass the fundamental constraint between the total quality factor (QT), free spectral range (FSR), and resonator size. In this work, we use a PM that presents doublets and triplets resonance splitting, all with high QT. 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.

  14. Laser Doppler anemometer signal processing for blood flow velocity measurements

    NASA Astrophysics Data System (ADS)

    Borozdova, M. A.; Fedosov, I. V.; Tuchin, V. V.

    2015-03-01

    A new method for analysing the signal in a laser Doppler anemometer based on the differential scheme is proposed, which provides the flow velocity measurement in strongly scattering liquids, particularly, blood. A laser Doppler anemometer intended for measuring the absolute blood flow velocity in animal and human near-surface arterioles and venules is developed. The laser Doppler anemometer signal structure is experimentally studied for measuring the flow velocity in optically inhomogeneous media, such as blood and suspensions of scattering particles. The results of measuring the whole and diluted blood flow velocity in channels with a rectangular cross section are presented.

  15. Falling Person Detection Using Multi-Sensor Signal Processing

    NASA Astrophysics Data System (ADS)

    Toreyin, B. Ugur; Soyer, A. Birey; Onaran, Ibrahim; Cetin, E. Enis

    2007-12-01

    Falls are one of the most important problems for frail and elderly people living independently. Early detection of falls is vital to provide a safe and active lifestyle for elderly. Sound, passive infrared (PIR) and vibration sensors can be placed in a supportive home environment to provide information about daily activities of an elderly person. In this paper, signals produced by sound, PIR and vibration sensors are simultaneously analyzed to detect falls. Hidden Markov Models are trained for regular and unusual activities of an elderly person and a pet for each sensor signal. Decisions of HMMs are fused together to reach a final decision.

  16. Fast, optically controlled Kerr phase shifter for digital signal processing.

    PubMed

    Li, R B; Deng, L; Hagley, E W; Payne, M G; Bienfang, J C; Levine, Z H

    2013-05-01

    We demonstrate an optically controlled Kerr phase shifter using a room-temperature 85Rb vapor operating in a Raman gain scheme. Phase shifts from zero to π relative to an unshifted reference wave are observed, and gated operations are demonstrated. We further demonstrate the versatile digital manipulation of encoded signal light with an encoded phase-control light field using an unbalanced Mach-Zehnder interferometer. Generalizations of this scheme should be capable of full manipulation of a digitized signal field at high speed, opening the door to future applications. PMID:23632488

  17. 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.

  18. Charge Correlations and Dynamical Instabilities in the Multifragment Emission Process

    SciTech Connect

    Moretto, L.G.; Rubehn, T.; Phair, L.; Colonna, N.; Wozniak, G.J.; Bowman, D.R.; Peaslee, G.F.; Carlin, N.; de Souza, R.T.; Gelbke, C.K.; Gong, W.G.; Kim, Y.D.; Lisa, M.A.; Lynch, W.; Williams, C.

    1996-09-01

    A new, sensitive method allows one to search for the enhancement of events with nearly equal-sized fragments as predicted by theoretical calculations based on volume or surface instabilities. Simulations have been performed to investigate the sensitivity of the procedure. Experimentally, charge correlations of intermediate mass fragments emitted from heavy ion reactions at intermediate energies have been studied. No evidence for a preferred breakup into equal-sized fragments has been found. {copyright} {ital 1996 The American Physical Society.}

  19. Reconfigurable Optical Signal Processing Based on a Distributed Feedback Semiconductor Optical Amplifier

    PubMed Central

    Li, Ming; Deng, Ye; Tang, Jian; Sun, Shuqian; Yao, Jianping; Azaña, José; Zhu, Ninghua

    2016-01-01

    All-optical signal processing has been considered a solution to overcome the bandwidth and speed limitations imposed by conventional electronic-based systems. Over the last few years, an impressive range of all-optical signal processors have been proposed, but few of them come with reconfigurability, a feature highly needed for practical signal processing applications. Here we propose and experimentally demonstrate an analog optical signal processor based on a phase-shifted distributed feedback semiconductor optical amplifier (DFB-SOA) and an optical filter. The proposed analog optical signal processor can be reconfigured to perform signal processing functions including ordinary differential equation solving and temporal intensity differentiation. The reconfigurability is achieved by controlling the injection currents. Our demonstration provitdes a simple and effective solution for all-optical signal processing and computing. PMID:26813252

  20. Reconfigurable Optical Signal Processing Based on a Distributed Feedback Semiconductor Optical Amplifier

    NASA Astrophysics Data System (ADS)

    Li, Ming; Deng, Ye; Tang, Jian; Sun, Shuqian; Yao, Jianping; Azaña, José; Zhu, Ninghua

    2016-01-01

    All-optical signal processing has been considered a solution to overcome the bandwidth and speed limitations imposed by conventional electronic-based systems. Over the last few years, an impressive range of all-optical signal processors have been proposed, but few of them come with reconfigurability, a feature highly needed for practical signal processing applications. Here we propose and experimentally demonstrate an analog optical signal processor based on a phase-shifted distributed feedback semiconductor optical amplifier (DFB-SOA) and an optical filter. The proposed analog optical signal processor can be reconfigured to perform signal processing functions including ordinary differential equation solving and temporal intensity differentiation. The reconfigurability is achieved by controlling the injection currents. Our demonstration provitdes a simple and effective solution for all-optical signal processing and computing.