Multichannel heterodyning for wideband interferometry, correlation and signal processing
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.
Multichannel heterodyning for wideband interferometry, correlation and signal processing
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.
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.
Task effects on BOLD signal correlates of implicit syntactic processing.
Caplan, David
2010-07-01
BOLD signal was measured in sixteen participants who made timed font change detection judgments in visually presented sentences that varied in syntactic structure and the order of animate and inanimate nouns. Behavioral data indicated that sentences were processed to the level of syntactic structure. BOLD signal increased in visual association areas bilaterally and left supramarginal gyrus in the contrast of sentences with object- and subject-extracted relative clauses without font changes in which the animacy order of the nouns biased against the syntactically determined meaning of the sentence. This result differs from the findings in a non-word detection task (Caplan et al, 2008a), in which the same contrast led to increased BOLD signal in the left inferior frontal gyrus. The difference in areas of activation indicates that the sentences were processed differently in the two tasks. These differences were further explored in an eye tracking study using the materials in the two tasks. Issues pertaining to how parsing and interpretive operations are affected by a task that is being performed, and how this might affect BOLD signal correlates of syntactic contrasts, are discussed. PMID:20671983
Queueing up for enzymatic processing: correlated signaling through coupled degradation
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
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.
Effects of correlated and independent noise on signal processing in neuronal systems
NASA Astrophysics Data System (ADS)
Liu, Feng; Hu, Bambi; Wang, Wei
2001-03-01
Stochastic resonance has recently received considerable attention demonstrating that noise can play a constructive role in signal processing. We investigate the effects of input noise on sensory processing via numerical simulation when they are independent of each other or spatially correlated in a globally coupled neuronal network. The network exhibits a coherent behavior in the absence of stimulation. Such ongoing activity has a remarkable influence on neuronal responses to stimuli. In the presence of a subthreshold periodic signal, the activity averaged over neurons can convey precise information about the stimulus in the case of independent noise. On the other hand, when the noise is correlated among the neurons, the average response is nearly as noisy and variable as the responses of the individual neurons. Thus, the spatially correlated noise diminishes the beneficial effects of pooling, although it can evoke synchronous firings of neurons. These suggest that response variability in cortical activity may be closely related to the correlation in input noise.
David A. Doheny
2004-01-01
Existing opportunities in advanced interceptor, satellite guidance and aircraft navigation technologies, requiring higher signal processing speeds and lower noise environments, are demanding Ring Laser Gyro (RLG) based Inertial Systems to reduce initialization and operational data latency as well as correlated noise magnitudes. Existing signal processing algorithms are often less than optimal when considering these requirements. Advancements in micro-electronic processes have
NASA Technical Reports Server (NTRS)
Casasent, D.
1978-01-01
The article discusses several optical configurations used for signal processing. Electronic-to-optical transducers are outlined, noting fixed window transducers and moving window acousto-optic transducers. Folded spectrum techniques are considered, with reference to wideband RF signal analysis, fetal electroencephalogram analysis, engine vibration analysis, signal buried in noise, and spatial filtering. Various methods for radar signal processing are described, such as phased-array antennas, the optical processing of phased-array data, pulsed Doppler and FM radar systems, a multichannel one-dimensional optical correlator, correlations with long coded waveforms, and Doppler signal processing. Means for noncoherent optical signal processing are noted, including an optical correlator for speech recognition and a noncoherent optical correlator.
Signal Processing: Introduction Digital Signal Processing
Rimon, Elon
Signal Processing: Introduction Digital Signal Processing Introduction Areas of Applications signals and processing #12;Signal Processing: Introduction DSP in various disciplines Communication, Finance ( Economic models, Stock market) and many more #12;Signal Processing: Introduction DSP
David M. Norman
1991-01-01
The application of signal processing technology to conventional weapons systems can lower operator workloads and enhance kill probabilities, while automating wide-area surveillance, target search and classification, target tracking, and aimpoint selection. Immediate opportunities exist for automatic target cueing in underwater and over-the-horizon targeting, as well as for airborne multiple-target fire control. By embedding the transit\\/receive electronics into conformal aircraft sensor
On a nonparametric detection method for array signal processing in correlated noise fields
Petre Stoica; Kon Max Wong; Qiang Wu
1996-01-01
The correct derivation of maximization of the likelihood function is presented, and the correct form of information theoretic criteria (ITC) for the determination of the number of signals in an unknown correlated noise field is shown. The possible pitfalls of using ITC under the circumstances are briefly considered
NASA Astrophysics Data System (ADS)
Norman, David M.
The application of signal processing technology to conventional weapons systems can lower operator workloads and enhance kill probabilities, while automating wide-area surveillance, target search and classification, target tracking, and aimpoint selection. Immediate opportunities exist for automatic target cueing in underwater and over-the-horizon targeting, as well as for airborne multiple-target fire control. By embedding the transit/receive electronics into conformal aircraft sensor arrays, a 'smart' skin can be created. Electronically scanned phased arrays can be used to yield accurate azimuthal and elevation positions while nullifying EW threats. Attention is given to major development thrusts in algorithm design.
Communications, and Signal Processing
Prodić, Aleksandar
Area 4 Control, Communications, and Signal Processing (Sensing, processing, coordination, communications and signal processing is concerned with: · how to sense & process data to produce useful communications ECE 464:Wireless communications ECE 469: Optical comm. & networks Signal processing ECE 431
NASA Astrophysics Data System (ADS)
Kailath, T.
An instructional and reference manual concerning the design and applications of signal processing systems is presented. Among the specific topics addressed are: advanced filter design; speech processing; and communications processing. Attention is also given to: radar and sonar signal processing; image processing; sophisticated analog signal processing devices; and VLSI technologies. The relations between signal processing algorithms, special purpose hardware architectures; and mathematical principles of signal processing techniques are also considered.
Abhayapala, Thushara D.
signals. As well as diversity reception [1], this includes such areas as acoustic systems, fixed in the use of multiple sensors--particularly, multiple antennas for transmission and/or reception of wireless
Signal Processing Information Base
NSDL National Science Digital Library
The Signal Processing Information Base(SPIB) is a project sponsored by the Signal Processing Society and the National Science Foundation. SPIB is a repository of data, papers, software, newsgroups, bibliographies, and addresses of interest to the signal processing community, as well as links to other relevant repositories.
Mechanical Systems Signal Processing
Ray, Asok
Mechanical Systems and Signal Processing Mechanical Systems and Signal Processing 21 (2007) 866 and analytical models. This paper attempts to address this inadequacy by taking advantage of advanced signal processing and pattern recognition tools. Since a vast majority of structural components that are prone
Kosko, Bart
488 IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 59, NO. 2, FEBRUARY 2011 Noise Benefits, Fellow, IEEE Abstract--Quantizer noise can improve statistical signal detec- tion in array- variance symmetric alpha-stable channel noise and for general- ized-Gaussian channel noise. Noise
Speech signal processing research
G. J. Culler; M. McCammon; J. F. McGill; D. E. Taylor; J. M. Vanderford
1978-01-01
Culler\\/Harrison, Inc. has developed a powerful, versatile signal processing capability for ARPA and utilized this capability to perform significant and diverse signal processing experiments. The contract called for construction, operation and maintenance of the CHI SIGNAL SYSTEM, a combination of equipment and software providing a unique marriage of computing power and on-line interactive control of that power. The system has
Speech signal processing research
G. J. Culler; M. McCammon; J. F. McGill; D. E. Taylor; J. M. Vanderford
1975-01-01
During this period, Culler\\/Harrison, Inc. has developed a powerful, versatile signal processing capability for ARPA and utilized this capability to perform significant and diverse signal processing experiments. The contract called for construction, operation and maintenance of the CHI SIGNAL SYSTEM, a combination of equipment and software providing a unique marriage of computing power and on-line interactive control of that power.
NSDL National Science Digital Library
Digital signal processing is a technique that uses digital methods to process signals. Processing a signal means manipulating it to improve it, change it, or alter it as required for some application. Some examples of processes are filtering, modulation and demodulation, mixing, spectrum analysis, compression and decompression, and many others. In the past, most of these processes have been accomplished with analog techniques and circuits. Today, that has changed. While analog processing has not disappeared, it is slowly being replaced by digital processing in most applications. DSP is now used in almost all electronic equipment and knowledge of its operation is critical to an overall knowledge and understanding of electronics. In digital processing, the analog signal to be processed is first converted to digital then processing is done by a computer. The computer output is then converted back to analog. This module describes this process and outlines the most common applications.
Signal Processing:Fourier Signal Processing:Fourier
Rimon, Elon
Signal Processing:Fourier #12;Signal Processing:Fourier Fourier methods · Continous signals FS) signals DFS Discrete Fourier Series DFT Discrete Fourier Transform #12;Signal Processing:Fourier #12;Signal Processing:Fourier #12;Signal Processing:Fourier Example: The square wave For this case ao = 0
Integrated Signal Processing and Signal Understanding 1
Massachusetts at Amherst, University of
Integrated Signal Processing and Signal Understanding 1 Victor Lesser, Hamid Nawab y , Malini standing of Signals, which permits sophisticated interaction between theorybased problem solving in signal processing and heuristic problemsolving in signal interpretation. The need for such a paradigm arises
Integrated Signal Processing and Signal Understanding1
Massachusetts at Amherst, University of
Integrated Signal Processing and Signal Understanding1 Victor Lesser, Hamid Nawaby, Malini Bhandaru- standing of Signals, which permits sophisticated interaction between theory-based problem solving in signal processing and heuristic problem-solving in signal interpretation. The need for such a paradigm arises
Copyright 2002 S. K. Mitra1 Signals and Signal ProcessingSignals and Signal Processing
Boato, Giulia
Copyright © 2002 S. K. Mitra1 Signals and Signal ProcessingSignals and Signal Processing · Signals play an important role in our daily life · A signal is a function of independent variables such as time, distance, position, temperature, and pressure · Some examples of typical signals are shown next #12
Hybrid photonic signal processing
NASA Astrophysics Data System (ADS)
Ghauri, Farzan Naseer
This thesis proposes research of novel hybrid photonic signal processing systems in the areas of optical communications, test and measurement, RF signal processing and extreme environment optical sensors. It will be shown that use of innovative hybrid techniques allows design of photonic signal processing systems with superior performance parameters and enhanced capabilities. These applications can be divided into domains of analog-digital hybrid signal processing applications and free-space---fiber-coupled hybrid optical sensors. The analog-digital hybrid signal processing applications include a high-performance analog-digital hybrid MEMS variable optical attenuator that can simultaneously provide high dynamic range as well as high resolution attenuation controls; an analog-digital hybrid MEMS beam profiler that allows high-power watt-level laser beam profiling and also provides both submicron-level high resolution and wide area profiling coverage; and all optical transversal RF filters that operate on the principle of broadband optical spectral control using MEMS and/or Acousto-Optic tunable Filters (AOTF) devices which can provide continuous, digital or hybrid signal time delay and weight selection. The hybrid optical sensors presented in the thesis are extreme environment pressure sensors and dual temperature-pressure sensors. The sensors employ hybrid free-space and fiber-coupled techniques for remotely monitoring a system under simultaneous extremely high temperatures and pressures.
Signals and Images Image processing
Lakey, Joseph D.
Signals and Images Wavelets Image processing Models and Approximations Data driven approximations;Signals and Images Wavelets Image processing Models and Approximations Data driven approximations or transcendental: Joe Lakey Wavelets Minimize Max #12;Signals and Images Wavelets Image processing Models
signal processing and oral communication
Penn, Gerald
SPOClab signal processing and oral communication Computational Linguistics, 5 December 2012 Frank University of Toronto #12;SPOClab signal processing and oral communication An introduction to SPOClab · SPOClab (Signal Processing and Oral Communication) is a new lab intersecting Computer Science
NASA Astrophysics Data System (ADS)
McWhirter, John G.
1989-12-01
The potential application of parallel computing techniques to digital signal processing for radar is discussed and two types of regular array processor are discussed. The first type of processor is the systolic or wavefront processor. The application of this type of processor to adaptive beamforming is discussed and the joint STL-RSRE adaptive antenna processor test-bed is reviewed. The second type of regular array processor is the SIMD parallel computer. One such processor, the Mil-DAP, is described, and its application to a varied range of radar signal processing tasks is discussed.
Armin Bruderlin; Lance Williams
1995-01-01
Techniques from the image and signal processing domain can be successfully applied to designing, modifying, and adapting ani- mated motion. For this purpose, we introduce multiresolution mo- tion filtering, multitarget motion interpolation with dynamic time- warping, waveshaping and motion displacement mapping. The techniques are well-suited for reuse and adaptation of existing mo- tion data such as joint angles, joint coordinates
Optimum combining of residual carrier array signals in correlated noises
NASA Technical Reports Server (NTRS)
Liang, R.; Suen, P. H.; Tan, H. H.
1996-01-01
An array feed combining system for the recovery of signal-to-noise ratio (SNR) loss due to antenna reflector deformation has been implemented and is currently being evaluated on the Jet Propulsion Laboratory 34-m DSS-13 antenna. The current signal-combining system operates under the assumption that the white Gaussian noise processes in the received signals from different array elements are mutually uncorrelated. However, experimental data at DSS 13 indicate that these noise processes are indeed mutually correlated. The objective of this work is to develop a signal-combining system optimized to account for the mutual correlations between these noise processes. The set of optimum combining weight coefficients that maximizes the combined signal SNR in the correlated noises environment is determined. These optimum weights depend on unknown signal and noise covariance parameters. A maximum-likelihood approach is developed to estimate these unknown parameters to obtain estimates of the optimum weight coefficients based on residual carrier signal samples. The actual combined signal SNR using the estimated weight coefficients is derived and shown to converge to the maximum achievable SNR as the number of signal samples increases. These results are also verified by simulation. A numerical example shows a significant improvement in SNR performance can be obtained, especially when the amount of correlation increases.
Multidimensional signal processing for ultrasonic signal classification
NASA Astrophysics Data System (ADS)
Kim, J.; Ramuhalli, P.; Udpa, L.; Udpa, S.
2001-04-01
Neural network based signal classification systems are being used increasingly in the analysis of large volumes of data obtained in NDE applications. One example is in the interpretation on ultrasonic signals obtained from inspection of welds where signals can be due to porosity, slag, lack of fusion and cracks in the weld region. Standard techniques rely on differences in individual A-scans to classify the signals. This paper proposes an ultrasonic signal classification technique based on the information in a group of signals and examining the statistical characteristics of the signals. The method was 2-dimensional signal processing algorithms to analyze the information in B- and B'-scan images. In this paper, 2-dimensional transform based coefficients of the images are used as features and a multilayer perceptron is used to classify them. These results are then combined to get the final classification for the inspected region. Results of applying the technique to data obtained from the inspection of welds are presented.
Nanotubes for noisy signal processing
NASA Astrophysics Data System (ADS)
Lee, Ian Yenyin
Nanotubes can process noisy signals. We present two central results in support of this general thesis and make an informed extrapolation that uses nanotubes to improve body armor. The first result is that noise can help nanotubes detect weak signals. The finding confirmed a stochastic-resonance theoretical prediction that noise can enhance detection at the nano-level. Laboratory experiments with nanotubes showed that three types of noise improved three measures of detection. Small amounts of Gaussian, uniform, and Cauchy additive white noise increased mutual-information, cross-correlation, and bit-error-rate measures before degrading them with further increases in noise. Nanotubes can apply this noise-enhancement and nanotube electrical and mechanical properties to improve signal processing. Similar noise enhancement may benefit a proposed nanotube-array cochlear-model spectral processing. The second result is that nanotube antennas can directly detect narrowband electromagnetic (EM) signals. The finding showed that nanotube and thin-wire dipoles are similar: They are resonant and narrowband and can implement linear-array designs if the EM waves in the nanotubes propagate at or near the free-space velocity of light. The nanotube-antenna prediction is based on a Fresnel-zone or near-zone analysis of antenna impedance using a quantum-conductor model. The analysis also predicts a failure to resonate if the nanotube EM-wave propagation is much slower than free-space light propagation. We extrapolate based on applied and theoretical analysis of body armor. Field experiments used a baseball comparison and statistical and other techniques to model body-armor bruising effects. A baseball comparison showed that a large caliber handgun bullet can hit an armored chest as hard as a fast baseball can hit a bare chest. Adaptive fuzzy systems learned to predict a bruise profile directly from the experimental data and also from statistical analysis of the data. Nanotube signal processing should help disguise armor by adapting camouflage to match changing backgrounds while nanotube additives should strengthen armor materials.
Digital signal processing the Tevatron BPM signals
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.
Signal Processing: Signals The characterization as well as analysis methods
Rimon, Elon
Signal Processing: Signals SIGNALS The characterization as well as analysis methods depends on the signal structure. The following are some classification possibilities. Deterministic vs. random Transient vs. continuous Stationary vs. nonstationary In practice we often encounter combinations of signal
Partial likelihood for signal processing
Tülay Adali; Hongmei Ni
2003-01-01
We present partial likelihood (PL) as an effective means for developing nonlinear techniques for signal processing. Posing signal processing problems in a likelihood setting provides a number of advantages, such as allowing the use of powerful tools in statistics and easy incorporation of model order\\/complexity selection into the problem by use of appropriate information-theoretic criteria. However, likelihood formulations in most
Secrecy extraction from no-signaling correlations
Scarani, Valerio; Gisin, Nicolas; Brunner, Nicolas; Masanes, Lluis; Pino, Sergi; Acin, Antonio [Group of Applied Physics, University of Geneva, 20, rue de l'Ecole-de-Medecine, CH-1211 Geneva 4 (Switzerland); School of Mathematics, University of Bristol, Bristol BS8 1TW (United Kingdom); ICFO--Institut de Ciencies Fotoniques, Mediterranean Technology Park, 08860 Castelldefels, Barcelona (Spain)
2006-10-15
Quantum cryptography shows that one can guarantee the secrecy of correlation on the sole basis of the laws of physics, that is, without limiting the computational power of the eavesdropper. The usual security proofs suppose that the authorized partners, Alice and Bob, have a perfect knowledge and control of their quantum systems and devices; for instance, they must be sure that the logical bits have been encoded in true qubits and not in higher dimensional systems. In this paper, we present an approach that circumvents this strong assumption. We define protocols, both for the case of bits and for generic d-dimensional outcomes, in which the security is guaranteed by the very structure of the Alice-Bob correlations, under the no-signaling condition. The idea is that if the correlations cannot be produced by shared randomness, then Eve has poor knowledge of Alice's and Bob's symbols. The present study assumes on the one hand that the eavesdropper Eve performs only individual attacks (this is a limitation to be removed in further work), and on the other hand that Eve can distribute any correlation compatible with the no-signaling condition (in this sense her power is greater than what quantum physics allows). Under these assumptions, we prove that the protocols defined here allow extracting secrecy from noisy correlations, when these correlations violate a Bell-type inequality by a sufficiently large amount. The region in which secrecy extraction is possible extends within the region of correlations achievable by measurements on entangled quantum states.
Nonlinear Transfer of Signal and Noise Correlations in Cortical Networks
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
Multichannel Signal Processing
MICHAEL L. HONIG; KENNETH STEIGLITZ; B. GOPINATH
Abstruct- We consider transmission of data over multiple coupled channels, such as bundles of twisted-pair copper wires in the local sub- scriber loop, and between central offices in the public switched tele- phone network. Transceiver designs for such channels typically treat the crosstalk between adjacent twisted pairs as random noise uncorrelated with the transmitted signal. We propose a transmitterheceiver pair
Method of single-fiber multimode interferometer speckle signal processing
Yuri N. Kulchin; Oleg B. Vitrik; Oleg V. Kirichenko; Oleg T. Kamenev; Yuri S. Petrov; Oleg G. Maksayev
1996-01-01
A method of correlation processing of speckle-signals formed by multimode interferometer is theoretically and experimentally investigated. The method permits to transform modulation of a speckle-pattern to optical or electrical signal, which linear depends on correlation coefficient of reference and current speckle patterns. The functional dependence of correlation coefficient from value of lengthening of interferometer is studied. The results allow to
Nanotubes for noisy signal processing
Ian Yenyin Lee
2005-01-01
Nanotubes can process noisy signals. We present two central results in support of this general thesis and make an informed extrapolation that uses nanotubes to improve body armor. The first result is that noise can help nanotubes detect weak signals. The finding confirmed a stochastic-resonance theoretical prediction that noise can enhance detection at the nano-level. Laboratory experiments with nanotubes showed
CONTROL, COMMUNICATION & SIGNAL PROCESSING (CCSP)
Liebling, Michael
1 CONTROL, COMMUNICATION & SIGNAL PROCESSING (CCSP) Department of Electrical & Computer Engineering courses and a thesis · In the CCSP area you are required to choose 4 major area courses and 2 minor area
CONTROL, COMMUNICATION & SIGNAL PROCESSING (CCSP)
Akhmedov, Azer
CONTROL, COMMUNICATION & SIGNAL PROCESSING (CCSP) Department of Electrical & Computer Engineering · In the CCSP area you are required to choose 4 major area courses and 2 minor area courses Department
Signal Processing: Modal Analysis Analytical and Experimental
Rimon, Elon
Signal Processing: Modal Analysis Analytical and Experimental Modal Analysis #12;Signal Processing: Modal Analysis #12;Signal Processing: Modal Analysis #12;Signal Processing: Modal Analysis 21222312222 f( && && && & & & )N(f)N(x)NN(c)NN(m 11 ×××× General: #12;Signal Processing: Modal Analysis Undamped system: [c] = 0
System for monitoring non-coincident, nonstationary process signals
Gross, Kenneth C.; Wegerich, Stephan W.
2005-01-04
An improved system for monitoring non-coincident, non-stationary, process signals. The mean, variance, and length of a reference signal is defined by an automated system, followed by the identification of the leading and falling edges of a monitored signal and the length of the monitored signal. The monitored signal is compared to the reference signal, and the monitored signal is resampled in accordance with the reference signal. The reference signal is then correlated with the resampled monitored signal such that the reference signal and the resampled monitored signal are coincident in time with each other. The resampled monitored signal is then compared to the reference signal to determine whether the resampled monitored signal is within a set of predesignated operating conditions.
Biomedical signal and image processing.
Cerutti, Sergio; Baselli, Giuseppe; Bianchi, Anna; Caiani, Enrico; Contini, Davide; Cubeddu, Rinaldo; Dercole, Fabio; Rienzo, Luca; Liberati, Diego; Mainardi, Luca; Ravazzani, Paolo; Rinaldi, Sergio; Signorini, Maria; Torricelli, Alessandro
2011-01-01
Generally, physiological modeling and biomedical signal processing constitute two important paradigms of biomedical engineering (BME): their fundamental concepts are taught starting from undergraduate studies and are more completely dealt with in the last years of graduate curricula, as well as in Ph.D. courses. Traditionally, these two cultural aspects were separated, with the first one more oriented to physiological issues and how to model them and the second one more dedicated to the development of processing tools or algorithms to enhance useful information from clinical data. A practical consequence was that those who did models did not do signal processing and vice versa. However, in recent years,the need for closer integration between signal processing and modeling of the relevant biological systems emerged very clearly [1], [2]. This is not only true for training purposes(i.e., to properly prepare the new professional members of BME) but also for the development of newly conceived research projects in which the integration between biomedical signal and image processing (BSIP) and modeling plays a crucial role. Just to give simple examples, topics such as brain–computer machine or interfaces,neuroengineering, nonlinear dynamical analysis of the cardiovascular (CV) system,integration of sensory-motor characteristics aimed at the building of advanced prostheses and rehabilitation tools, and wearable devices for vital sign monitoring and others do require an intelligent fusion of modeling and signal processing competences that are certainly peculiar of our discipline of BME. PMID:21642032
Optical Network Reconfiguration for Signal Processing Applications
Chamberlain, Roger
Optical Network Reconfiguration for Signal Processing Applications Roger D. Chamberlain Mark Reconfiguration for Signal Processing Applications," in Proc. of the IEEE International Conference on Application Reconfiguration for Signal Processing Applications Roger Chamberlain, Mark Franklin, and Praveen Krishnamurthy
Alpha-Stable Distributions in Signal Processing of Audio Signals
Mosegaard, Klaus
Alpha-Stable Distributions in Signal Processing of Audio Signals Preben Kidmose, Department of Mathematical Modelling, Section for Digital Signal Processing, Technical University of Denmark, Building 321 the applicability of stable distributions in audio processing, a classical problem from statistical signal
Java Digital Signal Processing Editor
NSDL National Science Digital Library
Professor Andreas Spanias of Arizona State University has supervised the development of this online digital signal processing (DSP) system simulation utility. This utility has many functions that allow the user to generate various signals, create filters, and analyze the responses. Other functions include Fourier Transforms, convolution, autocorrelation, and several speech processing tools. The interface is well designed and easy to use, and there are plenty of examples and documentation. However, some features are missing from it, such as the ability to print and save. The software is still being improved, though, so these problems might be fixed in the future.
Superconductive wideband analog signal correlator with buffered digital output
Green, J.B.; Anderson, A.C.; Withers, R.S.
1988-01-01
Analog superconductive components were integrated to form a device capable of cross correlation between two wideband analog input signals. Arrays of Nb/Nb/sub 2/O/sub 5//Pb tunnel junctions perform the mixing of delayed samples of two frequency-offset analog signals counterpropagating along a niobium-tapped transmission line. The resultant mixer products from the junction array are integrated and stored in a high-Q lumped element L-C resonator tuned to the signal difference frequency. A superconductive tunnel junction imbedded in the resonator circuit is operated as a variable threshold comparator to detect the time-integrated current stored in the resonator. Results are presented showing the correlation properties of such an individual correlator cell, together with the design and performance of a 4-junction-logic (4JL)-based digital address encoder to be used in a multichannel correlator device. The authors also discuss the important design issues as they relate to analog signal processing.
Signal Processing in Cognitive Radio
Jun Ma; Geoffrey Ye Li; Biing Hwang Juang
2009-01-01
Cognitive radio allows for usage of licensed frequency bands by unlicensed users. However, these unlicensed (cognitive) users need to monitor the spectrum continuously to avoid possible interference with the licensed (primary) users. Apart from this, cognitive radio is expected to learn from its surroundings and perform functions that best serve its users. Such an adaptive technology naturally presents unique signal-processing
High-Resolution Signal Processing
Nehorai, Arye
the head, respectively. This electromagnetic field is generated by neuronal activity in the brain of the brain. Arrays of EEG and MEG sensors measure electric potential on the scalp and magnetic field around signal processing is indeed recognized in such fields as astronomy, radar, sonar, seismology
Multirate signal processing in Ptolemy
J. Buck; S. Ha; E. A. Lee; D. G. Messerschmitt
1991-01-01
The use of two models of computation, synchronous dataflow (SDF) and dynamic dataflow (DDF), to design and implement signal processing applications with multiple sample rates is discussed. The SDF model is used for synchronous applications. SDF is amenable to compile-time scheduling, and hence is much more efficient at runtime. The design environment, Ptolemy, can simultaneously support multiple models of computation,
Signal processing for photovoltaic applications
S. Buddha; H. Braun; V. Krishnan; C. Tepedelenlioglu; A. Spanias; T. Yeider; T. Takehara
2012-01-01
The need for the usage of signal processing and pattern recognition techniques to monitor photovoltaic (PV) arrays and to detect and respond to faults with minimal human involvement is increasing. The data obtained from the array can be used to dynamically modify the array topology and improve array power output. This is beneficial especially when module mismatches such as shading,
Multiresolution signal processing for meshes
Igor Guskov; Wim Sweldens; Peter Schröder
1999-01-01
Abstract We generalize basic signal processing tools such as downsampling, upsampling, and filters to irregular connectivity triangle meshes This is accomplished through the design of a non - uniform relax - ation procedure whose weights depend on the geometry and we show its superiority over existing schemes whose weights depend only on connectivity This is combined with known mesh simpli
Introduction to Video Signal Processing
Yang, Shih-Hsuan
, video on demand, video surveillance, DVD, DV, digital VCR (DVR), ... Limitation: bandwidth TwoIntroduction to Video Signal Processing Shih-Hsuan Yang CSIE Department, NTUT #12;Contents Digital Multimedia Digital Video Human Visual Characteristics Color Spaces Video Compression 2 #12;Digital Multimedia
VLSI mixed signal processing system
NASA Astrophysics Data System (ADS)
Alvarez, A.; Premkumar, A. B.
An economical and efficient VLSI implementation of a mixed signal processing system (MSP) is presented in this paper. The MSP concept is investigated and the functional blocks of the proposed MSP are described. The requirements of each of the blocks are discussed in detail. A sample application using active acoustic cancellation technique is described to demonstrate the power of the MSP approach.
VLSI mixed signal processing system
NASA Technical Reports Server (NTRS)
Alvarez, A.; Premkumar, A. B.
1993-01-01
An economical and efficient VLSI implementation of a mixed signal processing system (MSP) is presented in this paper. The MSP concept is investigated and the functional blocks of the proposed MSP are described. The requirements of each of the blocks are discussed in detail. A sample application using active acoustic cancellation technique is described to demonstrate the power of the MSP approach.
EEG Correlates of Self-Referential Processing
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
ECE 468 Digital Signal Processing 1. History
Chen, Ying "Ada"
, digital image processing, signal processing for communications, biomedical signal processing, seismic data processing, etc. · DSP is not confined to 1D signals. Sometimes 2D, 3D or 4D signals. · Until recently by the heart are measured. 3 #12;Digital imaging: sp.cs.tut.fi/ Apart from those mentioned above, digital
Adaptive Fuzzy Systems for Multichannel Signal Processing
Plataniotis, Konstantinos N.
Adaptive Fuzzy Systems for Multichannel Signal Processing KONSTANTINOS N. PLATANIOTIS, MEMBER, IEEE Processing multichannel signals using digital signal process- ing techniques has received increased attention beginning in this area and 2) to provide a review for the reader who may be well versed in signal processing
The Numerical Tours of Signal Processing
Paris-Sud XI, Université de
1 The Numerical Tours of Signal Processing Advanced Computational Signal and Image Processing Gabriel Peyr´e Abstract The Numerical Tours of Signal Processing is an online collection of tutorials to learn advanced computational signal and image processing. These tours allow one to follow a step by step
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.
LSI's for digital signal processing
NORIHIKO OHWADA; TADAKATSU KIMURA; MASANOBU DOKEN
1979-01-01
This paper describes high-performance CMOS LSI's for digital signal-processing (DSP) technology, such as digital filter, fast Fourier transform (FFT), discrete Fourier transform (DFT), and digital phase-locked loop (DPLL). First, DSP functions for communication use, functional blocks to compose DSP functions, and the types of arithmetic for LSI are discussed. It is explained that multiplier (MPL), variable-length shift register (VSR), and
Computational Aspects in Statistical Signal Processing
Kundu, Debasis
14 Computational Aspects in Statistical Signal Processing D. Kundu 14.1 Introduction Signal such as communi- cations, radio location of objects, seismic signal processing and computer assisted medical diagnosis. Statistical signal processing is also used in many physical science applications
Detection of partially correlated signals in clutter using a multichannel model-based approach
James H. Michels; Griffiss AFB
1992-01-01
The author considers the Gaussian multichannel binary detection problem in which the signal and nonwhite clutter noise are Gaussian vector processes with unknown statistics. A generalized likelihood ratio using multichannel innovation processes is implemented via a model-based approach where the signal and clutter are assumed to be characterized by autoregressive vector processes with arbitrary temporal and cross-channel correlation. The innovations
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.
Subsurface conductive isolation of refraction correlative magnetic signals (SCIRCMS)
Erck, Eric Stephenson
2004-11-15
Isolation of terrestrially-observed magnetic signals by restoring their diffusive loss due to subsurface electrical conductivity sufficiently correlates these signals with those derived from the Alfven ionospheric electron ...
Nuclear sensor signal processing circuit
Kallenbach, Gene A. (Bosque Farms, NM); Noda, Frank T. (Albuquerque, NM); Mitchell, Dean J. (Tijeras, NM); Etzkin, Joshua L. (Albuquerque, NM)
2007-02-20
An apparatus and method are disclosed for a compact and temperature-insensitive nuclear sensor that can be calibrated with a non-hazardous radioactive sample. The nuclear sensor includes a gamma ray sensor that generates tail pulses from radioactive samples. An analog conditioning circuit conditions the tail-pulse signals from the gamma ray sensor, and a tail-pulse simulator circuit generates a plurality of simulated tail-pulse signals. A computer system processes the tail pulses from the gamma ray sensor and the simulated tail pulses from the tail-pulse simulator circuit. The nuclear sensor is calibrated under the control of the computer. The offset is adjusted using the simulated tail pulses. Since the offset is set to zero or near zero, the sensor gain can be adjusted with a non-hazardous radioactive source such as, for example, naturally occurring radiation and potassium chloride.
Statistical Signal Processing Debasis Kundu 1
Kundu, Debasis
Statistical Signal Processing Debasis Kundu 1 Signal processing may broadly be considered to involve the recovery of information from physical observations. The received signals is usually disturbed by thermal, electrical, at- mospheric or intentional interferences. Due to the random nature of the signal
A digital signal processing approach to interpolation
RONALD W. SCHAFER; LAWRENCE R. RABINER
1973-01-01
In many digital signal precessing systems, e.g., vacoders, modulation systems, and digital waveform coding systems, it is necessary to alter the sampling rate of a digital signal Thus it is of considerable interest to examine the problem of interpolation of bandlimited signals from the viewpoint of digital signal processing. A frequency dmnain interpretation of the interpolation process, through which it
Quasi-optimal signal processing in ground Forward Scattering Radar
Cheng Hu; M. Antoniou; M. Cherniakov; V. Sizov
2008-01-01
A signal processing algorithm for ground target detection using forward scattering radar (FSR) is presented in this paper. The effectiveness of the algorithm is shown using both simulated and experimental data. The algorithm is based on the matched filtering approach, where the correlation between the received signal and a set of pre-defined reference functions is calculated. The maximum of the
Signal Processing for Phased Array Feeds in Radio Astronomical Telescopes
Brian D. Jeffs; Karl F. Warnick; Jonathan Landon; Jacob Waldron; David Jones; J. Richard Fisher; Roger D. Norrod
2008-01-01
Relative to traditional waveguide feeds, phased array feeds (PAFs) for radio telescopes can increase the instrument field of view and sky survey speed. Unique challenges associated with PAF observations, including extremely low signal levels, long-term system gain stability requirements, spatially correlated noise due to mutual coupling, and tight beamshape tolerances, require the development of new array signal processing techniques for
Array signal processing for a wireless MEM sensor network
K. Yao; R. E. Hudson; C. W. Reed; D. Chen; T. L. Tung; F. Lorenzelli
1998-01-01
We first review the high-level signal processing architecture of a wireless MEM sensor system for source detection, signal enhancement, localization, and identification. A blind beamformer using only the measured data of randomly distributed sensors to form a sample correlation matrix is proposed. The maximum power collection criterion is used to obtain array weights from the dominant eigenvector of the sample
Stochastic Search for Signal Processing Algorithm Optimization
Stochastic Search for Signal Processing Algorithm Optimization Bryan Singer Manuela Veloso May address the complex task of signal processing optimization. We first introduce and discuss the complexities of this domain. In general, a single signal processing algorithm can be represented by a very
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.
Moura, José
3572 IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 56, NO. 8, AUGUST 2008 Algebraic Signal, IEEE Abstract--This paper introduces a general and axiomatic ap- proach to linear signal processing (SP) that we refer to as the al- gebraic signal processing theory (ASP). Basic to ASP is the linear signal
Theoretical analysis and optimization of CDS signal processing method for CCD image sensors
Jaroslav Hynecek
1992-01-01
The correlated double sampling (CDS) signal processing method used in processing of video signals from CCD image sensors is theoretically analyzed. The CDS signal processing is frequency used to remove noise, which is generated by the reset operation of the floating diffusion charge detection node, from the signal. The derived formulas for the noise power spectral density provide an invaluable
NASA Technical Reports Server (NTRS)
Ibrahim, K. M.; Wertheimer, G. D.; Bachalo, William D.
1991-01-01
The relative performance of current methods used for estimating the phase and the frequency in LDV and phase Doppler applications in low signal to noise ratio conditions is analyzed. These methods include the Fourier analysis and the correlation techniques. Three methods that use the correlation function for frequency and phase estimations are evaluated in terms of accuracy and speed of processing. These methods include: (1) the frequency estimation using zero crossings counting of the auto-correlation function, (2) the Blackman-Tukey method, and (3) the AutoRegressive method (AR). The relative performance of these methods is evaluated and compared with the Fourier analysis method which provides the optimum performance in terms of the Maximum Likelihood (ML) criteria.
Wavelets and Signal Processing John E. Gilbert
Wavelets and Signal Processing John E. Gilbert Mathematics in Science Lecture April 30, 2002. #12 of wavelets came from seismology, physics, and signal process- ing as much as from mathematics itself. In turn will describe some basic wave- let ideas and how they can be used in signal analysis and data detection
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.
In the Spotlight: Biomedical Signal Processing
Sergio Cerutti
2008-01-01
This article presents a review on biomedical signal processing. Discussions on traditional approaches, nonstationary and nonlinear systems, signal fusion, physiological modeling, and the MMM (multivariate, multiorgan and multiscale) paradigm are included.
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.
Correlation of signals of thermal acoustic radiation
NASA Astrophysics Data System (ADS)
Anosov, A. A.; Passechnik, V. I.
2003-03-01
The spatial correlation function is measured for the pressure of thermal acoustic radiation from a source (a narrow plasticine plate) whose temperature is made both higher and lower than the temperature of the receiver. The spatial correlation function of the pressure of thermal acoustic radiation is found to be oscillatory in character. The oscillation amplitude is determined not by the absolute temperature of the source but by the temperature difference between the source and the receiver. The correlation function changes its sign when a source heated with respect to the receiver is replaced by a cooled one.
A signal oriented stream processing system for pipeline monitoring
Tokmouline, Timur
2006-01-01
In this thesis, we develop SignalDB, a framework for composing signal processing applications from primitive stream and signal processing operators. SignalDB allows the user to focus on the signal processing task and avoid ...
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…
Signal processing and analyzing works of art
NASA Astrophysics Data System (ADS)
Johnson, Don H.; Johnson, C. Richard, Jr.; Hendriks, Ella
2010-08-01
In examining paintings, art historians use a wide variety of physico-chemical methods to determine, for example, the paints, the ground (canvas primer) and any underdrawing the artist used. However, the art world has been little touched by signal processing algorithms. Our work develops algorithms to examine x-ray images of paintings, not to analyze the artist's brushstrokes but to characterize the weave of the canvas that supports the painting. The physics of radiography indicates that linear processing of the x-rays is most appropriate. Our spectral analysis algorithms have an accuracy superior to human spot-measurements and have the advantage that, through "short-space" Fourier analysis, they can be readily applied to entire x-rays. We have found that variations in the manufacturing process create a unique pattern of horizontal and vertical thread density variations in the bolts of canvas produced. In addition, we measure the thread angles, providing a way to determine the presence of cusping and to infer the location of the tacks used to stretch the canvas on a frame during the priming process. We have developed weave matching software that employs a new correlation measure to find paintings that share canvas weave characteristics. Using a corpus of over 290 paintings attributed to Vincent van Gogh, we have found several weave match cliques that we believe will refine the art historical record and provide more insight into the artist's creative processes.
Ultrasonic Signal Processing for Structural Health Monitoring
Jennifer E. Michaels; Thomas E. Michaels
2004-01-01
Permanently mounted ultrasonic sensors are a key component of systems under development for structural health monitoring. Signal processing plays a critical role in the viability of such systems due to the difficulty in interpreting signals received from structures of complex geometry. This paper describes a differential feature-based approach to classifying signal changes as either ``environmental'' or ``structural''. Data are presented
Ultrasonic Signal Processing for Structural Health Monitoring
Jennifer E. Michaels; Thomas E. Michaels
2004-01-01
Permanently mounted ultrasonic sensors are a key component of systems under development for structural health monitoring. Signal processing plays a critical role in the viability of such systems due to the difficulty in interpreting signals received from structures of complex geometry. This paper describes a differential feature-based approach to classifying signal changes as either “environmental” or “structural”. Data are presented
IEEE TRANSACTIONS ON SIGNAL PROCESSING 0 IEEE TRANSACTIONS ON SIGNAL PROCESSING 1
Ghrist, Robert W.
IEEE TRANSACTIONS ON SIGNAL PROCESSING 0 1 #12;IEEE TRANSACTIONS ON SIGNAL PROCESSING 1 Topological localization via signals of opportunity Michael Robinson(1), Member, IEEE, Robert Ghrist(2) Abstract--We consider the problems of localization, disam- biguation, and mapping in a domain filled with signals
An object-oriented signal processing environment: The knowledge-based signal processing package
NASA Astrophysics Data System (ADS)
Dove, W. P.; Myers, C.; Milios, E. E.
1984-10-01
A LISP-based signal processing package for integrated numeric and symbolic manipulation of discrete-time signals is described. The package is based on the concept of signal abstraction in which a signal is defined by its non-zero domain and by a method for computing its samples. Most common signal processing operations are defined in the package and the package provides simple methods for the definition of new operators. The package provides facilities for the manipulation of infinite duration signals and periodic signals, for the efficient computation of signals over intervals, and for the catching of signal values. The package is currently being expanded to provide for manipulation of continuous-time signals and symbolic signal transformations, such as the Fourier transform, to form the basis of knowledge-based signal processing systems.
Bistatic SAR: Signal Processing and Image Formation.
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.
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.
Spatiological processes in intracellular signalling Michael Fisher
Malcolm, Grant
capabilities suggestive information processing activities. first sections this paper we selectively reviewBioSystems 55 (2000) Spatiological processes in intracellular signalling Michael Fisher a Grant. Recent findings from experimental biology indicate that many intracellular signalling systems show a high
Adaptive fuzzy systems for multichannel signal processing
KONSTANTINOS N. PLATANIOTIS; DIMITRIOS ANDROUTSOS; ANASTASIOS N. VENETSANOPOULOS
1999-01-01
Processing multichannel signals using digital signal processing techniques has received increased attention lately due to its importance in applications such as multimedia technologies and telecommunications. The objective of this paper is twofold: 1) to introduce adaptive filtering techniques to the reader who is just beginning in this area and 2) to provide a review for the reader who may be
Periodically correlated processes and their stationary dilations
NASA Technical Reports Server (NTRS)
Miamee, A. G.
1988-01-01
An explicit form for a stationary dilation for periodically correlated random processes is obtained. This is then used to give spectral conditions for a periodically correlated process to be non-deterministic, purely deterministic, minimal, and to have a positive angle between its past and future.
Correlating Notch Signaling with Thymocyte Maturation
Michael L Deftos; Ethan W Ojala; Michael J Bevan
1998-01-01
The Notch receptor and its ligands are involved in many developmental processes. They are highly expressed in the thymus and have been implicated in the CD4 versus CD8 lineage decision. We identified the constitutively active intracellular fragment of murine Notch-1 as capable of rendering thymomas resistant to glucocorticoid-induced apoptosis. This effect was confirmed in other T cell lines and in
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.
Transmit signal design for optimal estimation of correlated MIMO channels
Jayesh H. Kotecha; Akbar M. Sayeed
2004-01-01
We address optimal estimation of correlated multiple-input multiple-output (MIMO) channels using pilot signals, assuming knowledge of the second-order channel statistics at the transmitter. Assuming a block fading channel model and minimum mean square error (MMSE) estimation at the receiver, we design the transmitted signal to optimize two criteria: MMSE and the conditional mutual information between the MIMO channel and the
Study of a class of non-Gaussian signal processing problems
C. H. Chen
1980-01-01
A broad spectrum of correlated problem areas in nonGaussian signal processing is discussed. These include: (1) nonlinear adaptive procedures to assess their detection performance against transient signals; (2) nonlinear spectral analysis techniques such as the Maximum Entropy Spectral Analysis (MESA) and the Maximum Likelihood Method (MLM) to assess their detection performance against transient signals; (3) techniques for weak signal extraction
Signal/noise optimization strategies for stochastically estimated correlation functions
William Detmold; Michael G. Endres
2014-09-19
Numerical studies of quantum field theories usually rely upon an accurate determination of stochastically estimated correlation functions in order to extract information about the spectrum of the theory and matrix elements of operators. The reliable determination of such correlators is often hampered by an exponential degradation of signal/noise at late time separations. We demonstrate that it is sometimes possible to achieve significant enhancements of signal/noise by appropriately optimizing correlators with respect to the source and sink interpolating operators, and highlight the large range of possibilities that are available for this task. The ideas are discussed for both a toy model, and single hadron correlators in the context of quantum chromodynamics.
Demodulation signal processing in multiphoton imaging
Walter G. Fisher; Eric A. Wachter; David W. Piston
2002-01-01
Multiphoton laser scanning microscopy offers numerous advantages, but sensitivity can be seriously affected by contamination from ambient room light. Typically, this forces experiments to be performed in an absolutely dark room. Since mode-locked lasers are used to generate detectable signals, signal-processing can be used to avoid such problems by taking advantage of the pulsed characteristics of such lasers. Demodulation of
Networking Services: Signaling, QoS, Processing
Ning, Peng
Networking Services: Signaling, QoS, Processing Harry Perros Networking Apps What's behind your "Rebuffering"? ! In this book, the author unravels the mysteries of the signaling protocols that enables us and senior undergraduate students in computer science and computer engineering, and also a reference book
Detection of anomalous signals in temporally correlated data (Invited)
NASA Astrophysics Data System (ADS)
Langbein, J. O.
2010-12-01
Detection of transient tectonic signals in data obtained from large geodetic networks requires the ability to detect signals that are both temporally and spatially coherent. In this report I will describe a modification to an existing method that estimates both the coefficients of temporally correlated noise model and an efficient filter based on the noise model. This filter, when applied to the original time-series, effectively whitens (or flattens) the power spectrum. The filtered data provide the means to calculate running averages which are then used to detect deviations from the background trends. For large networks, time-series of signal-to-noise ratio (SNR) can be easily constructed since, by filtering, each of the original time-series has been transformed into one that is closer to having a Gaussian distribution with a variance of 1.0. Anomalous intervals may be identified by counting the number of GPS sites for which the SNR exceeds a specified value. For example, during one time interval, if there were 5 out of 20 time-series with SNR>2, this would be considered anomalous; typically, one would expect at 95% confidence that there would be at least 1 out of 20 time-series with an SNR>2. For time intervals with an anomalously large number of high SNR, the spatial distribution of the SNR is mapped to identify the location of the anomalous signal(s) and their degree of spatial clustering. Estimating the filter that should be used to whiten the data requires modification of the existing methods that employ maximum likelihood estimation to determine the temporal covariance of the data. In these methods, it is assumed that the noise components in the data are a combination of white, flicker and random-walk processes and that they are derived from three different and independent sources. Instead, in this new method, the covariance matrix is constructed assuming that only one source is responsible for the noise and that source can be represented as a white-noise random-number generator convolved with a filter whose spectral properties are frequency (f) independent at its highest frequencies, 1/f at the middle frequencies, and 1/f2 at the lowest frequencies. For data sets with no gaps in their time-series, construction of covariance and inverse covariance matrices is extremely efficient. Application of the above algorithm to real data potentially involves several iterations as small, tectonic signals of interest are often indistinguishable from background noise. Consequently, simply plotting the time-series of each GPS site is used to identify the largest outliers and signals independent of their cause. Any analysis of the background noise levels must factor in these other signals while the gross outliers need to be removed.
Didactic Platform for Biomedical Signal Processing: Digital Image Processing
E E de Souza; F M de Azevedo; J Marino-Neto
Recent studies about Biomedical Engineering issues, which are subjects offered in Electrical Engineering under- graduate courses in Brazil, have shown a great lack of investment in this field. That was the main motivation in devel- oping a Didactic Platform for Biomedical Signal Processing (DPBSP) which consists in a generalized and modular biomedical acquisition board, software to visualize and processing signals
Signal processing during and across saccades
Lidewij L. van Duren; Andries F. Sanders
1995-01-01
Visual perceptual processing has been found to occur exclusively during fixations of the eye (Sanders and Houtmans, 1985; Sanders and Rath, 1991). Does fixation time also reflect postperceptual processes such as target classification and response selection as well, or can these processes continue during a saccade? In a series of experiments on this question two signals were presented at an
Nonlinear signal processing applied to telecommunications
Kouroupetroglou, Georgios
Nonlinear signal processing applied to telecommunications Diamantis Kotoulas National. Nonlinear behaviour appears in almost all digital commu- nication systems, such as satellite systems be developed that tackle nonlinear system characteristics. An- other important issue in studying both linear
MMI Devices for Photonic Signal Processing
Laurence W. Cahill; Thanh Trung Le
2007-01-01
Low order MMI (multimode interference) devices are now being employed as integrated components of photonic filter circuits such as ring resonators. This paper examines further possible applications of MMI devices in photonic signal processing.
Optical signal processing using nonlinear fibers
Shigeki Watanabe; F. Futami
2002-01-01
Ultra-fast optical signal processing is a promising technology for future photonic networks. This paper describes possible\\u000a applications of nonlinear fibers to optical signal processing. The third-order optical nonlinearities in a fiber are discussed\\u000a by analyzing the interaction of co-propagating optical waves. The properties of a nonlinear fiber are then considered in terms\\u000a of optimizing the dispersion for achieving phase matching
Optical signal processing using nonlinear fibers
Shigeki Watanabe
2006-01-01
Ultra-fast optical signal processing is a promising technology for future photonic networks. This paper describes possible\\u000a applications of nonlinear fibers to optical signal processing. The third-order optical nonlinearities in a fiber are discussed\\u000a by analyzing the interaction of co-propagating optical waves. The properties of a nonlinear fiber are then considered in terms\\u000a of optimizing the dispersion for achieving phase matching
Biosignals: PsychoPhysio-Signal Processing concept
J. Rafiee; M. A. Rafiee; N. Prause
2009-01-01
This paper introduces the concept of PsychoPhysio-Signal processing (PPSP), which may partially combine psychology (e.g. psycho-physiology, neuro-psychology), urology, bio- engineering, applied mathematics (e.g. data analysis), and signal processing techniques to be helpful for design, model, manufacture, and analyze of theoretical and experimental systems for (human) sexual behaviors. For example, a real-time system is introduced to automatically detect movement artifacts existing
Non-commutative tomography and signal processing
NASA Astrophysics Data System (ADS)
Vilela Mendes, R.
2015-06-01
Non-commutative tomography is a technique originally developed and extensively used by Professors M A Man’ko and V I Man’ko in quantum mechanics. Because signal processing deals with operators that, in general, do not commute with time, the same technique has a natural extension to this domain. Here, a review is presented of the theory and some applications of non-commutative tomography for time series as well as some new results on signal processing on graphs.
Processing signals the optical way
J. Hecht
1983-01-01
The applications, techniques, and results of some uses of optical processing systems, as alternatives to analog and digital systems, are explored. Optical systems can be configured to perform mathematical operations on light passing through them, such as occurs in slide projectors, microscopes, and refracting telescopes. Fourier transformations can be carried out with a single lens, and reversed to obtain a
Signal Processing for Audio HCI
Dmitry N. Zotkin; Ramani Duraiswami
\\u000a This chapter reviews recent advances in computer audio processing from the viewpoint of improving the human-computer interface.\\u000a Microphone arrays are described as basic tools for untethered audio acquisition, and principles for the synthesis of realistic\\u000a virtual audio are outlined. The influence of room acoustics on audio acquisition and production is also considered. The chapter\\u000a finishes with a review of several
Signal Processing Model for Radiation Transport
Chambers, D H
2008-07-28
This note describes the design of a simplified gamma ray transport model for use in designing a sequential Bayesian signal processor for low-count detection and classification. It uses a simple one-dimensional geometry to describe the emitting source, shield effects, and detector (see Fig. 1). At present, only Compton scattering and photoelectric absorption are implemented for the shield and the detector. Other effects may be incorporated in the future by revising the expressions for the probabilities of escape and absorption. Pair production would require a redesign of the simulator to incorporate photon correlation effects. The initial design incorporates the physical effects that were present in the previous event mode sequence simulator created by Alan Meyer. The main difference is that this simulator transports the rate distributions instead of single photons. Event mode sequences and other time-dependent photon flux sequences are assumed to be marked Poisson processes that are entirely described by their rate distributions. Individual realizations can be constructed from the rate distribution using a random Poisson point sequence generator.
Digital signal processor and programming system for parallel signal processing
Van den Bout, D.E.
1987-01-01
This thesis describes an integrated assault upon the problem of designing high-throughput, low-cost digital signal-processing systems. The dual prongs of this assault consist of: (1) the design of a digital signal processor (DSP) which efficiently executes signal-processing algorithms in either a uniprocessor or multiprocessor configuration, (2) the PaLS programming system which accepts an arbitrary algorithm, partitions it across a group of DSPs, synthesizes an optimal communication link topology for the DSPs, and schedules the partitioned algorithm upon the DSPs. The results of applying a new quasi-dynamic analysis technique to a set of high-level signal-processing algorithms were used to determine the uniprocessor features of the DSP design. For multiprocessing applications, the DSP contains an interprocessor communications port (IPC) which supports simple, flexible, dataflow communications while allowing the total communication bandwidth to be incrementally allocated to achieve the best link utilization. The net result is a DSP with a simple architecture that is easy to program for both uniprocessor and multi-processor modes of operation. The PaLS programming system simplifies the task of parallelizing an algorithm for execution upon a multiprocessor built with the DSP.
Kaplan, Alexander
Analysis of cross-correlations in electroencephalogram signals as an approach to proactive on structure functions and power spectum estimates, to study the clinical electroencephalogram (EEG) signals-correlations, Electroencephalogram signals, Schizophrenia 1. Introduction The objective diagnosis of psychiatric disorders
Gossip Algorithms for Distributed Signal Processing
Alexandros G. Dimakis; Soummya Kar; José M. F. Moura; Michael G. Rabbat; Anna Scaglione
2010-01-01
Gossip algorithms are attractive for in-network processing in sensor networks because they do not require any specialized routing, there is no bottleneck or single point of failure, and they are robust to unreliable wireless network conditions. Recently, there has been a surge of activity in the computer science, control, signal processing, and information theory communities, developing faster and more robust
Haotic, Fractal, and Nonlinear Signal Processing. Proceedings
Katz, R.A. [Naval Undersea Warfare Center, Newport, RI (United States)
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)
Neural Correlates of Cognitive Processes LIDA Module
Memphis, University of
Neural Correlates of Cognitive Processes LIDA Module or Function Cognitive Processes Neural medial neurons Keene et al. 2006. Slipnet emotion nodes PAM-Emotions amygdala and orbito-frontal cortex PAM-emotion affecting learning basolateral amygdala, perirhinal cortex, entorhinal cortex Paz et al
Process Correlation Analysis Model for Process Improvement Identification
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
WAVELET TRANSFORMS FOR NONLINEAR SIGNAL PROCESSING Robert Nowak
WAVELET TRANSFORMS FOR NONLINEAR SIGNAL PROCESSING Robert Nowak Michigan State University East describe two new structures for nonlinear signal processing. The new structures simplify the analy- sis cients. While most existing approaches to nonlinear signal processing characterize the nonlinearity
STARCON -A Reconfigurable Fieldable Signal Processing Scott Brandt
Brandt, Scott A.
1 STARCON - A Reconfigurable Fieldable Signal Processing System Scott Brandt Theseus Research, Inc. John Budenske Alliant Techsystems Inc. Abstract Conventional fieldable signal processing systems utilize custom hardware manufactured and configured specifically for a single signal processing
ULTRASONIC SIGNAL PROCESSING FOR STRUCTURAL HEALTH MONITORING
Jennifer E. Michaels; Thomas E. Michaels
ABSTRACT. Permanently ,mounted ,ultrasonic sensors are a key ,component ,of systems ,under development,for structural health monitoring. Signa l processing plays a critical role in the viability of such systems ,due ,to the ,difficulty in interpreting signals ,received from ,structures of complex geometry. This paper describes a differential feature-based approach,to classifying signal changes,as either “environmental” or “structural”. Data ,are presented from
Correlated activity supports efficient cortical processing
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
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.
Methodological Framework for Estimating the Correlation Dimension in HRV Signals
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
Methodological framework for estimating the correlation dimension in HRV signals.
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
Hemodynamic signals correlate tightly with synchronized gamma oscillations.
Niessing, Jörn; Ebisch, Boris; Schmidt, Kerstin E; Niessing, Michael; Singer, Wolf; Galuske, Ralf A W
2005-08-01
Functional imaging methods monitor neural activity by measuring hemodynamic signals. These are more closely related to local field potentials (LFPs) than to action potentials. We simultaneously recorded electrical and hemodynamic responses in the cat visual cortex. Increasing stimulus strength enhanced spiking activity, high-frequency LFP oscillations, and hemodynamic responses. With constant stimulus intensity, the hemodynamic response fluctuated; these fluctuations were only loosely related to action potential frequency but tightly correlated to the power of LFP oscillations in the gamma range. These oscillations increase with the synchrony of synaptic events, which suggests a close correlation between hemodynamic responses and neuronal synchronization. PMID:16081740
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.
Xin, Jack
Ear Modeling and Sound Signal Processing Jack Xin Abstract Ear modeling can significantly improve sound signal processing and the design of hearing devices. Ear models based on mechanics and neu- ral phenomenology of the inner ear (cochlea) form a class of nonlinear nonlocal dispersive partial differential
Wavelength-domain RF photonic signal processing
NASA Astrophysics Data System (ADS)
Gao, Lu
This thesis presents a novel approach to RF-photonic signal processing applications based on wavelength-domain optical signal processing techniques using broadband light sources as the information carriers, such as femtosecond lasers and white light sources. The wavelength dimension of the broadband light sources adds an additional degree of freedom to conventional optical signal processing systems. Two novel wavelength-domain optical signal processing systems are presented and demonstrated in this thesis. The first wavelength-domain RF photonic signal processing system is a wavelength-compensated squint-free photonic multiple beam-forming system for wideband RF phased-array antennas. Such a photonic beam-forming system employs a new modulation scheme developed in this thesis, which uses traveling-wave tunable filters to modulate wideband RF signals onto broadband optical light sources in a frequency-mapped manner. The wavelength dimension of the broadband light sources provides an additional dimension in the wavelength-compensated Fourier beam-forming system for mapping the received RF frequencies to the linearly proportional optical frequencies, enabling true-time-delay beam forming, as well as other novel RF-photonic signal processing functions such as tunable filtering and frequency down conversion. A new slow-light mechanism, the SLUGGISH light, has also been discovered with an effective slow-light velocity of 86 m/s and a record time-bandwidth product of 20. Experimental demonstration of true-time-delay beam forming based on the SLUGGISH light effect has also been presented in this thesis. In the second wavelength-domain RF photonic signal processing system, the wavelength dimension increases the information carrying capacity by spectrally multiplexing multiple wavelength channels in a wavelength-division-multiplexing fiber-optic communication system. A novel ultrafast all-optical 3R (Re-amplification, Retiming, Re-shaping) wavelength converter based on interactions between (3+1)-D optical solitons has been developed and demonstrated numerically in this thesis, which can exchange information between different wavelength channels and enhance the network maneuverability. Dispersion management for the generation of (3+1)-D optical solitons using a pair of negative dispersive mirrors is proposed and demonstrated. An ultrafast all-optical wavelength converter based on the dragging interaction between light bullets with different colors is presented, which features a compact size of 100mumx 100mumx 1mm, an ultra-high conversion speed of over 1 TB/s, and a wavelength conversion range of more than 50 nm.
Cross-frequency Doppler sensitive signal processing
NASA Astrophysics Data System (ADS)
Wagstaff, Ronald A.
2005-04-01
When there is relative motion between an acoustic source and a receiver, a signal can be Doppler shifted in frequency and enter or leave the processing bins of the conventional signal processor. The amount of the shift is determined by the frequency and the rate of change in the distance between the source and the receiver. This frequency Doppler shifting can cause severe reductions in the processors performance. Special cross-frequency signal processing algorithms have recently been developed to mitigate the effects of Doppler. They do this by using calculation paths that cut across frequency bins in order to follow signals during frequency shifting. Cross-frequency spectral grams of a fast-flying sound source were compared to conventional grams, to evaluate the performance of this new signal processing method. The Doppler shifts in the data ranged up to 70 contiguous frequency bins. The resulting cross-frequency grams showed that three paths provided small to no improvement. Four paths showed improvements for either up-frequency or down-frequency shifting, but not for both. Two paths showed substantial improvement for both up-frequency and down-frequency shifting. The cross-frequency paths will be defined, and comparisons between conventional and cross-frequency grams will be presented. [Work supported by Miltec Corporation.
Guang-Ming Zhang; David M. Harvey
2012-01-01
Various signal processing techniques have been used for the enhancement of defect detection and defect characterisation. Cross-correlation, filtering, autoregressive analysis, deconvolution, neural network, wavelet transform and sparse signal representations have all been applied in attempts to analyse ultrasonic signals. In ultrasonic nondestructive evaluation (NDE) applications, a large number of materials have multilayered structures. NDE of multilayered structures leads to some
Guang-Ming Zhang; David M. Harvey
2011-01-01
Various signal processing techniques have been used for the enhancement of defect detection and defect characterisation. Cross-correlation, filtering, autoregressive analysis, deconvolution, neural network, wavelet transform and sparse signal representations have all been applied in attempts to analyse ultrasonic signals. In ultrasonic nondestructive evaluation (NDE) applications, a large number of materials have multilayered structures. NDE of multilayered structures leads to some
Processing in the Encrypted Domain using a Composite Signal Representation
Processing in the Encrypted Domain using a Composite Signal Representation Tiziano Bianchi1 , Thijs on encrypted signals via parallel processing and to reduce the size of the encrypted signals. Though many of the most common signal processing operations can be applied to composite signals, some operations require
Array signal processing using GARCH noise modeling
Hadi Amiri; Hamidreza Amindavar; Rodney Lynn Kirlin
2004-01-01
We propose a new method for modeling practical non-Gaussian and non-stationary noise in array signal processing. GARCH (generalized autoregressive conditional heteroscedasticity) models are introduced as the feasible model for the heavy tailed probability density functions (PDFs) and time varying variances of stochastic processes. We use the GARCH noise model in the maximum likelihood approach for the estimation of directions-of-arrival (DOAs).
Technical applications of acoustoopic signal processing units
Milos Klima; E. Kostal
1992-01-01
The authors consider the basic ideas of acoustooptic signal processing where an acoustooptic unit is used as a spatial modulator. The selection of applications is oriented for the purposes of the security technology. Some experimental results based upon mercurous halides are summarized. These experimentally verified bulk acoustooptic units have been applied as a part of a model of a spectrum
MEDICAL SIGNAL PROCESSING USING THE SOFTWARE MONITOR
L.' Parassenko; N. Townsend; G. Clifford; L. Mason; J. Burton; J. Price
The Software Monitor is a portable PC which is capable of processing and analysing in real time the vital physiological signals recorded non-invasively from healthy subjects or unwell hospital patients. Its main advantage is that it offers, in one intelligent monitor, the fusion of multiple sources of information. This makes it possible to track physiological instability (since unexpected combinations of
Adaptive signal processing in medical ultrasound beamforming
Francesco Viola; William F. Walker
2005-01-01
For over thirty years adaptive beamforming (AB) algorithms have been applied in RADAR and SONAR signal processing. Higher resolution and contrast is attainable using those algorithms at the price of an increased computational load. In this paper we consider four beamformers (BFs): Frost BF, Duvall BF, SSB, and SPOC. These algorithms are well know in the RADAR\\/SONAR literature. We have
Lightwave Neuromorphic Signal Processing [In The Spotlight
Mable P. Fok; David Rosenbluth; Konstantin Kravtsov; Paul R. Prucnal
2010-01-01
This article discusses a technique that promises to deliver improved optical computing. Specifically, neuromorphic engineering that can inspire novel optical computing devices. Neuromorphic engineering aims to develop practical computing and signal processing devices based on an understanding of the biophysics of neuronal computation.
Parallel Architecture for Universal Digital Signal Processing
Vijay K. Jaint; Hiroomi Hikawat
1994-01-01
The paper describes a parallel architecture for universal digital signal processing. This architecture uses not only multiply-accumulate but also nonlinear operations, such as reciprocal, squareroot, exponential, sine\\/cosine, etc. Several advanced algorithms can thus be mapped to this array architecture. Specifically, the paper focuses attention on two very diverse algorithms, namely the fast Fourier transform and the matrix LU decomposition. Only
Review of biomedical signal and image processing
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.
Call for Papers IEEE Signal Processing Society
Nehorai, Arye
· Interferometry, optical systems, multi-function operations, impulsive systems, tomography and SAR · PolarimetryCall for Papers IEEE Signal Processing Society Special Issue on Adaptive Waveform Design for Agile have to be optimally and adaptively integrated with electromagnetic phenomenology and other available
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.
International Conference on Signal Processing and Communications
Sharma, Vinod
for researchers from academia, research laboratories, and industries to come together to share and learn about-Time Signal Processing Cognitive Radio Network Coding Information Theory Coding for Data Communications Communications Smart Grid Physical Layer Security Prospective authors are invited to submit full-length (up
Electromagnetics-Related Aspects of Signaling and Signal Processing for UWB Short Range Radios*
Southern California, University of
Electromagnetics-Related Aspects of Signaling and Signal Processing for UWB Short Range Radios* A in electromagnetic-related aspects of UWB signaling schemas and signal processing. First, pulse shaping is developed in both the transmitter and receiver, and signal processing at the receiver end. To create efficient
Signal and Image Processing with Sinlets
Alexander Y. Davydov
2012-09-17
This paper presents a new family of localized orthonormal bases - sinlets - which are well suited for both signal and image processing and analysis. One-dimensional sinlets are related to specific solutions of the time-dependent harmonic oscillator equation. By construction, each sinlet is infinitely differentiable and has a well-defined and smooth instantaneous frequency known in analytical form. For square-integrable transient signals with infinite support, one-dimensional sinlet basis provides an advantageous alternative to the Fourier transform by rendering accurate signal representation via a countable set of real-valued coefficients. The properties of sinlets make them suitable for analyzing many real-world signals whose frequency content changes with time including radar and sonar waveforms, music, speech, biological echolocation sounds, biomedical signals, seismic acoustic waves, and signals employed in wireless communication systems. One-dimensional sinlet bases can be used to construct two- and higher-dimensional bases with variety of potential applications including image analysis and representation.
Intelligent processing of ultrasonic signals for process control applications
Grabec, I.; Grabec, D. (Univ. of Ljubljana, (Slovenia). Dept. of Physics); Sachse, W. (Cornell Univ., Ithaca, NY (United States). Dept. of Theoretical and Applied Sciences)
1993-10-01
The authors review here some of the approaches that have been used to apply intelligent, neural-like signal processing procedures to solve a number of acoustic emission (AE) and active ultrasonic (UT) process control measurement problems which can be expected to have important process control applications. Characteristics of these approaches is the use of a set of learning signals from an array of sensors to develop a memory containing prototypical pattern vectors composed of acoustic data and process characteristics. This memory can subsequently be utilized to process signals to optimally recover parameters of the manufacturing process. Approaches applicable for linear and non-linear problems have been developed. For the latter, algorithms implementing a multi-layered, feed-forward neural network or alternatively, a non-parametric, multi-dimensional regression approach called an automatic modeler have been developed. Here they illustrate this modeler by its application to characterize a drilling process and to recognize the finish of surfaces from the signals generated using a tactile sensor.
A Signal Processing Approach To Fair Surface Design Charles Robertson
Kazhdan, Michael
A Signal Processing Approach To Fair Surface Design Slide 1 Charles Robertson A Signal Processing: Charles Robertson A Signal Processing Approach To Fair Surface Design Slide 2 Charles Robertson Overview Introduction Fairing Subdivision Constraints Conclusions A Signal Processing Approach To Fair Surface Design
Call For Papers IEEE Transactions on Signal Processing
Sřrensen, Michael
Call For Papers IEEE Transactions on Signal Processing Special Issue on Signal Processing of packet networking offers a wide range of problems for which signal processing can provide elegant larger than their intersection. On one hand, we solicit papers from researchers in signal process- ing
Signal/noise enhancement strategies for stochastically estimated correlation functions
William Detmold; Michael G. Endres
2014-08-19
We develop strategies for enhancing the signal/noise ratio for stochastically sampled correlation functions. The techniques are general and offer a wide range of applicability. We demonstrate the potential of the approach with a generic two-state system, and then explore the practical applicability of the method for single hadron correlators in lattice quantum chromodynamics. In the latter case, we determine the ground state energies of the pion, proton, and delta baryon, as well as the ground and first excited state energy of the rho meson using matrices of correlators computed on an exemplary ensemble of anisotropic gauge configurations. In the majority of cases, we find a modest reduction in the statistical uncertainties on extracted energies compared to conventional variational techniques. However, in the case of the delta baryon, we achieve a factor of three reduction in statistical uncertainties. The variety of outcomes achieved for single hadron correlators illustrates an inherent dependence of the method on the properties of the system under consideration and the operator basis from which the correlators are constructed.
Electron correlation in an Auger process
Doering, J.P. (Department of Chemistry, Johns Hopkins University, Baltimore, Maryland 21218 (USA)); Coplan, M.A.; Cooper, J.W. (Institute for Physical Science and Technology, University of Maryland, College Park, Maryland 20742 (USA)); Moore, J.H. (Department of Chemistry and Biochemistry, University of Maryland, College Park, Maryland 20742 (USA))
1990-01-01
Coincident 205-eV electrons resulting from the double ionization of argon by electron impact have been measured for incident energies from 400 to 2200 eV. The two 205-eV electrons are produced by knockout of an argon 2{ital p} electron followed by 205-eV {ital LMM} Auger decay of the 2{ital p} vacancy. The cross section near threshold is an order of magnitude larger than at higher energies. In addition, an angular correlation is observed for low incident energies. The two electrons are emitted preferentially at a large angle to each other. The results suggest strong electron correlation in this process.
Interpretation of AMS-02 results: correlations among dark matter signals
Simone, Andrea De [CERN, Theory Division, CH-1211 Geneva 23 (Switzerland); Riotto, Antonio [Département de Physique Théorique and Centre for Astroparticle Physics (CAP), 24 quai E. Ansermet, CH-1211 Geneva (Switzerland); Xue, Wei, E-mail: andrea.desimone@sissa.it, E-mail: antonio.riotto@unige.ch, E-mail: wei.xue@sissa.it [SISSA, via Bonomea 265, I-34136 Trieste (Italy)
2013-05-01
The AMS-02 collaboration has recently released data on the positron fraction e{sup +}/(e{sup ?}+e{sup +}) up to energies of about 350 GeV. If one insists on interpreting the observed excess as a dark matter signal, then we find it is best described by a TeV-scale dark matter annihilating into ?{sup +}?{sup ?}, although this situation is already severely constrained by gamma-ray measurements.The annihilation into ?{sup +}?{sup ?} is allowed by gamma-rays more than ?{sup +}?{sup ?}, but it gives a poorer fit to AMS-02 data. Moreover, since electroweak corrections induce correlations among the fluxes of stable particles from dark matter annihilations, the recent AMS-02 data imply a well-defined prediction for the correlated flux of antiprotons. Under the assumption that their future measurements will not show any antiproton excess above the background, the dark matter interpretation of the positron rise will possibly be ruled out by only making use of data from a single experiment. This work is the first of a program where we emphasize the role of correlations among dark matter signals.
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.
C. Schutte; P. Rademeyer
1992-01-01
In focal plane signal processing applications it is imperative to minimize noise in the associated input circuit. The latter usually consists of MOS transistor preamplifiers and multiplexers. This paper concentrates on the 1\\/f noise generation in NMOS input signal processing circuits. A 1\\/f noise model for the subthreshold region is derived and correlated with 1\\/f noise measurements of NMOS transistors.
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.
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.
Mixed Signal Learning by Spike Correlation Propagation in Feedback Inhibitory Circuits
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
Signal Processing Track Assoc. Prof. idem Erolu Erdem
Ünay, Devrim
02.05.2013 1 Signal Processing Track Assoc. Prof. Çidem Erolu Erdem Bahçeehir University Department://staff.eng.bahcesehir.edu.tr/~cigdemeroglu What is a signal? Signals are functions of time or space, that usually carry information. For example: Electrical signals: voltages or currents in a circuit Acoustic signals: audio or speech signals (analog
Neural Correlates of Subliminal Language Processing
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
Macrocell design for concurrent signal processing
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.
Optical signal processing with magnetostatic waves
A. D. Fisher
1985-01-01
Magneto-optical devices based on Bragg diffraction of light by magnetostatic waves (MSWs) 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
Differential algorithms of digital signal processing
W. A. Pogribny
2010-01-01
Ageneral approach to constructing differential algorithms of digital signal processing (DSP) which contain the corresponding\\u000a transformation functions is provided. As an example the discrete Fourier transform algorithms, implemented using this approach,\\u000a and some derivative algorithms-Hartley transform, short-time Fourier transform and lapped transform, cosine transform, and\\u000a Mellin, Hilbert and wavelet transforms are presented. The use of these algorithms allows increasing efficiency
A PLATFORM FOR COLLABORATIVE ACOUSTIC SIGNAL PROCESSING
Hanbiao Wang; Lewis Girod; Nithya Ramanathan; Deborah Estrin; Kung Yao
In this paper, we present a platform for collaborative acoustic signal processing, and demonstrate its use with an example appli- cation. Our platform is built upon the Stargate Linux-based micro- server, and supports synchronized multi-channel acoustic data ac- quisition. We implement a dataflow-like staged event-driven pro- gramming model within the Emstar software framework that sim- plifies the development of collaborative
Digital signal processing for beam position feedback
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.
Optical fiber delay-line signal processing
K. P. Jackson; B. Moslehi; C. C. Cutler; J. W. Goodman; H. J. Shaw; S. A. Newton; M. Tur
1985-01-01
Single-mode optical fiber is an attractive delay medium for processing microwave frequency signals due to its extremely low loss (less than 0.1 dB\\/microsec) and large available time-bandwidth product (in excess of 100,000). Progress in the efficient tapping of light from single-mode fibers has made it possible to construct recirculating and nonrecirculating (tapped) delay-line structures that can perform a variety of
Correlation Between Eddy Current Signal Noise and Peened Surface Roughness
Wendt, S. E.; Hentscher, S. R.; Raithel, D. C.; Nakagawa, N. [Center for NDE, Iowa State University, Ames, IA 50011 (United States)
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.
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.
C language algorithms for digital signal processing
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.
Stergios Stergiopoulos; D. R. Munn; Nikitas Nikitakos
1998-01-01
This paper deals with the development of a processing technique that improves the signal-to-noise ratio (SNR) at the single sensor for a received signal that is embedded in a partially correlated noise field. The approach of this study is unique in that the noise is treated as being non-white and partially correlated. The concept of the proposed development is based
Exploiting parallelism within multidimensional multirate digital signal processing systems
Peng, Dongming
2004-09-30
The intense requirements for high processing rates of multidimensional Digital Signal Processing systems in practical applications justify the Application Specific Integrated Circuits designs and parallel processing ...
Hybrid integrated optic modules for real-time signal processing
NASA Astrophysics Data System (ADS)
Tsai, C. S.
1984-03-01
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.
Signal processing and tracking of arrivals in ocean acoustic tomography.
Dzieciuch, Matthew A
2014-11-01
The signal processing for ocean acoustic tomography experiments has been improved to account for the scattering of the individual arrivals. The scattering reduces signal coherence over time, bandwidth, and space. In the typical experiment, scattering is caused by the random internal-wave field and results in pulse spreading (over arrival-time and arrival-angle) and wander. The estimator-correlator is an effective procedure that improves the signal-to-noise ratio of travel-time estimates and also provides an estimate of signal coherence. The estimator-correlator smoothes the arrival pulse at the expense of resolution. After an arrival pulse has been measured, it must be associated with a model arrival, typically a ray arrival. For experiments with thousands of transmissions, this is a tedious task that is error-prone when done manually. An error metric that accounts for peak amplitude as well as travel-time and arrival-angle can be defined. The Viterbi algorithm can then be adapted to the task of automated peak tracking. Repeatable, consistent results are produced that are superior to a manual tracking procedure. The tracking can be adjusted by tuning the error metric in logical, quantifiable manner. PMID:25373953
Radar transponder apparatus and signal processing technique
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.
Radar transponder apparatus and signal processing technique
Axline, Jr., Robert M. (Albuquerque, NM); Sloan, George R. (Albuquerque, NM); Spalding, Richard E. (Albuquerque, NM)
1996-01-01
An active, phase-coded, time-grating transponder and a synthetic-aperture radar (SAR) and signal processor means, in combination, allow the recognition and location of the transponder (tag) in the SAR image and allow communication of information messages from the transponder to the SAR. The SAR is an illuminating radar having special processing modifications in an image-formation processor to receive an echo from a remote transponder, after the transponder receives and retransmits the SAR illuminations, and to enhance the transponder's echo relative to surrounding ground clutter by recognizing special transponder modulations from phase-shifted from the transponder retransmissions. The remote radio-frequency tag also transmits information to the SAR through a single antenna that also serves to receive the SAR illuminations. Unique tag-modulation and SAR signal processing techniques, in combination, allow the detection and precise geographical location of the tag through the reduction of interfering signals from ground clutter, and allow communication of environmental and status information from said tag to be communicated to said SAR.
Radar transponder apparatus and signal processing technique
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.
Unique portable signal acquisition/processing station
Garron, R.D.; Azevedo, S.G.
1983-05-16
At Lawrence Livermore National Laboratory, there are experimental applications requiring digital signal acquisition as well as data reduction and analysis. A prototype Signal Acquisition/Processing Station (SAPS) has been constructed and is currently undergoing tests. The system employs an LSI-11/23 computer with Data Translation analog-to-digital hardware. SAPS is housed in a roll-around cart which has been designed to withstand most subtle EMI/RFI environments. A user-friendly menu allows a user to access powerful data acquisition packages with a minimum of training. The software architecture of SAPS involves two operating systems, each being transparent to the user. Since this is a general purpose workstation with several units being utilized, an emphasis on low cost, reliability, and maintenance was stressed during conception and design. The system is targeted for mid-range frequency data acquisition; between a data logger and a transient digitizer.
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.
A Signal Processing Model of Quantum Mechanics
Chris Thron; Johnny Watts
2012-05-08
This paper develops a deterministic model of quantum mechanics as an accumulation-and-threshold process. The model arises from an analogy with signal processing in wireless communications. Complex wavefunctions are interpreted as expressing the amplitude and phase information of a modulated carrier wave. Particle transmission events are modeled as the outcome of a process of signal accumulation that occurs in an extra (non-spacetime) dimension. Besides giving a natural interpretation of the wavefunction and the Born rule, the model accommodates the collapse of the wave packet and other quantum paradoxes such as EPR and the Ahanorov-Bohm effect. The model also gives a new perspective on the 'relational' nature of quantum mechanics: that is, whether the wave function of a physical system is "real" or simply reflects the observer's partial knowledge of the system. We simulate the model for a 2-slit experiment, and indicate possible deviations of the model's predictions from conventional quantum mechanics. We also indicate how the theory may be extended to a field theory.
An Introduction to Signal Processing in Chemical Analysis
NSDL National Science Digital Library
Professor Tom O'Haver
This 26-page illustrated introduction to digital signal processing in chemical analysis covers signal arithmetic, signals and noise, smoothing, differentiation, resolution enhancement, harmonic analysis, convolution, deconvolution, Fourier filter, integration and peak area measurement, and curve fitting. It is accompanied by signal processing software for Macintosh with reference manual and tutorial (available for free download), video demonstrations, and Matlab signal processing modules for Mac, PC, and Unix.
Array signal processing: DOA estimation for missing sensors
Lalita Gupta; R. P. Singh
2010-01-01
Array signal processing involves signal enumeration and source localization. Array signal processing is centered on the ability to fuse temporal and spatial information captured via sampling signals emitted from a number of sources at the sensors of an array in order to carry out a specific estimation task: source characteristics (mainly localization of the sources) and\\/or array characteristics (mainly array
Digital Complex Signal Processing Techniques for Impulse Radio
Mike Shuo-wei Chen; Robert W. Brodersen
2006-01-01
This paper describes the digital complex signal processing techniques for a pulse-based UWB radio. The pro- posed baseband is essential to fully exploit the wideband signal characteristics as well as compensating the analog front-end impairments. The property and optimal usage of these signal pro- cessing blocks are analyzed for both data detection and precision ranging applications. The same signal processing
Inertial processing of vestibulo-ocular signals
NASA Technical Reports Server (NTRS)
Hess, B. J.; Angelaki, D. E.
1999-01-01
New evidence for a central resolution of gravito-inertial signals has been recently obtained by analyzing the properties of the vestibulo-ocular reflex (VOR) in response to combined lateral translations and roll tilts of the head. It is found that the VOR generates robust compensatory horizontal eye movements independent of whether or not the interaural translatory acceleration component is canceled out by a gravitational acceleration component due to simultaneous roll-tilt. This response property of the VOR depends on functional semicircular canals, suggesting that the brain uses both otolith and semicircular canal signals to estimate head motion relative to inertial space. Vestibular information about dynamic head attitude relative to gravity is the basis for computing head (and body) angular velocity relative to inertial space. Available evidence suggests that the inertial vestibular system controls both head attitude and velocity with respect to a gravity-centered reference frame. The basic computational principles underlying the inertial processing of otolith and semicircular canal afferent signals are outlined.
Wavelets in signal detection and identification comparative signal processing technology evaluation
Raghu Raghaven
1994-01-01
The Wavelet in Signal Detection and Identification: Comparative Signal Processing Technology Evaluation Program has been conducted by Lockheed Missiles and Space Company to develop wavelet based signal detection and classification techniques and compare them to Fourier time-frequency methods. The problem domain is submarine detection and identification using transient passive sonar signals. These nontraditional signals are critical in solving current antisubmarine
Anawake: Signal-Based Power Management For Digital Signal Processing Systems
Lazzaro, John
Anawake: Signal-Based Power Management For Digital Signal Processing Systems John Lazzaro and John@sst.ll.mit.edu Abstract Single-chip, low-power, programmable digital signal processing sys- tems are capable of hosting10 microwatts, in applications where speech signals are present with a sufficiently low duty cycle
Neural correlates of feedback processing in toddlers.
Meyer, Marlene; Bekkering, Harold; Janssen, Denise J C; de Bruijn, Ellen R A; Hunnius, Sabine
2014-07-01
External feedback provides essential information for successful learning. Feedback is especially important for learning in early childhood, as toddlers strongly rely on external signals to determine the consequences of their actions. In adults, many electrophysiological studies have elucidated feedback processes using a neural marker called the feedback-related negativity (FRN). The neural generator of the FRN is assumed to be the ACC, located in medial frontal cortex. As frontal brain regions are the latest to mature during brain development, it is unclear when in early childhood a functional feedback system develops. Is feedback differentiated on a neural level in toddlers and in how far is neural feedback processing related to children's behavioral adjustment? In an EEG experiment, we addressed these questions by measuring the brain activity and behavioral performance of 2.5-year-old toddlers while they played a feedback-guided game on a touchscreen. Electrophysiological results show differential brain activity for feedback with a more negative deflection for incorrect than correct outcomes, resembling the adult FRN. This provides the first neural evidence for feedback processing in toddlers. Notably, FRN amplitudes were predictive of adaptive behavior: the stronger the differential brain activity for feedback, the better the toddlers' adaptive performance during the game. Thus, already in early childhood toddlers' feedback-guided performance directly relates to the functionality of their neural feedback processing. Implications for early feedback-based learning as well as structural and functional brain development are discussed. PMID:24392905
Irregularities and Scaling in Signal and Image Processing: Multifractal Analysis
Paris-Sud XI, Université de
Irregularities and Scaling in Signal and Image Processing: Multifractal Analysis P. Abry , S: Multifractal analysis . . . . . . . . . . . . . . . . . . 7 1.4 Data analysis and Signal Processing underlying multifractal analysis. Third, it will reformulate these theoretical tools into a wavelet framework
Signal Processing in the PVLAS Experiment
E. Zavattini; G. Zavattini; G. Ruoso; E. Polacco; E. Milotti; M. Karuza; U. Gastaldi; G. Di Domenico; F. Della Valle; R. Cimino; S. Carusotto; G. Cantatore; M. Bregant
2005-09-22
Nonlinear interactions of light with light are well known in quantum electronics, and it is quite common to generate harmonic or subharmonic beams from a primary laser with photonic crystals. One suprising result of quantum electrodynamics is that because of the quantum fluctuations of charged fields, the same can happen in vacuum. The virtual charged particle pairs can be polarized by an external field and vacuum can thus become birefringent: the PVLAS experiment was originally meant to explore this strange quantum regime with optical methods. Since its inception PVLAS has found a new, additional goal: in fact vacuum can become a dichroic medium if we assume that it is filled with light neutral particles that couple to two photons, and thus PVLAS can search for exotic particles as well. PVLAS implements a complex signal processing scheme: here we describe the double data acquisition chain and the data analysis methods used to process the experimental data.
Processing, signaling, and physiological function of chemerin.
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
Super-Nyquist signal transmission and digital signal processing
NASA Astrophysics Data System (ADS)
Zhang, Junwen; Yu, Jianjun; Chi, Nan
2014-11-01
Super-Nyquist, also known as Fast-than-Nyquist (FTN), signal generation based on optical or electrical spectrum shaping methods has been demonstrated to be an efficient scheme for future high-capacity transmission systems. Super- Nyquist signal demodulations based on maximum a posteriori (MAP) or maximum likelihood sequence estimation (MLSE) on receiver side have been demonstrated in 100G, 200G and 400G systems, which enables PDM-QPSK transmission with 4bit/s/Hz net spectral efficiency (SE) at lower OSNR requirement and longer transmission distance. Further studies also show the highly filtering-tolerant advantage of the super-Nyquist signal when using the 9-QAMbased multi-modulus equalization. This feature is quite useful for signals transmission under the aggressive optical filtering in multiple reconfigurable optical add-drop multiplexers (ROADMs) transmission link. In this paper, we review the newly reported super-Nyquist experiments using the optical super-Nyquist filtering 9-QAM like signals based on multi-modulus equalization (MMEQ). We directly recover the Nyquist filtered QPSK to a 9-QAM like signal. We first successfully transmitted 100-GHz-grid, 20 channels single-carrier 440-Gb/s super-Nyquist 9-QAM-like signal over 3600-km ultra-large effective-area fiber (ULAF) at record a net SE of 4b/s/Hz (after excluding the 7% hard-decision FEC overhead). The highly filtering-tolerant performance of the 9-QAM liked super-Nyquist signal is also experimentally demonstrated. Using this scheme, we then successfully transmit 10 channels 440-Gb/s signal over 3000- km ULAF and 10 cascaded ROADMs with 100-GHz-grid based on the single-carrier ETDM 110-GBaud QPSK. It is the highest baud rate of all-ETDM signal reported with the highest net SE at this baud rate for PDM-QPSK signal.
GLAST Burst Monitor Signal Processing System
Bhat, P. Narayana; Briggs, Michael; Connaughton, Valerie; Paciesas, William; Preece, Robert [University of Alabama, NSSTC, 320 Sparkman Drive, Huntsville, AL 35805 (United States); Diehl, Roland; Greiner, Jochen; Kienlin, Andreas von; Lichti, Giselher; Steinle, Helmut [Max-Planck-Institute for Extraterrestrial Physics, Giessenbachstrasse 85748, Garching (Germany); Fishman, Gerald; Kouveliotou, Chryssa; Meegan, Charles; Wilson-Hodge, Colleen [Marshall Space Flight Center, VP62, Huntsville, AL 35812 (United States); Kippen, R. Marc [Los Alamos National Laboratory, ISR-1, MS B244, Los Alamos, NM 87545 (United States); Persyn, Steven [Southwest Research Institute, Dept. of Space Systems, 6220 Culebra Road, San Antonio, TX 78238 (United States)
2007-07-12
The onboard Data Processing Unit (DPU), designed and built by Southwest Research Institute, performs the high-speed data acquisition for GBM. The analog signals from each of the 14 detectors are digitized by high-speed multichannel analog data acquisition architecture. The streaming digital values resulting from a periodic (period of 104.2 ns) sampling of the analog signal by the individual ADCs are fed to a Field-Programmable Gate Array (FPGA). Real-time Digital Signal Processing (DSP) algorithms within the FPGA implement functions like filtering, thresholding, time delay and pulse height measurement. The spectral data with a 12-bit resolution are formatted according to the commandable look-up-table (LUT) and then sent to the High-Speed Science-Date Bus (HSSDB, speed=1.5 MB/s) to be telemetered to ground. The DSP offers a novel feature of a commandable and constant event deadtime. The ADC non-linearities have been calibrated so that the spectral data can be corrected during analysis. The best temporal resolution is 2 {mu}s for the pre-burst and post-trigger time-tagged events (TTE) data. The time resolution of the binned data types is commandable from 64 msec to 1.024 s for the CTIME data (8 channel spectral resolution) and 1.024 to 32.768 s for the CSPEC data (128 channel spectral resolution). The pulse pile-up effects have been studied by Monte Carlo simulations. For a typical GRB, the possible shift in the Epeak value at high-count rates ({approx}100 kHz) is {approx}1% while the change in the single power-law index could be up to 5%.
Image and Signal Processing LISP Environment (ISLE)
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.
Method of single-fiber multimode interferometer speckle-signal processing
Yuri N. Kulchin; Oleg B. Vitrik; Oleg V. Kirichenko; Oleg T. Kamenev; Yuri S. Petrov; O. G. Maksaev
1997-01-01
Theoretical and experimental methods of correlation processing of the speckle signals formed by a single-fiber multimode interferometer are investigated and demonstrated. These methods are based on (1) a photographic filter, (2) a standard computer, and (3) analog computing approaches. All of these methods enable the transformation modulation of the speckle pattern to be either optical or electrical signals, which linearly
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.
Mascarenhas, Walter Figueiredo
DENORMAL NUMBERS IN FLOATING POINT SIGNAL PROCESSING APPLICATIONS Denormal numbers in floating Signal Processing, CPU Copyright 2002-2005 Laurent de Soras Page 1/10 #12;DENORMAL NUMBERS IN FLOATING.............................................................................................................. 2 1. FLOATING POINT NUMBER CODING OVERVIEW...................................................... 3 1
Active voltammetric microsensors with neural signal processing.
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.
IEEE SIGNAL PROCESSING MAGAZINE Why Not? The Magazine Way
Liu, K. J. Ray
IEEE SIGNAL PROCESSING MAGAZINE Why Not? The Magazine Way 2 MAY 2004 K.J. Ray Liu, Editor and engineers, our job is to ask, "Why not?" This is also the spirit of IEEE Signal Processing Magazine to share these lost stories again? Certainly! Why not? IEEE Signal Processing Magazine is developing
Wavelet-Based Transformations for Nonlinear Signal Processing
Nowak, Robert
Wavelet-Based Transformations for Nonlinear Signal Processing Robert D. Nowak Department.dsp.rice.edu Submitted to IEEE Transactions on Signal Processing, February 1997 Revised June 1998 EDICS Numbers: SP-2 in the analysis and processing of real-world signals. In this paper, we introduce two new structures for nonlinear
IEEE SIGNAL PROCESSING MAGAZINE Sotirios A. Tsaftaris, Aggelos K. Katsaggelos,
Tsaftaris, Sotirios
IEEE SIGNAL PROCESSING MAGAZINE Sotirios A. Tsaftaris, Aggelos K. Katsaggelos, Thrasyvoulos N. Pappas, and Eleftherios T. Papoutsakis How Can DNA Computing Be Applied to Digital Signal Processing computing from a signal processing perspective. To assist in our presentation we also provided a very short
Overview of Digital Signal Processing (DSP) Chapter Intended Learning Outcomes
So, Hing-Cheung
Overview of Digital Signal Processing (DSP) Chapter Intended Learning Outcomes: (i) Understand basic terminology in DSP (ii) Differentiate DSP and analog signal processing (iii) Describe basic DSP and according to the two's complement representation. In digital signal processing (DSP), we deal
Preprint submitted to SAMPLING THEORY IN SIGNAL AND IMAGE PROCESSING
Bidegaray, Brigitte
Preprint submitted to SAMPLING THEORY IN SIGNAL AND IMAGE PROCESSING DVI file produced on October issue in signal process- ing for mobile applications. We investigate the link between the smooth- ness the power consumption of signal processing systems is the reduction of the number of samples. Non uniform
Multimedia Signal Processing for Behavioral Quantification in Neuroscience
Multimedia Signal Processing for Behavioral Quantification in Neuroscience Peter Andrews1 , Sigal that are in the area of multimedia signal processing. Automated analysis of video and audio recordings of animal for advanced multimedia signal processing. There are a number of MMSP tools that now exist which are directly
Intelligent signal processing for damage detection in composite materials
W. J. Staszewski
2002-01-01
Signal processing is an important element of any structural health monitoring system. The paper addresses the importance of intelligent signal processing for damage identification in composite materials. After an initial discussion as to what constitutes the overall signal processing, a number of examples of damage detection in composite materials are presented for illustration. These include: data denoising techniques, feature extraction
Development of an ASIC set for signal processing
Parimal A Patel; Hemal N. Kothari; J. F. Robb
1992-01-01
An approach to signal acquisition, digitization, and processing of low-frequency physiological signals is discussed. The approach uses a chip attached to a transducer through a digital wire placed at the sensing point. The wire transmits digital information instead of an analog signal to an application-specific integrated circuit (ASIC) signal processor. This digital wire\\/Visp chip set produces a noise-immune signal processing
Neurophysiological correlates of anhedonia in feedback processing.
Mies, Gabry W; Van den Berg, Ivo; Franken, Ingmar H A; Smits, Marion; Van der Molen, Maurits W; Van der Veen, Frederik M
2013-01-01
Disturbances in feedback processing and a dysregulation of the neural circuit in which the cingulate cortex plays a key role have been frequently observed in depression. Since depression is a heterogeneous disease, instead of focusing on the depressive state in general, this study investigated the relations between the two core symptoms of depression, i.e., depressed mood and anhedonia, and the neural correlates of feedback processing using fMRI. The focus was on the different subdivisions of the anterior cingulate cortex (ACC). Undergraduates with varying levels of depressed mood and anhedonia performed a time-estimation task in which they received positive and negative feedback that was either valid or invalid (i.e., related vs. unrelated to actual performance). The rostral cingulate zone (RCZ), corresponding to the dorsal part of the ACC, was less active in response to feedback in more anhedonic individuals, after correcting for the influence of depressed mood, whereas the subgenual ACC was more active in these individuals. Task performance was not affected by anhedonia, however. No statistically significant effects were found for depressed mood above and beyond the effects of anhedonia. This study therefore implies that increasing levels of anhedonia involve changes in the neural circuitry underlying feedback processing. PMID:23532800
Neurophysiological correlates of anhedonia in feedback processing
Mies, Gabry W.; Van den Berg, Ivo; Franken, Ingmar H. A.; Smits, Marion; Van der Molen, Maurits W.; Van der Veen, Frederik M.
2013-01-01
Disturbances in feedback processing and a dysregulation of the neural circuit in which the cingulate cortex plays a key role have been frequently observed in depression. Since depression is a heterogeneous disease, instead of focusing on the depressive state in general, this study investigated the relations between the two core symptoms of depression, i.e., depressed mood and anhedonia, and the neural correlates of feedback processing using fMRI. The focus was on the different subdivisions of the anterior cingulate cortex (ACC). Undergraduates with varying levels of depressed mood and anhedonia performed a time-estimation task in which they received positive and negative feedback that was either valid or invalid (i.e., related vs. unrelated to actual performance). The rostral cingulate zone (RCZ), corresponding to the dorsal part of the ACC, was less active in response to feedback in more anhedonic individuals, after correcting for the influence of depressed mood, whereas the subgenual ACC was more active in these individuals. Task performance was not affected by anhedonia, however. No statistically significant effects were found for depressed mood above and beyond the effects of anhedonia. This study therefore implies that increasing levels of anhedonia involve changes in the neural circuitry underlying feedback processing. PMID:23532800
Signal processing issues in reflection tomography
NASA Astrophysics Data System (ADS)
Cadalli, Nail
2001-12-01
This dissertation focuses on signal modeling and processing issues of the following problems in reflection tomography: synthetic aperture radar (SAR) imaging of a runway and surroundings from an aircraft approaching for landing, acoustic imaging of objects buried in soil, and lidar imaging of underwater objects. The highly squinted geometry of runway imaging necessitates the incorporation of wavefront curvature into the signal model. We investigate the feasibility of using the wavenumber-domain (? - k) SAR inversion algorithm, which models the actual curvature of the wavefront, for runway imaging. We demonstrate the aberrations that the algorithm can produce when the squint angle is close to 90° and show that high-quality reconstruction is still possible provided that the interpolation is performed accurately enough, which can be achieved by increasing the temporal sampling rate. We compare the performance with that of a more general inversion method (GIM) that solves the measurement equation directly. The performances of both methods are comparable in the noise- free case. Being inherently robust to noise, GIM produces superior results in the noisy case. We also present a solution to the left-right ambiguity of runway imaging using interferometric processing. In imaging of objects buried in soil, we pursue an acoustic approach primarily for detection and imaging of cultural artifacts. We have developed a mathematical model and associated computer software in order to simulate the signals acquired by the actual experimental system, and a bistatic SAR-type algorithm for reconstruction. In the reconstructions from simulated data, objects were detectable, but near-field objects suffered from shifts and smears. To account for wavefront curvature, we formulated processing of the simulated data using the 3-D version of the monostatic ? - k algorithm. In lidar imaging of underwater objects, we formulate the problem as a 3-D tomographic reconstruction problem. We have developed software to simulate lidar returns at airborne receivers using the bistatic lidar return equations. Our simulator can model multiple scattering and absorption for various water types and system parameters. Our simulated data fits the characteristics of real data very well. We present our reconstruction results from the simulated and real data, and comparatively discuss the reconstructions.
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.
Nonlinear Biochemical Signal Processing via Noise Propagation
Kyung Hyuk Kim; Hong Qian; Herbert M. Sauro
2013-09-10
Single-cell studies often show significant phenotypic variability due to the stochastic nature of intra-cellular biochemical reactions. When the numbers of molecules, e.g., transcription factors and regulatory enzymes, are in low abundance, fluctuations in biochemical activities become significant and such "noise" can propagate through regulatory cascades in terms of biochemical reaction networks. Here we develop an intuitive, yet fully quantitative method for analyzing how noise affects cellular phenotypes based on identifying a system's nonlinearities and noise propagations. We observe that such noise can simultaneously enhance sensitivities in one behavioral region while reducing sensitivities in another. Employing this novel phenomenon we designed three biochemical signal processing modules: (a) A gene regulatory network that acts as a concentration detector with both enhanced amplitude and sensitivity. (b) A non-cooperative positive feedback system, with a graded dose-response in the deterministic case, that serves as a bistable switch due to noise-induced bimodality. (c) A noise-induced linear amplifier for gene regulation that requires no feedback. The methods developed in the present work allow one to understand and engineer nonlinear biochemical signal processors based on fluctuation-induced phenotypes.
Serdijn, Wouter A.
W.A. SERDIJN: "A CLASSIFICATION OF ELECTRONIC SIGNAL-PROCESSING FUNCTIONS" 1 A classification was on analysis of the primary #12;W.A. SERDIJN: "A CLASSIFICATION OF ELECTRONIC SIGNAL-PROCESSING FUNCTIONS" 2 of electronic signal-processing functions Wouter A. Serdijn Delft University of Technology, Faculty
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.
Alfredo Contin; Stefano Pastore
2009-01-01
This paper describes a K-Means Clustering classification algorithm for the separation of Partial Discharge (PD) signals and pulsating noise due to multiple sources occurring in practical objects. It is based on the comparison of the Auto-Correlation Function (ACF) of the recorded signals assuming that the same source can generate signals having similar ACF while ACF differ when signals with different
Advanced Signal Processing and Condition Monitoring Session Keynote address
Paris-Sud XI, Université de
Advanced Signal Processing and Condition Monitoring Session Keynote address Nadine Martin GIPSA.martin@gipsa-lab.inpg.fr ABSTRACT When physical models are of a high complexity, a signal processing approach is helpful for providing accurate information about a system and its failures. The session entitled "Advanced Signal
Biomedical signal processing --application of optimization methods for machine learning
Absil, Pierre-Antoine
Biomedical signal processing -- application of optimization methods for machine learning problems Helmholtz Zentrum M¨unchen http://cmb.helmholtz-muenchen.de Grenoble, 16-Sep-2008 F. Theis Biomedical signal Biomedical signal processing -- application of optimization methods for machi #12;Data mining cocktail
Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing
Paris-Sud XI, Université de
Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2009, their characterization remains a very challenging goal of increasing interest. Until now, several signal processing tools of transient signals is nowadays a typical point of interest when we consider the multitude of existing
Missile signal processing common computer architecture for rapid technology upgrade
Daniel V. Rabinkin; Edward Rutledge; Paul Monticciolo
2004-01-01
Interceptor missiles process IR images to locate an intended target and guide the interceptor towards it. Signal processing requirements have increased as the sensor bandwidth increases and interceptors operate against more sophisticated targets. A typical interceptor signal processing chain is comprised of two parts. Front-end video processing operates on all pixels of the image and performs such operations as non-uniformity
Spagnolini, Umberto
A model of noise amplitude and the correlation of the components of the noise process due to their polarization. The signal is assumed to be white Gaussian. Noise is a superposition of M non-Gaussian processes, the signal is separated from the noise. Statistical model parameters of random processes are estimated
All-optical signal processing with photonic integrated circuits
C. Janz
2000-01-01
Optical techniques for bit-level processing of high-speed signals will be reviewed, with emphasis on key device “building blocks” and on demonstrated and potential system applications, particularly optical signal regeneration
Analysis of Correlated Traffic by Batch Renewal Process
Wei Li; Rod J. Fretwell; Demetres D. Kouvatsos
2009-01-01
The discovery of the batch renewal process (BRP) provides means to investigate the effect of traffic correlation independent of any other traffic characteristics. BRP is considered to be the least-biased choice traffic model, given only the measures of correlation, because the BRP is completely determined by the complete (infinitely denumerable) sets of count correlation and of interval correlation. A procedure
Ressler, Johann; Dirscherl, Andreas; Grothe, Helmut; Wolf, Bernhard
2007-02-01
In many cases of bioanalytical measurement, calculation of large amounts of data, analysis of complex signal waveforms or signal speed can overwhelm the performance of microcontrollers, analog electronic circuits or even PCs. One method to obtain results in real time is to apply a digital signal processor (DSP) for the analysis or processing of measurement data. In this paper we show how DSP-supported multiplying and accumulating (MAC) operations, such as time/frequency transformation, pattern recognition by correlation, convolution or filter algorithms, can optimize the processing of bioanalytical data. Discrete integral calculations are applied to the acquisition of impedance values as part of multi-parametric sensor chips, to pH monitoring using light-addressable potentiometric sensors (LAPS) and to the analysis of rapidly changing signal shapes, such as action potentials of cultured neuronal networks, as examples of DSP capability. PMID:17313351
Evdokimos I. Konstantinidis; Christos A. Frantzidis; Lazaros Tzimkas; Costas Pappas; P. D. Bamidis
2009-01-01
This paper investigates the benefits derived by adopting the use of Graphics Processing Unit (GPU) parallel programming in the field of biomedical signal processing. The differences in execution time when computing the Correlation Dimension (CD) of multivariate neurophysiological recordings and the Skin Conductance Level (SCL) are reported by comparing several common programming environments. Moreover, as indicated in this study, the
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.
Integrated optical signal processing with magnetostatic waves
NASA Astrophysics Data System (ADS)
Fisher, A. D.; Lee, J. N.
1984-03-01
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.
Optimal signal processing for continuous qubit readout
Shilin Ng; Mankei Tsang
2014-08-06
The measurement of a quantum two-level system, or a qubit in modern terminology, often involves an electromagnetic field that interacts with the qubit, before the field is measured continuously and the qubit state is inferred from the noisy field measurement. During the measurement, the qubit may undergo spontaneous transitions, further obscuring the initial qubit state from the observer. Taking advantage of some well known techniques in stochastic detection theory, here we propose a novel signal processing protocol that can infer the initial qubit state optimally from the measurement in the presence of noise and qubit dynamics. Assuming continuous quantum-nondemolition measurements with Gaussian or Poissonian noise and a classical Markov model for the qubit, we derive analytic solutions to the protocol in some special cases of interest using It\\={o} calculus. Our method is applicable to multi-hypothesis testing for robust qubit readout and relevant to experiments on qubits in superconducting microwave circuits, trapped ions, nitrogen-vacancy centers in diamond, semiconductor quantum dots, or phosphorus donors in silicon.
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.
Nerve Signal Processing using Artificial Neural Nets
Martin Bogdan; Alexei Babanine; Jörg Kaniecki; Wolfgang Rosenstiel
1995-01-01
In this paper we review the aim of the INTER1-project (Intelligent Neural InTERface), especiallyfrom the point of view of Artificial Neural Nets (ANN). We also propose a modus operandi to processreal nerve signals using ANN. We present a method to simulate nerve signals, first experience inseparating nerve signals from multi-array recorded data as well as first experiences using an artificialneural
Signal Processing 87 (2007) 489499 Pilot signal design algorithm for efficient symbol time offset
Kim, Hyung-Myung
2007-01-01
algorithms--Sine Algo- rithm, Shift Algorithm, and Sine and Shift Algo- rithm--with a purpose that the pilot signals have low correlation in the time domain. These algo- rithms are developed in terms of positions
Seiichi Nakamori; Aurora Hermoso-carazo; Josefa Linares-pérez
2006-01-01
This paper treats the least-squares linear smoothing problem for signal estimation using measure- ments contaminated by additive white noise correlated with the signal, with stochastic delays. We derive a general smoothing equation which is applied to obtain specific smoothing algorithms, which are referred in the signal estimation literature as fixed-point, fixed-interval, and fixed-lag smooth- ing. Using an innovation approach, the
Processing Motion Signals in Complex Environments
NASA Technical Reports Server (NTRS)
Verghese, Preeti
2000-01-01
Motion information is critical for human locomotion and scene segmentation. Currently we have excellent neurophysiological models that are able to predict human detection and discrimination of local signals. Local motion signals are insufficient by themselves to guide human locomotion and to provide information about depth, object boundaries and surface structure. My research is aimed at understanding the mechanisms underlying the combination of motion signals across space and time. A target moving on an extended trajectory amidst noise dots in Brownian motion is much more detectable than the sum of signals generated by independent motion energy units responding to the trajectory segments. This result suggests that facilitation occurs between motion units tuned to similar directions, lying along the trajectory path. We investigated whether the interaction between local motion units along the motion direction is mediated by contrast. One possibility is that contrast-driven signals from motion units early in the trajectory sequence are added to signals in subsequent units. If this were the case, then units later in the sequence would have a larger signal than those earlier in the sequence. To test this possibility, we compared contrast discrimination thresholds for the first and third patches of a triplet of sequentially presented Gabor patches, aligned along the motion direction. According to this simple additive model, contrast increment thresholds for the third patch should be higher than thresholds for the first patch.The lack of a measurable effect on contrast thresholds for these various manipulations suggests that the pooling of signals along a trajectory is not mediated by contrast-driven signals. Instead, these results are consistent with models that propose that the facilitation of trajectory signals is achieved by a second-level network that chooses the strongest local motion signals and combines them if they occur in a spatio-temporal sequence consistent with a trajectory. These results parallel the lack of increased apparent contrast along a static contour made up of similarly oriented elements.
PASSIVE SENSOR IMAGING USING CROSS CORRELATIONS OF NOISY SIGNALS IN A SCATTERING MEDIUM
Garnier, Josselin
PASSIVE SENSOR IMAGING USING CROSS CORRELATIONS OF NOISY SIGNALS IN A SCATTERING MEDIUM JOSSELIN's function between two passive sensors can be estimated from the cross correlation of recorded signal that the travel time can be effectively estimated when the ray joining the two sensors continues into the noise
Intelligent, onboard signal processing payload concept, addendum :
Shriver, P. M. (Patrick M.); Harikumar, J. (Jayashree); Briles, S. C. (Scott C.); Gokhale, M. (Maya)
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.
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.
International Scholarly Research Network ISRN Signal Processing
Boyer, Edmond
) for the representation of nonlinear signals. This approach is based on the spectral decomposition of partial differential equation- (PDE-) based operators which interpolate the characteristic points of a signal. The SID these components well suited to the separation of the noise or data in some scale analysis. Sparse representations
Gigahertz signal processing using reflex optoelectronic switching matrices
NASA Astrophysics Data System (ADS)
Lam, D. K. W.; Syrett, B. A.
1987-03-01
The application of reflex optoelectronic switching matrices (ROSM) to signal processing in the gigahertz region is analyzed. Various signal processing functions such as delay generation, loop filtering, word generation/detection, integration, and digital to analog conversion are identified and their respective realizations in a ROSM are presented. It is found that for dedicated signal processing functions, simpler submatrices instead of full matrices can be employed with significant reduction in complexity and cost. The performance of ROSM's using currently commercially available components confirms the feasibility of gigahertz signal processing with ROSM's.
Enhancement of echo-signal correlation in elastography using temporal stretching
Tomy Varghese; Jonathan Ophir
1997-01-01
Echo-signal decorrelation due to tissue compression is a significant source of error in tissue displacement estimates obtained using crosscorrelation. Tissue displacement estimates are used to compute strain values for imaging the elasticity of biological soft tissues. The correlation coefficient between the pre- and post-compression echo rf signals reduces rapidly with signal decorrelation due to increased compression. Miniscule reductions in the
Crossover scaling evaluation in mixed correlated signals by means of Detrended Fluctuation Analysis
NASA Astrophysics Data System (ADS)
Martínez-García, C. R.; Reyes-Ramírez, I.; Angulo-Brown, F.; Guzmán-Vargas, L.
2015-01-01
In this work we study the scaling behavior of signals constructed by a class of processes with "intrinsic trends" and correlated noises. We focus our attention in evaluating the appearence of a crossover in the scaling exponents obtained by means of the Detrended Fluctuation Analysis. In particular, we evaluate the conditions of the trend which leads to a crossover where the scaling exponent from small scales (?s) is smaller or larger than the corresponding exponent from large scales (?l). We find that decreasing trend leads to ?s > ?l, whereas an increasing trend results in ?s < ?l. We also find that when one introduces correlated noise into a decreasing or increasing trend map, there is a crossover which separates two regions with exponents related to the trend mainly over short scales for decreasing trends, while over large scales, the scaling exponent resembles the behavior of the increasing trend.
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.
Signal processing underlying extrinsic control of stem cell fate
Zandstra, Peter W.
Signal processing underlying extrinsic control of stem cell fate Ryan E. Davey and Peter W to control stem cell fate. Keywords stem cells, systems biology, signaling networks, extrinsic control Curr and the discovery that both bone mor- phogenic protein and Wnt signaling also promote self- renewal in mouse ES
PIECEWISE CONVEX ESTIMATION FOR SIGNAL PROCESSING Kurt S. Riedel
PIECEWISE CONVEX ESTIMATION FOR SIGNAL PROCESSING Kurt S. Riedel Courant Institute, New York of the unknown function. We outline how piecewise convex #12;tting may be applied to signal recov- ery sign in a small neighborhood about each #12;rst-stage change point. 1. SIGNAL RECOVERY Our basic tenet
PIECEWISE CONVEX ESTIMATION FOR SIGNAL PROCESSING Kurt S. Riedel
PIECEWISE CONVEX ESTIMATION FOR SIGNAL PROCESSING Kurt S. Riedel Courant Institute, New York of the unknown function. We outline how piecewise convex fitting may be applied to signal recov ery neighborhood about each firststage change point. 1. SIGNAL RECOVERY Our basic tenet is that ``Naturally
Model Based Signal Processing Algorithm for MIDP GPR
Kansas, University of
are faced with the problem of detecting weak signals buried in the sidelobes of stronger reflections signal (also called the Model Based Approach) offer better performance in terms of a minimum varianceModel Based Signal Processing Algorithm for MIDP GPR Visweswaran Srinivasamurthy, Dr. Muhammad
Radiation detector signal processing using sampling kernels without bandlimiting constraints
Jürgen Stein; Marcus J. Neuer; Claus-Michael Herbach; Guntram Pausch; Kai Ruhnau
2007-01-01
For the development of digital signal processing systems for fast scintillation detectors we comprehensively study the modeling of nuclear signals, deconvolution of detector pulses and signal sampling. Applications for new scintillators with light decay times of a few nanoseconds demand suitable low power digital systems running at lowest possible sampling rates. We are interested in accurate sub-nanosecond timing and optimal
Karsten Fyhn; Thomas Arildsen; Torben Larsen; Sřren Holdt Jensen
2011-01-01
To lower the sampling rate in a spread spectrum communication system using Direct Sequence Spread Spectrum (DSSS), we show that compressive signal processing can be applied to demodulate the received signal. This may lead to a decrease in power consumption in wireless receivers using spread spectrum technology. In classical compressive sensing, the receiver must mix the received signal with a
A WATERMARKING METHOD FOR SPEECH SIGNALS BASED ON TIMEWARPING SIGNAL PROCESSING CONCEPT
Paris-Sud XI, Université de
A WATERMARKING METHOD FOR SPEECH SIGNALS BASED ON TIMEWARPING SIGNAL PROCESSING CONCEPT Arnaud@ee.ryerson.ca ABSTRACT This paper deals with the watermarking of audio speech sig- nals which consists in introducing two signals are close in the timefrequency plane. From this embedding scheme, a watermark extraction
Lineshapes and Correlations in Two Dimensional Vibrational Signals of NMA
NASA Astrophysics Data System (ADS)
Hayashi, Tomoyuki; Zhuang, Wei; Abramavicius, Darius; Mukamel, Shaul
The coherent nonlinear response of the entire amide lineshapes of N-methyl acetamide (NMA) to three infrared pulses is simulated using an Electrostatic DFT map. Positive and negative cross-peaks contain signatures of correlation between the fundamentals and the combination state. The coupled amide I - III cross-peak lineshapes indicate an anti-correlation of frequency fluctuations, which is ascribed to the correlated hydrogen bond dynamics at C=O and N=H sites.
Automatic Recognition Of Primitive Changes In Manufacturing Process Signals
NASA Astrophysics Data System (ADS)
Love, P. L.; Simaan, M.
1986-03-01
Manufacturing processes are generally monitored by observing sampled process signals. The purpose of this monitoring is to ensure process, and thereby, product consistency and to help diagnose causes of process instability. The interpretation of process signals requires the recognition of what we refer to here as primitive variations, or changes, in signal values which are typically buried in a background of other process related variations and random noise. These primitive variations include changes such as positive or negative sharp peaks, sudden step-like increases or decreases, or gradual ramp-like variations in the signals. Such changes in a given signal indicate a process change which when combined with corresponding changes in other signals could lead to the identification of the cause, or at least a rank order of possible causes, which produced these changes. In this paper, we discuss a two-level AI-based procedure for automatic recognition of these primitive changes. This procedure essentially involves applying syntactic analysis either directly to the raw process signals or, whenever not possible, to a filtered version of them. The first level, therefore, involves applying special purpose nonlinear filters which are designed to enhance or isolate, a particular primitive variation in the signal. The second level consists of a Signal Interpreter process written in LISP. This process analyses the filtered signals and produces a data structure which represents the primitive variations. A description of the entire interpretation system will be presented, and an example illustrating the application of the method to a process signal of an actual Aluminum sheet rolling mill will be shown.
Ultrafast nonlinear optics on a chip: Application to signal processing
M. D. Pelusi; T. D. Vo; F. Luan; S. J. Madden; D.-Y. Choi; D. A. P. Bulla; B. Luther-Davies; B. J. Eggleton
2009-01-01
We review results on the recently developed dispersion-shifted, Chalcogenide waveguides demonstrating nonlinear signal processing on a compact monolithic platform with ultra-broadband capability and moderate launch powers of around 100 mW. Highlight results include broadband wavelength conversion of high-bit rate optical signals, time division multiplexing of 320 Gb\\/s signals and characterization of 320 Gb\\/s signals using a photonic chip based RF
Social Signal Processing: Understanding Nonverbal Communication in Social Interactions
Vinciarelli, Alessandro
Social Signal Processing: Understanding Nonverbal Communication in Social Interactions Alessandro Processing, human-human communication, nonverbal behavior, social interactions. ACM Classification Keywords A in human sciences have shown that nonverbal communication is the main channel through which we express
Computational Requirements for Media Signal Processing Vojin G. Oklobdzija
California at Davis, University of
processing of audio and video signals..It has been used increasingly in consumer electronic products be processed in parallel using operations on packed words in MMX-64, eight in EMP-128, and sixteen in EMP-256
A PURE CORDIC BASED FFT FOR RECONFIGURABLE DIGITAL SIGNAL PROCESSING
Götze, Jürgen
A PURE CORDIC BASED FFT FOR RECONFIGURABLE DIGITAL SIGNAL PROCESSING Benjamin Heyne, J¨urgen G¨otze University of Dortmund, Information Processing Lab Otto-Hahn-Str. 4, 44221 Dortmund, Germany E-Mail: benjamin.heyne
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.
An Energy-Efficient Biomedical Signal Processing Platform
Joyce Kwong; Anantha P. Chandrakasan
2011-01-01
This paper presents an energy-efficient processing platform for wearable sensor nodes, designed to support diverse biological signals and algorithms. The platform features a 0.5 V-1.0 V 16-bit microcontroller, SRAM, and accelerators for biomedical signal processing. Voltage scaling and block-level power gating allow optimizing energy efficiency under applica- tions of varying complexity. Programmable accelerators support numerous usage scenarios and perform signal
Signal Processing and Data Fusion for Autonomous Undersea Vehicles
John W. Irza; Mukund N. Desai
1989-01-01
The strategic and tactical applications for autonomous submersibles place great demands on the platforms' passive sonar signal and data processing abilities. It is necessary to overcome the limited acoustic aperture and lack of human supervision by exploiting synergism between front-end signal processing functions and back-end data fusion algorithms. An Information Management System Architecture is presented which represents the relationship between
Analog VLSI signal processing: Why, where, and how?
Eric A. Vittoz
1994-01-01
Analog VLSI signal processing is most effective when precision is not required, and is therefore an ideal solution for the implementation of perception systems. The possibility to choose the physical variable that represents each signal allows all the features of the transistor to be exploited opportunistically to implement very dense time- and amplitude-continuous processing cells. This paper describes a simple
Analog VLSI signal processing: Why, where, and how?
Eric A. Vittoz
1994-01-01
Analog VLSI signal processing is most effective when precision is not required, and is therefore an ideal solution for the implementation of perception systems. The possibility to choose the physical variable that represents each signal allows all the features of the transistor to be exploited opportunistically to implement very dense time- and amplitude- continuous processing cells. This paper describes a
Low power signal processing architectures for network microsensors
Michael J. Dong; K. Geoffrey Yung; William J. Kaiser
1997-01-01
Low power signal processing systems are required for distributed network microsensor techn- ology. Network microsensors now provide a new monitoring and control capability for civil and military applications in transportation, manufacturing, biomed- ical technology, environmental management, and safety and security systems. Signal processing methods for event detection have been developed with low power, parallel architectures that optimize performance for unique
Classification of no-signaling correlations and the guess your neighbor's input game
He-Ming Wang; Heng-Yun Zhou; Liang-Zhu Mu; Heng Fan
2014-09-11
We formulate a series of non-trivial equalities which are satisfied by all no-signaling correlations, meaning that no faster-than-light communication is allowed with the resource of these correlations. All quantum and classical correlations satisfy these equalities since they are no-signaling. By applying these equalities, we provide a general framework for solving the multipartite "guess your neighbor's input" (GYNI) game, which is naturally no-signaling but shows conversely that general no-signaling correlations are actually more non-local than those allowed by quantum mechanics. We confirm the validity of our method for number of players from 3 up to 19, thus providing convincing evidence that it works for the general case. In addition, we solve analytically the tripartite GYNI and obtain a computable measure of supra-quantum correlations. This result simplifies the defined optimization procedure to an analytic formula, thus characterizing explicitly the boundary between quantum and supra-quantum correlations. In addition, we show that the gap between quantum and no-signaling boundaries containing supra-quantum correlations can be closed by local orthogonality conditions in the tripartite case. Our results provide a computable classification of no-signaling correlations.
IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. XX, NO. XX, JANUARY XXXX 1 Relaxed Conditions the convention of modern digital signal processing by establishing that exact signal reconstruction is possible the fundamental doctrine of signal processing has been Shannon's theorem, which states that any continuous signal
Nebel, Jean-Christophe
1 Abstract-- Genomic Signal Processing is a new area of research that combines advanced digital signal processing methodologies for enhanced genetic data analysis. It has many promising applications signal processing methods: linear predictive coding, wavelet decomposition and fractal dimension
Neuromorphic opto-electronic integrated circuits for optical signal processing
NASA Astrophysics Data System (ADS)
Romeira, B.; Javaloyes, J.; Balle, S.; Piro, O.; Avó, R.; Figueiredo, J. M. L.
2014-08-01
The ability to produce narrow optical pulses has been extensively investigated in laser systems with promising applications in photonics such as clock recovery, pulse reshaping, and recently in photonics artificial neural networks using spiking signal processing. Here, we investigate a neuromorphic opto-electronic integrated circuit (NOEIC) comprising a semiconductor laser driven by a resonant tunneling diode (RTD) photo-detector operating at telecommunication (1550 nm) wavelengths capable of excitable spiking signal generation in response to optical and electrical control signals. The RTD-NOEIC mimics biologically inspired neuronal phenomena and possesses high-speed response and potential for monolithic integration for optical signal processing applications.
Nonlinear filtering for robust signal processing
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.
Power-law correlated processes with asymmetric distributions
NASA Astrophysics Data System (ADS)
Podobnik, Boris; Ivanov, Plamen Ch.; Jazbinsek, Vojko; Trontelj, Zvonko; Stanley, H. Eugene; Grosse, Ivo
2005-02-01
Motivated by the fact that many physical systems display (i) power-law correlations together with (ii) an asymmetry in the probability distribution, we propose a stochastic process that can model both properties. The process depends on only two parameters, where one controls the scaling exponent of the power-law correlations, and the other controls the degree of asymmetry in the distributions leaving the correlations unaffected. We apply the process to air humidity data and find that the statistical properties of the process are in a good agreement with those observed in the data.
Signal processing for an infrared array detector
M. A. Young; G. E. Smith; G. C. Pimentel
1989-01-01
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.
Moving source localization using seismic signal processing
NASA Astrophysics Data System (ADS)
Asgari, Shadnaz; Stafsudd, Jing Z.; Hudson, Ralph E.; Yao, Kung; Taciroglu, Ertugrul
2015-01-01
Accurate localization of a seismic source in a near-field scenario where the distances between sensors and the source are less than a few wavelengths of the generated signal has shown to be a challenging task. Conventional localization algorithms often prove to be ineffective, as near-field seismic signals exhibit characteristics different from the well-studied far-field signals. The current work is aimed at the employment of a seismic sensor array for the localization and tracking of a near-field wideband moving source. In this paper, the mathematical derivation of a novel DOA estimation algorithm-dubbed the Modified Kirlin Method-has been presented in details. The estimated DOAs are then combined using a least-squares optimization method for source localization. The performance of the proposed method has been evaluated in a field experiment to track a moving truck. We also compare the DOA estimation and source localization results of the proposed method with those of two other existing methods originally developed for localization of a stationary wideband source; Covariance Matrix Analysis and the Surface Wave Analysis. Our results indicate that both the Surface Wave Analysis and the Modified Kirlin Methods are effective in locating and tracking a moving truck.
Statistical Measures of Planck Scale Signal Correlations in Interferometers
Craig J. Hogan; Ohkyung Kwon
2015-06-26
A model-independent statistical framework is presented to interpret data from systems where the mean time derivative of positional cross correlation between world lines, a measure of spreading in a quantum geometrical wave function, is measured with a precision smaller than the Planck time. The framework provides a general way to constrain possible departures from perfect independence of classical world lines, associated with Planck scale bounds on positional information. A parametrized candidate set of possible correlation functions is shown to be consistent with the known causal structure of the classical geometry measured by an apparatus, and the holographic scaling of information suggested by gravity. Frequency-domain power spectra are derived that can be compared with interferometer data. Simple projections of sensitivity for specific experimental set-ups suggests that measurements will directly yield constraints on a universal time derivative of the correlation function, and thereby confirm or rule out a class of Planck scale departures from classical geometry.
Statistical Measures of Planck Scale Signal Correlations in Interferometers
Craig J. Hogan; Ohkyung Kwon
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. 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.
Dynamics of electron correlation processes in atoms and atomic collisions
NASA Astrophysics Data System (ADS)
Stolterfoht, N.
1990-08-01
The dynamics of electron correlation processes are discussed for atoms and ion-atom collision systems. These processes are introduced in analogy with stationary electron correlation phenomena which are well known from atomic structure theory. The role of the Hartree-Fock method in finding a solution within the independent-particle model is pointed out. The concept of configuration interaction is discussed in order to clarify the verification of electron correlation processes. Configuration mixing is treated in stationary states involving bound and continuum electrons. It is pointed out that a specific electron correlation effect in a stationary state corresponds to an analogous effect in a state which evolves in time. In separated atoms emphasis is given to the Auger effect. In ion-atom collisions double ionization and double excitation are analyzed as examples for processes involving dynamic electron correlation.
Millecamps, Alexandre; Lowry, Kristin A; Brach, Jennifer S; Perera, Subashan; Redfern, Mark S; Sejdi?, Ervin
2015-07-01
Gait accelerometry is an important approach for gait assessment. Previous contributions have adopted various pre-processing approaches for gait accelerometry signals, but none have thoroughly investigated the effects of such pre-processing operations on the obtained results. Therefore, this paper investigated the influence of pre-processing operations on signal features extracted from gait accelerometry signals. These signals were collected from 35 participants aged over 65years: 14 of them were healthy controls (HC), 10 had Parkinson?s disease (PD) and 11 had peripheral neuropathy (PN). The participants walked on a treadmill at preferred speed. Signal features in time, frequency and time-frequency domains were computed for both raw and pre-processed signals. The pre-processing stage consisted of applying tilt correction and denoising operations to acquired signals. We first examined the effects of these operations separately, followed by the investigation of their joint effects. Several important observations were made based on the obtained results. First, the denoising operation alone had almost no effects in comparison to the trends observed in the raw data. Second, the tilt correction affected the reported results to a certain degree, which could lead to a better discrimination between groups. Third, the combination of the two pre-processing operations yielded similar trends as the tilt correction alone. These results indicated that while gait accelerometry is a valuable approach for the gait assessment, one has to carefully adopt any pre-processing steps as they alter the observed findings. PMID:25935124
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.
B-Spline Signal Processing: Part I-Theory
Michael Unser; Akram Aldroubi; Murray Eden
1993-01-01
This paper describes a set of efficient filtering techniques for the processing and representation of signals in terms of continuous B-spline basis functions. We first consider the problem of determining the spline coefficients for an exact signal interpolation (direct B-spline transform). The reverse operation is the signal reconstruction from its spline coefficients with an optional zooming factor rn (indirect B-spline
Physics-based airborne GMTI radar signal processing
George R. Legters; Joseph R. Guerci
2004-01-01
The Knowledge-Aided Sensor Signal Processing and Expert Reasoning (KASSPER) program aims to improve airborne ground moving target indicator (GMTI) radar performance by taking into account all available prior knowledge. One powerful piece of information is that the radar return signal is a superposition of near-ideal plane-waves. A plane-wave signal and clutter model or sampled GMTI radar data can be used
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.,…
Intrator, Nathan
][3]. Analysis techniques, including time-domain, frequency- domain and modeling methods, have been developed analysis of vibro-acoustic heart signals for continuous non-invasive monitoring of cardiac functionality. 1Automatic Extraction of Physiological Features from Vibro-Acoustic Heart Signals: Correlation
Analog Integrated Circuits Design for Processing Physiological Signals
Yan Li; Carmen C. Y. Poon; Yuan-Ting Zhang
2010-01-01
Analog integrated circuits (ICs) designed for processing physiological signals are important building blocks of wearable and implantable medical devices used for health monitoring or restoring lost body functions. Due to the nature of physiological signals and the corresponding application scenarios, the ICs designed for these applications should have low power consumption, low cutoff frequency, and low input-referred noise. In this
Mutual information for stochastic signals and Lévy processes
Tyrone E. Duncan
2010-01-01
In this paper, some relations between estimation and mutual information are given by expressing two mutual information calculations in terms of two distinct estimation errors. Specifically the mutual information between a stochastic signal and a pure jump Levy process whose rate function depends on the signal is expressed in terms of a filtering error and the rate of change of
Two decades of array signal processing research: the parametric approach
H. Krim; M. Viberg
1996-01-01
The quintessential goal of sensor array signal processing is the estimation of parameters by fusing temporal and spatial information, captured via sampling a wavefield with a set of judiciously placed antenna sensors. The wavefield is assumed to be generated by a finite number of emitters, and contains information about signal parameters characterizing the emitters. A review of the area of
Signal processing by the HOG MAP kinase pathway Pascal Hersen
Mahadevan, L.
Signal processing by the HOG MAP kinase pathway Pascal Hersen , Megan N. McClean§ , L. Mahadevan osmolarity. This proto- typical pathway, the HOG pathway, is shown to act as a low-pass filter, integrating and the quantification of their information capacity. bandwidth HOG pathway microfluidics signal transduction
Prognostics using morphological signal processing and computational intelligence
B. Samanta; C. Nataraj
2008-01-01
A procedure is presented for monitoring and prognostics of machine conditions using computational intelligence (CI) techniques. The machine vibration signals are processed using morphological operations to extract an entropy based feature characterizing the signal shape-size complexity for assessment of machine conditions. An evolutionary average entropy of the system is introduced as the dasiamonitoring indexpsila for prognostics of the system condition.
Transformational Design of Digital Signal Processing Applications
Peter F. A. Middelhoek
1994-01-01
In the design of modern digital systems, such as image processing systems, it is, because of their complexity, of great importance that correctness is guaranteed during the design. Transformational design is a method that integrates guaranteed correctness into the design process. Correctness-by-construction is obtained by applying local behavior-preserving transformations —which have themselves already been proven correct— to derive an implementation
Neural Correlates of Processing Negative and Sexually Arousing Pictures
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
Signal processing for an infrared array detector
Young, M.A.; Smith, G.E.; Pimentel, G.C. (Laboratory of Chemical Biodynamics, Lawrence Berkeley Laboratory, University of California, Berkeley, California 94720 (US))
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.
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.
Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing
Boyer, Edmond
Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2011, Integration, and Segregation: From Biology to Artificial Image Processing Systems Jan D. Bouecke,1 Emilien for Neural Information Processing, Ulm University, James-Franck-Ring, 89069 Ulm, Germany 2 Equipe Projet
Mechanoluminescent pulse pressure sensors. Processing of output optical signal
N. Yu. Makarova; K. V. Tatmyshevskii
2007-01-01
The process of mechanoluminescence transformation of a pulse pressure sensor is considered. The process consists in excitation\\u000a of emission under the action of mechanical loading. An algorithm for use in processing the output optical signal of the sensor\\u000a that makes it possible to determine an input shock pulse is presented.
Advanced Turbulence Measurements and Signal Processing for Hydropower Flow Characterization
performance testing, and computational fluid dynamics (CFD) model validation. Synchronized ADV Arrays · ORNL (MHK) development sites and around scaled MHK turbine technologies in the laboratory Doppler Velocimetry and Profiling · ORNL has developed signal post-processing algorithms for ADVs
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.
An Energy-Efficient Biomedical Signal Processing Platform
Kwong, Joyce
This paper presents an energy-efficient processing platform for wearable sensor nodes, designed to support diverse biological signals and algorithms. The platform features a 0.5V-1.0V 16b microcontroller, SRAM, and ...
Informatics and Mathematical Modelling / Intelligent Signal Processing 1Jan Larsen
Informatics and Mathematical Modelling / Intelligent Signal Processing 1Jan Larsen LSA Algorithms Ph.D.-student Lasse Lohilahti Mřlgaard #12;Informatics and Mathematical Modelling / Intelligent interpretation Results in retrieval Demos Castsearch Wikipedia #12;Informatics and Mathematical Modelling
Johnson Corrections Corrections to Array Signal Processing: Concepts and Techniques
Johnson Corrections Corrections to Array Signal Processing: Concepts and Techniques Don H. Johnson." The sentence below the equation should read "...cone shaped: it is shown in Fig. 3.10." 87 The line after
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.
Springer.com Handbook of Signal Processing Systems
Bhattacharyya, Shuvra S.
Processors by Jarmo Takala (5) Application Specific Instruction Set DSP Processors by Dake Liu (6) Coarse) Mapping Decidable Signal Processing Graphs into FPGA Implementations by Roger Woods (5) Dynamic
Array signal processing in the NASA Deep Space Network
NASA Technical Reports Server (NTRS)
Pham, Timothy T.; Jongeling, Andre P.
2004-01-01
In this paper, we will describe the benefits of arraying and past as well as expected future use of this application. The signal processing aspects of array system are described. Field measurements via actual tracking spacecraft are also presented.
28. Perimeter acquisition radar building room #302, signal process and ...
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
Optimization of Signal Processing Software for Control System Implementation
Bhattacharyya, Shuvra S.
Optimization of Signal Processing Software for Control System Implementation Shuvra S of control systems -- the portion of a digitally- implemented control system between the sensor outputs almost all controllers are implemented digitally. In many complex or geographically distributed systems
Signal processing in biological cells : proteins, networks, and models
Said, Maya Rida, 1976-
2005-01-01
This thesis introduces systematic engineering principles to model, at different levels of abstraction the information processing in biological cells in order to understand the algorithms implemented by the signaling pathways ...
Ali Bashashati; Mehrdad Fatourechi; Rabab K Ward; Gary E Birch
2007-01-01
Brain–computer interfaces (BCIs) aim at providing a non-muscular channel for sending commands to the external world using the electroencephalographic activity or other electrophysiological measures of the brain function. An essential factor in the successful operation of BCI systems is the methods used to process the brain signals. In the BCI literature, however, there is no comprehensive review of the signal
Universal signal processing method for multimode reflective sensors
Larson, Robert Eugene
1988-01-01
UNIVERSAL SIGNAL PROCESSING METHOD FOR MULTIMODE REFLECTIVE SENSORS A Thesis by ROBERT EUGENE LARSON Submitted to the Office of Graduate Studies of Texas A8cM University in partial fulfillment of the requirements for the degree of MASTER... Member) Cyrus Ostowari (Member) Mark H. Weichold Jo W. Howse (Head Of Department) December 1988 ABSTRACT Universal Signal Processing Method for Multimode Reflective Sensors. (December 1988) Robert Eugene Larson, B. S. , Texas A&M University...
All-optical signal processing using dynamic Brillouin gratings
Santagiustina, Marco; Chin, Sanghoon; Primerov, Nicolay; Ursini, Leonora; Thévenaz, Luc
2013-01-01
The manipulation of dynamic Brillouin gratings in optical fibers is demonstrated to be an extremely flexible technique to achieve, with a single experimental setup, several all-optical signal processing functions. In particular, all-optical time differentiation, time integration and true time reversal are theoretically predicted, and then numerically and experimentally demonstrated. The technique can be exploited to process both photonic and ultra-wide band microwave signals, so enabling many applications in photonics and in radio science. PMID:23549159
Native signal processing on the Ultrasparc in the Ptolemy environment
William Chen; H. John Reekie; Sunil Bhave; Edward A. Lee
1996-01-01
We have implemented a number of real-time signal processing kernels and applications within the Ptolemy simulation and code generation environment. Our goal is to make it easy to generate real-time programs with configurable interactive user interfaces. As part of this project, we have developed and benchmarked some key signal processing kernels for the new UltraSparc Visual Instruction Set. We present
Compiling Signal Processing Code embedded in Haskell via LLVM
Thielemann, Henning
2010-01-01
We discuss a programming language for real-time audio signal processing that is embedded in the functional language Haskell and uses the Low-Level Virtual Machine as back-end. With that framework we can code with the comfort and type safety of Haskell while achieving maximum efficiency of fast inner loops and full vectorisation. This way Haskell becomes a valuable alternative to special purpose signal processing languages.
Two-Dimensional Signal Processing in Radon Space
Roger Lee Easton Jr.
1986-01-01
This dissertation considers a method for processing two-dimensional (2-D) signals (e.g. imagery) by transformation to a coordinate space where the 2-D operation separates into orthogonal 1-D operations. After processing, the 2-D output is reconstructed by a second coordinate transformation. This approach is based on the Radon transform, which maps a two-dimensional Cartesian representation of a signal into a series of
Fiber-Optic Interconnection Networks for Signal Processing Applications
Magnus Jonsson
1999-01-01
In future parallel radar signal processing systems, with high bandwidth demands, new interconnection technologies are needed. The same reasoning can be made for other signal processing applications, e.g., those involving multimedia. Fiber-optic networks are a promising alternative and a lot of work have been done. In this paper, a number of fiber-optic interconnection architectures are reviewed, especially from a radar
All-optical signal processing using dynamic Brillouin gratings
NASA Astrophysics Data System (ADS)
Santagiustina, Marco; Chin, Sanghoon; Primerov, Nicolay; Ursini, Leonora; Thévenaz, Luc
2013-04-01
The manipulation of dynamic Brillouin gratings in optical fibers is demonstrated to be an extremely flexible technique to achieve, with a single experimental setup, several all-optical signal processing functions. In particular, all-optical time differentiation, time integration and true time reversal are theoretically predicted, and then numerically and experimentally demonstrated. The technique can be exploited to process both photonic and ultra-wide band microwave signals, so enabling many applications in photonics and in radio science.
Hardware implementation of surface electromyogram signal processing: A survey
Ahmad Jamal Salim; Soo Yew Guan
2011-01-01
This paper surveys the previous and ongoing research on surface electromyogram (sEMG) signal processing implementation through various hardware platforms. The development of system that incorporates sEMG analysis capability is essential in rehabilitation devices, prosthesis arm\\/limb and pervasive healthcare in general. Most advanced EMG signal processing algorithms rely heavily on computational resource of a PC that negates the elements of portability,
Correlation between ICI and the carrier signal in OFDM under Doppler spread influence
Rainfield Y. Yen; Hong-Yu Liu; C. M. Wu
2009-01-01
In this paper, we derive an exact expression for the power correlation between the inter-carrier interference (ICI) and the carrier signal and show that the correlation is non-negligible for normal Doppler spread values. However, the correlation tends to vanish as Doppler spread approaches infinity. Then, the symbol error rates (SERs) for M-QAM OFDM systems over frequency-selective Ricean fading channels based
Introduction ME SIGNAL PROCESSING FOR COMMUNICATIONS
Langendoen, Koen
Mbps) 1000 800 600 400 200 0 SpatialCapacity(kbps/m2) UltraWideBand 1000 kbps/m2 IEEE 802.11a 55 kbps University of Technology Dept. EEMCS Delft, The Netherlands 1 #12;Topics Multiple-antenna processing Radio astronomy Space-time coding for wireless communications Localization based on multiple antenna measurements
Tool Integration for Signal Processing Architectural Exploration
Davis, Rhett
. A solution for mitigating the design process is providing open source IP cores and system-level synthesizers. This paper presents our view of what a framework for creating and analyzing open- source IP cores should look described in SystemC and Verilog code. We illustrate the use of our framework via two case studies: finite
Automated Architectural Exploration for Signal Processing Algorithms
Davis, Rhett
. A solution for mitigating the design process is providing open source IP cores and system-level synthesizers. This paper presents our view of a framework for creating and analyzing open- source IP cores. We discuss our framework by exploring and analyzing architectural variations of two case studies: finite impulse response
Image processing of biological signals with computers
P. K. Singhal; V. R. Singh
1995-01-01
Image processing, with the help of digital computers, is gaining importance, day by day, especially in the medical fields. Diagnostic data from the human body is complex in nature and becomes difficult to analyse. Specialists use different techniques to get a clear picture of the human anatomy, but due to complexity of structure, it has been always difficult to interpret
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.
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.
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.
Techniques of EMG signal analysis: detection, processing, classification and applications
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
Simplified signal processing for an airborne CO2 Doppler lidar
NASA Technical Reports Server (NTRS)
Schwiesow, R. L.; Spowart, M. P.
1992-01-01
In the development of the National Center for Atmospheric Research (NCAR) airborne infrared lidar system (NAILS), we have emphasized a simple, modular design to suit the instrument to its mission of providing measurements of atmospheric structure and dynamics from an aircraft platform. Based on our research to this point, we believe that a significant simplification of the signal processing approach compared to that now used is possible by using high speed digitization of the signal. The purpose here is to place signal processing in the context of the overall system design and to explore the basis of the alternative technique so that the community can comment on the approach.
Correlation Spectroscopy of Minor Fluorescent Species: Signal Purification and Distribution Analysis
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
Microscopic realization of cross-correlated noise processes
Shit, Anindita; Banik, Suman Kumar; Chaudhuri, Jyotipratim Ray
2010-01-01
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.
Microscopic realization of cross-correlated noise processes.
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
Correlation Processing Of Local Seismic Data: Applications for Autonomous Sensor Deployments
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.
processing techniques such as denoising and detection typically model the wavelet coefficients as independent and image processing. The wavelet domain provides a natural setting for many applications involving real886 IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 46, NO. 4, APRIL 1998 Wavelet-Based Statistical
DESIGN OF A REAL-TIME DIGITAL SIGNAL PROCESSING AUDIO PROCESSING TECHNIQUE
Jagielski, Christopher
2012-04-24
, for taking me in as a research student and guiding me in this process with so much enthusiasm and support. vi NOMENCLATURE A/D Analog-to-Digital D/A Digital-to-Analog DSK Digital Signal Processing Starter Kit DSP Digital Signal Processing EVM... .................................................................. 4 Real-time DSP design considerations ............................................. 4 Motivation ....................................................................................... 6 Organization of the thesis...
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.
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.
Wavelet-Based Decompositions for Nonlinear Signal Processing Robert D. Nowak and Richard G. Baraniuk
Wavelet-Based Decompositions for Nonlinear Signal Processing Robert D. Nowak and Richard G and processing of real-world signals. This paper develops new signal decompositions for nonlinear analysis for the nonlinear signal decompositions. The nonlinear signal decompositions are also applied to signal processing
Publish date: 06/27/2011 ECE 4364: Digital Signal Processing
Gelfond, Michael
Publish date: 06/27/2011 ECE 4364: Digital Signal Processing Credit / Contact hours: 3 / 3 Course Signal Processing, 3E, Prentice Hall, 2009. Catalog description: An introduction to digital signal digital signal processing techniques to analyze discrete time signals and systems. 3. Apply digital signal
Genomic Signal Processing: Predicting Basic Molecular Biological Principles
NASA Astrophysics Data System (ADS)
Alter, Orly
2005-03-01
Advances in high-throughput technologies enable acquisition of different types of molecular biological data, monitoring the flow of biological information as DNA is transcribed to RNA, and RNA is translated to proteins, on a genomic scale. Future discovery in biology and medicine will come from the mathematical modeling of these data, which hold the key to fundamental understanding of life on the molecular level, as well as answers to questions regarding diagnosis, treatment and drug development. Recently we described data-driven models for genome-scale molecular biological data, which use singular value decomposition (SVD) and the comparative generalized SVD (GSVD). Now we describe an integrative data-driven model, which uses pseudoinverse projection (1). We also demonstrate the predictive power of these matrix algebra models (2). The integrative pseudoinverse projection model formulates any number of genome-scale molecular biological data sets in terms of one chosen set of data samples, or of profiles extracted mathematically from data samples, designated the ``basis'' set. The mathematical variables of this integrative model, the pseudoinverse correlation patterns that are uncovered in the data, represent independent processes and corresponding cellular states (such as observed genome-wide effects of known regulators or transcription factors, the biological components of the cellular machinery that generate the genomic signals, and measured samples in which these regulators or transcription factors are over- or underactive). Reconstruction of the data in the basis simulates experimental observation of only the cellular states manifest in the data that correspond to those of the basis. Classification of the data samples according to their reconstruction in the basis, rather than their overall measured profiles, maps the cellular states of the data onto those of the basis, and gives a global picture of the correlations and possibly also causal coordination of these two sets of states. Mapping genome-scale protein binding data using pseudoinverse projection onto patterns of RNA expression data that had been extracted by SVD and GSVD, a novel correlation between DNA replication initiation and RNA transcription during the cell cycle in yeast, that might be due to a previously unknown mechanism of regulation, is predicted. (1) Alter & Golub, Proc. Natl. Acad. Sci. USA 101, 16577 (2004). (2) Alter, Golub, Brown & Botstein, Miami Nat. Biotechnol. Winter Symp. 2004 (www.med.miami.edu/mnbws/alter-.pdf)
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.
Collaborative Signal and Information Processing: An Information-Directed Approach
Zhao Feng; Jie Liu; Juan Julia Liu; Leonidas J. Guibas; James Reich
2003-01-01
This article describes information-based ap- proaches to processing and organizing spatially distributed, multi-modal sensor data in a sensor network. Energy con- strained networked sensing systems must rely on collabora- tive signal and information processing (CSIP) to dynami- cally allocate resources, maintain multiple sensing foci, and attend to new stimuli of interest, all based on task require- ments and resource constraints.
A TWO-LEVEL RECONFIGURABLE ARCHITECTURE FOR DIGITAL SIGNAL PROCESSING
Delgado-Frias, José G.
A TWO-LEVEL RECONFIGURABLE ARCHITECTURE FOR DIGITAL SIGNAL PROCESSING Mitchell J. Myjak and José G processing (DSP). The architecture consists of a two-level array of cells and interconnections. DSP been fabricated using a modest 0.5-µm CMOS technology. Circuit simulations indicate that the cell
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.
Paris-Sud XI, Université de
1542 IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 58, NO. 3, MARCH 2010 ARMA Signals With Specified probability distri- bution of ARMA signals. By using a particular form of modeling such signals with random generation of ARMA signals with arbitrary specified marginal dis- tribution function. Their properties
Information processing and signal integration in bacterial quorum sensing
Mehta, Pankaj; Goyal, Sidhartha; Long, Tao; Bassler, Bonnie L; Wingreen, Ned S
2009-01-01
Bacteria communicate using secreted chemical signaling molecules called autoinducers in a process known as quorum sensing. The quorum-sensing network of the marine bacterium Vibrio harveyi uses three autoinducers, each known to encode distinct ecological information. Yet how cells integrate and interpret the information contained within these three autoinducer signals remains a mystery. Here, we develop a new framework for analyzing signal integration on the basis of information theory and use it to analyze quorum sensing in V. harveyi. We quantify how much the cells can learn about individual autoinducers and explain the experimentally observed input–output relation of the V. harveyi quorum-sensing circuit. Our results suggest that the need to limit interference between input signals places strong constraints on the architecture of bacterial signal-integration networks, and that bacteria probably have evolved active strategies for minimizing this interference. Here, we analyze two such strategies: manipulation of autoinducer production and feedback on receptor number ratios. PMID:19920810
Li, Xuefeng, E-mail: lixfpost@163.com [School of Science, Xi'an University of Post and Telecommunications, Xi'an, 710121 (China)] [School of Science, Xi'an University of Post and Telecommunications, Xi'an, 710121 (China); Cao, Guangzhan; Liu, Hongjun [Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, 710119 (China)] [Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, 710119 (China)
2014-04-15
Based on solving numerically the generalized nonlinear Langevin equation describing the nonlinear dynamics of stochastic resonance by Fourth-order Runge-Kutta method, an aperiodic stochastic resonance based on an optical bistable system is numerically investigated. The numerical results show that a parameter-tuning stochastic resonance system can be realized by choosing the appropriate optical bistable parameters, which performs well in reconstructing aperiodic signals from a very high level of noise background. The influences of optical bistable parameters on the stochastic resonance effect are numerically analyzed via cross-correlation, and a maximum cross-correlation gain of 8 is obtained by optimizing optical bistable parameters. This provides a prospective method for reconstructing noise-hidden weak signals in all-optical signal processing systems.
NASA Astrophysics Data System (ADS)
Li, Xuefeng; Cao, Guangzhan; Liu, Hongjun
2014-04-01
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.
Field-quadrature and photon-number correlations produced by parametric processes.
McKinstrie, C J; Karlsson, M; Tong, Z
2010-09-13
In a previous paper [Opt. Express 13, 4986 (2005)], formulas were derived for the field-quadrature and photon-number variances produced by multiple-mode parametric processes. In this paper, formulas are derived for the quadrature and number correlations. The number formulas are used to analyze the properties of basic devices, such as two-mode amplifiers, attenuators and frequency convertors, and composite systems made from these devices, such as cascaded parametric amplifiers and communication links. Amplifiers generate idlers that are correlated with the amplified signals, or correlate pre-existing pairs of modes, whereas attenuators decorrelate pre-existing modes. Both types of device modify the signal-to-noise ratios (SNRs) of the modes on which they act. Amplifiers decrease or increase the mode SNRs, depending on whether they are operated in phase-insensitive (PI) or phase-sensitive (PS) manners, respectively, whereas attenuators always decrease these SNRs. Two-mode PS links are sequences of transmission fibers (attenuators) followed by two-mode PS amplifiers. Not only do these PS links have noise figures that are 6-dB lower than those of the corresponding PI links, they also produce idlers that are (almost) completely correlated with the signals. By detecting the signals and idlers, one can eliminate the effects of electronic noise in the detectors. PMID:20940873
Optimization of Signal Processing Algorithms Raza Ahmed and Brian L. Evans
Evans, Brian L.
algorithms. Our prototype environment is written in Mathematica. 1 Introduction We optimize signal processingOptimization of Signal Processing Algorithms Raza Ahmed and Brian L. Evans razaa implementations of one-dimensional and multidimensional signal processing algorithms by rewriting subexpressions
Modelling coloured residual noise in gravitational-wave signal processing
Christian Röver; Renate Meyer; Nelson Christensen
2010-12-12
We introduce a signal processing model for signals in non-white noise, where the exact noise spectrum is a priori unknown. The model is based on a Student's t distribution and constitutes a natural generalization of the widely used normal (Gaussian) model. This way, it allows for uncertainty in the noise spectrum, or more generally is also able to accommodate outliers (heavy-tailed noise) in the data. Examples are given pertaining to data from gravitational wave detectors.
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.
Reconfigurable Computing for Digital Signal Processing: A Survey
Russell Tessier; Wayne Burleson
2001-01-01
Abstract. Steady advances in VLSI technology and design tools have extensively expanded,the application do- main of digital signal processing over the past decade. While application-specific integrated circuits (ASICs) and programmable,digital signal processors (PDSPs) remain the implementation,mechanisms,of choice for many,DSP applications, increasingly new system implementations based on reconfigurable computingare being considered. These flexible platforms, which offer the functional efficiency of hardware
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.
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.
Methods for the digital processing and transmission of speech signals
NASA Astrophysics Data System (ADS)
Nazarov, M. V.; Prokhorov, Iu. N.
Methods for increasing the efficiency of digital speech transmission systems are examined. In particular, attention is given to probabilistic models of speech signals, digital representation of speech, and digital processing (parameter evaluations, filtering, prediction, and detection) of speech signals in systems with pulse-code modulation (PCM), delta modulation, and differential PCM, as well as in vocoders. The dispersion of the effective estimates of the parameters and the relative noise immunity of speech signals are assessed. Results of experimental studies of various speech transmission systems are reported.
Fyhn, Karsten; Larsen, Torben; Jensen, Sřren Holdt
2011-01-01
To lower the sampling rate in a spread spectrum communication system using Direct Sequence Spread Spectrum (DSSS), we show that compressive signal processing can be applied to demodulate the received signal. This may lead to a decrease in power consumption in wireless receivers using spread spectrum technology. In classical compressive sensing, the receiver must mix the received signal with a pseudo-random noise signal. Our receiver structure does not require this, as we exploit the spreading of the signal already done in the transmitter. Our theoretical work is exemplified with a numerical experiment using the IEEE 802.15.4 standard and the 2.4 GHz band specification. The numerical results support our theoretical findings and indicate that compressive sensing may be used successfully in spread spectrum communication systems. The penalty is the noise folding that occurs.
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.
Extraction of low frequency signals from cross-correlations of the infrasonic ambient noise
NASA Astrophysics Data System (ADS)
Landčs, Matthieu; Shapiro, Nikolaď; 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.
DOA estimation from temporally and spatially correlated narrowband signals with noncircular sources
Sonia Ben Hassen; Faouzi Bellili; Abdelaziz Samet; Sofiene Affes
2011-01-01
In this paper, we develop for the first time a method of estimating the DOA parameters assuming noncircular and spatially and temporally correlated signals. The new approach is based on the two-sided IV-SSF method (instrumental variable signal with subspace fitting). It will be shown that our newly developed method outperforms the classical two-sided IV-SSF in terms of lower bias and
Detectors and signal processing for high-energy physics
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.
Overview of seismic signal conversion and processing operations
Lum, P.K.
1991-03-01
URS/John A. Blume & Associates, Engineers (URS/Blume) is assigned by the US Department of Energy the responsibility of providing support to the safety program of the Nevada Operations Office (DOE-NV) with respect to documentation of seismic motion and evaluation of the effects of ground motion on structures and facilities. In this capacity, URS/Blume conducts a seismic documentation program with the primary objective of measuring, for analysis and evaluation, the ground structural response motion resulting from underground nuclear explosions (here called events), principally at the Nevada Test Site (NTS). This report gives a brief overview of the current operation and other related functions for processing seismic signals such as: basic information on the seismic recording systems and stations; a brief description of hardware, hardware configurations, and software; data formats; processing techniques used to convert seismic signals to computer compatible format; signal reduction and processing; and data controls. 12 refs., 7 figs., 3 tabs.
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).
An implementation of signal processing algorithms for ultrasonic NDE
Ericsson, L.; Stepinski, T. [Uppsala Univ. (Sweden). Dept. of Technology, Circuits and Systems
1994-12-31
Probability of detection flaws during ultrasonic pulse-echo inspection is often limited by the presence of backscattered echoes from the material structure. A digital signal processing technique for removal of this material noise, referred to as split spectrum processing (SSP), has been developed and verified using laboratory experiments during the last decade. The authors have performed recently a limited scale evaluation of various SSP techniques for ultrasonic signals acquired during the inspection of welds in austenitic steel. They have obtained very encouraging results that indicate promising capabilities of the SSP for inspection of nuclear power plants. Thus, a more extensive investigation of the technique using large amounts of ultrasonic data is motivated. This analysis should employ different combinations of materials, flaws and transducers. Due to the considerable number of ultrasonic signals required to verify the technique for future practical use, a custom-made computer software is necessary. At the request of the Swedish nuclear power industry the authors have developed such a program package. The program provides a user-friendly graphical interface and is intended for processing of B-scan data in a flexible way. Assembled in the program are a number of signal processing algorithms including traditional Split Spectrum Processing and the more recent Cut Spectrum Processing algorithm developed by them. The program and some results obtained using the various algorithms are presented in the paper.
Wavelet-based correlations of impedance cardiography signals and heart rate variability
NASA Astrophysics Data System (ADS)
Podtaev, Sergey; Dumler, Andrew; Stepanov, Rodion; Frick, Peter; Tziberkin, Kirill
2010-04-01
The wavelet-based correlation analysis is employed to study impedance cardiography signals (variation in the impedance of the thorax z(t) and time derivative of the thoracic impedance (- dz/dt)) and heart rate variability (HRV). A method of computer thoracic tetrapolar polyrheocardiography is used for hemodynamic registrations. The modulus of wavelet-correlation function shows the level of correlation, and the phase indicates the mean phase shift of oscillations at the given scale (frequency). Significant correlations essentially exceeding the values obtained for noise signals are defined within two spectral ranges, which correspond to respiratory activity (0.14-0.5 Hz), endothelial related metabolic activity and neuroendocrine rhythms (0.0095-0.02 Hz). Probably, the phase shift of oscillations in all frequency ranges is related to the peculiarities of parasympathetic and neuro-humoral regulation of a cardiovascular system.
Signaling pathways of PDZ2 domain: A molecular dynamics Interaction Correlation Analysis
Kong, Yifei; Karplus, Martin
2008-01-01
PDZ domains are found in many signaling proteins. One of their functions is to provide scaffolds for forming membrane-associated protein complexes by binding to the carboxyl termini of its partners. PDZ domains are thought to play a signal transduction role by propagating the information that binding has occurred to remote sites. In the current study, a molecular dynamics simulation based approach, referred to an interaction correlation analysis, is applied to the PDZ2 domain to identity the possible signal transduction pathways. A residue correlation matrix is constructed from the interaction energy correlation between all residue pairs obtained from the molecular dynamics simulations. Two continuous interaction pathways, starting at the ligand binding pocket, are identified by a hierarchical clustering analysis of the residue correlation matrix. One pathway is mainly localized at the N terminal side of helix ?1 and the adjacent C terminus of loop ?1–?2. The other pathway is perpendicular to the central ? sheet toward the side of PDZ2 domain opposite to the ligand binding pocket. The present results extend previous studies based on multiple sequence analysis, NMR and molecular dynamics simulations. Importantly, they reveal the energetic origin of the long-range coupling. The PDZ2 results, as well as the earlier rhodopsin analysis, show that the interaction correlation analysis is a robust approach for determining pathways of intramolecular signal transduction. PMID:18618698
ISLE (Image and Signal Processing LISP Environment) reference manual
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.
R e p r i n t e d f r o m Signal Processing 66 (1998) 203-217
1998-01-01
: Signal Theory, Stochastic Processes, Detection and Estimation, Spectral Analysis, Filtering, Signal Technology, Speech Processing, Radar Signal Process- ing, Sonar Signal Processing, Special Signal ProcessingR e p r i n t e d f r o m SIGNAL PROCESSING Signal Processing 66 (1998) 203-217 A noise robust
Integrated optic modules for multichannel deflection/switching and signal processing
NASA Astrophysics Data System (ADS)
Tsai, Chen S.
1986-07-01
This report describes the investigation and realization of a number of new hybrid integrated optic device modules in LiNbO3 waveguides under the sponsorship of the Army Research Office. All of these device modules possess the desirable characteristics of very large bandwidth (GHz or higher), very small substrate size along the optical path (typically 1.5 cm), single-mode optical propagation, and low drive power requirement. The devices utilize either acoustooptic or electrooptic 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 processings, communications, and computing. Some of the specific applications include correlation of RF signals, fiber-optic sensing, optical systollic array computing and multiport switching/routing, and analog-to-digital conversion of wideband RF signal.
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.
Optical signal acquisition and processing in future accelerator diagnostics
Jackson, G.P. (Fermi National Accelerator Lab., Batavia, IL (United States)); Elliott, A. (Illinois Univ., Chicago, IL (United States))
1992-01-01
Beam detectors such as striplines and wall current monitors rely on matched electrical networks to transmit and process beam information. Frequency bandwidth, noise immunity, reflections, and signal to noise ratio are considerations that require compromises limiting the quality of the measurement. Recent advances in fiber optics related technologies have made it possible to acquire and process beam signals in the optical domain. This paper describes recent developments in the application of these technologies to accelerator beam diagnostics. The design and construction of an optical notch filter used for a stochastic cooling system is used as an example. Conceptual ideas for future beam detectors are also presented.
Optical signal acquisition and processing in future accelerator diagnostics
Jackson, G.P. [Fermi National Accelerator Lab., Batavia, IL (United States); Elliott, A. [Illinois Univ., Chicago, IL (United States)
1992-12-31
Beam detectors such as striplines and wall current monitors rely on matched electrical networks to transmit and process beam information. Frequency bandwidth, noise immunity, reflections, and signal to noise ratio are considerations that require compromises limiting the quality of the measurement. Recent advances in fiber optics related technologies have made it possible to acquire and process beam signals in the optical domain. This paper describes recent developments in the application of these technologies to accelerator beam diagnostics. The design and construction of an optical notch filter used for a stochastic cooling system is used as an example. Conceptual ideas for future beam detectors are also presented.
Atmospheric Radar Signal Processing using Bivariate Empirical Mode Decomposition
NASA Astrophysics Data System (ADS)
Sreenivasulu Reddy, Thatiparthi
2012-07-01
This paper is based upon the analysis of real-time data collected from the MST radar, NARL, CityplaceGadanki, country-regionIndia. We apply a new method, Bivariate Empirical Mode Decomposition (BEMD), to the complex time series data for estimating the Doppler frequencies and thus find the parameters like zonal (u), meridonal (v) and Vertical Wind speed (w) etc. BEMD is an algorithm for the analysis of multicomponent signals that breaks them down into a number of amplitude and frequency modulated signals, termed as Intrinsic Mode Functions (IMFs), which are basis functions for representing the signal. In a noisy signal, decomposed IMFs are a combination of IMFs of both signal and noise. By comparing with the characteristics of noise-only IMFs, we will remove the noise-dominant IMFs from the noisy signal. We reconstruct the signal with remaining IMFs and thus denoising the signal. Due to the adaptive nature of the basis functions, EMD is ideally suited than any other method like the Spectrogram, Wavelet etc for analyzing nonlinear and non-stationary processes. Initially, we apply BEMD for simulated signals such as Doppler, Bumps etc. under various noise conditions and then apply the same for the radar data. Results have been validated using Global Positioning System Sonde data. Finally, we classify the noise as Gaussian or not associated with the radar signal received form vertical as well as non vertical directions in the higher bins of the atmosphere using different parameters like Skewness, Kurtosis, Negentropy (Syntropy) and incorporating some tests such as Autocorrelation test, Power Spectral Density test, Partial Autocorrelation test.
Diffraction tomographic signal processing algorithms for tunnel detection
Witten, A.J.
1993-08-01
Signal processing algorithms have been developed for wave based imaging using diffraction tomography. The basis for this image reconstruction procedure is the generalized projection slice theorem (GPST) which, for homogeneous waves, is an analytic relationship between the spatial Fourier transform of the acquired data and the spatial Fourier transform of the spatial profile (object function) of the object being imaged. Imaging within geophysical diffraction tomography when only homogeneous waves are considered can then be accomplished by inversion of the GPST using standard numerical techniques. In an attenuating background medium or when eddy currents or static fields are considered, a generalized GPST can be derived that involves both real and complex spatial frequencies. In this case, direct Fourier inversion is not possible because of the presence of the complex frequencies. Although direct inversion and, hence, complete imaging is not possible for such cases, the generalized CPST`S can be used to analytically shift the location of data templates matched to specified targets and these templates can, in turn, be correlated with acquired data to detect and estimate the location of the specified targets. Since GPST`s are used directly in the detection problem, there is no need to numerically invert the intergal transform of the object function. For this reason, target detection can be accomplished in a computationally efficient manner independent of the type of measurement or background geologic conditions. A number of GPST`s are derived and the use of GPST`s for both imaging and detection of subsurface voids is demonstrated in several recent applications.
Calcium Signals: The Lead Currency of Plant Information Processing
Kudla, Jörg; Batisti?, Oliver; Hashimoto, Kenji
2010-01-01
Ca2+ signals are core transducers and regulators in many adaptation and developmental processes of plants. Ca2+ signals are represented by stimulus-specific signatures that result from the concerted action of channels, pumps, and carriers that shape temporally and spatially defined Ca2+ elevations. Cellular Ca2+ signals are decoded and transmitted by a toolkit of Ca2+ binding proteins that relay this information into downstream responses. Major transduction routes of Ca2+ signaling involve Ca2+-regulated kinases mediating phosphorylation events that orchestrate downstream responses or comprise regulation of gene expression via Ca2+-regulated transcription factors and Ca2+-responsive promoter elements. Here, we review some of the remarkable progress that has been made in recent years, especially in identifying critical components functioning in Ca2+ signal transduction, both at the single-cell and multicellular level. Despite impressive progress in our understanding of the processing of Ca2+ signals during the past years, the elucidation of the exact mechanistic principles that underlie the specific recognition and conversion of the cellular Ca2+ currency into defined changes in protein–protein interaction, protein phosphorylation, and gene expression and thereby establish the specificity in stimulus response coupling remain to be explored. PMID:20354197
Simmonds, Benjamin; Chacron, Maurice J.
2015-01-01
Correlations between the activities of neighboring neurons are observed ubiquitously across systems and species and are dynamically regulated by several factors such as the stimulus' spatiotemporal extent as well as by the brain's internal state. Using the electrosensory system of gymnotiform weakly electric fish, we recorded the activities of pyramidal cell pairs within the electrosensory lateral line lobe (ELL) under spatially localized and diffuse stimulation. We found that both signal and noise correlations were markedly reduced (>40%) under the latter stimulation. Through a network model incorporating key anatomical features of the ELL, we reveal how activation of diffuse parallel fiber feedback from granule cells by spatially diffuse stimulation can explain both the reduction in signal as well as the reduction in noise correlations seen experimentally through independent mechanisms. First, we show that burst-timing dependent plasticity, which leads to a negative image of the stimulus and thereby reduces single neuron responses, decreases signal but not noise correlations. Second, we show trial-to-trial variability in the responses of single granule cells to sensory input reduces noise but not signal correlations. Thus, our model predicts that the same feedback pathway can simultaneously reduce both signal and noise correlations through independent mechanisms. To test this prediction experimentally, we pharmacologically inactivated parallel fiber feedback onto ELL pyramidal cells. In agreement with modeling predictions, we found that inactivation increased both signal and noise correlations but that there was no significant relationship between magnitude of the increase in signal correlations and the magnitude of the increase in noise correlations. The mechanisms reported in this study are expected to be generally applicable to the cerebellum as well as other cerebellum-like structures. We further discuss the implications of such decorrelation on the neural coding strategies used by the electrosensory and by other systems to process natural stimuli. PMID:25569283
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.
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.
Timashev, Serge F; Polyakov, Yuriy S; Demin, Sergey A; Kaplan, Alexander Ya
2011-01-01
We apply flicker-noise spectroscopy (FNS), a time series analysis method operating on structure functions and power spectrum estimates, to study the clinical electroencephalogram (EEG) signals recorded in children/adolescents (11 to 14 years of age) with diagnosed schizophrenia-spectrum symptoms at the National Center for Psychiatric Health (NCPH) of the Russian Academy of Medical Sciences. The EEG signals for these subjects were compared with the signals for a control sample of chronically depressed children/adolescents. The purpose of the study is to look for diagnostic signs of subjects' susceptibility to schizophrenia in the FNS parameters for specific electrodes and cross-correlations between the signals simultaneously measured at different points on the scalp. Our analysis of EEG signals from scalp-mounted electrodes at locations F3 and F4, which are symmetrically positioned in the left and right frontal areas of cerebral cortex, respectively, demonstrates an essential role of frequency-phase synchroniz...
Calculation of impulse response to a pseudo-random binary signal in a two stirred tank process
F. P. Schlosser
1973-01-01
A simple heat transfer process assembled for various studies of automated process control in the laboratory was selected to determine if the pseudo random binary signals transmitted to a heater in a stirred tank would produce a variation in the temperature of the water in a second stirred tank, such that the temperature could be correlated to the heat input
Analysis of signal processing techniques in pulsed thermography
NASA Astrophysics Data System (ADS)
Lopez, Fernando; Ibarra-Castanedo, Clemente; Maldague, Xavier; de Paulo Nicolau, Vicente
2013-05-01
Pulsed Thermography (PT) is one of the most widely used approaches for the inspection of composites materials, being its main attraction the deployment in transient regime. However, due to the physical phenomena involved during the inspection, the signals acquired by the infrared camera are nearly always affected by external reflections and local emissivity variations. Furthermore, non-uniform heating at the surface and thermal losses at the edges of the material also represent constraints in the detection capability. For this reason, the thermographics signals should be processed in order to improve - qualitatively and quantitatively - the quality of the thermal images. Signal processing constitutes an important step in the chain of thermal image analysis, especially when defects characterization is required. Several of the signals processing techniques employed nowadays are based on the one-dimensional solution of Fourier's law of heat conduction. This investigation brings into discussion the three-most used techniques based on the 1D Fourier's law: Thermographic Signal Reconstruction (TSR), Differential Absolute Contrast (DAC) and Pulsed Phase Thermography (PPT), applied on carbon fiber laminated composites. It is of special interest to determine the detection capabilities of each technique, allowing in this way more reliable results when performing an inspection by PT.
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.
Monitoring Signaling Processes in Living Cells Using Biosensors
NSDL National Science Digital Library
Klaus Hahn (Scripps Research Institute; Department of Cell Biology; REV)
2003-10-21
This collection of nine animations shows how different types of biosensors report changes in cellular processes through the production of a visually detectable signal. Biosensors can be created by attaching one or more fluorescent proteins (such as green fluorescent protein) to a target protein or peptide or by attaching a fluorescent dye that is sensitive to its environment to a protein or peptide. Conformational changes in proteins in response to ligand binding, changes in the concentration of cellular metabolites or signaling messengers, changes in protein localization, and changes in protein activity or covalent modification can all be detected with biosensors. These animations can be used separately or together to illustrate how molecular biology, chemistry, and microscopy have converged to allow cellular processes to be visualized in living cells. Several of the animations describe the production of a fluorescent resonance energy transfer (FRET) signal.
Signal processing and physiological modeling--part 1: Surface analysis.
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
Compendium of digital signal processing Lapo Boschi (lapo.boschi@upmc.fr)
Boschi, Lapo
Compendium of digital signal processing Lapo Boschi (lapo.boschi@upmc.fr) August 31, 2014 time. A system is any process that produces an output signal in response to an input signal: Terminology for signals and systems. A system is any process that generates an output signal, e.g. y(t) or y
FPGA-Based Filterbank Implementation for Parallel Digital Signal Processing 1
De Leon, Phillip
5.1.1 FPGA-Based Filterbank Implementation for Parallel Digital Signal Processing 1 Stephan Berner 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
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).
NASA Technical Reports Server (NTRS)
Couvillon, L. A., Jr.; Carl, C.; Goldstein, R. M.; Posner, E. C.; Green, R. R. (inventors)
1973-01-01
A method and apparatus are described for synchronizing a received PCM communications signal without requiring a separate synchronizing channel. The technique provides digital correlation of the received signal with a reference signal, first with its unmodulated subcarrier and then with a bit sync code modulated subcarrier, where the code sequence length is equal in duration to each data bit.
Correlator mixing and mass reduction as signals of chiral symmetry restoration
Paris-Sud XI, Université de
Correlator mixing and mass reduction as signals of chiral symmetry restoration April 28, 1999 J Chiral symmetry restoration in a dense medium is to some extent a consequence of the nuclear pion cloud contribution associated with chi- ral symmetry restoration. Using the quark-meson coupling model we find
GRAPE: a CASE tool for digital signal parallel processing
Rudy Lauwereins; Marc Engels; J. Peperstraete; E. Steegmans; J. Van Ginderdeuren
1990-01-01
The use of computer-aided software engineering (CASE) tools for stream-oriented real-time digital signal processing (DSP) applications is discussed. These applications are characterized by a continuous stream of data samples or a continuous stream of blocks of data samples arriving at the processing facility at time instances completely determined by the outside world. An overview of existing development tools for DSP
A Communication Interface for Multiprocessor Signal Processing Systems
Sankalita Saha; Shuvra S. Bhattacharyya; Wayne Wolf
2006-01-01
Parallelization of embedded software is often desir- able for power\\/performance-related considerations for computation-intensive applications that frequently occur in the signal-processing domain. Although hardware support for parallel computation is increasingly available in embed- ded processing platforms, there is a distinct lack of effec- tive software support. One of the most widely known ef- forts in support of parallel software is the
A rapid prototyping framework for audio signal processing algorithms
N. VoB; T. Eisenbach; B. Mertsching
2004-01-01
We present a rapid-prototyping environment for functional verification and test of digital signal processing algorithms. The environment consists of a Virtex-ll device on a PCI-card and an appropriate generic software backend which is used to pre- and post-process the data and to transfer it to the FPGA and pull the results from it. It is designed to meet real-time requirements
Social Signal Processing: Understanding Social Interactions through Nonverbal Behavior Analysis
Vinciarelli, Alessandro
Social Signal Processing: Understanding Social Interactions through Nonverbal Behavior Analysis A), the domain aimed at automatic understanding of social in- teractions through analysis of nonverbal behavior, nonverbal behavior analysis is used as a key to automatic understanding of social interactions. This pa- per
IEEE SIGNAL PROCESSING MAGAZINE6 September 2004 leadership reflections
Nehorai, Arye
IEEE SIGNAL PROCESSING MAGAZINE6 September 2004 leadership reflections ntellect and timing are both major factors in our careers. There are those who are extremely bright, have the good fortune of being in our careers. There are those who are extremely bright, have the good fortune of being in the right
Signal Processing Algorithms for Ultra-Wideband Wireless Communications
Langendoen, Koen
. . . . . . . . . . . . . . . . . . 12 2.1.2 Standardization and applications . . . . . . . . . . . . . . . . . 14 2.1.3 UWB channelsSignal Processing Algorithms for Ultra-Wideband Wireless Communications PROEFSCHRIFT ter to Ultra-Wideband Radio . . . . . . . . . . . . . . . . 11 2.1.1 Impulse Radio Ultra-Wideband
Signal processing in scanning thermoacoustic tomography in biological tissues
Wang, Lihong
Signal processing in scanning thermoacoustic tomography in biological tissues Yuan Xu and Lihong V Microwave-induced thermoacoustic tomography was explored to image biological tissues. Short microwave pulses-induced thermoacoustic waves were detected with a focused ultrasonic transducer to obtain two-dimensional tomographic
RO module RTD analyses based on directly processing conductivity signals
Qingfeng Yang; Alexander Drak; David Hasson; Raphael Semiat
2007-01-01
Residence time distribution (RTD) techniques can be used to diagnose the flow characteristics in spiral wound reverse osmosis (RO) modules. However, the methods of processing tracer response conductivity signals and mathematically modeling of RTD curves often involve complicated steps including conductivity-concentration transformation, baseline selection and the use of exit age distribution function of Et, or dimensionless exit age distribution function
Robust Microphone Array Signal Processing against Diffuse Noise
Paris-Sud XI, Université de
Robust Microphone Array Signal Processing against Diffuse Noise ( ) Nobutaka Ito tel-00691931 Introduction 1 1.1 Motivation for noise suppression and direction-of-arrival estimation . . . . . 1 1 2 Tasks Considered and State of the Art 6 2.1 Definition of noise suppression and direction
Diffraction tomographic signal processing algorithms for tunnel detection
1993-01-01
Signal processing algorithms have been developed for wave based imaging using diffraction tomography. The basis for this image reconstruction procedure is the generalized projection slice theorem (GPST) which, for homogeneous waves, is an analytic relationship between the spatial Fourier transform of the acquired data and the spatial Fourier transform of the spatial profile (object function) of the object being imaged.
STATISTICAL SIGNAL PROCESSING FOR AUTOMOTIVE SAFETY SYSTEMS Fredrik Gustafsson
Gustafsson, Fredrik
STATISTICAL SIGNAL PROCESSING FOR AUTOMOTIVE SAFETY SYSTEMS Fredrik Gustafsson Department The amount of software in general and safety systems in particular increases rapidly in the automotive- cessing area. 1. INTRODUCTION Henry Ford revolutionized the automotive industry more than 100 years ago
CORDIC-based VLSI architectures for digital signal processing
Y. H. Hu
1992-01-01
The evolution of CORDIC, an iterative arithmetic computing algorithm capable of evaluating various elementary functions using a unified shift-and-add approach, and of CORDIC processors is reviewed. A method to utilize a CORDIC processor array to implement digital signal processing algorithms is presented. The approach is to reformulate existing DSP algorithms so that they are suitable for implementation with an array
Bioimaging: A new frontier area for signal processing research
J.-C. Olivo-Marin
2009-01-01
It is now a common consensus that in-depth understanding of biological systems requires robust and systematic quantification of their spatiotemporal characteristics. This endeavour has been significantly enlightened over the past decades thanks to the numerous advances in fluorescent probes, labeling techniques and microscopy systems. It is likewise a consensus that more powerful and specific signal\\/image processing methods are henceforth required
VOLUME 7, ISSUE 3 JULY 2011 Signal Processing in Acoustics
Jaffe, Jules
VOLUME 7, ISSUE 3 JULY 2011 Signal Processing in Acoustics Acoustics Today A publication of the Acoustical Society of America Model-Based Ocean Acoustics Physical and Engineering Acoustics Speech have been applied to data with biological origins: "Three-dimensional passive acoustic localization
Signal processing in medical imaging and image-guided intervention
Milan Sonka
2011-01-01
Thisis an introductionto a specialsession ofICASSP devoted to signalprocessing techniquesin medicalimagingand image analysis that consists of this introduction and 5 research presentations, each addressingone aspect of the medicalimaging field in which signal processing plays an irreplaceable role. The topics cover a broad spectrum of medical imaging problems from image acquisition to image analysis to populationbased anatomical modeling. The focus is
Adventures in Radio Astronomy Instrumentation and Signal Processing
Masci, Frank
using radio telescopes. Modern radio telescopes have significant digital signal processing demands of spectrometers for enabling improved pulsar2 sci- ence on the Allen Telescope Array, the Hartebeesthoek Radio Observatory telescope, the Nan¸cay Radio Telescope, and the Parkes Radio Telescope. We also present work
Adventures in Radio Astronomy Instrumentation and Signal Processing
California at Berkeley, University of
- tizing and processing analogue astronomical signals collected using radio telescopes. Modern radio pulsar2 sci- ence on the Allen Telescope Array, the Hartebeesthoek Radio Observatory telescope, the Nan¸cay Radio Telescope, and the Parkes Radio Telescope. We also present work that we conducted
Software synthesis and code generation for signal processing systems
S. S. Bhartacharyya; Rainer Leupers; Peter Marwedel
2000-01-01
The role of software is becoming increasingly important in the implementation of digital signal processing (DSP) applications. As this trend intensifies, and the complexity of applications escalates, we are seeing an increased need for automated tools to aid in the development of DSP software. This paper reviews the state of the art in programming language and compiler technology for DSP
A Signal Processing View on Packet Sampling and Anomaly Detection
Boyer, Edmond
of packet sampling, before using sampled data for networking applications. The effect of sampling that are involved in data preprocessing and anomaly detection. As mentioned before, packet sampling is applied1 A Signal Processing View on Packet Sampling and Anomaly Detection Daniela Brauckhoff, Kave
Deep Learning and Its Applications to Signal and Information Processing
Dong Yu; Li Deng
2011-01-01
INTRODUCTION TO DEEP LEARNING Many traditional machine learning and signal processing techniques exploit shallow architectures, which contain a single layer of nonlinear feature transformation. Examples of shallow architectures are conventional hidden Markov models (HMMs), linear or nonlinear dynamical systems, conditional random fields (CRFs), maximum entropy (MaxEnt) models, support vector machines (SVMs), kernel regression, and multilayer perceptron (MLP) with a single
Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing
Gabbouj, Moncef
Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2009 dominant colors that are prominent in a visual scenery is of utmost importance since the human visual basic categories. In [2], Mojsilovi´c et al. performed a series of psychophysical experiments analyzing
Hindawi Publishing Corporation EURASIP Journal on Applied Signal Processing
Reisslein, Martin
of the video. The video bit stream allows for transmission experiments from which the visual qualityHindawi Publishing Corporation EURASIP Journal on Applied Signal Processing Volume 2006, Article ID 42083, Pages 121 DOI 10.1155/ASP/2006/42083 A Framework for Advanced Video Traces: Evaluating Visual
Genomic Signal Processing: From Matrix Algebra to Genetic Networks
Utah, University of
#12;2 Genomic Signal Processing: From Matrix Algebra to Genetic Networks Orly Alter Summary DNA integrative model. These models provide mathematical descriptions of the genetic networks that generate. These models are illustrated in the analyses of RNA expression data from yeast and human during their cell
Signal processing and waveform selection strategies in multistatic radar systems
Ivan Bradaric; Gerard T. Capraro; Michael C. Wicks; Peter Zulch
2007-01-01
The multistatic ambiguity function has recently been used as a tool for analyzing multistatic radar systems. It was demonstrated that the multistatic ambiguity function with proper analytical foundation and corresponding graphic representation can serve as a guideline for developing multistatic radar signal processing rules. In this work we use this newly developed approach to combine optimal selection of weights for
Metamaterials for threat reduction applications: imaging, signal processing, and cloaking
Metamaterials for threat reduction applications: imaging, signal processing, and cloaking R. D structured materials, termed metamaterials (MM), has dramati- cally expanded our view of electromagnetic with metamaterials provides a promising approach--from a device perspective--towards fill- ing this gap
Simulation on large scale of acoustic signals for array processing
Boyer, Edmond
. Traditional simulators are often based on ray tracing and aggregation [1]. With such an approach, the energySimulation on large scale of acoustic signals for array processing Gerard Llort-Pujol, Christophe relies on the use of acoustic rays but adds a volume description of the propagation by building tubes
Data wordlength reduction for low-power signal processing software
Kyungtae Han; Brian L. Evans
2004-01-01
Reducing power consumption prolongs battery life and increases integration. In digital CMOS designs, switching activity is closely connected with the total power consumption. Switching activity on programmable processors implementing linear filters, fast Fourier transforms, and other signal processing operations is dominated by the hardware multiplier. In this paper, we employ wordlength reduction of multiplicands to reduce switching activity in hardware
Optoelectronic signal processing using finite impulse response neural networks
Paulo Eduardo H. B. Xavier da Silveira
2001-01-01
This thesis investigates the use of finite impulse response neural network as the computational algorithm for efficient optoelectronic signal processing. The study begins with the analysis and development of different suitable algorithms, followed by the optoelectronic design of single-layer and multi-layer architectures, and it is concluded with the presentation of the results of a successful experimental implementation. First, finite impulse
Signal processing in the cochlea: The structure equations
2011-01-01
Background Physical and physiological invariance laws, in particular time invariance and local symmetry, are at the outset of an abstract model. Harmonic analysis and Lie theory are the mathematical prerequisites for its deduction. Results The main result is a linear system of partial differential equations (referred to as the structure equations) that describe the result of signal processing in the cochlea. It is formulated for phase and for the logarithm of the amplitude. The changes of these quantities are the essential physiological observables in the description of signal processing in the auditory pathway. Conclusions The structure equations display in a quantitative way the subtle balance for processing information on the basis of phase versus amplitude. From a mathematical point of view, the linear system of equations is classified as an inhomogeneous - equation. In suitable variables the solutions can be represented as the superposition of a particular solution (determined by the system) and a holomorphic function (determined by the incoming signal). In this way, a global picture of signal processing in the cochlea emerges. PMID:22656650
Applets for Chromatography, Signal Processing and General Analytical Chemistry
NSDL National Science Digital Library
This site offers Java-based applets as organized in 4 categories: analytical and general chemistry, instrumental chemical analysis, instrumentation/signal processing, data analysis/chemometrics. Each applet includes a short introduction followed by a user controlled input of experimental conditions, such as seen for diffusion in electrochemistry.
Real-Time Convex Optimization in Signal Processing
Jacob Mattingley; Stephen Boyd
2010-01-01
This article shows the potential for convex optimization methods to be much more widely used in signal processing. In particular, automatic code generation makes it easier to create convex optimization solvers that are made much faster by being designed for a specific problem family. The disciplined convex programming framework that has been shown useful in transforming problems to a standard
INTRODUCTION TO RADAR SIGNAL & DATA PROCESSING : THE OPPORTUNITY
A. Farina
1. SUMMARY This paper introduces to the lecture series dedicated to the knowledge-based radar signal and data processing. Knowledge-based expert system (KBS) is in the realm of artificial intelligence. KBS consists of a knowledge base containing information specific to a problem domain and an inference engine that employs reasoning to yield decisions. KBS have been built: some are very complex
Signal processing and data acquisition for hybrid pixel detectors
A. W. Lynch; S. Tjoa; A. Berry
2009-01-01
The hardware, firmware and software required to perform digital signal processing and data acquisition for a prototype pixelated cadmium zinc telluride (CZT) nuclear spectroscopic detector developed at the Monash Centre for Synchrotron Science has been implemented and assessed. The system uses a modular PCI-Card design incorporating a CycloneIIż FPGA with three daughter boards facilitating analogue or digital interfaces. This system
Signal processing for passive impact damage detection in composite structures
Pietro Pedemonte; Wieslaw J. Staszewski; Francesco Aymerich; Mike S. Found; Pierluigi Priolo
2001-01-01
The problem of impact damage detection in composite structures using piezoceramic sensors is addressed. Piezoceramic sensors are bonded on the composite specimen and used in a passive mode to acquire the strain data from dropweight impact tests. The paper is focused on the comparative study of various signal processing techniques which can extract features related to different impact energy levels
Open Architecture for Signal Processing Lab Distance Learning
Mihai-Dan Steriu; Franck Luthon
2006-01-01
We present a global architecture (software and hardware) for the remote implementation of practical laboratory works in the field of electronics, automation or signal processing. The students can not only do simulations and virtual instrumentation, but they can also do real-world experiments in connection with the physics of the phenomenon under study, through observation or control. This is done remotely
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…
Correlations in single photon amplification : stimulated versus spontaneous processes
Boyer, Edmond
873 Correlations in single photon amplification : stimulated versus spontaneous processes A of a single photon. It is shown that this amplifier thus appears not at all as a « photon cloner » but rather recently, it has been pointed out that novel questions arise when single photon optical amplification
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…
Ephraim, Yariv
104 IEEE SIGNAL PROCESSING LETTERS, VOL. 10, NO. 4, APRIL 2003 Extension of the Signal Subspace, Fellow, IEEE Abstract--The signal subspace approach for speech enhance- ment is extended to colored are presented. These estimators minimize the average signal dis- tortion power for given constraints
Cohen, Israel
IEEE SIGNAL PROCESSING LETTERS, VOL. 10, NO. 9, SEPTEMBER 2003 259 Multichannel Signal Detection, we present a multichannel signal detec- tion approach that is particularly advantageous matrix that is unable to block all of the desired signal components, and a noise canceler that is adapted
Lee, Jae Hong
IEEE SIGNAL PROCESSING LETTERS, VOL. 11, NO. 11, NOVEMBER 2004 887 PAPR Reduction of OFDM Signals peak-to-average power ratio (PAPR) of the transmitted signal. Partial transmit sequence (PTS) technique can improve the PAPR statistics of OFDM signals. In the PTS technique, the data block
Automating the Modeling and Optimization of the Performance of Signal Processing Algorithms
Veloso, Manuela M.
Automating the Modeling and Optimization of the Performance of Signal Processing Algorithms Bryan W not necessarily reflect the position or the policy of the Defense Advanced Research Projects Agency (DARPA. #12;Keywords: Machine learning, signal processing, signal transform optimization, automatic
Advanced signal processing methods for pulsed laser vibrometry.
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
Bruce Allen; Joseph D. Romano
1997-10-27
We analyze the signal processing required for the optimal detection of a stochastic background of gravitational radiation using laser interferometric detectors. Starting with basic assumptions about the statistical properties of a stochastic gravity-wave background, we derive expressions for the optimal filter function and signal-to-noise ratio for the cross-correlation of the outputs of two gravity-wave detectors. Sensitivity levels required for detection are then calculated. Issues related to: (i) calculating the signal-to-noise ratio for arbitrarily large stochastic backgrounds, (ii) performing the data analysis in the presence of nonstationary detector noise, (iii) combining data from multiple detector pairs to increase the sensitivity of a stochastic background search, (iv) correlating the outputs of 4 or more detectors, and (v) allowing for the possibility of correlated noise in the outputs of two detectors are discussed. We briefly describe a computer simulation which mimics the generation and detection of a simulated stochastic gravity-wave signal in the presence of simulated detector noise. Numerous graphs and tables of numerical data for the five major interferometers (LIGO-WA, LIGO-LA, VIRGO, GEO-600, and TAMA-300) are also given. The treatment given in this paper should be accessible to both theorists involved in data analysis and experimentalists involved in detector design and data acquisition.
Inuk Kang; Christophe Dorrer; Liming Zhang; Mihaela Dinu; Mahmoud Rasras; Lawrence L. Buhl; Steven Cabot; Ashish Bhardwaj; Xiang Liu; Mark A. Cappuzzo; L. Gomez; A. Wong-Foy; Y. F. Chen; Niloy K. Dutta; Sanjay S. Patel; David T. Neilson; C. Randy Giles; A. Piccirilli; James Jaques
2008-01-01
We present experimental investigations of the dynamical properties of semiconductor optical amplifiers (SOAs) and their impacts in all-optical signal processing using SOAs. We introduce ultrafast optical signal characterization techniques to fully characterize the gain and phase dynamics of SOAs. We elucidate a consequence of the slow carrier recovery as pattern-dependent phase fluctuation in wavelength conversion of on-off -keyed signals. We
Exploiting the Analogy Between Traces and Signal Processing
Adrian Kuhn; Orla Greevy
2006-01-01
The main challenge of dynamic analysis is the huge\\u000a volume of data, making it difficult to extract high\\u000a level views. Most techniques developed so far adopt\\u000a a fine-grained approach to address this issue. In\\u000a this paper we introduce a novel approach\\u000a representing entire traces as signals in time.\\u000a Drawing this analogy between dynamic analysis and\\u000a signal processing, we are able
The Scientist and Engineer's Guide to Digital Signal Processing
NSDL National Science Digital Library
Smith, Steven W.
2002-01-01
Dr. Steve Smith offers his book about digital signal processing (DSP) free, in its entirety, on this site. The DSP guide introduces the reader to the fundamentals, and then delves into digital filters, applications, and complex techniques. All 33 chapters can be downloaded individually or as a whole. The book is quite well written, with plenty of figures, graphs, and illustrations that accompany the text. Smith derives equations for topics such as Fourier and Laplace transforms, and he clearly defines the terms and how to use them. This book is excellent for college students in a DSP or signals communications course.
A novel optoelectronic oscillator based on all optical signal processing
NASA Astrophysics Data System (ADS)
Li, Cheng-xin; Chen, Fu-shen; Zhang, Jia-hong; Mao, Jiu-bing
2013-09-01
A novel dual-loop optoelectronic oscillator (OEO), which is constructed based on all optical signal processing, is proposed and analyzed. By inserting an erbium-doped fiber amplifier (EDFA) and a fiber Bragg grating (FBG) on the optical domain, the amplification and filter are implemented in the OEO loop. The performance of the OEO is improved without any electronic filter or electronic amplifier. A theoretical analysis is performed, and the generated microwave signal exhibits good performance with phase noise lower than -120 dBc/Hz at 10 kHz and a high side-mode suppression ratio (SMSR).
Dynamic force signal processing system of a robot manipulator
NASA Technical Reports Server (NTRS)
Uchiyama, M.; Kitagaki, K.; Hakomori, K.
1987-01-01
If dynamic noises such as those caused by the inertia forces of the hand can be eliminated from the signal of the force sensor installed on the wrist of the robot manipulator and if the necessary information of the external force can be detected with high sensitivity and high accuracy, a fine force feedback control for robots used in high speed and various fields will be possible. As the dynamic force sensing system, an external force estimate method with the extended Kalman filter is suggested and simulations and tests for a one axis force were performed. Later a dynamic signal processing system of six axes was composed and tested. The results are presented.
Snore related signals processing in a private cloud computing system.
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
Application of image processing technology to 2-D signal processing (Abstract Only)
NASA Astrophysics Data System (ADS)
Meckley, John R.
1991-04-01
The analytical and processing developments in the field of Image Understanding over the last 15 years have led to the creation of a set of processing tools for the detection, characterization (feature extraction), and classification of 2 dimensional signals. This set of tools is applicable to 2 dimensional signals other than the traditional "image" type signals. In particular, for passive sonar detection processing several 2 dimensional signal transforms are generated from the 1 dimensional sensor time series data. These transforms are selected in order to concentrate signal energy locally within the 2 dimensional transform. A classic example is the Lofargram which is a grequency versus time transform of the time series data. If the acoutic source is emitting tones (for example from machinery) then the Lofargram will contain line like structures.
PostDoc position available: Uncertainty Principles in Signal Processing, and Applications to
Feichtinger, Hans Georg
PostDoc position available: Uncertainty Principles in Signal Processing, and Applications to Audio Signals A 1-year PostDoc position is available at the Signal and Image Processing group at LATP in Signal processing and more general data processing. There is a possibility of extending the position
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.
Lithography process controllers and photoresist monitoring by signal response metrology (SRM)
NASA Astrophysics Data System (ADS)
Yang, He Rong; Weng, Tang Chun; Tzai, Wei-Jhe; Chen, Chien-Hao; Yu, Chun-Chi; Chu, Wei-Yuan; Yoo, Sungchul; Huang, Chien-Jen; Cheng, Chao-Yu
2015-03-01
For advanced lithography metrology, SCD (Scatterometry Critical Dimension) is a common metrology technique applied to control processes. SCD has the capability to report accurate data information such as CD (Critical Dimensions), photoresist SWA (Side Wall Angle) and photoresist HT (Height). The shape of photoresist correlates with inline process controllers, namely scanner focus and dose. However, SCD is a model-based metrology method. In order to decode the process controllers, it requires computation from a geometric model. Once the model extracts the resist shape information from the spectra, one needs further correlation of those geometric parameters with the process controllers for monitoring. Thus, information loss through multiple modeling is a major concern. Indeed, during data transformation, noise and model approximation can distort the signals, in other words, the critical parameters, focus and dose, may not be measured accurately. This study therefore seeks a methodology to monitor focus and dose with the least amount of information transformation. Signal Response Metrology is a new measurement technique that obviates the need for geometric modeling by directly correlating focus, dose or CD to the spectral response of a SCD-based metrology tool.
Neural cross-correlation and signal decorrelation: insights into coding of auditory space.
Saberi, Kourosh; Petrosyan, Agavni
2005-07-01
The auditory systems of humans and many other species use the difference in the time of arrival of acoustic signals at the two ears to compute the lateral position of sound sources. This computation is assumed to initially occur in an assembly of neurons organized along a frequency-by-delay surface. Mathematically, the computations are equivalent to a two-dimensional cross-correlation of the input signals at the two ears, with the position of the peak activity along this surface designating the position of the source in space. In this study, partially correlated signals to the two ears are used to probe the mechanisms for encoding spatial cues in stationary or dynamic (moving) signals. It is demonstrated that a cross-correlation model of the auditory periphery coupled with statistical decision theory can predict the patterns of performance by human subjects for both stationary and motion stimuli as a function of stimulus decorrelation. Implications of these findings for the existence of a unique cortical motion system are discussed. PMID:15833312
Photoplethysmogram signal quality estimation using repeated Gaussian filters and cross-correlation.
Karlen, W; Kobayashi, K; Ansermino, J M; Dumont, G A
2012-10-01
Pulse oximeters are monitors that noninvasively measure heart rate and blood oxygen saturation (SpO2). Unfortunately, pulse oximetry is prone to artifacts which negatively impact the accuracy of the measurement and can cause a significant number of false alarms. We have developed an algorithm to segment pulse oximetry signals into pulses and estimate the signal quality in real time. The algorithm iteratively calculates a signal quality index (SQI) ranging from 0 to 100. In the presence of artifacts and irregular signal morphology, the algorithm outputs a low SQI number. The pulse segmentation algorithm uses the derivative of the signal to find pulse slopes and an adaptive set of repeated Gaussian filters to select the correct slopes. Cross-correlation of consecutive pulse segments is used to estimate signal quality. Experimental results using two different benchmark data sets showed a good pulse detection rate with a sensitivity of 96.21% and a positive predictive value of 99.22%, which was equivalent to the available reference algorithm. The novel SQI algorithm was effective and produced significantly lower SQI values in the presence of artifacts compared to SQI values during clean signals. The SQI algorithm may help to guide untrained pulse oximeter users and also help in the design of advanced algorithms for generating smart alarms. PMID:22986287
Missile signal processing common computer architecture for rapid technology upgrade
NASA Astrophysics Data System (ADS)
Rabinkin, Daniel V.; Rutledge, Edward; Monticciolo, Paul
2004-10-01
Interceptor missiles process IR images to locate an intended target and guide the interceptor towards it. Signal processing requirements have increased as the sensor bandwidth increases and interceptors operate against more sophisticated targets. A typical interceptor signal processing chain is comprised of two parts. Front-end video processing operates on all pixels of the image and performs such operations as non-uniformity correction (NUC), image stabilization, frame integration and detection. Back-end target processing, which tracks and classifies targets detected in the image, performs such algorithms as Kalman tracking, spectral feature extraction and target discrimination. In the past, video processing was implemented using ASIC components or FPGAs because computation requirements exceeded the throughput of general-purpose processors. Target processing was performed using hybrid architectures that included ASICs, DSPs and general-purpose processors. The resulting systems tended to be function-specific, and required custom software development. They were developed using non-integrated toolsets and test equipment was developed along with the processor platform. The lifespan of a system utilizing the signal processing platform often spans decades, while the specialized nature of processor hardware and software makes it difficult and costly to upgrade. As a result, the signal processing systems often run on outdated technology, algorithms are difficult to update, and system effectiveness is impaired by the inability to rapidly respond to new threats. A new design approach is made possible three developments; Moore's Law - driven improvement in computational throughput; a newly introduced vector computing capability in general purpose processors; and a modern set of open interface software standards. Today's multiprocessor commercial-off-the-shelf (COTS) platforms have sufficient throughput to support interceptor signal processing requirements. This application may be programmed under existing real-time operating systems using parallel processing software libraries, resulting in highly portable code that can be rapidly migrated to new platforms as processor technology evolves. Use of standardized development tools and 3rd party software upgrades are enabled as well as rapid upgrade of processing components as improved algorithms are developed. The resulting weapon system will have a superior processing capability over a custom approach at the time of deployment as a result of a shorter development cycles and use of newer technology. The signal processing computer may be upgraded over the lifecycle of the weapon system, and can migrate between weapon system variants enabled by modification simplicity. This paper presents a reference design using the new approach that utilizes an Altivec PowerPC parallel COTS platform. It uses a VxWorks-based real-time operating system (RTOS), and application code developed using an efficient parallel vector library (PVL). A quantification of computing requirements and demonstration of interceptor algorithm operating on this real-time platform are provided.
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.
Noise-benefit forbidden-interval theorems for threshold signal detectors based on cross correlations
NASA Astrophysics Data System (ADS)
Mitaim, Sanya; Kosko, Bart
2014-11-01
We show that the main forbidden interval theorems of stochastic resonance hold for a correlation performance measure. Earlier theorems held only for performance measures based on mutual information or the probability of error detection. Forbidden interval theorems ensure that a threshold signal detector benefits from deliberately added noise if the average noise does not lie in an interval that depends on the threshold value. We first show that this result holds for correlation for all finite-variance noise and for all forms of infinite-variance stable noise. A second forbidden-interval theorem gives necessary and sufficient conditions for a local noise benefit in a bipolar signal system when the noise comes from a location-scale family. A third theorem gives a general condition for a local noise benefit for arbitrary signals with finite second moments and for location-scale noise. This result also extends forbidden intervals to forbidden bands of parameters. A fourth theorem gives necessary and sufficient conditions for a local noise benefit when both the independent signal and noise are normal. A final theorem derives necessary and sufficient conditions for forbidden bands when using arrays of threshold detectors for arbitrary signals and location-scale noise.
Forghanifard, Mohammad Mahdi; Taleb, Shaghayegh; Abbaszadegan, Mohammad Reza
2015-04-01
Notch signaling is an important cellular pathway which affects the development and function of many organs. It plays critical roles in maintaining of progenitor stem cell population as well as balancing cell proliferation, survival, differentiation and apoptosis. It has been shown that notch signaling is aberrantly activated during the carcinogenesis of a variety of human cancers. In this study we aimed to explore activation of this signaling pathway in esophageal squamous cell carcinoma (ESCC) through expressional analysis of notch signaling target genes. The mRNA expression of HEY1and HEY2 was comparatively analyzed by real-time PCR in tumor and related margin normal tissues of 50 ESCC patients. Comparative quantitative real-time PCR indicates the overexpression of HEY1 and HEY2 in 54 and 30 % of ESCC samples, respectively. Overexpression of HEY1 was significantly associated with stage of the tumor (p?=?0.048) and tumor location (p?=?0.008). HEY2 overexpression was also significantly correlated to node metastasis of tumor cells (p?=?0.043). Overexpression of HEY1 and HEY2 in ESCC is correlated to different indices of poor prognosis and it is extrapolated that such overexpression is important in progression and development of ESCC tumorigenesis. To the best of our knowledge, this is the first report introducing aberrant activation of notch signaling target genes in ESCC, where it plays roles in development and progression of the malignancy and may be considered in therapeutic modalities to restrict ESCC progression. PMID:25361534
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.
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.
Wang, Yulin; Tian, Xuelong
2014-08-01
In order to improve the speech quality and auditory perceptiveness of electronic cochlear implant under strong noise background, a speech enhancement system used for electronic cochlear implant front-end was constructed. Taking digital signal processing (DSP) as the core, the system combines its multi-channel buffered serial port (McBSP) data transmission channel with extended audio interface chip TLV320AIC10, so speech signal acquisition and output with high speed are realized. Meanwhile, due to the traditional speech enhancement method which has the problems as bad adaptability, slow convergence speed and big steady-state error, versiera function and de-correlation principle were used to improve the existing adaptive filtering algorithm, which effectively enhanced the quality of voice communications. Test results verified the stability of the system and the de-noising performance of the algorithm, and it also proved that they could provide clearer speech signals for the deaf or tinnitus patients. PMID:25464779
Wang, Yulin; Tian, Xuelong
2014-08-01
In order to improve the speech quality and auditory perceptiveness of electronic cochlear implant under strong noise background, a speech enhancement system used for electronic cochlear implant front-end was constructed. Taking digital signal processing (DSP) as the core, the system combines its multi-channel buffered serial port (McBSP) data transmission channel with extended audio interface chip TLV320AIC10, so speech signal acquisition and output with high speed are realized. Meanwhile, due to the traditional speech enhancement method which has the problems as bad adaptability, slow convergence speed and big steady-state error, versiera function and de-correlation principle were used to improve the existing adaptive filtering algorithm, which effectively enhanced the quality of voice communications. Test results verified the stability of the system and the de-noising performance of the algorithm, and it also proved that they could provide clearer speech signals for the deaf or tinnitus patients. PMID:25508410
Neural correlates of variations in event processing during learning in basolateral amygdala
Roesch, Matthew R.; Calu, Donna J.; Esber, Guillem R.; Schoenbaum, Geoffrey
2010-01-01
The discovery that dopamine neurons signal errors in reward prediction has demonstrated that concepts empirically-derived from the study of animal behavior, can be used to understand the neural implementation of reward learning. Yet the learning theory models linked to phasic dopamine activity treat attention to events such as cues and rewards as static quantities; other models, such as Pearce-Hall, propose that learning might be influenced by variations in processing of these events. A key feature of these accounts is that event processing is modulated by unsigned rather than signed reward prediction errors. Here we tested whether neural activity in rat basolateral amygdala conforms to this pattern by recording single-units in a behavioral task in which rewards were unexpectedly delivered or omitted. We report that neural activity at the time of reward in provided an unsigned error signal with characteristics consistent with those postulated by these models. This neural signal increased immediately after a change in reward, and stronger firing was evident whether the value of the reward increased or decreased. Further, as predicted by these models, the change in firing developed over several trials as expectations for reward were repeatedly violated. This neural signal was correlated with faster orienting to predictive cues after changes in reward, and abolition of the signal by inactivation of basolateral amygdala disrupted this change in orienting and retarded learning in response to changes in reward. These results suggest that basolateral amygdala serves a critical function in attention for learning. PMID:20164330
On measuring surface-wave phase velocity from station-station1 cross-correlation of ambient signal2
Boschi, Lapo
-correlation, and phase and group velocities.22 1 Introduction23 The ability to observe coherent surface-wave signal fromOn measuring surface-wave phase velocity from station-station1 cross-correlation of ambient signal2Â¨urich)5 July 30, 20126 Abstract7 We apply two different algorithms to measure surface-wave phase velocity
V. F. Baranov; T. I. Gerasimova; É. P. Gulin
2007-01-01
For noiselike signals reflected from a rough sea surface and received by a correlation receiver, the effect achieved at the receiver output as a result of frequency averaging of signal fluctuations is considered. Expressions characterizing the effect of frequency averaging are derived by using the generalized two-scale model describing the frequency correlation of strong fluctuations of the transfer function. Results
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.
NASA Astrophysics Data System (ADS)
Yang, Z.; Jiang, T.; Xu, X.; Jia, H.
2014-12-01
Correlation detection method is generally used to detect seismic data of electromagnetic seismic vibrator, which is widely applicated for shallow mineral prospecting. By analyzing field seismic data from electromagnetic and hydraulic seismic vibrators in mining area, we find when media underground is complex or the base-plate of vibrator is coupled poorly with ground, there is a 9.30 m positioning precision error and false multiple waves in the electromagnetic vibrator data reference to hydraulic vibrator data. The paper analyzes the theoretical reason of above problems by studying how the signal of electromagnetic vibrator is excited, then proposes a new method of correlation detection based on the reconstructed excitation signal (CDBRES). CDBRES includes following steps. First, it extracts the direct wave signal from seismometer near base-plate of electromagnetic vibrator. Next, it reconstructs the excitation signal according to the extracted direct wave. Then, it detects the seismic data using cross-correlation with the reconstructed excitation signal as a reference. Finally, it uses spectrum whitening to improve detection quality. We simulate with ray-tracing method, and simulation results show that the reconstructed excitation signal is extremely consistence with the ideal excitation signal, the correlation coefficient between them is up to 0.9869. And the signal of electromagnetic vibrator is detected correctly with CDBRES method. Then a field comparison experiment between hydraulic vibrator MiniVib T15000 and electromagnetic vibrator PHVS 500 was carried out near a copper and nickel deposit area. Their output force are 30000N and 300N, respectively. Though there is a great output force difference, the detection result of PHVS 500 using CDBRES method is still consistent with MiniVib T15000. Reference to the MiniVib T15000, the positioning error of PHVS 500 is only 0.93m in relatively stronger noise level. In addition, false multiple waves are invisible. In summary, CDBRES method can be used for high precision detection of electromagnetic vibrator in mining area and complex media prospecting. It is of great significance in high resolution seismic exploration too.
Haghpanahi, Masoumeh; Borkholder, David A
2014-08-01
Noninvasive fetal ECG (fECG) monitoring has potential applications in diagnosing congenital heart diseases in a timely manner and assisting clinicians to make more appropriate decisions during labor. However, despite advances in signal processing and machine learning techniques, the analysis of fECG signals has still remained in its preliminary stages. In this work, we describe an algorithm to automatically locate QRS complexes in noninvasive fECG signals obtained from a set of four electrodes placed on the mother's abdomen. The algorithm is based on an iterative decomposition of the maternal and fetal subspaces and filtering of the maternal ECG (mECG) components from the fECG recordings. Once the maternal components are removed, a novel merging technique is applied to merge the signals and detect the fetal QRS (fQRS) complexes. The algorithm was trained and tested on the fECG datasets provided by the PhysioNet/CinC challenge 2013. The final results indicate that the algorithm is able to detect fetal peaks for a variety of signals with different morphologies and strength levels encountered in clinical practice. PMID:25069479
Cathedral-II: A Silicon Compiler for Digital Signal Processing
H. De Man; J. Rabaey; L. Claesen
1986-01-01
The article describes the status of work at IMEC on the Cathedral-II silicon compiler. The compiler was developed to synthesize synchronous multiprocessor system chips for digital signal processing. It is a continuation of work on the Cathedral-I operational silicon compiler for bit-serial digital filters. Cathedral-II is based on a żmeet in the middleż design method that encourages a total separation
Collaborative Signal Processing for Distributed Classification in Sensor Networks
Ashwin D’Costa; Akbar M. Sayeed
2003-01-01
Sensor networks provide virtual snapshots of the physical world via distributed wireless nodes that can sense in different\\u000a modalities, such as acoustic and seismic. Classiffication of objects moving through the sensor field is an important application\\u000a that requires collaborative signal processing (CSP) between nodes. Given the limited resources of nodes, a key constraint\\u000a is to exchange the least amount of
Annoyance reduction using active noise control with adaptive signal processing
NASA Astrophysics Data System (ADS)
Eriksson, L. J.; Allie, M. C.
An overview is presented of noise control engineering utilizing active noise control with adaptive signal processing. Noise management through the utilization of computer-aided silencing permits sound to be controlled instead of simply reduced. The noise control engineer moves in the direction of an acoustic object creation through spectrum shaping that is acceptable and possesses the characteristics which make a positive contribution to the overall environment.
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.
Energy-efficient signal processing via algorithmic noise-tolerance
Rajamohana Hegde; Naresh R. Shanbhag
1999-01-01
In this paper, we propose a framework for low-energy digital signal processing (DSP) where the supply voltage is scaled beyond the critical voltage required to match the critical path delay to the throughput. This deliberate introduction of input-dependent errors leads to degradation in the algorithmic performance, which is com- pensated for via algorithmic noise-tolerance (ANT) schemes. The resulting setup that
Signal processing for perpendicular recording channels with intertrack interference
Weijun Tan; J. R. Cruz
2005-01-01
Signal processing techniques for perpendicular magnetic recording channels with intertrack interference (ITI) are studied in this paper. Both single-track and joint-track equalization and detection algorithms are considered. Modified minimum mean-square error equalization methods are used to select optimum generalized partial response targets for ITI channels with either dominant additive white Gaussian noise or media noise. Simulation results show that good
Recent progress in parametric amplification and signal processing
Stojan Radic; Colin J. McKinstrie; Yikai Su
2004-01-01
Recent advances in fiber parametric amplifiers are reviewed. The physics, operation and applications of two-pump parametric fiber amplifiers are described. Methods for broadband, equalized parametric gain exceeding that of conventional EDFAs are discussed. The inherent nonlinear nature of parametric amplifiers forms a basis for all-optical signal processing. Optical regeneration in high-order, two-pump parametric amplifiers is described and demonstrated. All-optical penalty
Signal processing in a nonperiodically time-varying magnetoelastic medium
B. A. Auld; JEFFREY H. COLLINS; H. ROLAND ZAPP
1968-01-01
Wave propagation in a nonperiodically time-varying medium provides a means for realizing in simple physical structures a variety of signal-processing operations, such as frequency translation and coding, variable delay recall, gating, time-scale stretching or shrinking, and time reversal. The use of low-velocity modes, such as acoustic, spin, or magnetoelastic waves in solids, reduces the length of the propagation structure required
Lab Exercises: Digital Signal Processing with Field Programmable Gate Arrays
NSDL National Science Digital Library
Dr. Uwe Meyer-Baese
This website features a collection of eight laboratory experiments in the use of Field Programmable Gate Arrays (FPGAs), user-configurable semiconductor devices, for digital signal processing (DSP). The labs cover both leading FPGA vendors (Xilinx and Altera), provide a MatLab/Simulink-based design flow and are intended for use in university-level classes in electrical and computer engineering. Site materials include downloadable files in two versions compatible with each vendor's devices, and student worksheets.
IC signal-processing circuit for TV receivers
A. Cense; J. Rongen
1969-01-01
An IC signal-processing circuit that can be applied in both black-and-white and color receivers is described. The integrated circuit combines the following functions: video preamplifier; keyed AGC detector, operating on top sync level; AGC amplifier for IF and tuner control; noise canceling circuits for AGC and sync circuits; sync separator; automatic horizontal sync; and vertical sync pulse separator. Due to
Adaptive control technique for accelerators using digital signal processing
Eaton, L.; Jachim, S.; Natter, E.
1987-01-01
The use of present Digital Signal Processing (DSP) techniques can drastically reduce the residual rf amplitude and phase error in an accelerating rf cavity. Accelerator beam loading contributes greatly to this residual error, and the low-level rf field control loops cannot completely absorb the fast transient of the error. A feedforward technique using DSP is required to maintain the very stringent rf field amplitude and phase specifications. 7 refs.
Optical signal and image processing device optimized for optical readout
M. Vieira; M. Fernandes; P. Louro; C. Mendes; R. Schwarz; Yu. Vigranenko
2005-01-01
Large area (4×4cm2) optical signal and image processing (OSIP) devices were produced at low temperatures by Plasma Enhanced Chemical Vapour Deposition (PE-CVD). The OSIP device consists of two stacked sensing\\/switching diodes (p(SiC:H)\\/i(Si:H)\\/n(SiC:H)) with an internal light blocking layer between them and two semitransparent contacts. An optical scanner is used for charge readout. In this work the main emphasis will be
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.
Optoelectronic signal processing using finite impulse response neural networks
NASA Astrophysics Data System (ADS)
H. B. Xavier da Silveira, Paulo Eduardo
2001-08-01
This thesis investigates the use of finite impulse response neural network as the computational algorithm for efficient optoelectronic signal processing. The study begins with the analysis and development of different suitable algorithms, followed by the optoelectronic design of single-layer and multi-layer architectures, and it is concluded with the presentation of the results of a successful experimental implementation. First, finite impulse response adaptive filters and neural networks-the algorithmic building blocks-are introduced, followed by a description of finite impulse response neural networks. This introduction is followed by a historical background, describing early optoelectronic implementations of these algorithms. Next, different algorithms capable of temporal back-propagation are derived in detail, including a novel modification to the conventional algorithm, called delayed-feedback back- propagation. Based on these algorithms, different optoelectronic processors making use of adaptive volume holograms and three-dimensional optical processing are developed. Two single-layer architectures are presented: the input delay plane architecture and the output delay plane architecture. By combining them it is possible to implement both forward and backward propagation in two complementary multi-layer architectures: the first making use of the conventional temporal back-propagation and the second making use of delayed feedback back-propagation. Next, emphasis is given to a specific application: the processing of signals from adaptive antenna arrays. This research is initiated by computer simulations of different scenarios with multiple broadband signals and jammers, in planar and circular arrays, studying issues such as the effect of modulator non-linearities to the performance of the array, and the relation between the number of jammers and the final nulling depth. Two sets of simulations are presented: the first set applied to RF antenna arrays and the second set applied to an experimental implementation of a sonar adaptive array. Experimental results are presented for a single-layer optical processor making use of a scrolling spatial light modulator for representing the input signal and its delayed versions, photorefractive dynamic gratings for implementing the adaptive weights, differential heterodyning for bipolar signal representation, a phase- locked loop for controlling the optical path length, providing long term interferometric stabilization, and acousto-optic modulators for modulating the feedback error signal. Results for multiple beam-forming and jammer nulling are presented for planar and circular adaptive arrays. Finally, it is also shown how one can determine the position of the signal source from the images diffracted from the photorefractive hologram used to store the dynamic weights.
Hesse, C W; James, C J
2007-10-01
Conventional methods for monitoring clinical (epileptiform) multichannel electroencephalogram (EEG) signals often involve morphological, spectral or time-frequency analysis on individual channels to determine waveform features for detecting and classifying ictal events (seizures) and inter-ictal spikes. Blind source separation (BSS) methods, such as independent component analysis (ICA), are increasingly being used in biomedical signal processing and EEG analysis for extracting a set of underlying source waveforms and sensor projections from multivariate time-series data, some of which reflect clinically relevant neurophysiological (epileptiform) activity. The work presents an alternative spatial approach to source tracking and detection in multichannel EEG that exploits prior knowledge of the spatial topographies of the sensor projections associated with the target sources. The target source sensor projections are obtained by ICA decomposition of data segments containing representative examples of target source activity, e.g. a seizure or ocular artifact. Source tracking and detection are then based on the subspace correlation between individual target sensor projections and the signal subspace over a moving window. Different window lengths and subspace correlation threshold criteria reflect transient or sustained target source activity. To study the behaviour and potential application of this spatial source tracking and detection approach, the method was used to detect (transient) ocular artifacts and (sustained) seizure activity in two segments of 25-channel EEG data recorded from one epilepsy patient on two separate occasions, with promising and intuitive results. PMID:17701236
Hesse, C W; James, C J
2005-11-01
Conventional methods for monitoring clinical (epileptiform) multichannel electroencephalogram (EEG) signals often involve morphological, spectral or time-frequency analysis on individual channels to determine waveform features for detecting and classifying ictal events (seizures) and inter-ictal spikes. Blind source separation (BSS) methods, such as independent component analysis (ICA), are increasingly being used in biomedical signal processing and EEG analysis for extracting a set of underlying source waveforms and sensor projections from multivariate time-series data, some of which reflect clinically relevant neurophysiological (epileptiform) activity. The work presents an alternative spatial approach to source tracking and detection in multichannel EEG that exploits prior knowledge of the spatial topographies of the sensor projections associated with the target sources. The target source sensor projections are obtained by ICA decomposition of data segments containing representative examples of target source activity, e.g. a seizure or ocular artifact. Source tracking and detection are then based on the subspace correlation between individual target sensor projections and the signal subspace over a moving window. Different window lengths and subspace correlation threshold criteria reflect transient or sustained target source activity. To study the behaviour and potential application of this spatial source tracking and detection approach, the method was used to detect (transient) ocular artifacts and (sustained) seizure activity in two segments of 25-channel EEG data recorded from one epilepsy patient on two separate occasions, with promising and intuitive results. PMID:16594304
Nonlinear fiber applications for ultrafast all-optical signal processing
NASA Astrophysics Data System (ADS)
Kravtsov, Konstantin
In the present dissertation different aspects of all-optical signal processing, enabled by the use of nonlinear fibers, are studied. In particular, we focus on applications of a novel heavily GeO2-doped (HD) nonlinear fiber, that appears to be superior to many other types of nonlinear fibers because of its high nonlinearity and suitability for the use in nonlinear optical loop mirrors (NOLMs). Different functions, such as all-optical switching, thresholding, and wavelength conversion, are demonstrated with the HD fibers in the NOLM configuration. These basic functions are later used for realization of ultrafast time-domain demultiplexers, clock recovery, detectors of short pulses in stealth communications, and primitive elements for analog computations. Another important technology that benefits from the use of nonlinear fiber-based signal processing is optical code-division multiple access (CDMA). It is shown in both theory and experiment that all-optical thresholding is a unique way of improving existing detection methods for optical CDMA. Also, it is the way of implementation of true asynchronous optical spread-spectrum networks, which allows full realization of optical CDMA potential. Some aspects of quantum signal processing and manipulation of quantum states are also studied in this work. It is shown that propagation and collisions of Thirring solitons lead to a substantial squeezing of quantum states, which may find applications for generation of squeezed light.
Signal Processing Effects for Ultrasonic Guided Wave Scanning of Composites
Roth, D.J. [NASA Glenn Research Center, Cleveland, OH 44135 (United States); Cosgriff, L.M.; Martin, R.E. [Cleveland State University, Cleveland, OH 44120 (United States); Burns, E.A. [Michigan Technological University, Houghton, MI 49931 (United States); Teemer, L. [Florida A and M University - Florida State University, Tallahassee, FL 32310 (United States)
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.
COLLEGE OF LIBERAL ARTS SIGNAL PROCESSING FOR HEARING AND SPEECH SCIENCES
Heinz, Michael G.
.g., hearing-aid and cochlear-implant signal processing), applications to speech, and digital signal processing. Practical experience with digital signal processing (primarily in MATLAB) will supplement lectures them with me. Course Goals 1) To develop a basic understanding of the principles of signals and systems
1852 IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 47, NO. 7, JULY 1999 Wavelet-Based Transformations
1852 IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 47, NO. 7, JULY 1999 Wavelet-Based Transformations for Nonlinear Signal Processing Robert D. Nowak, Member, IEEE, and Richard G. Baraniuk, Senior-world signals. In this paper, we introduce two new structures for nonlinear signal processing. The new
Tsakalides, Panagiotis
Chapter 7 Future Work Traditionally, classical array signal processing has dealt with two major aspects of spa- tial processing, namely localization of a signal of interest or of an interfering signal processing is dependent upon consideration of the interrelations of the di erent components of a signal
Madhusudan Bhandary
1989-01-01
Likelihood ratio tests for mean-slippage outlier(s) and Roy's (1953) union-intersection principle for dispersion-slippage outlier(s) are applied in the signal processing data. Procedures to get approximate critical values of the tests are given.Then likelihood ratio tests and intuitive tests are suggested to test the rank of ? in the presence of mean-slippage and dispersion-slippage outliers, respectively, where is the covariance matrix
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.
Bassel F. Beidas; Charles L. Weber
1995-01-01
A general framework that theoretically links the higher-order correlation (HOC) domain with statistical decision theory is explored. It is then applied to the problem of classification of M-ary frequency shift keying (MFSK) signals when contaminated by additive white Gaussian noise (AWGN). In particular, we propose a novel class of classifiers that utilizes time-domain HOC operations while completely avoiding the explicit
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.
Signal detection in FDA AERS database using Dirichlet process.
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. Copyright © 2015?John Wiley & Sons, Ltd. PMID:25924820
NASA Astrophysics Data System (ADS)
Bashashati, Ali; Fatourechi, Mehrdad; Ward, Rabab K.; Birch, Gary E.
2007-06-01
Brain computer interfaces (BCIs) aim at providing a non-muscular channel for sending commands to the external world using the electroencephalographic activity or other electrophysiological measures of the brain function. An essential factor in the successful operation of BCI systems is the methods used to process the brain signals. In the BCI literature, however, there is no comprehensive review of the signal processing techniques used. This work presents the first such comprehensive survey of all BCI designs using electrical signal recordings published prior to January 2006. Detailed results from this survey are presented and discussed. The following key research questions are addressed: (1) what are the key signal processing components of a BCI, (2) what signal processing algorithms have been used in BCIs and (3) which signal processing techniques have received more attention?
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.
Douglas, Scott C.
IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 51, NO. 7, JULY 2003 1905 Bussgang Blind Deconvolution for Impulsive Signals Heinz Mathis and Scott C. Douglas, Senior Member, IEEE Abstract--Many blind deconvolution algorithms have been de- signed to extract digital communications signals corrupted by in- tersymbol
Ramanujan sums for signal processing of low frequency noise
M. Planat; H. C. Rosu; S. Perrine
2002-09-01
An aperiodic (low frequency) spectrum may originate from the error term in the mean value of an arithmetical function such as M\\"obius function or Mangoldt function, which are coding sequences for prime numbers. In the discrete Fourier transform the analyzing wave is periodic and not well suited to represent the low frequency regime. In place we introduce a new signal processing tool based on the Ramanujan sums c_q(n), well adapted to the analysis of arithmetical sequences with many resonances p/q. The sums are quasi-periodic versus the time n of the resonance and aperiodic versus the order q of the resonance. New results arise from the use of this Ramanujan-Fourier transform (RFT) in the context of arithmetical and experimental signals
Manganese-Mediated MRI Signals Correlate With Functional ?-Cell Mass During Diabetes Progression.
Meyer, Anke; Stolz, Katharina; Dreher, Wolfgang; Bergemann, Jennifer; Holebasavanahalli Thimmashetty, Vani; Lueschen, Navina; Azizi, Zahra; Khobragade, Vrushali; Maedler, Kathrin; Kuestermann, Ekkehard
2015-06-01
Diabetes diagnostic therapy and research would strongly benefit from noninvasive accurate imaging of the functional ?-cells in the pancreas. Here, we developed an analysis of functional ?-cell mass (BCM) by measuring manganese (Mn(2+)) uptake kinetics into glucose-stimulated ?-cells by T1-weighted in vivo Mn(2+)-mediated MRI (MnMRI) in C57Bl/6J mice. Weekly MRI analysis during the diabetes progression in mice fed a high-fat/high-sucrose diet (HFD) showed increased Mn(2+)-signals in the pancreas of the HFD-fed mice during the compensation phase, when glucose tolerance and glucose-stimulated insulin secretion (GSIS) were improved and BCM was increased compared with normal diet-fed mice. The increased signal was only transient; from the 4th week on, MRI signals decreased significantly in the HFD group, and the reduced MRI signal in HFD mice persisted over the whole 12-week experimental period, which again correlated with both impaired glucose tolerance and GSIS, although BCM remained unchanged. Rapid and significantly decreased MRI signals were confirmed in diabetic mice after streptozotocin (STZ) injection. No long-term effects of Mn(2+) on glucose tolerance were observed. Our optimized MnMRI protocol fulfills the requirements of noninvasive MRI analysis and detects already small changes in the functional BCM. PMID:25804940
NASA Astrophysics Data System (ADS)
Takehara, Shintaro; Ogawa, Akihito; Nagai, Yuji; Morishita, Naoki; Matsumaru, Masaaki; Okamoto, Yutaka; Kashihara, Yutaka
2003-02-01
The partial response and maximum likelihood (PRML) signal processing method is effective for fabricating high-density optical disks because it allows inter-symbol interference in decoding. However, some deterioration factors, namely impulse response fluctuations and signal level fluctuations, still exist even though PRML signal processing is adopted. A combined adaptive controlled PRML signal processing method is proposed to surmount the problem of these two deterioration factors simultaneously. The key points of the combined adaptive controlled PRML signal processing are that the gain of the Viterbi decoder is unity and the expected signal takes into account the reference levels controlled in the adaptive controlled Viterbi decoder. The effectiveness of such processing is confirmed using simulated reproduced signals and actual reproduced signals. The characteristics in terms of the tangential tilt of the disk and the signal asymmetry are ameliorated by adopting the combined adaptive controlled PRML signal processing method.
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.
Oxytocin effects on neural correlates of self-referential processing.
Liu, Yi; Sheng, Feng; Woodcock, Kate A; Han, Shihui
2013-10-01
Oxytocin (OT) influences how humans process information about others. Whether OT affects the processing of information about oneself remains unknown. Using a double-blind, placebo-controlled within-subject design, we recorded event-related potentials (ERPs) from adults during trait judgments about oneself and a celebrity and during judgments on word valence, after intranasal OT or placebo administration. We found that OT vs. placebo treatment reduced the differential amplitudes of a fronto-central positivity at 220-280 ms (P2) during self- vs. valence-judgments. OT vs. placebo treatment tended to reduce the differential amplitude of a late positive potential at 520-1000 ms (LPP) during self-judgments but to increase the differential LPP amplitude during other-judgments. OT effects on the differential P2 and LPP amplitudes to self- vs. celebrity-judgments were positively correlated with a measure of interdependence of self-construals. Thus OT modulates the neural correlates of self-referential processing and this effect varies as a function of interdependence. PMID:23965321
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.
Bandyopadhyay, Antar
Functional brain signal processing : EEG and fMRI Electroencephalogram (EEG): Cortical sources the course. 2. Electroencephalogram processing using neural networks, C. Robert, J.-F. Gaudy and A. M. Limoge
In silico detection of control signals: mRNA 3'-end-processing sequences in diverse species.
Graber, J H; Cantor, C R; Mohr, S C; Smith, T F
1999-11-23
We have investigated mRNA 3'-end-processing signals in each of six eukaryotic species (yeast, rice, arabidopsis, fruitfly, mouse, and human) through the analysis of more than 20,000 3'-expressed sequence tags. The use and conservation of the canonical AAUAAA element vary widely among the six species and are especially weak in plants and yeast. Even in the animal species, the AAUAAA signal does not appear to be as universal as indicated by previous studies. The abundance of single-base variants of AAUAAA correlates with their measured processing efficiencies. As found previously, the plant polyadenylation signals are more similar to those of yeast than to those of animals, with both common content and arrangement of the signal elements. In all species examined, the complete polyadenylation signal appears to consist of an aggregate of multiple elements. In light of these and previous results, we present a broadened concept of 3'-end-processing signals in which no single exact sequence element is universally required for processing. Rather, the total efficiency is a function of all elements and, importantly, an inefficient word in one element can be compensated for by strong words in other elements. These complex patterns indicate that effective tools to identify 3'-end-processing signals will require more than consensus sequence identification. PMID:10570197
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.
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.
Automatic signal processing of front monitor radar for tunneling machines
Sato, Toru [Kyoto Univ. (Japan). Dept. of Electronics and Communication] [Kyoto Univ. (Japan). Dept. of Electronics and Communication; Takeda, Kenya [NTT Co. Ltd., Chiba (Japan)] [NTT Co. Ltd., Chiba (Japan); Nagamatsu, Takashi [Mitsubishi Heavy Industries, Ltd., Tokyo (Japan)] [Mitsubishi Heavy Industries, Ltd., Tokyo (Japan); Wakayama, Toshio [Mitsubishi Electric Corp., Kamakura, Kanagawa (Japan)] [Mitsubishi Electric Corp., Kamakura, Kanagawa (Japan); Kimura, Iwane [Osaka Inst. of Tech., Hirakata, Osaka (Japan)] [Osaka Inst. of Tech., Hirakata, Osaka (Japan); Shinbo, Tetsuya [Komatsu Co. Ltd., Kanagawa (Japan)] [Komatsu Co. Ltd., Kanagawa (Japan)
1997-03-01
It is planned to install a front monitoring impulse radar on the surface of the rotating drill of tunneling machines in order to detect obstacles such as casing pipes of vertical borings. The conventional aperture synthesis technique can no more be applied to such cases because the radar image of a pipe dies not constituent a hyperbola as is the case for linear scanning radars. The authors have developed a special purpose signal processing algorithm with the aid of the discrete model fitting method, which can be used for any pattern of scanning. The details of the algorithm are presented together with the results of numerical simulations and test site experiments.
Iowegian's dspGuru: Digital Signal Processing Central
NSDL National Science Digital Library
dspGuru is a site dedicated to digital signal processing (DSP) designers. It has a good collection of resources for both beginners and seasoned users. Many open-source software titles can be freely downloaded, ranging from implementations of DSP algorithms to compilers and other software development tools. Five frequently asked questions lists cover some important DSP subjects, like finite and infinite impulse response filters and Fourier transforms. There is also a section called Tribal Knowledge that is filled with common techniques and tricks that experienced DSP designers know, "but isn't in the textbooks."
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.
Real-time fractal signal processing in the time domain
NASA Astrophysics Data System (ADS)
Hartmann, András; Mukli, Péter; Nagy, Zoltán; Kocsis, László; Hermán, Péter; Eke, András
2013-01-01
Fractal analysis has proven useful for the quantitative characterization of complex time series by scale-free statistical measures in various applications. The analysis has commonly been done offline with the signal being resident in memory in full length, and the processing carried out in several distinct passes. However, in many relevant applications, such as monitoring or forecasting, algorithms are needed to capture changes in the fractal measure real-time. Here we introduce real-time variants of the Detrended Fluctuation Analysis (DFA) and the closely related Signal Summation Conversion (SSC) methods, which are suitable to estimate the fractal exponent in one pass. Compared to offline algorithms, the precision is the same, the memory requirement is significantly lower, and the execution time depends on the same factors but with different rates. Our tests show that dynamic changes in the fractal parameter can be efficiently detected. We demonstrate the applicability of our real-time methods on signals of cerebral hemodynamics acquired during open-heart surgery.
Pan, Wen-Ju; Thompson, Garth; Magnuson, Matthew; Majeed, Waqas; Jaeger, Dieter
2011-01-01
Abstract Resting-state functional magnetic resonance imaging (fMRI) is widely used for exploring spontaneous brain activity and large-scale networks; however, the neural processes underlying the observed resting-state fMRI signals are not fully understood. To investigate the neural correlates of spontaneous low-frequency fMRI fluctuations and functional connectivity, we developed a rat model of simultaneous fMRI and multiple-site intracortical neural recordings. This allowed a direct comparison to be made between the spontaneous signals and interhemispheric connectivity measured with the two modalities. Results show that low-frequency blood oxygen level-dependent (BOLD) fluctuations (<0.1?Hz) correlate significantly with slow power modulations (<0.1?Hz) of local field potentials (LFPs) in a broad frequency range (1–100?Hz) under isoflurane anesthesia (1%–1.8%). Peak correlation occurred between neural and hemodynamic activity when the BOLD signal was delayed by ?4?sec relative to the LFP signal. The spatial location and extent of correlation was highly reproducible across studies, with the maximum correlation localized to a small area surrounding the site of microelectrode recording and to the homologous area in the contralateral hemisphere for most rats. Interhemispheric connectivity was calculated using BOLD correlation and band-limited LFP (1–4, 4–8, 8–14, 14–25, 25–40, and 40–100?Hz) coherence. Significant coherence was observed for the slow power changes of all LFP frequency bands as well as in the low-frequency BOLD data. A preliminary investigation of the effect of anesthesia on interhemispheric connectivity indicates that coherence in the high-frequency LFP bands declines with increasing doses of isoflurane, whereas coherence in the low-frequency LFP bands and the BOLD signal increases. These findings suggest that resting-state fMRI signals might be a reflection of broadband LFP power modulation, at least in isoflurane-anesthetized rats. PMID:22433008
NASA Astrophysics Data System (ADS)
Bai, Chunyan; Du, Luchun; Mei, Dongcheng
2009-09-01
The stochastic resonance (SR) phenomenon induced by a multiplicative periodic signal in a logistic growth model with correlated noises is studied by using the theory of signal-to-noise ratio ( SNR) in the adiabatic limit. The expressions of the SNR are obtained. The effects of multiplicative noise intensity ? and additive noise intensity D, and correlated intensity ? on the SNR are discussed respectively. It is found that the existence of a maximum in the SNR is the identifying characteristic of the SR phenomena. In comparison with the SR induced by additive periodic signal, some new features are found: (1) When SNR as a function of ? for fixed ratio of ? and D, the varying of ? can induce a stochastic multi-resonance, and can induce a re-entrant transition of the peaks in SNR vs ?; (2) There exhibits a doubly critical phenomenon for SNR vs D and ?, i.e., the increasing of D (or ?) can induce the critical phenomenon for SNR with respect to ? (or D); (3) The doubly stochastic resonance effect appears when ? and D are simultaneously varying in SNR, i.e., the increment of one noise intensity can help the SR on another noise intensity come forth.
NASA Astrophysics Data System (ADS)
Bai, Chunyan; Du, Luchun; Mei, Dongcheng
2009-09-01
The stochastic resonance (SR) phenomenon induced by a multiplicative periodic signal in a logistic growth model with correlated noises is studied by using the theory of signal-to-noise ratio (SNR) in the adiabatic limit. The expressions of the SNR are obtained. The effects of multiplicative noise intensity ? and additive noise intensity D, and correlated intensity ? on the SNR are discussed respectively. It is found that the existence of a maximum in the SNR is the identifying characteristic of the SR phenomena. In comparison with the SR induced by additive periodic signal, some new features are found: (1) When SNR as a function of ? for fixed ratio of ? and D, the varying of ? can induce a stochastic multi-resonance, and can induce a re-entrant transition of the peaks in SNR vs ?; (2) There exhibits a doubly critical phenomenon for SNR vs D and ?, i.e., the increasing of D (or ?) can induce the critical phenomenon for SNR with respect to ? (or D); (3) The doubly stochastic resonance effect appears when ? and D are simultaneously varying in SNR, i.e., the increment of one noise intensity can help the SR on another noise intensity come forth.
Stochastic simulation of spatially correlated geo-processes
Christakos, G.
1987-01-01
In this study, developments in the theory of stochastic simulation are discussed. The unifying element is the notion of Radon projection in Euclidean spaces. This notion provides a natural way of reconstructing the real process from a corresponding process observable on a reduced dimensionality space, where analysis is theoretically easier and computationally tractable. Within this framework, the concept of space transformation is defined and several of its properties, which are of significant importance within the context of spatially correlated processes, are explored. The turning bands operator is shown to follow from this. This strengthens considerably the theoretical background of the geostatistical method of simulation, and some new results are obtained in both the space and frequency domains. The inverse problem is solved generally and the applicability of the method is extended to anisotropic as well as integrated processes. Some ill-posed problems of the inverse operator are discussed. Effects of the measurement error and impulses at origin are examined. Important features of the simulated process as described by geomechanical laws, the morphology of the deposit, etc., may be incorporated in the analysis. The simulation may become a model-dependent procedure and this, in turn, may provide numerical solutions to spatial-temporal geologic models. Because the spatial simu??lation may be technically reduced to unidimensional simulations, various techniques of generating one-dimensional realizations are reviewed. To link theory and practice, an example is computed in detail. ?? 1987 International Association for Mathematical Geology.
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.
Gravity influences top-down signals in visual processing.
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
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.
NASA Technical Reports Server (NTRS)
Rosen, Paul A.
2012-01-01
Discusses: (1) JPL Radar Overview and Historical Perspective (2) Signal Processing Needs in Earth and Planetary Radars (3) Examples of Current Systems and techniques (4) Future Perspectives in signal processing for radar missions
de Leon, Alex R.
for a Postdoctoral Fellow in the areas of electronics, circuits, signal processing, and control specifically dealing in circuits, signal processing, electronics, mechanical engineering, sensors, and numerical modeling. Experience with circuits and electronics development is advantageous. The successful candidates will have
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.
Enthalpy-entropy correlations as chemical guides to unravel self-assembly processes.
Piguet, Claude
2011-08-28
Intermolecular connections play a crucial role in biology (recognition, signalling, binding), in physics (material cohesion) and in chemistry ((supra)molecular engineering). While a phenomenological thermodynamic free-energy approach for modelling self-assemblies is now at hand, a more satisfying description based on the chemically-intuitive enthalpic and entropic contributions remains elusive. On the other hand, the innumerable reports of empirical enthalpy/entropy correlations characterizing intermolecular interactions justify a questioning about the emergence and exploitation of an apparent 'fourth law of thermodynamics', which could provide a simple manipulation of intermolecular binding processes. This tutorial Perspective aims at highlighting the current level of non-quantum rationalization of enthalpy-entropy correlations and their chemical consequences on the tuning and on the programming of intermolecular interactions in pure materials, and in diluted solutions. PMID:21629958