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The EVLA Correlator - Signal Processing for UltraSensitive Astronomy  

Microsoft Academic Search

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

P. E. Dewdney; B. R. Carlson



An Enhanced Correlation Processing Multipath Mitigation Technique for BOC Signals  

Microsoft Academic Search

Multipath is an issue of paramount importance in the GNSS context. The presence of reflected signals gives place to a worrying bias when estimating the propagation delay of the direct signal. This paper presents the design and the evaluation of a correlation processing technique that computes an estimation of the tracking error induced by the presence of multipath. This technique

Vincent Heiries; D. Rovirasy; Vincent Calmettes; Lionel Ries



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

Microsoft Academic Search

We describe the design of a correlator system for ground and space-based\\u000aVLBI. The correlator contains unique signal processing functions: flexible LO\\u000afrequency switching for bandwidth synthesis; 1 ms dump intervals, multi-rate\\u000adigital signal-processing techniques to allow correlation of signals at\\u000adifferent sample rates; and a digital filter for very high resolution\\u000across-power spectra. It also includes autocorrelation, tone extraction,



Task effects on BOLD signal correlates of implicit syntactic processing  

PubMed Central

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.

Caplan, David



Processing Near Infrared Spectroscopy Signals Using Canonical Correlation Analysis  

Microsoft Academic Search

Functional near infrared spectroscopy signals (fNIRS) are measured by a number of LED-detector pairs. Estimation of event related responses from these signals needs multivariate analysis methods. This study concentrates on a particular multivariate method, namely the canonical correlation analysis and investigates its use for eliminating trend and noise effects from fNIRS signals and estimating event related haemodynamic response. Proposed methods

K. Ciftci; B. Sankur; A. Akin; Y. P. Kahya



Optical signal processing - Fourier transforms and convolution/correlation  

NASA Astrophysics Data System (ADS)

The application of Fourier techniques and linear-systems theory to the analysis and synthesis of optical systems is described in a theoretical review, and Fourier-based optical signal-processing methods are considered. Topics examined include monochromatic wave fields and their phasor representation, wave propagation, Fourier-transform and spectrum analysis with a spherical lens, coherent and incoherent imaging and spatial filtering, and a channelized spectrum analyzer (using both spherical and cylindrical lenses) for multiple one-dimensional input signals.

Rhodes, William T.


CMOS camera with on-chip signal processing for optical correlators  

NASA Astrophysics Data System (ADS)

The design and simulation results of a 64 X 64 pixels smart CMOS photodiode sensor array are presented. The chip is capable of capturing an image as well as performing real time on-chip signal processing on 3 X 3 kernel array of the image. The size of the optical system is significantly reduced by integrating the signal processing circuits on chip. It is particularly suitable for applications such as optical correlators or image processing system. The chip is designed using 0.8 micrometers standard CMOS process technology. It is incorporated with processing circuitry to implement low-pass and high-pass image filters as well as the processing algorithm required by a 1/f binary phase optical correlation system.

Kwok, Terence C.; Wilkinson, Tim D.; Crossland, William A.



A compact acousto-optic correlator for rapid GPS signal processing  

Microsoft Academic Search

We propose in this paper a GPS signal processing unit based on the acousto-optic technic. A 10323-point compact correlator is reviewed. It is matched to the GPS sequences through time compression hardware. Acquisition is implemented with a single Doppler-frequency search loop. The main advantage of the system is rapidity. The 1023-point correlation is performed in the 25-?s aperture of the

O. Bazzi; R. Torguet; C. Bruneel; J. C. Kastelik



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

Microsoft Academic Search

A unique lag-based VLBI correlator system has been developed for the purpose of supporting S2-based space VLBI observations in both the Japanese-led VSOP mission and the Canadian Geodetic VLBI program. The system architecture has been designed so that replication of a small number of modules can be used to construct systems with a wide range of sizes. Optimized for a

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



Signal processing  

Microsoft Academic Search

Space-variant coordinate transformations may be profitably applied to many signal processing problems; for example, image convolutions are often computed by multiplying the Fourier transforms of the images rather than by direct methods (i.e., shift, multiply, and add). Some signal processing algorithms are presently under study that operate on projection-based representations of the function. The best known projection representation is the

Roger L. Easton Jr.; R. L. Jr



Correlating behavioral responses to FMRI signals from human prefrontal cortex: examining cognitive processes using task analysis.  


The aim of this methods paper is to describe how to implement a neuroimaging technique to examine complementary brain processes engaged by two similar tasks. Participants' behavior during task performance in an fMRI scanner can then be correlated to the brain activity using the blood-oxygen-level-dependent signal. We measure behavior to be able to sort correct trials, where the subject performed the task correctly and then be able to examine the brain signals related to correct performance. Conversely, if subjects do not perform the task correctly, and these trials are included in the same analysis with the correct trials we would introduce trials that were not only for correct performance. Thus, in many cases these errors can be used themselves to then correlate brain activity to them. We describe two complementary tasks that are used in our lab to examine the brain during suppression of an automatic responses: the stroop(1) and anti-saccade tasks. The emotional stroop paradigm instructs participants to either report the superimposed emotional 'word' across the affective faces or the facial 'expressions' of the face stimuli(1,2). When the word and the facial expression refer to different emotions, a conflict between what must be said and what is automatically read occurs. The participant has to resolve the conflict between two simultaneously competing processes of word reading and facial expression. Our urge to read out a word leads to strong 'stimulus-response (SR)' associations; hence inhibiting these strong SR's is difficult and participants are prone to making errors. Overcoming this conflict and directing attention away from the face or the word requires the subject to inhibit bottom up processes which typically directs attention to the more salient stimulus. Similarly, in the anti-saccade task(3,4,5,6), where an instruction cue is used to direct only attention to a peripheral stimulus location but then the eye movement is made to the mirror opposite position. Yet again we measure behavior by recording the eye movements of participants which allows for the sorting of the behavioral responses into correct and error trials(7) which then can be correlated to brain activity. Neuroimaging now allows researchers to measure different behaviors of correct and error trials that are indicative of different cognitive processes and pinpoint the different neural networks involved. PMID:22759999

DeSouza, Joseph F X; Ovaysikia, Shima; Pynn, Laura



Multigigahertz range-Doppler correlative signal processing in optical memory crystals.  


Analog optical signal processing of complex radio-frequency signals for range-Doppler radar information is theoretically described and experimentally demonstrated using crystalline optical memory materials and off-the-shelf photonic components. A model of the range-Doppler processing capability of the memory material for the case of single-target detection is presented. Radarlike signals were emulated and processed by the memory material; they consisted of broadband (> 1 GHz), spread-spectrum, pseudorandom noise sequences of 512 bits in length, which were binary phase-shift keyed on a 1.9 GHz carrier and repeated at 100 kHz over 7.5 ms. Delay (range) resolution of 8 ns and Doppler resolution of 130 Hz over 100 kHz were demonstrated. PMID:16422164

Harris, Todd L; Merkel, Kristian D; Mohan, R Krishna; Chang, Tiejun; Cole, Zachary; Olson, Andy; Babbitt, Wm Randall



Advanced signal processing  

NASA Astrophysics Data System (ADS)

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

Creasey, D. J.



Digital Signal Processing Tools  

NSDL National Science Digital Library

A collection of seven Java applets and associated tutorials are available on this site from the Signals and Systems Group at the University of Edinburgh. The tools illustrate various concepts of digital signal processing, like convolution, correlation, the Fourier transform, and discrete-time applications of each. Seven other applets that demonstrate more advanced concepts are also available, but no documentation or explanation accompanies them. A few conference publications and reports related to these educational materials are presented.



Signal Processing, Analog,  

National Technical Information Service (NTIS)

In recent years the term analog signal processing has been used to distinguish between traditional continuous-time signal-processing techniques and the more recently popularized techniques in digital signal processing. In this chapter, the term analog is ...

W. K. Jenkins



Quo vadis, signal processing?  

NASA Astrophysics Data System (ADS)

When Light propagates through optical elements (such as lenses), it undergoes a transform. The input and the output data take the form of light and optical elements that perform different mathematical operations on light represent the linear transform. The transform is performed not on the discrete elements of the data but on the whole vector at once, and most significantly, at the speed of light. The great advantages offered by optical processing are that it offers enormous parallelism, operating on all data points simultaneously, very low latency, a high transform rate and low power dissipation. The outcome is enormously increased speed and a reduction in the amount of associated cooling required. The Optical Signal Processor (OSP) increases the speed of processing transforms by many orders of magnitude. The Signal Processor is also reconfigurable and can be dynamically tailored to the required transform type. One advantage of an optical processor is that it allows software designers to work at a much higher level of abstraction. This is because the device executes transforms instead of the ordinary MACs in the case of DSPs. Instead of handling algorithms at individual data points, algorithms for handling the entire vector could be processed, shortening the computational complexity and speeding the time-to-market for new products. An optical filter can be represented as a generic function, the most fundamental of the optical processor. The impulse response of this filter is defined with respect to frequency of light. Any transform on light can be represented as a combination of linear transforms. This is fundamentally the law of optical signal processing. The most important application of an OSP in Optical Networking is Pattern recognition, and this can easily be done by the usual cross-correlation technique that is common in digital signal processing. The OSP can be programmed to autocorrelate against specific temporal reference waveforms, viz. Data. The decoding is done without electronic processing. And of course, the routing of optical signals is based on content. This paper provides insight to this efficient and novel method of computation and signal processing.

Guha, Dipnarayan



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.


Digital Signal Processing  

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.



SETI Signal Processing  

Microsoft Academic Search

Recently, NASA has launched an ambitious program to search for extraterrestrial intelligent life. The program, called Project SETI, involves the development of a very high speed digital signal processing system employing state-of-the-art technology. The system is comprised of a wideband, high resolution digital spectrum analyzer followed by a signal thresholder and system computer. The role of the signal thresholder is

Edgar Satorius; Rachael Brady



Postreinforcement signal processing.  


Postreinforcement signal processing by rats was demonstrated in six experiments that used a discrete-trials choice procedure. Experiment 1 assessed the extent to which rats are able to transfer knowledge about associations between postreinforcement signal durations and choice responses to conditions where a particular signal duration preceded the opportunity to make a choice response. In Experiment 2 the generality of the transfer effect was demonstrated by using both signal duration and signal modality as relevant stimulus attributes for the postreinforcement signals. The role of the relative durations of the reinforcement-signal gap and the intertrial interval was investigated in Experiment 3. In order to assess the effects of within-trial and between-trial signal relations on the acquisition of a temporal discrimination, both pre-and postreinforcement signals were presented on each trial in Experiments 4 and 5. The effects of pre- and postreinforcement signal relations on the steady-state performance of a temporal bisection task across three different signal ranges were studied in Experiment 6. The conclusion is that rats readily process various stimulus attributes of postreinforcement signals and that relations between postreinforcement signals, choice responses, and prereinforcement signals are major determinants of choice behavior. PMID:3989476

Meck, W H



Geophysical signal processing  

SciTech Connect

Draws together a number of areas of knowledge to give unified coverage of the subject: the geophysical applications of digital signal processing. The presentation has a strong applications orientation. The coverage connects and unifies several fields, namely wave propagation, digital signal processing, spectral analysis, and computer methods. The book covers many topics in depth.

Robinson, E.A.; Durrani, T.S.



Signal processing software tools  

Microsoft Academic Search

A signal processing software system is described which allows the simulation of systems described by block diagrams or signal-flow graphs. Component systems are allowed to be multi-input, multi-output, and to be programmed in any language. A high level dataflow language describes the interconnection of the components. Special display software was written to allow any signal in the system to be

D. Johnson



Process Signal Features Analysis  

Microsoft Academic Search

\\u000a In this chapter, a phase plane analysis method has been proposed as a new way of analyzing nonstationary signals, based on\\u000a wavelet theory. Some basic concepts are defined to form a theoretical framework of this method. Several possible applications\\u000a are discussed. This approach offers the potential for building new intelligent process signal analysis systems to identifying\\u000a the process “finger prints”,

Xue-dong Dai; B. Joseph; R. L. Motard


Statistical Signal Processing  

NASA Astrophysics Data System (ADS)

The transfer of acoustic information can be represented as consisting of three parts: the source, the medium, and the receiver. The transmitted information (signal) arrives at the receiver distorted by the medium and corrupted by noise. Thus, even when the signal is deterministic in nature, a complete description of the received signal must be a statistical one. That is to say, any processing carried out on the received energy must contain the best characterization of the distortion by the medium and corruption by the noise that is available, and this can only be done in terms of statistics.

Sullivan, Edmund J.


Array signal processing  

SciTech Connect

This is the first book to be devoted completely to array signal processing, a subject that has become increasingly important in recent years. The book consists of six chapters. Chapter 1, which is introductory, reviews some basic concepts in wave propagation. The remaining five chapters deal with the theory and applications of array signal processing in (a) exploration seismology, (b) passive sonar, (c) radar, (d) radio astronomy, and (e) tomographic imaging. The various chapters of the book are self-contained. The book is written by a team of five active researchers, who are specialists in the individual fields covered by the pertinent chapters.

Haykin, S.; Justice, J.H.; Owsley, N.L.; Yen, J.L.; Kak, A.C.



Motion signal processing  

Microsoft Academic Search

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

Armin Bruderlin; Lance Williams



Pulsar signal processing  

Microsoft Academic Search

The paper reviews the principal methods which have been used in searching for and processing pulsar signals, with only a minimum amount of attention given to the physical implications of pulsar data. The fast folding algorithm (FFA) and fast Fourier transform (FFT) methods of period searching are described along with digital dispersion search techniques. The effect of interstellar dispersion on

T. H. Hankins; B. J. Rickett



Microwave photonic signal processing.  


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

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



Long range correlation in earthquake precursory signals  

NASA Astrophysics Data System (ADS)

Research on earthquake prediction has drawn serious attention of the geophysicist, geologist and investigators in different fields of science across the globe for many decades. Researchers around the world are actively working on recording pre-earthquake changes in non-seismic parameters through a variety of methods that include anomalous changes in geochemical parameters of the Earth's crust, geophysical properties of the lithosphere as well as ionosphere etc. Several works also have been done in India to detect earthquake precursor signals using geochemical and geophysical methods. However, very few works have been done so far in India in this field through the application of nonlinear techniques to the recorded geophysical and geochemical precursory signals for earthquakes. The present paper deals with a short review of the early works on geochemical precursors that have been carried out in India as yet. With a view to detect earthquake precursory signals by means of gas-geochemical method we developed a network of seismo-geochemical monitoring observatories in India in hot springs and mud volcano crater. In the last few years we detected several geochemical anomalies and those were observed prior to some major earthquakes that occurred within a radius of 1500 km from the test sites. In the present paper we have applied nonlinear techniques to the long term, real-time and natural data sets of radon-222 and associated gamma originated out of the terrestrial degassing process of the earth. The results reveal a clear signature of the long range correlation present in the geochemical time series. This approach appears to be a potential tool to explore intrinsic information hidden within the earthquake precursory signals.

Chaudhuri, H.; Barman, C.; Iyengar, A. N. S.; Ghose, D.; Sen, P.; Sinha, B.



Locally Measured Neuronal Correlates of Functional MRI Signals  

Microsoft Academic Search

\\u000a Functional MRI (fMRI) utilizes changes in metabolic and hemodynamic signals in order to infer the underlying local changes\\u000a in neuronal activity. fMRI signals are therefore an indirect measure of neuronal activity, with the involvement of intermediary\\u000a processes of neurovascular coupling and MRI measurements. This chapter summarizes the current concepts surrounding the neuronal\\u000a correlates of fMRI signals measured locally and the

Amir Shmuel


Nanotubes for noisy signal processing  

NASA Astrophysics Data System (ADS)

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.

Lee, Ian Yenyin


Digital signal processing the Tevatron BPM signals  

SciTech Connect

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.

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



Survey of Radar Signal Processing.  

National Technical Information Service (NTIS)

During the last decade, considerable progress has been made in radar signal processing, and this report states its present status. The three broad areas of coherent processing, noncoherent detection, and track-while-scan systems are discussed. Specificall...

G. V. Trunk



Signal processing for automotive applications  

Microsoft Academic Search

The complexity of automobiles has increased sharply. Consumer demands for better performance at a low cost have caused a boom in electrical components. Many of these components require the use of signal processing techniques to provide the desired response. The authors discuss signal processing for use in “smart” sensor design for automotive applications. The paper begins with a general overview

Tony Gioutsos



Trends in radar signal processing  

Microsoft Academic Search

It is thought that the commercial very large scale intergration (VLSI) efforts, along with the military Very High Speed Integrated Circuits (VHSIC) program, will be of overwhelming importance in the future development of digital radar signal processing and data processing. Sucess in VLSI\\/VHSIC goals will also reduce software costs through the use of oversized low-cost signal processor hardware, for example

E. Brookner



Integrating ocean acoustics and signal processing  

NASA Astrophysics Data System (ADS)

The combination of ocean acoustical physics and signal processing has been the central theme of our research over the last twenty years. In particular, the thrust of our research has been in matched field processing, waveguide invariant physics, time reversal acoustics, acoustic communications, sensitivity kernel analysis, and correlation based noised processing. Common to all these areas is the complexity of the medium so that our research goals have been to either overcome the downside of the complexity or, more interestingly, actually utilize propagation and noise complexity and diversity in the extraction of signal and environmental acoustic information. We present examples emphasizing this common theme.

Kuperman, W. A.; Song, H. C.



Neural Network Communications Signal Processing.  

National Technical Information Service (NTIS)

This final technical report describes the research and development results of the Neural Network Communications Signal Processing (NNCSP) Program. The objectives of the NNCSP program are to: (1) develop and implement a neural network and communications si...

D. Tebbe J. Doner T. Billhartz



Systolic processor for signal processing  

SciTech Connect

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

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



Statistical signal processing approach to DNA repair  

Microsoft Academic Search

Signal processing, and especially statistical signal processing, is a field in which generic tools for modeling, analysis and processing of signals are developed. Traditionally, it has been used in technology, and most modern technological systems apply advanced signal processing. However, the post-genomic era introduces challenges which, from a signal processing point of view, may lead to new understanding and promising

R. Sever; H. Messer



Immunocomputing for intelligent signal processing  

Microsoft Academic Search

Based on immunocomputing (IC), this paper describes an approach to intelligent signal processing. The approach includes both\\u000a low-level feature extraction and high-level (intelligent) pattern recognition. The key model is the formal immune network\\u000a (FIN), which includes apoptosis (programmed cell death) and immunization and controls them by cytokines (messenger proteins).\\u000a Such FIN can be formed from the signal or combination of

Alexander O. Tarakanov



Timing control and signal processing design of the MOPITT instrument  

Microsoft Academic Search

The MOPITT instrument operates on the principle of correlation spectroscopy where the incoming signal is modulated by gas filter and chopper mechanisms and synchronously demodulated within the signal processing system. The performance and flexibility required by the MOPITT instrument resulted in the development of a novel timing control and signal processing design. This design synchronizes modulation and demodulation from a

Dennis Henry; John P. Hackett; James R. Drummond; Roger Colley



Long-time Correlations in Electromyography Signals  

NASA Astrophysics Data System (ADS)

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

Zurcher, Ulrich; Maynard, Rachel



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.


Signal processor for processing ultrasonic receiver signals  


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

Fasching, George E. (Morgantown, WV)



FPGA based signal processing structures  

Microsoft Academic Search

This paper presents the implementation method for two signal processing structures, a digital FIR filter and a discrete Fourier transform, using programmable logic structures and VHDL hardware description language. In the field of telecommunications FPGAs are beginning to be more frequently used as a result of the significant DSP-oriented architectural enhancements that Altera and Xilinx producers offer: hardwired on-chip multipliers

I. Lie; C. Beschiu; S. Nanu



Multirate signal processing in Ptolemy  

Microsoft Academic Search

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,

J. Buck; S. Ha; E. A. Lee; D. G. Messerschmitt



New Tool for Signal Processing.  

National Technical Information Service (NTIS)

Recent work has continued to study applications of the Weil transform to radar signal processing and, in a parallel effort, to multi-access spread spectrum communications. The main thrust of the work is the relationship between the Weil transform of a wav...

L. Auslander



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

NASA Astrophysics Data System (ADS)

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

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



Lower Bounds on the Maximum Cross Correlation of Signals.  

National Technical Information Service (NTIS)

Some communication systems require sets of signals with impulse-like autocorrelation functions and small cross correlation. There is considerable literature on signals with impulse-like autocorrelation functions but little on sets of signals with small cr...

L. R. Welch



Broadband source localization using matched correlation processing  

NASA Astrophysics Data System (ADS)

For many years, model-based signal processing algorithms using Matched Field Processing (MFP) techniques have been analyzed with the goal of improving the capability of passive sonar systems for localizing quiet underwater sources. Recently, researchers at DRDC Atlantic have been investigating Matched Correlation Processing (MCP) as a faster alternative to MFP. In this method, the cross-correlations for a source as measured with a pair of hydrophones in a horizontal array are matched with those generated with a correlation model for many candidate ranges and depths along a candidate bearing. These matches are carried out with a number of hydrophone pairs to form many ambiguity surfaces. The maximum on the average of these surfaces is assumed to yield the best estimate of the source position. By carrying out this procedure over a number of candidate bearings, a full 3-D search for the source location is achieved. Since 2002, a number of localization trials have been carried out east of Nova Scotia, Canada. During those trials, an array was deployed on the sea floor and used to collect acoustic signals from various broadband sources. In this paper, we describe the broadband MCP localization technique and show some localization results from those trials.

Ebbeson, Gordon R.; Matthews, Marie-Noël R.; Heard, Garry J.; Desharnais, Francine; Thomson, David J.



Wave-based signal processing  

NASA Astrophysics Data System (ADS)

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

McClure, Mark Richard


Signal processing in cellular clocks  

PubMed Central

Many biochemical events within a cell need to be timed properly to occur at specific times of day, after other events have happened within the cell or in response to environmental signals. The cellular biochemical feedback loops that time these events have already received much recent attention in the experimental and modeling communities. Here, we show how ideas from signal processing can be applied to understand the function of these clocks. Consider two signals from the network s(t) and r(t), either two variables of a model or two experimentally measured time courses. We show how s(t) can be decomposed into two parts, the first being a function of r(t), and the second the derivative of a function of r(t). Geometric principles are then derived that can be used to understand when oscillations appear in biochemical feedback loops, the period of these oscillations, and their time course. Specific examples of this theory are provided that show how certain networks are prone or not prone to oscillate, how individual biochemical processes affect the period, and how oscillations in one chemical species can be deduced from oscillations in other parts of the network.

Forger, Daniel B.



Signal processing for distributed sensor concept: DISCO  

NASA Astrophysics Data System (ADS)

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

Rafailov, Michael K.



Digital Signal Processing and Machine Learning  

NASA Astrophysics Data System (ADS)

Any brain-computer interface (BCI) system must translate signals from the users brain into messages or commands (see Fig. 1). Many signal processing and machine learning techniques have been developed for this signal translation, and this chapter reviews the most common ones. Although these techniques are often illustrated using electroencephalography (EEG) signals in this chapter, they are also suitable for other brain signals.

Li, Yuanqing; Ang, Kai Keng; Guan, Cuntai


Signal Representation and Processing of Nucleotide Sequences  

Microsoft Academic Search

Sets of related signals can be represented by separating their joint variation and showing the individual signal offsets with respect to this reference. An example is the genomic signal analysis of pathogen variability. The conversion of symbolic nucleotide sequences to genomic signals allows to use signal processing methods to analyze genomic data. This approach reveals striking regularities in the distribution

Paul Dan Cristea; Rodica Tuduce; Iulian Nastac; Jan Cornelis; Rudi Deklerck; Marius Andrei



An overview of signal processing in astronomy  

Microsoft Academic Search

Abstract only given, as follows: signal processing is extensively used in astronomy for spectroscopy and synthetic imaging. Signals from celestial sources are stochastic in nature and weak compared to local sources of noise. Thus the emphasis is on improving the signal-to-noise-ratio. This necessitates the use of large bandwidths and real time processing of the signal. Considerable practical gain is obtained

S. R. Kulkarni



A digital signal processing approach to interpolation  

Microsoft Academic Search

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




Network-Centric Distributed Signal Processing.  

National Technical Information Service (NTIS)

This project investigates distributed signal processing in the context of sensor enhanced mobile ad hoc networks. The objective of the project is twofold. First, the research aims to create a new framework for Network Centric Signal Processing that facili...

L. Tong



No-signaling, perfect bipartite dichotomic correlations and local randomness  

SciTech Connect

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

Seevinck, M. P. [Institute for Mathematics, Astrophysics and Particle Physics, Faculty of Science and Centre for the History of Philosophy and Science, Faculty of Philosophy, Radboud University Nijmegen (Netherlands)



Characterization of cyclostationary random signal processes  

Microsoft Academic Search

Many communication and control systems employ signal formats that involve some form of periodic processing operation. Signals produced by samplers, scanners, multiplexors, and modulators are familiar examples. Often these signals are appropriately modeled by random processes that are cyclostationary (CS), i.e., processes with statistical parameters, such as mean and autocorrelation, that fluctuate periodically with time. In this paper we examine




The problem of signal correlation in spaced antennas  

Microsoft Academic Search

Signal correlation in an array of spaced antennas, with sharply differing directivity-characteristics, is studied as a function of angle of arrival and antenna spacing in the presence of a fluctuating field. An expression is obtained for the signal correlation coefficient, and consideration is given to the effect of different directivity characteristics (e.g., sharply directional and weakly directional) of different antennas

E. Sh. Goikhman; A. K. Zhitetskii



Mining Machine Control Signal Processing System  

SciTech Connect

A signal processing system for an underground mining machine having a steerable mineral cutter and a sensor which senses natural radiation emitted from rock strata overlaying the radiation absorbing mineral and which derives a sensor signal representative of the cutting horizon of the cutter, comprises processing means for receiving and processing the sensor signal to derive an operational signal indicative of the cutter horizon of the cutter, calibration means for accepting a fed in calibration signal representative of a known existing condition of the cutting horizon and comparator means for comparing the derived operational signal with the calibration signal to determine an error in the derived operational signal and for instructing the processing means to apply a suitable correction to the derived operational signal.

Fecitt, G.J.



The EEG Signal Process Based on EEMD  

Microsoft Academic Search

Hilbert Huang Transform (HHT), which is based on EMD (Empirical Mode Decomposition) and Hilbert transform method, is a new signal analysis method. It suits for analyzing the non-linear and non-stationary signals, such as EEG signal particularly. The traditional EMD method has the Mode Mixing problem. Therefore a new method basing on Ensemble Empirical Mode Decomposition (EEMD) for processing the signal

Zhu Xiao-jun; Lv Shi-qin; Liu-juan Fan; Xue-li Yu



Stochastic search for signal processing algorithm optimization  

Microsoft Academic Search

This paper presents an evolutionary algorithm for searching for the optimal implementations of signal transforms and compares this approach against other search techniques. A single signal processing algorithm can be represented by a very large number of different but mathematically equivalent formulas. When these formulas are implemented in actual code, unfortunately their running times differ significantly. Signal processing algorithm optimization

Bryan Singer; Manuela M. Veloso



Robust techniques for signal processing - A survey  

Microsoft Academic Search

A survey which focuses on minimax robust signal-processing schemes is examined. Although key results of other robust statistical procedures are considered, the emphasis is on the contributions made in robust signal processing. It is shown that robustness formulations take two basic forms: robustness with respect to uncertain second-order statistical properties (spectral properties) of signals of noise and robustness with respect

S. A. Kassam; H. V. Poor



Pseudocolor engraving prints using signal processing methods  

NASA Astrophysics Data System (ADS)

In this contribution we propose an application for pseudo-color engraving-prints. Usually, the prints that are made with relief and intaglio techniques, are black and white images composite by a group of binary lines. Several texture and gray levels are obtained changing direction and density of lines in the print. We propose an application based signal processing methods to pseudo-color black and white prints. The proposed method can be done in real time using a white light optical correlator. The different color channels R, G and B could be encode simultaneously using a color film for filter representation. In this way the pseudo-color processing can be done in one cycle of the optical processor.

Hoelck, D.; Barbe, J.



Processing Aftershock Sequences Using Waveform Correlation  

NASA Astrophysics Data System (ADS)

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

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



[Dynamic pulse signal acquisition and processing].  


In order to obtain and process pulse signal in real-time, the integer coefficients notch, low-pass filters and an envelope filtering method were designed in consideration of the characteristics of disturbances in pulse signal and then were verified by MATLAB. The pulse signal was processed on DSP in time domain and frequency domain after simplifying the programming. The pulse wave height and pulse rate were calculated in real-time, and the pulse signal's spectrum was illustrated by FFT. The results show that the filters can effectively suppress the interference in pulse signal, and the system can detect and analyze the dynamic pulse signal in real-time. PMID:22737882

Zhang, Aihua; Chou, Yongxin



Signal processing for single tooth milling monitoring  

NASA Astrophysics Data System (ADS)

This paper describes the systematic development of a signal processing scheme aimed at monitoring tool wear development during a specific machining process. Classical processing schemes in the time and frequency domain are first used in order to obtain general signal characteristics. A signal generation model, using the concept of cyclostationary processes is then developed. A final processing scheme is then matched to extract specific features from the signal. Both the systematic approach, as well as the finally implemented scheme seem to offer viable approaches to the general task of monitoring high frequency vibrations in machine tools.

Braun, S.; Rotberg, J.; Lenz, E.



Psychophysiological correlates of face processing in social phobia  

Microsoft Academic Search

Social phobia has been associated with abnormal processing of angry faces, which directly signal disapproval—a situation that social phobics fear. This study investigated the electrophysiological correlates of emotional face processing in socially phobic and non-phobic individuals. Subjects identified either the gender (modified emotional Stroop task) or the expression of angry, happy, or neutral faces. Social phobics showed no deviations from

Iris-Tatjana Kolassa; Wolfgang H. R. Miltner



Signal Propagation in Cortical Networks: A Digital Signal Processing Approach  

PubMed Central

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

Rodrigues, Francisco Aparecido; da Fontoura Costa, Luciano



Signal Processing and Neural Network Simulator  

NASA Astrophysics Data System (ADS)

The signal processing and neural network simulator (SPANNS) is a digital signal processing simulator with the capability to invoke neural networks into signal processing chains. This is a generic tool which will greatly facilitate the design and simulation of systems with embedded neural networks. The SPANNS is based on the Signal Processing WorkSystemTM (SPWTM), a commercial-off-the-shelf signal processing simulator. SPW provides a block diagram approach to constructing signal processing simulations. Neural network paradigms implemented in the SPANNS include Backpropagation, Kohonen Feature Map, Outstar, Fully Recurrent, Adaptive Resonance Theory 1, 2, & 3, and Brain State in a Box. The SPANNS was developed by integrating SAIC's Industrial Strength Neural Networks (ISNN) Software into SPW.

Tebbe, Dennis L.; Billhartz, Thomas J.; Doner, John R.; Kraft, Timothy T.



Process Dissociation and Mixture Signal Detection Theory  

ERIC Educational Resources Information Center

|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…

DeCarlo, Lawrence T.



Process Dissociation and Mixture Signal Detection Theory  

ERIC Educational Resources Information Center

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…

DeCarlo, Lawrence T.



Quantum correlations in predictive processes  

NASA Astrophysics Data System (ADS)

We consider the role of quantum correlations in the efficient use of information by a predictive quantum system, generalizing a recently proposed classical measure of nonpredictive information to the quantum regime. We show that, as a quantum system changes state, the nonpredictive information held by another correlated quantum system is exactly equal to the extractable work that is lost from the second system. We use quantum discord to quantify the quantum contribution, and demonstrate the possibility of improved thermodynamic efficiency due to a negative “quantum part” of the lost work. We also give a thermodynamic interpretation to quantum discord, as the reduction in extractable work under an optimal classical approximation of a quantum memory.

Grimsmo, Arne L.



Signal processing in 2 dimensional Doppler echocardiography  

Microsoft Academic Search

Summary Blood flow recordings made by 2 dimensional Doppler echocardiography can sometimes be understood more easily than conventional Doppler recordings, because of the anatomical 2 dimensional presentation. In contrast, signal processing has become more complicated and requires more explanation. In 2 dimensional Doppler echocardiography the analog ultrasonic signal received by the transducer is converted into an audible signal, which next

Hans Bot; Ben J. Delemarre; Cees A. Visser; Arend J. Dunning



New technologies for signal processing  

Microsoft Academic Search

The signal processors considered include the charge-transfer device (CTD) and the surface acoustic-wave (SAW) device. A CTD is an array of closely spaced capacitors fabricated by using metal oxide semiconductor technology. The basic operation of a CTD delay line is discussed along with two applications that are made possible by the unique capabilities of the CTD. In SAW devices information

R. W. Brodersen; R. M. White



FPGA-Based Digital Signal Processing Trainer  

Microsoft Academic Search

Field programmable gate arrays (FPGAs) have been used in a wide range of applications including the field of digital signal processing (DSP). This paper presents the use of an FPGA in the implementation of a DSP trainer that will serve as an educational tool to effectively teach the fundamental principles of digital signal processing. This trainer is capable of performing

Rosula S. Reyes; Carlos M. Oppus; Jose Claro N. Monje; Noel S. Patron; Raphael A. Gonzales; Jovilyn Therese B. Fajardo



Signal Processing in WiMAX System  

Microsoft Academic Search

The aim of this work is to describe physical layer digital signal processing in the WiMAX system. A physical layer transfer chain flow chart is drawn and all important aspects of digital signal processing are discussed. For this purpose a transfer chain model in Matlab was made. The results of this work concern the WiMAX system's resistance to disturbance.

M. Skapa; S. Hanus



Studies in Statistical Signal Processing.  

National Technical Information Service (NTIS)

Several new results in the modeling, analysis and prediction of nonstationary second order processes have been developed. They include (1) the derivation of constant-parameter lattice filters for general nonstationary processes; (2) the development of fas...

T. Kailath



Correlation Spectroscopy of Minor Species: Signal Purification and Distribution Analysis  

SciTech Connect

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

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



Moving target detection via digital time domain correlation of random noise radar signals  

Microsoft Academic Search

Ultra-wideband random noise radar theoretically has a thumbtack ambiguity function, which cannot be realized due to hardware, processing, and environmental limitations. Velocity estimation using traditional Doppler processing is not practicable for ultra-wideband random noise radar because of the large fractional bandwidth. Through analysis, this paper explores moving target detection using digital correlation processing of random noise signals in the time

James R. Lievsay; Geoffrey A. Akers



Signal processing methods for MFE plasma diagnostics  

SciTech Connect

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

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



Digital signal processing techniques for high accuracy ultrasonic range measurements  

Microsoft Academic Search

Several digital signal processing (DSP) methods are analyzed and compared with respect to the expected errors for an ultrasonic range measurement arrangement. These include L1, L2 norms and correlation with different approaches for envelope extraction. The influence of different factors such as signal-to-noise ratio (SNR), sampling frequency, and digitizing resolution on measurement errors is analyzed using a synthetic approach through

M. Parrilla; J. J. Anaya; C. Fritsch



Correlation of nighttime MF signal strength with solar activity  

NASA Astrophysics Data System (ADS)

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

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


Surface electromyography signal processing and classification techniques.  


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

Chowdhury, Rubana H; Reaz, Mamun B I; Ali, Mohd Alauddin Bin Mohd; Bakar, Ashrif A A; Chellappan, K; Chang, T G



Stochastic Processes for Canonical Correlation Analysis  

Microsoft Academic Search

We consider two stochastic process methods for performing canonical correlation analysis (CCA). The flrst uses a Gaussian Process formulation of regression in which we use the current projection of one data set as the target for the other and then repeat in the opposite direction. The second uses a Dirichlet process of Gaussian models where the Gaussian models are determined

Colin Fyfe; Gayle Leen



Blind deconvolution through digital signal processing  

Microsoft Academic Search

This paper addresses the problem of deconvolving two signals when both are unknown. The authors call this problem blind deconvolution. The discussion develops two related solutions which can be applied through digital signal processing in certain practical cases. The case of reverberated and resonated sound forms the center of the development. The specific problem of restoring old acoustic recordings provides

T. M. Cannon; R. B. Ingebretsen



Detection of anomalous signals in temporally correlated data (Invited)  

NASA Astrophysics Data System (ADS)

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.

Langbein, J. O.



Spatial processing of signals received by platform mounted sonar  

Microsoft Academic Search

Acoustic signals received by platform mounted sonar arrays can be spatially processed to enhance the detection of targets in the presence of both ambient and platform generated (self) noise. Ambient noise in the ocean, such as that due to distant shipping or biological choruses, are known to be spatially correlated. The platform generated noise will be of near-field origin and

I. S. D. Solomon; A. J. Knight



Hardware Implementations of Fourier Transform Signal Processing.  

National Technical Information Service (NTIS)

Methods for signal processing using transform techniques are reviewed with the aim of putting these into perspective, clarifying the chief options available to an intending user and indicating how he should choose between them, bearing in mind the constra...

J. B. G. Roberts D. Greenhalgh G. M. Dillard



Digital Signal Processing Leveraged for Intrusion Detection.  

National Technical Information Service (NTIS)

This thesis describes the development and evaluation of a novel system called the Network Attack Characterization Tool (NACT). The NACT employs digital signal processing to detect network intrusions, by exploiting the Lomb- Scargle periodogram method to o...

T. J. Erickson



Signal Processing Applications of Systolic Array Technology.  

National Technical Information Service (NTIS)

Architectures and algorithms are examined for exploiting the large number of degrees of freedom available in current VLSI and projected VHSIC integrated circuit technologies to provide real-time implementations for sonar signal processing tasks. Such real...

H. J. Whitehouse J. M. Speiser K. Bromley



Uncertainty, fuzzy logic, and signal processing  

Microsoft Academic Search

In this paper we focus on model-based statistical signal processing and how some problems that are associated with it can be solved using fuzzy logic. We explain how uncertainty (which is prevalent in statistical signal processing applications) can be handled within the framework of fuzzy logic. Type-1 singleton and non-singleton fuzzy logic systems (FLSs) are reviewed. Type-2 FLSs, which are

Jerry M. Mendel



Adaptive filtering in biological signal processing.  


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

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



Gaussian processes for canonical correlation analysis  

Microsoft Academic Search

We consider several stochastic process methods for performing canonical correlation analysis (CCA). The first uses a Gaussian process formulation of regression in which we use the current projection of one data set as the target for the other and then repeat with the second projection as the target for adapting the parameters of the first. The second uses a method

Colin Fyfe; Gayle Leen; Pei Ling Lai



Novel sonar signal processing tool using Shannon entropy  

SciTech Connect

Traditionally, conventional signal processing extracts information from sonar signals using amplitude, signal energy or frequency domain quantities obtained using spectral analysis techniques. The object is to investigate an alternate approach which is entirely different than that of traditional signal processing. This alternate approach is to utilize the Shannon entropy as a tool for the processing of sonar signals with emphasis on detection, classification, and localization leading to superior sonar system performance. Traditionally, sonar signals are processed coherently, semi-coherently, and incoherently, depending upon the a priori knowledge of the signals and noise. Here, the detection, classification, and localization technique will be based on the concept of the entropy of the random process. Under a constant energy constraint, the entropy of a received process bearing finite number of sample points is maximum when hypothesis H{sub 0} (that the received process consists of noise alone) is true and decreases when correlated signal is present (H{sub 1}). Therefore, the strategy used for detection is: (I) Calculate the entropy of the received data; then, (II) compare the entropy with the maximum value; and, finally, (III) make decision: H{sub 1} is assumed if the difference is large compared to pre-assigned threshold and H{sub 0} is otherwise assumed. The test statistics will be different between entropies under H{sub 0} and H{sub 1}. Here, we shall show the simulated results for detecting stationary and non-stationary signals in noise, and results on detection of defects in a Plexiglas bar using an ultrasonic experiment conducted by Hughes. {copyright} {ital 1996 American Institute of Physics.}

Quazi, A.H. [Code 3122, Naval Undersea Warfare Center, Detachment, New London, Connecticut 06320 (United States)



Sonar signal processing using probabilistic signal and ocean environmental models.  


Acoustic signals propagating through the ocean are refracted, scattered, and attenuated by the ocean volume and boundaries. Many aspects of how the ocean affects acoustic propagation are understood, such that the characteristics of a received signal can often be predicted with some degree of certainty. However, acoustic ocean parameters vary with time and location in a manner that is not, and cannot be, precisely known; some uncertainty will always remain. For this reason, the characteristics of the received signal can never be precisely predicted and must be described in probabilistic terms. A signal processing structure recently developed relies on knowledge of the ocean environment to predict the statistical characteristics of the received signal, and incorporates this description into the processor in order to detect and classify targets. Acoustic measurements at 250 Hz from the 1996 Strait of Gibraltar Acoustic Monitoring Experiment are used to illustrate how the processor utilizes environmental data to classify source depth and to underscore the importance of environmental model fidelity and completeness. PMID:19206791

Culver, R Lee; Camin, H John



Multi-dimensional signal processing research program  

NASA Astrophysics Data System (ADS)

This Semiannual Technical Summary covers the period 1 October 1982 through 31 March 1983. It describes the significant results of the Lincoln Laboratory Multi-Dimensional Signal Processing Research Program, sponsored by the Rome Air Development Center, in the areas of multiprocessor architectures for image processing and algorithms for object detection and region classification in aerial reconnaissance imagery.

Dudgeon, D. E.



Programmable Radar Signal Processing Using the Rap  

Microsoft Academic Search

This paper describes the architecture of the Raytheon Associative\\/Array Processor (RAP) and its application to real-time radar signal processing. The nature of radar computations is analyzed and parallel processing requirements are characterized. The effects of these requirements upon the design of the RAP are described. Features of the operational RAP system are discussed. Finally, an implementation of a Constant False

George R. Couranz; Mark S. Gerhardt; Charles J. Young



Calibration of Correlation Radiometers Using Pseudo-Random Noise Signals  

PubMed Central

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

Perez, Isaac Ramos; Bosch-Lluis, Xavi; Camps, Adriano; Alvarez, Nereida Rodriguez; Hernandez, Juan Fernando Marchan; Domenech, Enric Valencia; Vernich, Carlos; de la Rosa, Sonia; Pantoja, Sebastian



Calibration of correlation radiometers using pseudo-random noise signals.  


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

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



Signal processing in 2 dimensional Doppler echocardiography.  


Blood flow recordings made by 2 dimensional Doppler echocardiography can sometimes be understood more easily than conventional Doppler recordings, because of the anatomical 2 dimensional presentation. In contrast, signal processing has become more complicated and requires more explanation. In 2 dimensional Doppler echocardiography the analog ultrasonic signal received by the transducer is converted into an audible signal, which next is digitized and analyzed for its mean frequency and variance. Data collection and processing require application of multigating and high speed frequency analysis, generally based upon autocorrelation. Some artifacts may be perceived, such as color reversal due to aliasing, deceptively colored tissue surfaces due to beam motion, and wall motion ghost signals due to multiple reflections. Color flow imaging is appropriate for a rapid scan of the heart cavities to detect and roughly evaluate flow abnormalities. Quantification is still accomplished by switching to conventional Doppler mode. PMID:3323330

Bot, H; Delemarre, B J; Visser, C A; Dunning, A J



Numerical optimization method for array signal processing  

Microsoft Academic Search

This paper presents a novel and efficient extrema-mapping algorithm, which we call the roller-coaster algorithm. Two versions of the algorithm, the one-dimensional (1-D) and the two-dimensional (2-D) roller-coaster, are developed. Its applicability to array signal processing is demonstrated. We use it to solve a multiple source direction finding problem using multiple signal classification (MUSIC), beamformer, and minimum variance methods, and

R. Tweg; B. Porat



An introduction to digital signal processing  

NASA Astrophysics Data System (ADS)

An introduction to digital signal processing (DSP) is presented for those who need to understand and use DSP without going through a full course of study. The topics addressed include: signals and systems, sampled data and the Z transform, sinusoidal responses of LSI systems, couplets and elementary filters, the discrete Fourier transform, the continuous Fourier integral transform, application of the Fourier transform to DSP, digital filter design, inverse filtering and deconvolution, spectral factorization, power spectral estimation, and multidimensional DSP.

Karl, John H.


Digital processing of signals from femtosecond combs  

NASA Astrophysics Data System (ADS)

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

?ížek, Martin; Šmíd, Radek; Buchta, Zden?k.; Mikel, B?etislav; Lazar, Josef; ?íp, Ondrej



Real-time holographic correlation of two video signals by using bacteriorhodopsin films  

Microsoft Academic Search

A dual-axis joint-Fourier-transform correlator is described with two liquid-crystal television screens as input devices and a bacteriorhodopsin film as the active holographic material in the Fourier plane. The experimental data presented demonstrate that this system is capable of processing two independent video signals in real time with a signal-to-noise ratio of 45 dB.

R. Thoma; N. Hampp



Software development kit for electrophysiological signals processing.  


A software development kit (SDK) for electrophysiological signal processing (hardware control, storage, and graphic visualization) is presented. Its architecture is described, and emphasis is made on the underlying technology. Results obtained in continuous EEG and Evoked Potential monitoring at Cuban Neuroscience Center are presented. PMID:8591309

Carballosa, J; De Armas, J; Leonard, J



Biomedical signal processing: present and future  

Microsoft Academic Search

Summary form only given, as follows. Biomedical signal processing is a rapidly expanding field with a wide range of applications. These range from the construction of artificial limbs and aids for the disabled to the development of sophisticated medical imaging systems that can operate in a non-invasive manner to give real time views of the workings of the human body.

Y. Attikiouzel



Optimizing Arithmetic Elements For Signal Processing  

Microsoft Academic Search

Minimizing the power consumption and area of circuits is important for digital signal processing because of the large number of cir- cuits that are integrated to implement a system. For arithmetic circuits, it is also important to maximize the speed. This paper reports on the dynamic power dissipation, area, and speed of CMOS implementations of' several different adders and multipliers.

Thomas K. Callaway; Earl E. Swartzlander



Signal Processing Challenges for Neural Prostheses  

Microsoft Academic Search

Cortically controlled prostheses are able to translate neural activity from the cerebral cortex into control signals for guiding computer cursors or prosthetic limbs. While both noninvasive and invasive electrode techniques can be used to measure neural activity, the latter promises considerably higher levels of performance and therefore functionality to patients. The process of translating analog voltages recorded at the electrode

Michael D. Linderman; Gopal Santhanam; Caleb T. Kemere; Vikash Gilja; Stephen O'Driscoll; Byron M. Yu; Afsheen Afshar; Stephen I. Ryu; Krishna V. Shenoy; Teresa H. Meng



Signal Processing Test Facility Target Simulator.  

National Technical Information Service (NTIS)

A Target Simulator was designed, built, and installed in the Signal Processing Test Facility (SPTF) located at the Floyd Test Annex, RADC, Rome, N.Y. It is used to generate fixed and moving targets for evaluation of the performance of the high-resolution ...

J. M. Tegins



Information theoretic criteria for the determination of the number of signals in spatially correlated noise  

Microsoft Academic Search

The problem of determining the number of signals in high-resolution array processing when the noise is spatially correlated (having an unknown covariance matrix) is examined. By considering a model in which two sensor arrays are well separated such that their noise outputs are uncorrelated, the authors develop a likelihood function whose maximum can be expressed in a very simple form

Q. T. Zhang; Kon Max Wong



Scaling radio astronomy signal correlation on heterogeneous supercomputers using variousdata distribution methodologies  

NASA Astrophysics Data System (ADS)

Next generation radio telescopes will require orders of magnitude more computing power to provide a view of the universe with greater sensitivity. In the initial stages of the signal processing flow of a radio telescope, signal correlation is one of the largest challenges in terms of handling huge data throughput and intensive computations. We implemented a GPU cluster based software correlator with various data distribution models and give a systematic comparison based on testing results obtained using the Fornax supercomputer. By analyzing the scalability and throughput of each model, optimal approaches are identified across a wide range of problem sizes, covering the scale of next generation telescopes.

Wang, Ruonan; Harris, Christopher



Signal processing methods to improve high resolution ECG signal averaging  

Microsoft Academic Search

Coherent signal averaging as a method to enhance signal to noise ratio (SNR) relies on the determination of a fiducial point for temporal alignment of signals. Various alignment methods have been proposed but they produce alignment errors when the signal is corrupted with noise, resulting in a low-pass filtering effect on the averaged signal. In high resolution ECG, alignment errors

Luis G. Herrera-Bendezu; Bart G. Denys; P. S. Reddy



Signal processing of multi-channel data  

US Patent & Trademark Office Database

An approach for providing non-commutative approaches to signal processing. Quaternions are used to represent multi-dimensional data (e.g., three- and four-dimensional data). Additionally, a linear predictive coding scheme (e.g., based on the Levinson algorithm) that can be applied to wide class of signals in which the autocorrelation matrices are not invertible and in which the underlying arithmetic is not commutative. That is, the linear predictive coding scheme multi-channel can handle singular autocorrelations, both in the commutative and non-commutative cases. This approach also utilizes random path modules to replace the statistical basis of linear prediction.

Paris; Alan T. (Jackson, MS)



Thirty years of underwater acoustic signal processing in China  

NASA Astrophysics Data System (ADS)

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

Li, Qihu



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

NASA Astrophysics Data System (ADS)

The AMS-02 collaboration has recently released data on the positron fraction e+/(e-+e+) 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 ?+?-, although this situation is already severely constrained by gamma-ray measurements.The annihilation into ?+?- is allowed by gamma-rays more than ?+?-, 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.

De Simone, Andrea; Riotto, Antonio; Xue, Wei



Adaptive Signal Processing Relationship to Adaptive Observer Parameter Identification.  

National Technical Information Service (NTIS)

The acoustic signal processing method of LMS adaptive filtering is related to the problem of system parameter identification. Adaptive signal processing is dictated by the nonstationary ocean acoustic environment. Improvements in adaptive signal processin...

D. O. Molnar G. L. Mitchell R. G. Clapham



Complementary contributions of indeterminism and signaling to quantum correlations  

SciTech Connect

Simple quantitative measures of indeterminism and signaling, I and S, are defined for models of statistical correlations. It is shown that any such model satisfies a generalized Bell-type inequality, with tight upper bound B(I,S). This upper bound explicitly quantifies the complementary contributions required from indeterminism and signaling, for modeling any given violation of the standard Bell-Clauser-Horne-Shimony-Holt (Bell-CHSH) inequality. For example, all models of the maximum quantum violation must either assign no more than 80% probability of occurrence to some underlying event, and/or allow a nonlocal change of at least 60% in an underlying marginal probability of one observer in response to a change in measurement setting by a distant observer. The results yield a corresponding complementarity relation between the numbers of local random bits and nonlocal signaling bits required to model a given violation. A stronger relation is conjectured for simulations of singlet states. Signaling appears to be a useful resource only if a 'gap' condition is satisfied, corresponding to being able to nonlocally flip some underlying marginal probability p to its complementary value 1-p.

Hall, Michael J. W. [Theoretical Physics, Research School of Physics and Engineering, Australian National University, Canberra, ACT 0200 (Australia)



Enhanced multistatic active sonar signal processing.  


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

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



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

PubMed Central

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

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



B-spline signal processing. I. Theory  

Microsoft Academic Search

The use of continuous B-spline representations for signal processing applications such as interpolation, differentiation, filtering, noise reduction, and data compressions is considered. The B-spline coefficients are obtained through a linear transformation, which unlike other commonly used transforms is space invariant and can be implemented efficiently by linear filtering. The same property also applies for the indirect B-spline transform as well

M. Unser; A. Aldroubi; M. Eden



Digital Signal Processing in Home Entertainment  

Microsoft Academic Search

\\u000a Abstract In the last decade or so, audio and video media switched from analog to digital and so did consumer electronics.\\u000a In this chapter we explore how digital signal processing has affected the creation, distribution, and consumption of digital\\u000a media in the home. By using “photos”, “music”, and “video” as the three core media of home entertainment, we explore how

Konstantinos Konstantinides


Digital signal processing for beam position feedback  

SciTech Connect

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.

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



Correlation Between Eddy Current Signal Noise and Peened Surface Roughness  

NASA Astrophysics Data System (ADS)

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

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



Using Seismic Signals to Forecast Volcanic Processes  

NASA Astrophysics Data System (ADS)

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

Salvage, R.; Neuberg, J. W.



An intelligent onboard signal processing payload concept  

NASA Astrophysics Data System (ADS)

Our approach to onboard processing will enable a quicker return and improved quality of processed data from small, remote-sensing satellites. We describe an intelligent payload concept which processes RF lightning signal data onboard the spacecraft in a power-aware manner. Presently, onboard processing is severely curtailed due to the conventional management of limited resources and "power-unaware" payload designs. Delays of days to weeks are commonly experienced before raw data is received, processed into a human-usable format, and finally transmitted to the end-user. We enable this resource-critical technology of onboard processing through the concept of Algorithm Power Modulation (APM). APM is a decision process used to execute a specific software algorithm, from a suite of possible algorithms, to make the best use of the available power. The suite of software algorithms chosen for our application is intended to reduce the probability of false alarms through post-processing. Each algorithm however also has a cost in energy usage. A heuristic decision tree procedure is used which selects an algorithm based on the available power, time allocated, algorithm priority, and algorithm performance. We demonstrate our approach to power-aware onboard processing through a preliminary software simulation.

Shriver, Patrick; Harikumar, Jayashree; Briles, Scott D.; Gokhale, Maya




SciTech Connect

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




An intelligent, onboard signal processing payload concept  

SciTech Connect

Our approach to onboard processing will enable a quicker return and improved quality of processed data from small, remote-sensing satellites. We describe an intelligent payload concept which processes RF lightning signal data onboard the spacecraft in a power-aware manner. Presently, onboard processing is severely curtailed due to the conventional management of limited resources and power-unaware payload designs. Delays of days to weeks are commonly experienced before raw data is received, processed into a human-usable format, and finally transmitted to the end-user. We enable this resource-critical technology of onboard processing through the concept of Algorithm Power Modulation (APM). APM is a decision process used to execute a specific software algorithm, from a suite of possible algorithms, to make the best use of the available power. The suite of software algorithms chosen for our application is intended to reduce the probability of false alarms through postprocessing. Each algorithm however also has a cost in energy usage. A heuristic decision tree procedure is used which selects an algorithm based on the available power, time allocated, algorithm priority, and algorithm performance. We demonstrate our approach to power-aware onboard processing through a preliminary software simulation.

Shriver, P. M. (Patrick M.); Harikumar, J. (Jayashree); Briles, S. C. (Scott C.); Gokhale, M. (Maya)



Radar transponder apparatus and signal processing technique  


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.

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



Radar transponder apparatus and signal processing technique  


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.

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



Radar transponder apparatus and signal processing technique  


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.

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



Nonlinear real-time optical signal processing  

NASA Astrophysics Data System (ADS)

This report summarizes the results of a research program in nonlinear real-time optical signal processing. The program began April 15, 1981 and ended June 30, 1984. The research effort has centered on optical sequential logic systems and their use in digital optical computers, and on variable grating mode (VGM) liquid crystal spatial light modulators. As part of this study, parallel and twisted nematic liquid crystal light valve (LCLV) devices have been used as a nonlinear element in a feedback arrangement to implement a binary sequential logic system. A computer generated hologram fabricated on an e-beam system serves as a beamsteering interconnection element. A completely optical oscillator and frequency divider have been experimentally demonstrated, and various circuit interconnection techniques have been explored. Variable-grating mode (VGM) liquid crystal devices that perform local spatial frequency modulation as a function of the incident intensity have also been investigated. These devices can be used for nonlinear processing by selection and recombination of devices can be used for nonlinear processing by selection and recombination of these spatial frequency components. These devices have many interesting physical effects with useful applications in both analog and numerical optical signal processing.

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



Signal processing in ocean bottom seismographs for refraction seismology  

Microsoft Academic Search

This paper presents some experimental results on the application of signal processing techniques to underwater seismic signals. The novelty of this paper stems from the fact that it is the first paper, to the best of the authors' knowledge, dealing with a comprehensive processing of signals obtained from active refraction seismology. In particular, this paper has adapted known signal processing

Iban Rodríguez; A. Manuel-Lazaro; A. Carlosena; A. Bermudez; J. del Rio; S. S. Panahi



Signal Processing in Ocean Bottom Seismographs for Refraction Seismology  

Microsoft Academic Search

This paper presents some experimental results on the application of signal processing techniques to underwater seismic signals. The novelty of this paper stems from the fact that it is the first paper, to the best of the authors' knowledge, dealing with a comprehensive processing of signals obtained from active refraction seismology. In particular, this paper has adapted known signal processing

Iban Rodríguez; Alfonso Carlosena; Antoni Bermúdez; Shahram Shariat Panahi



Neural processes of preparatory control for stop signal inhibition.  


This study investigated the preparatory control of motor inhibition and motor execution using a stop signal task (SST) and functional magnetic resonance imaging (fMRI). In the SST, a frequent "go" signal triggered a prepotent response and a less frequent "stop" signal prompted the inhibition of this response. Preparatory control of motor inhibition and execution in the stop signal trials were examined by contrasting brain activation between stop success and stop error trials during the fore-period, in which participants prepared to respond to go or to stop. Results from 91 healthy adults showed greater activation in the right prefrontal cortex and inferior parietal lobule during preparatory motor inhibition. Preparatory motor execution activated bilateral putamen, primary motor cortices, posterior cingulate cortex, ventromedial prefrontal cortex, and superior temporal/intraparietal sulci. Furthermore, the extents of these inhibition and execution activities were inversely correlated across subjects. On the basis of a median split of the stop signal reaction time (SSRT), subjects with short SSRT showed greater activity in the right orbital frontal cortex during preparatory inhibition. These new findings suggest that the go and stop processes interact prior to target presentation in the SST, in accord with recent computational models of stop signal inhibition. PMID:21976392

Hu, Sien; Li, Chiang-Shan R



Efficient audio signal processing for embedded systems  

NASA Astrophysics Data System (ADS)

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

Chiu, Leung Kin


Design of experiments in Biomedical Signal Processing Course.  


Biomedical Signal Processing is one of the most important major subjects in Biomedical Engineering. The contents of Biomedical Signal Processing include the theories of digital signal processing, the knowledge of different biomedical signals, physiology and the ability of computer programming. Based on our past five years teaching experiences, in order to let students master the signal processing algorithm well, we found that the design of experiments following algorithm was very important. In this paper we presented the ideas and aims in designing the experiments. The results showed that our methods facilitated the study of abstractive signal processing algorithms and made understanding of biomedical signals in a simple way. PMID:19162973

Li, Ling; Li, Bin



Signal processing II: Theories and applications; Proceedings of the Second European Signal Processing Conference, Universitaet Erlangen-Nuernberg, Erlangen, West Germany, September 12-16, 1983  

NASA Astrophysics Data System (ADS)

Studies and developments related to signal processing are discussed, taking into account the pointwise convergence of sampling series, linear operators and discrete transforms, white noises, the statistical properties of rice fading processes, the application of relay- and polarity-correlation to the analysis of speech signals, the generalized synthesis of recursive digital filters in the frequency domain by linear programming, the stability of certain time-varying digital filters, and a syntactic approach to image analysis. Other topics considered are concerned with speech and sound processing, detection and estimation, software, and hardware. Attention is given to objectives and approaches in biomedical signal processing, new perspectives to noise reduction in evoked potential processing, a minicomputer assisted audiometry system, signal processing in computing tomography, and geophysical signal analysis. No individual items are abstracted in this volume

Schuessler, H. W.


Digital signal processing for radioactive decay studies  

SciTech Connect

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

Miller, D.; Madurga, M.; Paulauskas, S. V. [Department of Physics and Astronomy, University of Tennessee, Knoxville, TN 37996 (United States); Ackermann, D.; Heinz, S.; Hessberger, F. P.; Hofmann, S. [GSI Helmholtzzentrum fuer Schwerionenforschung, D-64220, Darmstadt (Germany); Grzywacz, R. [Department of Physics and Astronomy, University of Tennessee, Knoxville, TN 37996 (United States); Physics Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States); Miernik, K.; Rykaczewski, K. [Physics Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States); Tan, H. [XIA LLC, Hayward, CA 94544 (United States)



A new vibration signal processing method for gearbox fault detection  

Microsoft Academic Search

In this paper, a new vibration signal processing method, an adaptive narrow-band interference cancellation is developed to remove the periodic signals and background noises from the vibration signals. Narrow-band interference cancellation techniques are widely applied in signal processing of communication systems to remove the narrow-band interferences. The vibration signals of a gearbox with a damaged gear tooth contain periodic signals

David He; Ruoyu Li



FFT and PLL based GPS signal processing for Software GPS Receiver  

Microsoft Academic Search

This paper presents FFT and PLL based GPS signal acquisition and tracking algorithms for a software GPS receiver. Conventional\\u000a hardware based acquisition and tracking have some restrictions in processing signal with poor signal to noise ratio. The FFT\\u000a of digitized local signals of multiple carrier frequencies for a specified Doppler band are pre-computed and are circular\\u000a correlated with the digitized

Ko Sun-jun; Won Jong-hoon; Lee Ja-sung



Image and Signal Processing LISP Environment (ISLE)  

SciTech Connect

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.

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



Active voltammetric microsensors with neural signal processing.  

SciTech Connect

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.

Vogt, M. C.



Design and Validation of an Accurate GPS Signal and Receiver Truth Model for Comparing Advanced Receiver Processing Techniques.  

National Technical Information Service (NTIS)

Recent increases in the computational power of computers and digital signal processors have made possible new, novel signal tracking techniques in GPS receivers. One such technique is known as Direct Correlators Output Processing (DCOP). This technique re...

P. M. Corbell



Neural correlates of impulse control during stop signal inhibition in cocaine-dependent men.  


Altered impulse control is associated with substance use disorders, including cocaine dependence. We sought to identify the neural correlates of impulse control in abstinent male patients with cocaine dependence (PCD). Functional magnetic resonance imaging (fMRI) was conducted during a stop signal task that allowed trial-by-trial evaluation of response inhibition. Fifteen male PCD and 15 healthy control (HC) subjects, matched in age and years of education, were compared. Stop signal reaction time (SSRT) was derived on the basis of a horse race model. By comparing PCD and HC co-varied for stop success rate, task-related frustration rating, and post-error slowing, we isolated the neural substrates of response inhibition, independent of attentional monitoring (of the stop signal) and post-response processes including affective responses and error monitoring. Using region of interest analysis, we found no differences between HC and PCD who were matched in stop signal performance in the pre-supplementary motor area (pre-SMA) previously shown to be associated with SSRT. However, compared with HC, PCD demonstrated less activation of the rostral anterior cingulate cortex (rACC), an area thought to be involved in the control of stop signal inhibition. The magnitude of rACC activation also correlated negatively with the total score and the impulse control subscore of the Difficulty in Emotion Regulation Scale in PCD. The current study thus identified the neural correlates of altered impulse control in PCD independent of other cognitive processes that may influence stop signal performance. Relative hypoactivation of the rACC during response inhibition may represent a useful neural marker of difficulties in impulse control in abstinent cocaine-dependent men who are at risk of relapse. PMID:17895916

Li, Chiang-shan Ray; Huang, Cong; Yan, Peisi; Bhagwagar, Zubin; Milivojevic, Verica; Sinha, Rajita




Microsoft Academic Search

This tutorial contribution presents a short historical introduction and a survey of hypercomplex algebras in conjunction with some beneficial applications in predominantly time-based digital signal processing. Potential advantages and shortcomings of hypercom- plex digital signal processing are discussed.

Daniel Alfsmann; Heinz G. Göckler; Stephen J. Sangwine; Todd A. Ell



Ultrasonic signal processing and tissue characterization  

NASA Astrophysics Data System (ADS)

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

Mu, Zhiping


Tunable signal processing through modular control of transcription factor translocation  

PubMed Central

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

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



Nonlinear biochemical signal processing via noise propagation  

NASA Astrophysics Data System (ADS)

Single-cell studies often show significant phenotypic variability due to the stochastic nature of intra-cellular biochemical reactions. When the numbers of molecules, e.g., transcription factors and regulatory enzymes, are in low abundance, fluctuations in biochemical activities become significant and such ``noise'' can propagate through regulatory cascades in terms of biochemical reaction networks. Here we develop an intuitive, yet fully quantitative method for analyzing how noise affects cellular phenotypes based on identifying a system's nonlinearities and noise propagations. We observe that such noise can simultaneously enhance sensitivities in one behavioral region while reducing sensitivities in another. Employing this novel phenomenon we designed three biochemical signal processing modules: (a) A gene regulatory network that acts as a concentration detector with both enhanced amplitude and sensitivity. (b) A non-cooperative positive feedback system, with a graded dose-response in the deterministic case, that serves as a bistable switch due to noise-induced ultra-sensitivity. (c) A noise-induced linear amplifier for gene regulation that requires no feedback. The methods developed in the present work allow one to understand and engineer nonlinear biochemical signal processors based on fluctuation-induced phenotypes.

Kim, Kyung Hyuk; Qian, Hong; Sauro, Herbert M.



Exponential signal synthesis in digital pulse processing  

NASA Astrophysics Data System (ADS)

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

Jordanov, Valentin T.



Signal processing aspects of nonlinear acoustics  

NASA Astrophysics Data System (ADS)

The topic of nonlinear acoustics has been included at previous NATO study institutes going back to 1966. The first treatment, by Berktay, speculated on the possibilities nonlinear effects might offer. In 1968, Mellen illustrated some of these possibilities through laboratory tank experiments. Berktay returned in 1972 to present some engineering models for the design of parametric sources. In 1976, Bjorno presented a survey of theoretical and experimental results on parametric arrays developed at several laboratories. Today, research and development in nonlinear acoustics has gravitated toward applications. The present paper therefore addresses applications with a view towards outlining the unique features of nonlinear arrays, especially with regard to signal processing. Both nonlinear sources and receivers will be discussed.

Muir, T. G.; Goldsberry, T. G.



The PRISM 2.2 real time signal processing system  

Microsoft Academic Search

A description is given of the PRISM 2.2 system, a general purpose real-time signal processing system designed for very easy development and modification of signal processing applications. Both the hardware and software are flexible and easily modified to support changing project requirements. Use of additional hardware requires only an update of the configuration file. Signal processing block diagrams are easily

K. Stanwood; A. Bourdon



Multidimensional signal processing in spatial-spectral holographic media  

NASA Astrophysics Data System (ADS)

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

Schlottau, Friso


10th IEEE Signal Processing Workshop on Statistical Signal and Array Processing.  

National Technical Information Service (NTIS)

This is the Proceedings of the 10th IEEE Workshop on Statistical Signal and Array Processing (SSAP), which was held at the Pocono Manor Inn, Pocono Manor, Pa during the period of August 14th-16th, 2000. The Workshop featured four keynote speakers whose ta...

M. G. Amin



Meteor radar signal processing and error analysis  

NASA Astrophysics Data System (ADS)

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

Kang, Chunmei


Neural correlates of implicit and explicit combinatorial semantic processing  

PubMed Central

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

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



Classification of correlation signatures of spread spectrum signals using neural networks  

Microsoft Academic Search

The authors discuss the application of artificial neural networks (ANNs) to the classification of spread spectrum signals based on signal type or spreading technique. Radial basis function networks (RBFNs) and back-propagation networks (BPNs) were used to classify the correlation signatures of the signals. Correlation signatures of four types or classes were obtained from United States Army Harry Diamond Laboratories: direct

R. A. Chapman; D. M. Norman; D. R. Zahirniak; S. K. Rogers; M. E. Oxley



Dynamic range control of audio signals by digital signal processing  

NASA Astrophysics Data System (ADS)

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

Gilchrist, N. H. C.


Research on signal processing of inductosyn based on FPGA  

Microsoft Academic Search

In order to improve reliability of Inductosyn signal processing system and save FPGA resources, the article uses a single-chip SOC system design, making the sine\\/cosine signal power, pulse filling phase detection and data processing integrated into an FPGA, and optimizing the signal circuit of sine \\/ cosine through the technology of point symmetry and axial symmetry. Research on the circuit

Xianquan Wang; Min Wu; Jiqin Feng; Cun Dong; Lina Lou



Signal processing possibilities for pulse radars using polarimetric information  

Microsoft Academic Search

Radars using polarimetric signal information are different from most existing radars, which work on complex scalars and are only able to measure one element of the scattering matrix of a reflecting object. This paper addresses the use of the additional polarimetric information in signal processing. Signal processing problems, their grouping, and their structure are reviewed, and the generation of features

G. Wanielik



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

PubMed Central

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

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



Design of hardware correlator for BOC(1,1) baseband signal  

Microsoft Academic Search

BOC signal structure was introduced in this paper. BOC signal modulation and BOC(1,1) auto-correlation function were analyzed in detail. Based on the signal acquisition, tracking loop for BOC(1,1), a hardware design with FPGA chip was presented for the correlator, implemented using EP2S60 from Altera Co. The hardware correlator architecture and functions were described with two key modules, i.e. Pseudo-Random Noise

Dong-Kai Yang; Wei-Qiang Li; Xian-Yang Liu; Yuan Feng



Hybrid optical-digital system for the processing of pulsar signals  

Microsoft Academic Search

Experimental results are presented on an acoustooptic correlator with time integration. It is shown that the use of this device for the processing of pulsar signals can reduce the influence of the dispersion of the interstellar medium, and can improve the parameters of radiometer with which it is used. A linear CCD photodetector array is used in the correlator along

N. A. Esepkina; N. A. Bukharin; Iu. A. Kotov; B. A. Kotov; A. V. Mikhailov



Signal-processing capabilities of a computerized ultrasonic scanning bridge  

Microsoft Academic Search

Digital signal processing techniques were implemented using a computerized ultrasonic scanning bridge. Signals are processed in A-Scan, B-Scan, and C-Scan mode. In A-Scan mode general arithmetic and transform techniques such as addition, subtraction, multiplication, division, differential, integration, Fourier transforms and calculated functions are utilized. B-Scan mode signal processing options are analytic function, split spectrum processing, frequency domain windowing, and spatial

R. L. McKinney; D. Boyd; A. Kuramoto; B. McDonald



Overview of seismic signal processing equipment and procedures  

SciTech Connect

The report provides a brief overview of the automatic data processing equipment (ADPE) and procedures used for processing seismic signals. The discussion includes 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; and basic procedures for analysis of the processed signals. 8 refs., 8 figs., 2 tabs.

Igusa, T.; Lum, P.K.W.



Design of hardware correlator for BOC(1,1) baseband signal  

NASA Astrophysics Data System (ADS)

BOC signal structure was introduced in this paper. BOC signal modulation and BOC(1,1) auto-correlation function were analyzed in detail. Based on the signal acquisition, tracking loop for BOC(1,1), a hardware design with FPGA chip was presented for the correlator, implemented using EP2S60 from Altera Co. The hardware correlator architecture and functions were described with two key modules, i.e. Pseudo-Random Noise (PRN) code generator and Numerical Control Oscillator(NCO). The practical test results show that the designed hardware correlator can work steadily and correctly, which is valid for the BOC(1,1) signal acquisition and tracking.

Yang, Dong-Kai; Li, Wei-Qiang; Liu, Xian-Yang; Feng, Yuan



Intelligent, onboard signal processing payload concept, addendum :  

SciTech Connect

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.

Shriver, P. M. (Patrick M.); Harikumar, J. (Jayashree); Briles, S. C. (Scott C.); Gokhale, M. (Maya)



Investigation of Charge Coupled Devices for Signal Processing.  

National Technical Information Service (NTIS)

This report describes a noise correlation processor for automatic low frequency noise power spectra measurements, theoretical analysis of hot electron effects and trapping noise in silicon charge coupled devices, small-signal equivalent circuit measuremen...

C. T. Sah P. C. Chan J. F. Detry Y. C. Sun



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

PubMed Central

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

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



Psychophysiological correlates of face processing in social phobia.  


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

Kolassa, Iris-Tatjana; Miltner, Wolfgang H R



Adventures in Radio Astronomy Instrumentation and Signal Processing  

Microsoft Academic Search

This thesis describes the design and implementation of several instruments for digitizing and processing analogue astronomical signals collected using radio telescopes. Modern radio telescopes have significant digital signal processing demands that are typically best met using custom processing engines implemented in Field Programmable Gate Arrays. These demands essentially stem from the ever-larger analogue bandwidths that astronomers wish to observe, resulting

Peter L. McMahon



An energy-efficient biomedical signal processing platform  

Microsoft Academic Search

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 accelerators for biomedical signal processing. Voltage scaling and block-level power gating allow optimizing energy efficiency under applications of varying complexity. Programmable accelerators support numerous usage scenarios and perform signal processing tasks at

Joyce Kwong; Anantha P. Chandrakasan



The use of digital signal processors (DSPs) in real-time processing of multi-parametric bioelectronic signals.  


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

Ressler, Johann; Dirscherl, Andreas; Grothe, Helmut; Wolf, Bernhard



Neural Correlates of Morphological Processes in Hebrew  

Microsoft Academic Search

Is morphology a discrete and independent element of lexical structure or does it simply reflect a fine tuning of the system to the statistical correlation that exists among the orthographic and semantic properties of words? Imaging studies in English failed to show unequivocal morphological activation that is distinct from semantic or orthographic activation. Cognitive research in Hebrew has revealed that

Atira Bick; Gadi Goelman; Ram Frost



Clinical correlates of high signal lesions on magnetic resonance imaging in Alzheimer's disease  

Microsoft Academic Search

The pathophysiology and clinical significance of high signal lesions, visualized on magnetic resonance imaging (MRI) in patients with Alzheimer's disease (AD), remain controversial. Since they are known to correlate with vascular disease and vascular risk factors, we reviewed the clinical correlates of periventricular high signal (PVH) and subcortical white matter lesions (WML) in a sample of 106 patients with probable

David A. Bennett; David W. Gilley; Robert S. Wilson; Michael S. Huckman; Jacob H. Fox



Bio-impedance signal processing using adaptive digital filter  

Microsoft Academic Search

Bio-impedance evaluation is one of the medicine diagnostic methods for the evaluation of tissue perfusion. The bioimpedance on the patient's body surface is evaluated by analogue HF-vector Z-meter. The Z signal is converted into a digital form and further digitally processed and filtered. Spurious disturbing signals distorting the bio-impedance signal are suppressed by adaptive FIR filter.

Vaclav Papez; Stanislava Papezova



Signal Processing for Spatial Sound Reproduction with Wave Field Synthesis  

Microsoft Academic Search

Wave Field Synthesis is a technique for spatial sound reproduction that overcomes the limitations of classical stereophonic techniques. A thorough analysis of acoustic wave propagation prinicples delivers the technical description in terms of loudspeaker array technology. Suitable signal processing methods convert the source signals into driving signals for each loudspeaker. The suitability of this concept has been demonstrated by a

Rudolf Rabenstein; Sascha Spors


Social Signal Processing: Understanding social interactions through nonverbal behavior analysis  

Microsoft Academic Search

This paper introduces social signal processing (SSP), the domain aimed at automatic understanding of social interactions through analysis of nonverbal behavior. The core idea of SSP is that nonverbal behavior is machine detectable evidence of social signals, the relational attitudes exchanged between interacting individuals. Social signals include (dis-)agreement, empathy, hostility, and any other attitude towards others that is expressed not

A. Vinciarelli; H. Salamin; M. Pantic



Correlations Between Single Cell Signaling Dynamics and Protein Expressions Profiles.  

National Technical Information Service (NTIS)

A platform technology for monitoring signaling pathways in single T cells using optical nanoprobes has been developed to provide a stable and biocompatible environment for the cells, and allow acquisition of additional data on cellular metabolic and physi...

J. P. Wikswo



Classification of correlation signatures of spread spectrum signals using neural networks  

Microsoft Academic Search

The major goals of this thesis were to determine if Artificial Neural Networks (ANNs) could be trained to classify the correlation signatures of two classes of spread spectrum signals and four classes of spread spectrum signals. Also, the possibility of training an ANN to classify features of the signatures other than signal class was investigated. Radial Basis Function Networks and

Richard A. Chapman



The theory of adaptive antenna arrays under conditions of correlated noise signals  

NASA Astrophysics Data System (ADS)

The analytic inversion of the covariant noise matrix is used to study an adaptive antenna array receiving correlated noise signals. Analyses are presented of the suppression of correlated noise signals, variations of the signal/noise plus interference ratio, and the duration of noise suppression. Attention is also given to noise suppression in the case when part of the noise arrives from the direction of the main maximum of the radiation pattern.

Litvinov, O. S.



New video signal-processing LSIs for 8 mm VCRs  

Microsoft Academic Search

A fully integrated bipolar large-scale integration (LSI) signal processing system is described. The system is composed of a single-chip Y\\/C signal processor, a multifunction charge-coupled device (CCD) comb filter a head amplifier with active equalizers, and a PAL signal processor. About 8800 elements are integrated in the single-chip Y\\/C signal processor which takes the place of 5 ICs in a

T. Fukuda; K. Nishitani; F. Yamaguchi; K. Abe; T. Narabu



Effects of signal spectrum varying on signal processing by parameter-induced stochastic resonance  

NASA Astrophysics Data System (ADS)

The effects of signal spectrum varying on signal processing by the method of parameter-induced stochastic resonance (PSR) are investigated. For a binary signal with a smooth power spectral density (PSD), when the PSD curve becomes sharper and narrower, the performance of the nonlinear system via PSR is better. For a multi-frequency signal formed by sine waves with different frequencies, the larger the signal spectral density is, the lower the ability of the PSR system processing signal is. And the signal-to-noise ratio (SNR) gain of the PSR system is increased with the increasing height of the spectral line. Moreover, with the method of PSR, the stochastic signal (the combination of sine waves and noise) improvement is obvious. The results obtained via this method are superior to those with a linear filter.

Li, Jianlong; Xu, Bohou



Surface EMG signal processing during isometric contractions  

Microsoft Academic Search

This paper provides an overview of techniques suitable for the estimation, interpretation and understanding of time variations that affect the surface electromyographic (EMG) signal during sustained voluntary or electrically elicited contractions. These variations concern amplitude variables, spectral variables and muscle fiber conduction velocity, are interdependent and are referred to as the `fatigue plot'. The fatigue plot provides information suitable for

Roberto Merletti; Loredana R. Lo Conte



Statistical signal processing for automotive safety systems  

Microsoft Academic Search

The amount of software in general and safety systems in particular increases rapidly in the automotive industry. The trend is that functionality is decentralized, so new safety functions are distributed to common shared computer hardware, sensors and actuators using central data buses. This paper overviews recent and future safety systems, and high-lights the big challenges for researchers in the signal

Fredrik Gustafsson



Signal processing for plane wave actuators  

NASA Astrophysics Data System (ADS)

Plane wave actuators without an enclosure per se have a forward and backward radiation. The backward radiation is unwanted in many applications when a single direction radiation is desired. To avoid the disadvantages of an enclosure a system is proposed, which provides a high suppression of the unwanted backward radiation using a pair of plane wave actuators. This is achieved by adapted input signal filters. The influences of the second plane wave actuator to the forward radiated signal are suppressed as well. Additionally, the system also provides for- and backward radiation of different signals with a high suppression of the radiation directions crosstalk. The required power for the signal suppression depends on the physical damping of the plane wave actuators and the space in between. The first realized prototype is designed for flat panel dipole loudspeakers to deal with the mentioned problems in the acoustic domain. The filter design and a calibration algorithm for any given pairs of dipole loudspeaker are explained. The good performance of the developed system is proven by measurement results with the prototype system.

Corbach, T.; Holters, M.; Zölzer, U.



Robust Signal Processing in Living Cells  

PubMed Central

Cellular signaling networks have evolved an astonishing ability to function reliably and with high fidelity in uncertain environments. A crucial prerequisite for the high precision exhibited by many signaling circuits is their ability to keep the concentrations of active signaling compounds within tightly defined bounds, despite strong stochastic fluctuations in copy numbers and other detrimental influences. Based on a simple mathematical formalism, we identify topological organizing principles that facilitate such robust control of intracellular concentrations in the face of multifarious perturbations. Our framework allows us to judge whether a multiple-input-multiple-output reaction network is robust against large perturbations of network parameters and enables the predictive design of perfectly robust synthetic network architectures. Utilizing the Escherichia coli chemotaxis pathway as a hallmark example, we provide experimental evidence that our framework indeed allows us to unravel the topological organization of robust signaling. We demonstrate that the specific organization of the pathway allows the system to maintain global concentration robustness of the diffusible response regulator CheY with respect to several dominant perturbations. Our framework provides a counterpoint to the hypothesis that cellular function relies on an extensive machinery to fine-tune or control intracellular parameters. Rather, we suggest that for a large class of perturbations, there exists an appropriate topology that renders the network output invariant to the respective perturbations.

Steuer, Ralf; Waldherr, Steffen; Sourjik, Victor; Kollmann, Markus



Robust signal processing in living cells.  


Cellular signaling networks have evolved an astonishing ability to function reliably and with high fidelity in uncertain environments. A crucial prerequisite for the high precision exhibited by many signaling circuits is their ability to keep the concentrations of active signaling compounds within tightly defined bounds, despite strong stochastic fluctuations in copy numbers and other detrimental influences. Based on a simple mathematical formalism, we identify topological organizing principles that facilitate such robust control of intracellular concentrations in the face of multifarious perturbations. Our framework allows us to judge whether a multiple-input-multiple-output reaction network is robust against large perturbations of network parameters and enables the predictive design of perfectly robust synthetic network architectures. Utilizing the Escherichia coli chemotaxis pathway as a hallmark example, we provide experimental evidence that our framework indeed allows us to unravel the topological organization of robust signaling. We demonstrate that the specific organization of the pathway allows the system to maintain global concentration robustness of the diffusible response regulator CheY with respect to several dominant perturbations. Our framework provides a counterpoint to the hypothesis that cellular function relies on an extensive machinery to fine-tune or control intracellular parameters. Rather, we suggest that for a large class of perturbations, there exists an appropriate topology that renders the network output invariant to the respective perturbations. PMID:22215991

Steuer, Ralf; Waldherr, Steffen; Sourjik, Victor; Kollmann, Markus



Digital Signal Processing Applications in Cochlear-Implant Research.  

National Technical Information Service (NTIS)

We have developed a facility that enables scientists to investigate a wide range of sound-processing schemes for human subjects with cochlear implants. This digital signal processing (DSP) facility-named the Programmable Interactive System for Cochlear Im...

J. Tierney M. A. Zissman D. K. Eddington



Effects of Correlated Sub-Samples in Statistical Process Control  

Microsoft Academic Search

This paper considers the effects of correlated data within subgroups that have been defined for the purposes of statistical process control. Such correlation may arise if the grouping is accomplished because of simplicity in data collection, such as multiple but similar measurements on a single product or multiple station machines. The effect of correlated measurements within the subgroup is shown

John B. Neuhardt



Field cross correlator for analysis of ultrafast signals.  


The cross-correlation function between two light fields is recorded with the help of a new device. The proposed correlator exhibits ultrashort time resolution. The optical path difference between the two interfering beams does not have to be known with interferometric precision. The experimental dynamic range proved to be as large as 10(5). The device features imaging capabilities that could be applied to the analysis of two-dimensional images with ultrashort time resolution. PMID:20963013

Dou, K; Débarre, A; Gouët, J L; Lorgeré; Tchénio, P



An Energy-Efficient Biomedical Signal Processing Platform  

Microsoft Academic Search

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

Joyce Kwong; Anantha P. Chandrakasan



Signal processing in ocean bottom seismographs for refraction seismology  

Microsoft Academic Search

This communication presents some experimental results about the wavelet techniques applied to seismic signal processing. These techniques have been used to process seismic signal and now we'll applied these well know techniques to refraction seismology. Ocean Bottom Seismometer, OBS, represents the achievement of a joint work from different scientific and technological disciplines as electronics, mechanics, acoustics, communications, information technology, marine

I. Rodriguez; A. Manuel; A. Carlosena; A. Bermudez; J. del Rio; S. Shariat



Mobile social signal processing: vision and research issues  

Microsoft Academic Search

This paper introduces the First International Workshop on Mobile Social Signal Processing (SSP). The Workshop aims at bringing together the Mobile HCI and Social Signal Processing research communities. The former investigates approaches for effective interaction with mobile and wearable devices, while the latter focuses on modeling, analysis and synthesis of nonverbal behavior in human{human and human-machine interactions. While dealing with

Alessandro Vinciarelli; Roderick Murray-Smith; Hervé Bourlard



Visualizing brain images in an undergraduate signal processing course  

Microsoft Academic Search

This paper describes a MRI brain image visualization approach for an undergraduate signal processing course in a liberal art college environment. Owing to the highly mathematical nature of signal processing theory, using visualized biomedical images may increase students' curiosity in both the course itself and the biomedical science in general. The visualization tool is constructed with incremental level of difficulty,

Lin Cheng



Image processing on ECG chart for ECG signal recovery  

Microsoft Academic Search

Medical imaging plays an indispensable role on medical informatics. Most of imaging processing technologies is focused on the identification of the locations of diseases on MRI, CT, PET, and SPECT images. However, only a few researches focused on one dimension signal recovery or reconstruction of electronic signals. Spatial and frequency methods were provided to process on colour or gray-level electrocardiogram

T. W. Shen; T. F. Laio



Some digital signal processing techniques for induction machines diagnosis  

Microsoft Academic Search

? Abstract - This paper investigates the recent advances on digital signal processing techniques for induction machines diagnosis. Since non-invasive sensors offer a relatively simple and cost effective fault diagnosis, more emphasis is given to stator current analysis rather than vibration or acoustic analysis in induction machines. Here, further interest has been paid on modern signal processing techniques with a

Shahin Hedayati Kia; Humberto Henao; Gerard-Andre Capolino



Correlates of linguistic rhythm in the speech signal  

Microsoft Academic Search

Spoken languages have been classified by linguists according to their rhythmic properties, and psycholinguists have relied on this classification to account for infants’ capacity to discriminate languages. Although researchers have measured many speech signal properties, they have failed to identify reliable acoustic characteristics for language classes. This paper presents instrumental measurements based on a consonant\\/vowel segmentation for eight languages. The

Franck Ramus; Marina Nespor; Jacques Mehler



Hemodynamic Signals Correlate Tightly with Synchronized Gamma Oscillations  

Microsoft Academic Search

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

Jörn Niessing; Boris Ebisch; Kerstin E. Schmidt; Michael Niessing; Wolf Singer; Ralf A. W. Galuske



Signal processing strategies in acoustic elastography  

Microsoft Academic Search

Elastography is a remote sensing technique for imaging the elastic properties of biological tissues. An essential feature is tissue deformation (strain) that is measured by cross correlating ultrasonic echo waveforms acquired before and after a weak static compression. To fully exploit the large object contrast available among body tissues, many dependent experimental parameters must be carefully adjusted. This paper outlines

M. F. Insana; M. Biegen; P. Chaturvedi; T. J. Hall; M. Bertrand



Optical and analog electronic signal processing  

Microsoft Academic Search

A two lens optical Fourier transformation is shown to be equivalent to an electronic chirp transform. For discrete time signals this transformation becomes the discrete chirp-z-transform. The chirp-z-transform can be implemented using either charge transfer devices or surface acoustic wave devices. Through the use of appropriate architectures, a long one-dimensional chirp-z-transform can be rewritten as a modular chirp-z transform using

H. Whitehouse



A cardiac signal monitoring and processing system  

Microsoft Academic Search

The social and economic impact of cardiovascular diseases and the importance of efficient early diagnostic tools are self-evident. This project finds its motivation in the foreseeable impact that an accurate, non-invasive and easy-to-use instrument for hemodynamic condition assessment could introduce on the diagnosis and follow-up of these diseases. It aims at developing and testing of a microcontroller based signal monitoring

V. G. Almeida; T. M. Pereira; H. C. Pereira; J. M. R. Cardoso; C. Correia



An Efficient Signal Processing Scheme Using Signal Compression for Software GPS Receivers  

Microsoft Academic Search

The software GPS receivers based on the SDR technology provide the ability to easily adapt the other signal processing algorithms without changing or modifying the hardware of the GPS receiver. However, it is difficult to implement the software GPS receivers using a commercial processor because of the heavy computational burden for processing the GPS signals in real-time. This paper proposes

Deuk Jae Cho; Deok Won Lim; Sang Jeong Lee



Enhanced Differential Correlation Method for the Acquisition of Galileo Signals  

Microsoft Academic Search

In this paper, we analyze an enhanced differential non-coherent integration method for the acquisition stage of a BOC-modulated CDMA signal in the new European Galileo satellite navigation system. This method, denoted by DN2, offers an improved suppression of any temporally uncorrelated interferers. Background noise is naturally the most obvious source of temporally uncorrelated interference, but, for example, in CDMA systems,

Elina Pajala; Elena Simona Lohan; Toni Huovinen; Markku Renfors



Statistical mechanics and visual signal processing  

NASA Astrophysics Data System (ADS)

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

Potters, Marc; Bialek, William



Design of a GaAs acousto-optic correlator for real-time processing  

Microsoft Academic Search

In this paper, the design and the simulation of a GaAs acousto-optic correlator for synthetic aperture radar (SAR) data processing are reported. The proposed integrated circuit is available for airborne applications and is able to operate with side-looking focused radar. The range compression is performed by the acousto-optic correlator, driven by the received signal, and the azimuth data compression is

Mario N. Armenise; Fabrizio Impagnatiello; Vittorio M. Passaro; Evangelista Pansini



Correlates of Capture of Attention and Inhibition of Return across Stages of Visual Processing  

Microsoft Academic Search

How do visual signals evolve from early to late stages in sensory processing? We explored this question by examining two neural correlates of spatial attention. The capture of attention and inhibition of return refer to the initial advantage and subsequent disadvantage to respond to a visual target that follows an irrelevant visual cue at the same location. In the intermediate

Jillian H. Fecteau; Douglas P. Munoz



Active voltammetric microsensors with neural signal processing  

Microsoft Academic Search

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

Michael C. Vogt; Laura R. Skubal



Synthesis of algorithms of space-time signal processing in the frequency domain using the discrete Fourier transformation  

Microsoft Academic Search

Optimal digital algorithms of space-time signal processing are synthesized on the assumption that the observed processes are the result of discrete Fourier transformations of samples from the elements of an antenna array of arbitrary configuration. The detection of determinate, quasi-determinate, and stochastic signals is examined with allowance for conditions on the intervals of space and time correlations of the input

R. Sh. Aleiner; B. I. Ianover



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

NASA Astrophysics Data System (ADS)

We introduce a general framework of the Mixed-correlated ARFIMA (MC-ARFIMA) processes which allows for various specifications of univariate and bivariate long-term memory. Apart from a standard case when H=12(Hx+Hy), MC-ARFIMA also allows for processes with H<12(Hx+Hy) but also for long-range correlated processes which are either short-range cross-correlated or simply correlated. The major contribution of MC-ARFIMA lies in the fact that the processes have well-defined asymptotic properties for Hx, Hy and H, which are derived in the paper, so that the processes can be used in simulation studies comparing various estimators of the bivariate Hurst exponent H. Moreover, the framework allows for modeling of processes which are found to have H<12(Hx+Hy).

Kristoufek, Ladislav



Signal processing for an infrared array detector  

SciTech Connect

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.

Young, M.A.; Smith, G.E.; Pimentel, G.C. (Laboratory of Chemical Biodynamics, Lawrence Berkeley Laboratory, University of California, Berkeley, California 94720 (US))



Time reversal signal processing for communication.  

SciTech Connect

Time-reversal is a wave focusing technique that makes use of the reciprocity of wireless propagation channels. It works particularly well in a cluttered environment with associated multipath reflection. This technique uses the multipath in the environment to increase focusing ability. Time-reversal can also be used to null signals, either to reduce unintentional interference or to prevent eavesdropping. It does not require controlled geometric placement of the transmit antennas. Unlike existing techniques it can work without line-of-sight. We have explored the performance of time-reversal focusing in a variety of simulated environments. We have also developed new algorithms to simultaneously focus at a location while nulling at an eavesdropper location. We have experimentally verified these techniques in a realistic cluttered environment.

Young, Derek P.; Jacklin, Neil; Punnoose, Ratish J.; Counsil, David T.



New correlation functions for multi-particle processes  

NASA Astrophysics Data System (ADS)

We propose a new family of correlation functions for the study of multi-particle processes, the ``split-bin'' correlation functions. Split-bin correlation functions are similar to scaled factorial moments, but they are less susceptible to some systematic errors, such as double-counting of particles. Unlike scaled factorial moments, split-bin correlation functions can be constructed using continuous variables, such as transverse energy. They can also be used to help differentiate between correlations due to jet-like and resonance-like sources.

Voloshin, Sergei; Seibert, David



Anti-correlated networks, global signal regression, and the effects of caffeine in resting-state functional MRI.  


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

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



B-Spline Signal Processing: Part I-Theory  

Microsoft Academic Search

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

Michael Unser; Akram Aldroubi; Murray Eden



Methods and analysis of processing signals of incremental optoelectronic transducer.  


This article is a presentation of designed methods which interpolate signals from the optoelectronic transducer. This enables a way to distinguish the motion direction of the optoelectronic transducer and also to increase its accuracy. In this article methods based on logic functions, logic functions and RC circuits, phase processing were analyzed. In methods which are based on processing logic functions of transducer's signals there is a possibility of two times and four times increase in the transducer glass scale. The presented method of generating and processing sine signals with 18 degrees of the shift enables the reception of square signals with five times higher frequency compared to the basic signals. This method is universal and it can be used to the different scale of frequency multiplication of the optoelectronic transducer. The simulations of the methods were performed by using the MATLAB-SIMULINK software. PMID:19791953

Szcze?niak, Adam; Szcze?niak, Zbigniew



Subcortical processes of motor response inhibition during a stop signal task.  


Previous studies have delineated the neural processes of motor response inhibition during a stop signal task, with most reports focusing on the cortical mechanisms. A recent study highlighted the importance of subcortical processes during stop signal inhibition in 13 individuals and suggested that the subthalamic nucleus (STN) may play a role in blocking response execution (Aron and Poldrack, 2006. Cortical and subcortical contributions to Stop signal response inhibition: role of the subthalamic nucleus. J Neurosci 26, 2424-2433). Here in a functional magnetic resonance imaging (fMRI) study we replicated the finding of greater activation in the STN during stop (success or error) trials, compared to go trials, in a larger sample of subjects (n=30). However, since a contrast between stop and go trials involved processes that could be distinguished from response inhibition, the role of subthalamic activity during stop signal inhibition remained to be specified. To this end we followed an alternative strategy to isolate the neural correlates of response inhibition (Li et al., 2006a. Imaging response inhibition in a stop signal task--neural correlates independent of signal monitoring and post-response processing. J Neurosci 26, 186-192). We compared individuals with short and long stop signal reaction time (SSRT) as computed by the horse race model. The two groups of subjects did not differ in any other aspects of stop signal performance. We showed greater activity in the short than the long SSRT group in the caudate head during stop successes, as compared to stop errors. Caudate activity was positively correlated with medial prefrontal activity previously shown to mediate stop signal inhibition. Conversely, bilateral thalamic nuclei and other parts of the basal ganglia, including the STN, showed greater activation in subjects with long than short SSRT. Thus, fMRI delineated contrasting roles of the prefrontal-caudate and striato-thalamic activities in mediating motor response inhibition. PMID:18485743

Li, Chiang-Shan Ray; Yan, Peisi; Sinha, Rajita; Lee, Tien-Wen



Fluctuations and correlations as a signal of deconfinement  

SciTech Connect

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

Konchakovski, V. P., E-mail: [Giessen University, Institute for Theoretical Physics (Germany); Bratkovskaya, E. L. [Frankfurt University, Institute for Theoretical Physics (Germany); Cassing, W. [Giessen University, Institute for Theoretical Physics (Germany); Gorenstein, M. I. [Bogolyobov Institute for Theoretical Physics (Ukraine)



Neural networks in signal and image processing  

Microsoft Academic Search

Neural network (NN) research has gone a long way in the past decade. NNs now consist of many thousands of highly interconnected processing elements that can encode, store and recall relationships between different patterns by altering the weighting coefficients of inputs in a systematic way. Although they can generate reasonable outputs from unknown input patterns, and they can tolerate a

Evangelia Micheli-Tzanakou



Signal detection for uniform renewal processes  

NASA Astrophysics Data System (ADS)

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

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



Signal-processing capabilities of a computerized ultrasonic scanning bridge  

NASA Astrophysics Data System (ADS)

Digital signal processing techniques were implemented using a computerized ultrasonic scanning bridge. Signals are processed in A-Scan, B-Scan, and C-Scan mode. In A-Scan mode general arithmetic and transform techniques such as addition, subtraction, multiplication, division, differential, integration, Fourier transforms and calculated functions are utilized. B-Scan mode signal processing options are analytic function, split spectrum processing, frequency domain windowing, and spatial averaging. In S-Scan mode available manipulations are addition, subtraction, multiplication, division, inversion, high and low pass filtering, and edge enhancement. A-Scans and B-Scans are processed using an array processor and a DEC (Digital Equipment Corp.) LSI 11/23 computer. C-Scan images are processed using a Peritek VC6-512Q graphics display board. Results have proved favorable both in processing time and in additional information provided by the techniques.

McKinney, R. L.; Boyd, D.; Kuramoto, A.; McDonald, B.


Investigation of topics in radar signal processing  

NASA Astrophysics Data System (ADS)

A promising image reconstruction algorithm proposed by W. Lawton for spotlight-mode synthetic aperture radar (SAR) is studied. The spatial domain image is produced through a series of convolutions and DFTs, all performed using FFTs. It is shown that the algorithm implements a form of trapezoidal-to-Cartesian interpolation followed by an FFT. A simplified back-projection algorithm is proposed for spotlight-mode SAR in which the filtered projections are obtained automatically by choosing the radar waveform to be the impulse response of the desired filter. The filtering is accomplished through the physical mechanism of the waveform reflecting off the target, which is described by a convolution. A parallel architecture is described for the back-projection of the filtered projections and its computational and memory requirements are analyzed. A basic derivation is given of bistatic spotlight-mode SAR (BSSAR). It is shown that BSSAR can be explained using the projection-slice theorem from computed tomography. The locations were found of the Fourier domain samples and examine the shape of the Fourier grid for several special cases of transmitter and receiver motions. The chirp-z interpolation algorithm, which is a promising approach to interpolation between two uniform grids with arbitrary spacings is considered. The least squares ambiguity function synthesis problem was studied, which has applications in range-Doppler radar imaging and time-frequency signal analysis. The solution is presented for least squares ambiguity function synthesis both in the continuous and discrete time-frequency domains.

Arikan, Orhan


Signal processing methods for upper airway and pulmonary dysfunction diagnosis  

Microsoft Academic Search

Methods and algorithms for the analysis of acoustical pulmonary signals and their application to pulmonary diagnosis are examined. The analysis of breath and adventitious sounds, voice sounds and percussion, and snoring and stridor is considered. It is shown that analysis of the acoustic characteristics of the thorax by sophisticated signal processing methods shows promise for assisting clinical diagnosis. The technique

A. Cohen



Data Analysis as the Search for Signals in Noisy Processes.  

ERIC Educational Resources Information Center

|Explores challenges of learning to think about data as signal and noise. Examines the signal/noise metaphor in the context of three different statistical processes: (1) repeated measures; (2) measuring individuals; and (3) dichotomous events. Makes several recommendations for research and instruction on the basis of this analysis. (Author/KHR)|

Konold, Clifford; Pollatsek, Alexander



Adaptive blind signal processing-neural network approaches  

Microsoft Academic Search

Learning algorithms and underlying basic mathematical ideas are presented for the problem of adaptive blind signal processing, especially instantaneous blind separation and multichannel blind deconvolution\\/equalization of independent source signals. We discuss developments of adaptive learning algorithms based on the natural gradient approach and their properties concerning convergence, stability, and efficiency. Several promising schemas are proposed and reviewed in the paper.




Analog Integrated Circuits Design for Processing Physiological Signals  

Microsoft Academic Search

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

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



Anthropometric and Demographic Correlates of Dual-Axis Swallowing Accelerometry Signal Characteristics: A Canonical Correlation Analysis  

Microsoft Academic Search

Swallowing accelerometry has been proposed as a potential minimally invasive tool for collecting assessment information about\\u000a swallowing. The first step toward using sounds and signals for dysphagia detection involves characterizing the healthy swallow.\\u000a The purpose of this article is to explore systematic variations in swallowing accelerometry signals that can be attributed\\u000a to demographic factors (such as participant gender and age)

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



Real-time modular distributed signal processing  

NASA Astrophysics Data System (ADS)

It is pointed out that recent developments in the fields of optical and focal plane technologies have resulted in a proliferation of new advanced sensor types. This is true in particular for sensors developed for ballistic missile defense (BMD). A description is given of a methodology that has been developed to analyze the real-time processing requirements of these sensors. The methodology defines real-time processing architectures using a versatile and flexible set of architectural building blocks currently under development. The various types of sensors are also described. These include spectral imaging sensors, ambient optics sensors, laser radars, wide angle optics, endo interceptor sensors, high endo designation sensors, and two-color UV sensors.

Gross, J. S.; Patel, J. N.; Kobler, V.



Time series analysis and signal processing  

Microsoft Academic Search

Time series analysis is the analysis of the data collected sequentially in time. These data are usually represented as linear\\/nonlinear discrete-time models. The time-series models are used to analyse and predict the data. A linear time series is modeled by linear difference equations involving the time series and the white noise or the innovation process. Such ARMA(p, q) models can

S. A. Pavan Kumar; P. K. Bora



Low-Delay Signal Processing for Digital Hearing Aids  

Microsoft Academic Search

Digital signal processing in modern hearing aids is typically performed in a subband or transform domain that introduces analysis-synthesis delays in the forward path. Long forward-path delays are not desirable because the processed sound combines with the unprocessed sound that arrives at the cochlea through the vent and changes the sound quality. Nonethe- less, subband domain processing for digital hearing

Ashutosh Pandey; V. John Mathews



Waveguide Studies for Fiber Optics and Optical Signal Processing Applications.  

National Technical Information Service (NTIS)

This report describes investigations of waveguide components for use in multimode fiber optics and in optical signal processing. Measurements of beam expansion and polarization properties of distributed Bragg deflectors are described. Measurements of the ...

E. Garmire



Comparative analysis of genomic signal processing for microarray data clustering.  


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 in bioinformatics and next generation of healthcare systems, in particular, in the field of microarray data clustering. In this paper we present a comparative performance analysis of enhanced digital spectral analysis methods for robust clustering of gene expression across multiple microarray data samples. Three digital signal processing methods: linear predictive coding, wavelet decomposition, and fractal dimension are studied to provide a comparative evaluation of the clustering performance of these methods on several microarray datasets. The results of this study show that the fractal approach provides the best clustering accuracy compared to other digital signal processing and well known statistical methods. PMID:22157075

Istepanian, Robert S H; Sungoor, Ala; Nebel, Jean-Christophe



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

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

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


Classification of Correlation Signatures of Spread Spectrum Signals Using Neural Networks.  

National Technical Information Service (NTIS)

The major goals of this thesis were to determine if Artificial Neural Networks (ANNs) could be trained to classify the correlation signatures of two classes of spread spectrum signals and four classes of spread spectrum signals. Also, the possibility of t...

R. A. Chapman



A survey of signal processing algorithms in brain–computer interfaces based on electrical brain signals  

Microsoft Academic Search

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

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



The Correlation of Vibration Signal Features to Cutting Tool Wear in a Metal Turning Operation  

Microsoft Academic Search

This paper describes a tool-wear monitoring procedure in a metal turning operation using vibration features. Machining of\\u000a EN24 was carried out using coated grooved inserts, and on-line vibration signals were obtained. The measured tool-wear forms\\u000a were correlated to features in the vibration signals in the time and frequency domains. Analysis of the results suggested\\u000a that the vibration signals’ features were



All-optical signal processing using dynamic Brillouin gratings  

NASA Astrophysics Data System (ADS)

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.

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



Optical design and signal processing for a microcrack detection system  

Microsoft Academic Search

This paper presents optical design, proof-of-principle experiments, and post-signal processing for a wafer microcrack detection system. Cylindrical lens and Solid Immersion Lens (SIL) are used for the optical module. Near-field probe array is also investigated for future implementation. For post-signal processing, Probabilistic Neural Network (PNN) is used in order to identify vibration-induced deviation. Derived Short-Time Discrete Wavelet Transform (STDWT) is

Wen-Ren Yang; Yu-Lin Li



Native signal processing on the Ultrasparc in the Ptolemy environment  

Microsoft Academic Search

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

William Chen; H. John Reekie; Sunil Bhave; Edward A. Lee



All-optical signal processing based on semiconductor optical amplifiers  

Microsoft Academic Search

In this paper, we review the recent progress in the optical signal processing based on the nonlinearity of semiconductor optical\\u000a amplifiers (SOAs). The four important optical signal processing functional blocks in optical switching are presented, i.e.,\\u000a optical wavelength conversion, optical regeneration, optical logic, and optical format conversion. We present a brief overview\\u000a of optical wavelength conversion, and focus on various

Yong Liu; Ligong Chen; Tianxiang Xu; Jinglei Mao; Shangjian Zhang; Yongzhi Liu


Microscopic realization of cross-correlated noise processes.  


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

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



Improvement of ECG signal quality measurement using correlation and diversity-based approaches.  


A large proportion of cardiovascular diseases might be preventable, however, majority of this diseases occurs in rural areas where there is a poor presence of cardiologists. To overcome this issue, the use of wearable devices within the telemedicine framework would be of benefit. However, implementation of processing algorithms in smart-phones at mobile environments imposes restrictions ensuring high measurement quality of acquired ECG data, while maintaining low computation burden. This work presents an algorithm for scoring the quality of measured ECG recordings is developed. Particularly, a quality score is provided that takes into account the proportional correlation observed in acceptable signals based on a diversity scheme, and their inverse relation with standard deviation. Testing of proposed algorithm is carried out upon two different databases, the first one is of own production, while the second one is obtained from Physionet. As a result, high values of sensitivity and specificity are achieved. PMID:23366877

Martínez-Tabares, F J; Espinosa-Oviedo, J; Castellanos-Dominguez, G



Matched filter for DS-CDMA of up to 50 MChip\\/s based on sampled analog signal processing  

Microsoft Academic Search

The matched filter (MF) is known as the fastest method for acquisition of DS-CDMA signals. The MF calculates a cross-correlation between an input signal and a filtering coefficient employed for modulation. Power consumption of the MF is a key issue for realizing multimedia hand-held terminals. Recently, a MF that uses analog signal processing has achieved a maximum processing rate of

Toshinobu Shibano; K. Lizuka; M. Miyamoto; M. Osaka; R. Miyama; A. Kito



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

PubMed Central

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.

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



A Study on Signal Group Processing of AUTOSAR COM Module  

NASA Astrophysics Data System (ADS)

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.

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




Microsoft Academic Search

In this paper, a signal acquisition algorithm for Galileo positioning is derived starting from the time domain correla- tion. The overall correlation is decomposed into coherent integration, smaller size correlations and combining with BOC removal. The complexity of this algorithm is compared in terms of memory consumption and arithmetic complexity. Estimates show a significant reduction in both measures.

Harri Sorokin; Elena-Simona Lohan; Jarmo Takala


Signal processing in optical coherence tomography for aerospace material characterization  

NASA Astrophysics Data System (ADS)

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

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



Optimization of FPGA processing of GEM detector signal  

NASA Astrophysics Data System (ADS)

This paper presents analysis of processing method of the signal from Gas Electron Multiplier (GEM) detector acquired in our Field-Programmable Gate Array (FPGA) based readout system. We have found that simple processing of GEM signal received from the charge amplifier, sampled at 100MHz with 10-bit resolution, after low-pass filtering with 15 MHz cut-off frequency, provides accuracy similar to obtained by processing of the raw GEM signal sampled at 2.5 GHz frequency with 8-bit resolution. Even when 3 bits are lost due to long term instability of the detector and analog part of the system - resulting in 7-bit effective resolution, the reasonable accuracy is still preserved. Additionally we have analyzed computational power required to perform the real-time analysis of the GEM signal, taking into consideration resources offered by the FPGA chip used in the prototype platform.

Zabo?otny, Wojciech M.; Czarski, Tomasz; Chernyshova, Maryna; Czyrkowski, Henryk; D?browski, Ryszard; Dominik, Wojciech; Jakubowska, Katarzyna; Karpi?ski, Les?aw; Kasprowicz, Grzegorz; Kierzkowski, Krzysztof; Kud?a, Ignacy M.; Po?niak, Krzysztof; Rzadkiewicz, Jacek; Sa?apa, Zbigniew; Scholz, Marek



High-speed optical coherence tomography signal processing on GPU  

NASA Astrophysics Data System (ADS)

The signal processing speed of spectral domain optical coherence tomography (SD-OCT) has become a bottleneck in many medical applications. Recently, a time-domain interpolation method was proposed. This method not only gets a better signal-to noise ratio (SNR) but also gets a faster signal processing time for the SD-OCT than the widely used zero-padding interpolation method. Furthermore, the re-sampled data is obtained by convoluting the acquired data and the coefficients in time domain. Thus, a lot of interpolations can be performed concurrently. So, this interpolation method is suitable for parallel computing. An ultra-high optical coherence tomography signal processing can be realized by using graphics processing unit (GPU) with computer unified device architecture (CUDA). This paper will introduce the signal processing steps of SD-OCT on GPU. An experiment is performed to acquire a frame SD-OCT data (400A-lines×2048 pixel per A-line) and real-time processed the data on GPU. The results show that it can be finished in 6.208 milliseconds, which is 37 times faster than that on Central Processing Unit (CPU).

Li, Xiqi; Shi, Guohua; Zhang, Yudong



Simplified signal processing for impedance spectroscopy with spectrally sparse sequences  

NASA Astrophysics Data System (ADS)

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

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



The matched-lag filter: detecting broadband multipath signals with auto- and cross-correlation functions.  


Signal detection is considered for uncertain noise variance and a broadband source of unknown waveform and emission time. The signal travels to the receivers along paths with unknown delays. Using a new "matched-lag filter," the presence or absence of the signal is estimated from the auto- and cross-correlation functions of the receptions. Like a matched filter, correlation functions provide the first stage of gain in signal-to-noise ratio because the paths are assumed to be partially coherent. The second stage achieves additional gain by searching only over physically possible arrangements of signals in the auto- and cross-correlation functions while excluding forbidden arrangements. These stages enable the matched-lag filter to behave like a matched filter within a matched filter. In an ideal case, simulations of the matched-lag filter yield probabilities of detection that are, with one and two receivers, 4.1 and 366 times, respectively, that obtained from the conventional energy detector at a false-alarm probability of 0.001. The matched-lag filter has applications to wireless communications and the detection of acoustic signals from animals, vehicles, ships, and nuclear blasts. The matched-lag filter more completely describes signal structure than stochastic detection and communication theories whose specified auto-correlation function does not prohibit forbidden arrangements. PMID:11386553

Spiesberger, J L



Theoretical performance of a complex cross-correlator with Gaussian signals  

NASA Astrophysics Data System (ADS)

Analytical expressions are obtained for the joint probability density function PDF of the in-phase (X) and quadrature (Y) output signals of a complex cross-correlator when the inputs are narrowband partially correlated Gaussian signals. The PDF and cumulative distribution function (CDF) for the modulus (X-squared + y-squared) exp 1/2 are then derived, and applied to the problem of detecting a Gaussian noise jammer in the presence of uncorrelated Gaussian noise. Results are presented in the form of curves showing the value of input correlation coefficient required to achieve a specified detection probability versus the number of samples integrated, for various false alarm probabilities.

Milne, K.



Performance of different processing schemes in seismic noise cross-correlations  

NASA Astrophysics Data System (ADS)

The estimation of the Green's function between two points on the Earth's surface by the cross-correlation of seismic noise time-series became a widely used method in seismology. In general, very long time-series (months to years) as well as massive normalization and/or data selection are necessary to obtain useful cross-correlation functions. One task of this study is to evaluate the influence of different established normalization methods on the obtained cross-correlation functions. Furthermore, we evaluate two waveform preserving time domain normalizations as well as a new fully automated data selection approach. The cross-correlation functions analysed in this study are obtained from 12 months of seismic noise recorded in 2004 at five seismic stations in the United States with station distances on a continental scale. For practical reasons, the cross-correlation functions of such long time-series are calculated by stacking the cross-correlation functions obtained from shorter time windows. We use this stacking process for the implementation of the waveform preserving time domain normalizations. The time window length is in general an important parameter of the cross-correlation processing, as it influences the normalization and data selection. Therefore, we evaluate the cross-correlation functions obtained with 47 different time window lengths between one hr and 24 hr. The time domain normalizations intend to suppress the influence of transient signals like earthquake waves as well as long-term (e.g. seasonal) amplitude variations. We compare the proposed waveform preserving time domain normalizations with the established running absolute mean normalization and the one-bit normalization. We demonstrate that a waveform preserving time domain normalization can replace a non-linear time domain normalization, if a time window length similar to the duration of the typically occurring transient signals is used. Next to the time domain normalizations also the spectral whitening in the frequency domain is evaluated. Spectral whitening is a powerful normalization to improve the emergence of broad-band signals in seismic noise cross-correlations. Nevertheless, we observe spectral whitening to depend strongly on the time window length. An unwanted amplification of a persistent microseism signal is observed on the continental scale with time windows shorter than 12 hr. Our approach of automated data selection is based on a statistical time-series classification and reliably excludes time windows with transient signals occurring contemporaneously at both sites (e.g. earthquake waves). This data selection approach is capable to replace a non-linear time domain normalization, but no improvement of the waveform symmetry or the signal-to-noise ratio of the cross-correlation functions is observed in general.

Groos, J. C.; Bussat, S.; Ritter, J. R. R.



Neural Correlates of Semantic Competition during Processing of Ambiguous Words  

ERIC Educational Resources Information Center

The current study investigated the neural correlates that underlie the processing of ambiguous words and the potential effects of semantic competition on that processing. Participants performed speeded lexical decisions on semantically related and unrelated prime-target pairs presented in the auditory modality. The primes were either ambiguous…

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



Trouble at Rest: How Correlation Patterns and Group Differences Become Distorted After Global Signal Regression  

PubMed Central

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

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



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


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

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



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

SciTech Connect

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.

Dodge, D A



Queueing up for enzymatic processing: correlated signaling through coupled degradation  

Microsoft Academic Search

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

Natalie A Cookson; William H Mather; Tal Danino; Octavio Mondragón-Palomino; Ruth J Williams; Lev S Tsimring; Jeff Hasty



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

NASA Astrophysics Data System (ADS)

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

Volman, Vladislav; Levine, Herbert



Low power, compact charge coupled device signal processing system  

NASA Astrophysics Data System (ADS)

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.

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



A software environment for digital signal-processing simulations  

Microsoft Academic Search

A signal-processing software system is described which allows the simulation of systems described by block diagrams or signal-flow graphs. A high-level data-flow language describes the interconnection of the components. All configurations of interconnections are allowed, including those containing feedback. Component systems (blocks) are allowed to be multi-input, multi-output, and to be programmed in any language. Blocks are implemented as separate

Don H. Johnson; Robert E. Vaughan



Multigigahertz range-Doppler correlative processing in crystals  

NASA Astrophysics Data System (ADS)

Spectral-spatial holographic crystals have the unique ability to resolve fine spectral features (down to kilohertz) in an optical waveform over a broad bandwidth (over 10 gigahertz). This ability allows these crystals to record the spectral interference between spread spectrum waveforms that are temporally separated by up to several microseconds. Such crystals can be used for performing radar range-Doppler processing with fine temporal resolution. An added feature of these crystals is the long upper state lifetime of the absorbing rare earth ions, which allows the coherent integration of multiple recorded spectra, yielding integration gain and significant processing gain enhancement for selected code sets, as well as high resolution Doppler processing. Parallel processing of over 10,000 beams could be achieved with a crystal the size of a sugar cube. Spectral-spatial holographic processing and coherent integration of up to 2.5 Gigabit per second coded waveforms and of lengths up to 2047 bits has previously been reported. In this paper, we present the first demonstration of Doppler processing with these crystals. Doppler resolution down to a few hundred Hz for broadband radar signals can be achieved. The processing can be performed directly on signals modulated onto IF carriers (up to several gigahertz) without having to mix the signals down to baseband and without having to employ broadband analog to digital conversion.

Harris, Todd L.; Babbitt, Wm. R.; Merkel, Kristian D.; Mohan, R. Krishna; Cole, Zachary; Olson, Andy



Scanning near-field optical microscopy signal processing and resolution.  


To increase the signal-to-noise ratio and to remove the spatially slow varying signals, a lock-in amplifier is often used in scanning probe microscopy. The signal reconstructed from the lock-in data contains the contributions of the evanescent and homogeneous waves that are mixed in the near-field zone (i.e., at a very short distance). The resolution is determined and a method is given to suppress the useless background information. Experimental images of nanoparticles are processed. PMID:17415394

Grosges, Thomas; Barchiesi, Dominique



The mathematical theory of signal processing and compression-designs  

NASA Astrophysics Data System (ADS)

The mathematical theory of signal processing, named processor coding, will be shown to inherently arise as the computational time dual of Shannon's mathematical theory of communication which is also known as source coding. Source coding is concerned with signal source memory space compression while processor coding deals with signal processor computational time compression. Their combination is named compression-designs and referred as Conde in short. A compelling and pedagogically appealing diagram will be discussed highlighting Conde's remarkable successful application to real-world knowledge-aided (KA) airborne moving target indicator (AMTI) radar.

Feria, Erlan H.



A statistical analysis on the correlation between LF signal disturbances and strong earthquakes  

NASA Astrophysics Data System (ADS)

Data of seven years observations in Petropavlovsk-Kamchatsky are used for further statistical study on the correlation between disturbances in subionospheric LF signal and strong earthquakes. Nighttime difference amplitude and phase of the signal 40 kHz from JJY transmitter in Japan are analysed. It is found that anomalies of LF signal are observed in 15-20 % cases for earthquakes with ?=5.5-6.5. The signal behavior about the date of nine the strongest earthquakes with ??7, which occurred in the wave path sensitivity zone during 2000-2008, is analysed in detail. Clear anomalies in amplitude and phase of the signal are observed in five cases for quiet geomagnetic conditions. In two cases earthquakes were preceded by strong geomagnetic activity which could obscure effect from earthquakes. These results confirm our previous statistical works and testify the efficiency of VLF/LF radio signal method for strong earthquakes forecast.

Rozhnoi, Alexander; Solovieva, Maria; Molchanov, Oleg; Hayakawa, Masashi; Biagi, Pier Francesco; Schwingenschuh, Konrad



Probing many-particle correlations in semiconductor quantum wells using double-quantum-coherence signals  

PubMed Central

Multidimensional analysis of coherent signals is commonly used in nuclear magnetic resonance to study correlations among spins. These techniques were recently extended to the femtosecond regime and applied to chemical, biological and semiconductor systems. In this work, we apply a two-dimensional correlation spectroscopy technique which employs double-quantum-coherence to investigate many-body effects in a semiconductor quantum well. The signal is detected along the direction k1+ k2? k3, where k1, k2 and k3 are the pulse wave vectors in chronological order. We show that this signal is particularly sensitive to many-body correlations which are missed by time-dependent Hartree-Fock approximation. The correlation energy of two-exciton can be probed with a very high resolution arising from a two-dimensional correlation spectrum, where two-exciton couplings spread the cross peaks along both axes of the 2D spectrum to create a characteristic highly resolved pattern. This level of detail is not available from conventional one-dimensional four-wave mixing or other two-dimensional correlation spectroscopy signals such as the photo echo (?k1+ k2+ k3).

Yang, Lijun; Mukamel, Shaul



Digital processing of RF signals from optical frequency combs  

NASA Astrophysics Data System (ADS)

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

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



Research on mud pulse signal data processing in MWD  

NASA Astrophysics Data System (ADS)

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

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



An expert system for correlation of radar and passive sensor signals  

SciTech Connect

This paper describes a system for automating the correlation task by combining high-speed hardware with symbolic pattern-matching software to perform correlation of active and passive signals in real time. The first section of this paper describes the hardware and software used to implement the inference engine so that correlations can be performed in real time. The second section describes the expert system, with emphasis on the heuristics used to code the correlator efficiently. The final section describes the simulation environment under which the system is operated current efforts, and plans for further development. 2 refs., 2 figs.

Williams, L.C.; Gamberini, R.J.



Surface wave delay line acoustooptic devices for signal processing.  


Several acoustooptic devices have been developed for use as electronic signal processors at the Harry Diamond Laboratories. These devices use the Bragg interaction between a coherent light beam and surface acoustic waves propagating in a transparent crystalline delay line. Both real-time convolution and correlation of signals have been performed, and a real-time continuous Fourier transform has also been achieved. A programmable memory correlator has been demonstrated. This device uses a newly discovered photorefractive effect to store an image of a surface acoustic wave in a lithium niobate delay line. An acoustooptic implementation of the triple-product convolver is under active development. This device has been proposed for use in conjunction with charge-coupled-device chirp-Z-transform modules to perform very long discrete Fourier transforms and to do omega-k beam forming. PMID:20212749

Berg, N J; Lee, J N; Casseday, M W; Udelson, B J



The modeling of MMI structures for signal processing applications  

NASA Astrophysics Data System (ADS)

Microring resonators are promising candidates for photonic signal processing applications. However, almost all resonators that have been reported so far use directional couplers or 2×2 multimode interference (MMI) couplers as the coupling element between the ring and the bus waveguides. In this paper, instead of using 2×2 couplers, novel structures for microring resonators based on 3×3 MMI couplers are proposed. The characteristics of the device are derived using the modal propagation method. The device parameters are optimized by using numerical methods. Optical switches and filters using Silicon on Insulator (SOI) then have been designed and analyzed. This device can become a new basic component for further applications in optical signal processing. The paper concludes with some further examples of photonic signal processing circuits based on MMI couplers.

Le, Thanh Trung; Cahill, Laurence W.



Actin Cytoskeleton-Dependent Dynamics of the Human Serotonin1A Receptor Correlates with Receptor Signaling  

PubMed Central

Analyzing the dynamics of membrane proteins in the context of cellular signaling represents a challenging problem in contemporary cell biology. Lateral diffusion of lipids and proteins in the cell membrane is known to be influenced by the cytoskeleton. In this work, we explored the role of the actin cytoskeleton on the mobility of the serotonin1A (5-HT1A) receptor, stably expressed in CHO cells, and its implications in signaling. FRAP analysis of 5-HT1AR-EYFP shows that destabilization of the actin cytoskeleton induced by either CD or elevation of cAMP levels mediated by forskolin results in an increase in the mobile fraction of the receptor. The increase in the mobile fraction is accompanied by a corresponding increase in the signaling efficiency of the receptor. Interestingly, with increasing concentrations of CD used, the increase in the mobile fraction exhibited a correlation of ?0.95 with the efficiency in ligand-mediated signaling of the receptor. Radioligand binding and G-protein coupling of the receptor were found to be unaffected upon treatment with CD. Our results suggest that signaling by the serotonin1A receptor is correlated with receptor mobility, implying thereby that the actin cytoskeleton could play a regulatory role in receptor signaling. These results may have potential significance in the context of signaling by GPCRs in general and in the understanding of GPCR-cytoskeleton interactions with respect to receptor signaling in particular.

Ganguly, Sourav; Pucadyil, Thomas J.; Chattopadhyay, Amitabha



Digital signal processing utilizing a generic instruction set  

NASA Astrophysics Data System (ADS)

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

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


The Savant Hypothesis: is autism a signal-processing problem?  


Autism is being investigated through many different approaches. This paper suggests the genetic, perceptual, cognitive, and histological findings ultimately manifest themselves as variations of the same signal-processing problem of defective compression. The Savant Hypothesis is formulated from first principles of both mathematical signal-processing and primary neuroscience to reflect the failure of compression. The Savant Hypothesis is applied to the problem of autism in a surprisingly straightforward application. The enigma of the autistic savant becomes intuitive when observed from this approach. PMID:20347529

Fabricius, Thomas



Optical signal acquisition and processing in future accelerator diagnostics  

SciTech Connect

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.

Jackson, G.P. [Fermi National Accelerator Lab., Batavia, IL (United States); Elliott, A. [Illinois Univ., Chicago, IL (United States)



Atmospheric Radar Signal Processing using Bivariate Empirical Mode Decomposition  

NASA Astrophysics Data System (ADS)

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.

Sreenivasulu Reddy, Thatiparthi



Crosstalk between Wnt Signaling and RNA Processing in Colorectal Cancer  

PubMed Central

RNA processing involves a variety of processes affecting gene expression, including the removal of introns through RNA splicing, as well as 3' end processing (cleavage and polyadenylation). Alternative RNA processing is fundamentally important for gene regulation, and aberrant processing is associated with the initiation and progression of cancer. Deregulated Wnt signaling, which is the initiating event in the development of most cases of human colorectal cancer (CRC), has been linked to modified RNA processing, which may contribute to Wnt-mediated colonic carcinogenesis. Crosstalk between Wnt signaling and alternative RNA splicing with relevance to CRC includes effects on the expression of Rac1b, an alternatively spliced gene associated with tumorigenesis, which exhibits alternative RNA splicing that is influenced by Wnt activity. In addition, Tcf4, a crucial component of Wnt signaling, also exhibits alternative splicing, which is likely involved in colonic tumorigenesis. Modulation of 3' end formation, including of the Wnt target gene COX-2, also can influence the neoplastic process, with implications for CRC. While many human genes are dependent on introns and splicing for normal levels of gene expression, naturally intronless genes exist with a unique metabolism that allows for intron-independent gene expression. Effects of Wnt activity on the RNA metabolism of the intronless Wnt-target gene c-jun is a likely contributor to cancer development. Further, butyrate, a breakdown product of dietary fiber and a histone deacetylase inhibitor, upregulates Wnt activity in CRC cells, and also modulates RNA processing; therefore, the interplay between Wnt activity, the modulation of this activity by butyrate, and differential RNA metabolism in colonic cells can significantly influence tumorigenesis. Determining the role played by altered RNA processing in Wnt-mediated neoplasia may lead to novel interventions aimed at restoring normal RNA metabolism for therapeutic benefit. Therefore, this minireview presents a brief overview of several aspects of RNA processing of relevance to cancer, which potentially influence, or are influenced by, Wnt signaling activity.

Bordonaro, Michael



Calcium Signals: The Lead Currency of Plant Information Processing  

PubMed Central

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.

Kudla, Jorg; Batistic, Oliver; Hashimoto, Kenji



Diffraction tomographic signal processing algorithms for tunnel detection  

SciTech Connect

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.

Witten, A.J.



A wavelet threshold denoising method for ultrasonic signal based on EMD and correlation coefficient analysis  

Microsoft Academic Search

Ultrasonic image processing apparatus usually use TGC amplifiers for the appropriate amplification of far-field echoes to compensate for image quality reduction due to far-field signal attenuation. However, along with the signal enhancement, the far field noises are also amplified in a certain level. For a scanning line of RF, it generates a type of noise with large far field noises

Mingjian Sun; Yi Shen; Wei Zhang



Monitoring Signaling Processes in Living Cells Using Biosensors  

NSDL National Science Digital Library

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.

Klaus Hahn (Scripps Research Institute;Department of Cell Biology; REV)



A single chip VLSI architecture for radar signal processing  

NASA Astrophysics Data System (ADS)

The problem of how much radar signal processing one can achieve with a single chip signal processor is investigated through the design of a processor architecture suitable for single chip implementation using very large scale integration (VLSI) technology. The design of the single chip processor departs from existing processor designs both in the way it is structured and the manner in which it performs computations. Major emphasis is placed on taking advantage of the parallelism and pipelining inherent in radar signal processing functions, and on novel processor architecture capable of mapping high-level computations (i.e., complex primitives such as Fast Fourier Transform) directly into hardware. The single chip design is based on state-of-the-art technology and utilizes bit-serial arithmetic and externally supplied First-In First-Out memory.

Kanopoulos, N.


In-situ photo-polymerization study of Si-(bis-GMA)/TEGDMA by correlations of PA signals  

NASA Astrophysics Data System (ADS)

The photo-polymerization reaction of Si-(bis-GMA)/TEGDMA (a bis-GMA modified with silyl groups and mixed with TEDGMA) has been studied by pulsed photoacoustic (PA) and FTIR techniques. The light from a pulsed laser is focused on the surface of the sample for both to activate the chemical reaction and generate PA signals. The in-situ acquisition of the PA signals, during photo-polymerization (PP), in consecutive way, permits to follow changes in its physical properties. The structural changes during polymer formation are recovered by a numerical procedure based on correlation coefficients r_i. This numerical procedure, applied to digitally recorded PA signals, allows the construction of a PP profile dri /dT_i, and permits to detect the phase transitions during the whole process including the gel region. The obtained results are in agreement with those obtained from the FTIR analysis, under similar conditions.

Rivera, F.; Navarrete, M.; Vera-Graziano, R.; Sobral, H.



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

NASA Astrophysics Data System (ADS)

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

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



Neural Correlates of Sublexical Processing in Phonological Working Memory  

ERIC Educational Resources Information Center

|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…

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



Physical characteristics of diblock polyacetylene copolymers: processability-conductivity correlation  

SciTech Connect

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

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



Neural Correlates of Bridging Inferences and Coherence Processing  

ERIC Educational Resources Information Center

|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…

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



DSPSR: Digital Signal Processing Software for Pulsar Astronomy  

Microsoft Academic Search

dspsr is a high-performance, open-source, object-oriented, digital signal processing software library and application suite for use in radio pulsar astronomy. Written primarily in C++, the library implements an extensive range of modular algorithms that can optionally exploit both multiple-core processors and general-purpose graphics processing units. After over a decade of research and development, dspsr is now stable and in widespread

W. van Straten; M. Bailes



Signal processing in the cochlea: The structure equations  

PubMed Central

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.



A new collaborative active learning tool for signal processing education  

Microsoft Academic Search

This paper introduces a distributed object based collaboration system called Collaboard, which can be effectively used to conduct signal processing classes in an interactive fashion. Collaboard allows a group of users in a heterogeneous network environment to share multimedia objects, such as text, geometric entities, equations, images, audio\\/video objects, and OLETM objects. Collaboard supports multiple user groups and allows a

Saad Lamouri; Y. Ozturk; Hilseyin Abut



Technology and Signal Processing for Brain-Machine Interfaces  

Microsoft Academic Search

Neural interfaces hold the promise to become one of the great technological advancements of the 21st century because they can provide new means of communication by directly accessing and interpreting brain intentional states. This article presents a set of grand challenges for brain-machine interfaces (BMI) and investigates recent advances in neurotechnology and signal processing methods to overcome them.

Justin C. Sanchez; Jose C. Principe; Toshikazu Nishida; Rizwan Bashirullah; John Harris; Jose Fortes



CORDIC-based VLSI architectures for digital signal processing  

Microsoft Academic Search

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

Y. H. Hu



Time delay estimation for passive sonar signal processing  

Microsoft Academic Search

An overview of applied research in passive sonar signal processing estimation techniques for naval systems is presented. The naval problem that motivates time delay estimation is the source state estimation problem. A discussion of this problem in terms of estimating the position and velocity of a moving acoustic source is presented. Optimum bearing and range estimators are presented for the

G. Carter



Space or time adaptive signal processing by neural network models  

Microsoft Academic Search

Part I. Starting from the properties of networks with backward lateral inhibitions, we define an algorithm for adaptive spatial sampling of line-structured images. Applications to character recognition are straightforward. Part II. Let be an array of n sensors, each sensitive to an unknown linear combination of n sources. This is a classical problem in Signal Processing. But what is less

J. Herault; C. Jutten



Reconfigurable signal processing ASIC architecture for high speed data communications  

Microsoft Academic Search

A flexible and reconfigurable signal processing ASIC architecture has been developed, simulated and synthesized. The proposed architecture can be used to realize any one of several functional blocks needed for the physical layer implementation of high speed data communication systems operating at symbol rates over 60 Msamples\\/sec. In fact, multiple instances of a chip based on this architecture each operating

Eugene Grayver; Babak Daneshrad



Functional Languages in Signal Processing Applied to Prosthetic Limb Control  

Microsoft Academic Search

This article describes how one can use functional languages to develop a dedicated system for controlling a prosthetic arm. It shows the prototype artificial limb along with the development of the various algorithms and software used to process electromyographic (EMG) signals, to be used as inputs for the control mechanism. Great emphasis is also laid on the parametric modelling used

Alcimar Barbosa Soares; Antonio Claudio Paschoarelli Veiga; Adriano de Oliveira Andrade; Antonio Costa Pereira; Jamil Salem Barbar



Pipelined ALU for Signal Processing to Implement Interval Arithmetic  

Microsoft Academic Search

There are many applications within digital signal processing (DSP) that require the user to know how various numerical errors (uncertainty) affect the result. This uncertainty is represented by replacing non-interval values with intervals. Since most DSPs operate in real time environments, fast processors are needed to implement interval arithmetic. The goal is to develop a platform in which interval arithmetic

Ruchir Guptel; William W. Edmonson; Senanu Ocloo; Winser E. Alexander



Yarn hairiness parameterization using a coherent signal processing technique  

Microsoft Academic Search

The aim of this paper is to present an automatic yarn hairiness parameterization method based on optical sensors. Hairiness measurements are performed using a coherent signal processing technique for higher resolution. Using this optical technique together with electronic instrumentation and custom developed software, it is possible to quantify all traditional hairiness parameters (i.e. hairiness (H), its coefficient of variation (CVH)

Vítor Carvalho; Paulo Cardoso; Michael Belsley; Rosa M. Vasconcelos; Filomena O. Soares



Guidelines for affective signal processing (ASP): From lab to life  

Microsoft Academic Search

This article presents the rationale behind ACII2009's special session: Guidelines for Affective Signal Processing (ASP): From lab to life. Although affect is embraced by both science and engineering, its recognition has not reached a satisfying level. Through a concise overview of ASP and the automatic classification of affect, we provide understanding for the problems encountered. Next, we identify guidelines for

Egon L. van den Broek; Joris H. Janssen; Joyce H. D. M. Westerink; J. Cohn; A. Nijholt; M. Pantic



Digital signal processing in electrical engineering technology programs  

Microsoft Academic Search

Digital signal processing (DSP) is one of the most demanding areas in today's job market for electronic engineering graduates. Because of the need for this particular area, if not all but, most electrical\\/electronic engineering departments have already integrated this popular subject in their curriculum. To understand DSP, a good knowledge of advanced mathematics is required. This, in turn, has created

Massoud Moussavi



Signal processing algorithms for hyperspectral remote sensing of chemical plumes  

Microsoft Academic Search

Long-wave infrared (LWIR) hyperspectral imaging sensors are widely used for the detection and identification of released chemical agents in many civilian and military applications. Current hyperspectral system capabilities are limited by variation in the background clutter as opposed to the physics of photon detection. Hence, the development of statistical models for background clutter and optimum signal processing algorithms that exploit

Dimitris Manolakis



A high dynamic magnetooptic current transformer with optimized signal processing  

Microsoft Academic Search

In the power industry current has to be measured for metering and protection purposes. Conventional sensor setups need two transformers to realize the high dynamic range. By a new mixed analog\\/digital signal processing algorithm, the performances of a high accuracy revenue metering and a fast, high dynamic protection metering magnetooptic current sensor were combined into one single unit. The system

Stephan Mohr; Thomas Bosselmann



Cancer systems biology: signal processing for cancer research.  


In this editorial we introduce the research paradigms of signal processing in the era of systems biology. Signal processing is a field of science traditionally focused on modeling electronic and communications systems, but recently it has turned to biological applications with astounding results. The essence of signal processing is to describe the natural world by mathematical models and then, based on these models, develop efficient computational tools for solving engineering problems. Here, we underline, with examples, the endless possibilities which arise when the battle-hardened tools of engineering are applied to solve the problems that have tormented cancer researchers. Based on this approach, a new field has emerged, called cancer systems biology. Despite its short history, cancer systems biology has already produced several success stories tackling previously impracticable problems. Perhaps most importantly, it has been accepted as an integral part of the major endeavors of cancer research, such as analyzing the genomic and epigenomic data produced by The Cancer Genome Atlas (TCGA) project. Finally, we show that signal processing and cancer research, two fields that are seemingly distant from each other, have merged into a field that is indeed more than the sum of its parts. PMID:21439242

Yli-Harja, Olli; Ylipää, Antti; Nykter, Matti; Zhang, Wei



Evaluating EVD and SVD errors in signal processing environments  

Microsoft Academic Search

In practical signal processing environments, the error perturbations in the eigenvalue decomposition (EVD) or singular value decomposition (SVD) will be due to both noise and numerical errors. Many numerical analysts have touted the SVD as being superior to the EVD because it has less numerical error. However, these errors are often insignificant when the noise perturbation is large enough. Since

Eugene Scott Baker; Ronald D. DeGroat



Signal-processing applications of charge-coupled devices  

Microsoft Academic Search

This review paper discusses the physics of CCDs, examines some CCD input and output schemes, and considers ways to measure and compensate CCD inefficiency. Some applications of CCDs are discussed, including transversal filters, spectral analysis, and MTI radar and TV ghost suppression. Work being done at IIT Delhi on various aspects of CCD theory, fabrication, and signal processing applications is

S. C. Dutta Roy; A. B. Bhattacharyya; J. M. Vasi; V. G. Das; L. Shankar; N. Kapur




Microsoft Academic Search

In many areas of signal processing, the trend of addressing problems with increased complexity continues. This is best reflected by the forms of the models used for describing phe- nomena of interest. Typically, in these models the number of unknowns that have to be estimated is large and the as- sumptions about noise distributions are often non-tractable for analytical derivations.

Petar M. Djuri


Reinforcing the understanding of signal processing concepts using audio exercises  

Microsoft Academic Search

In the near future, multimedia techniques will be used more extensively in signal processing education because the technology is available and the benefits to student learning and information retention are high. Using a variety of teaching techniques helps a wider range of students, who have different learning styles, and enhances student skills in their weaker areas. This paper describes a

J. W. Pierre; R. F. Kubichek; J. C. Hamann



Signal processing of sensor node data for vehicle detection  

Microsoft Academic Search

We describe an algorithm and experimental work for vehicle detection using sensor node data. Both acoustic and magnetic signals are processed for vehicle detection. We propose a real-time vehicle detection algorithm called the adaptive threshold algorithm (ATA). The algorithm first computes the time-domain energy distribution curve and then slices the energy curve using a threshold updated adaptively by some decision

J. Ding; S.-Y. Cheung; C.-W. Tan; P. Varaiya



Signal Processing Applications of Magneto-Optic Thin Films.  

National Technical Information Service (NTIS)

During the past few years, radar communication and sonar system performance requirements have increased to a point where it is necessary to store and process a far greater number of electrical signals, in as near real time as possible, than ever before. L...

R. E. Eschelbach



A Signal Processing System for Underwater Acoustic ROV Communication  

Microsoft Academic Search

A high performance system for communication with untethered underwater vehicles is presented. The system is centered around multiple digital processors which perform a variety of signal processing tasks. The processors are combined into an array using a flexible architecture designed for communication prcessing. A basic system has been tested at 5 kbit\\/sec over the Rayleigh-fading multipath channel in Woods Hole

Lee E. Freitag; J. A. Catipovic



Cross-correlation analysis of mechanomyographic signals detected in two axes.  


The purpose of this study was to use laser displacement sensors to examine the cross-correlation of surface mechanomyographic (MMG) signals detected from the rectus femoris muscle in perpendicular and transverse axes during isometric muscle actions of the leg extensors. Ten healthy men (mean +/- SD age = 22.1 +/- 1.6 years) and ten healthy women (age = 24.4 +/- 2.8 years) volunteered to perform submaximal to maximal isometric muscle actions of the dominant leg extensors. During each muscle action, two separate MMG signals were detected from the rectus femoris with laser displacement sensors. One MMG sensor was oriented in an axis that was perpendicular (PERP) to the muscle surface, and the second sensor was oriented in an axis that was transverse (TRAN) to the muscle surface. For each subject and force level, the MMG signals from the PERP and TRAN sensors were cross-correlated. The results showed maximum cross-correlation coefficients that ranged from R(x)(,y) = 0.273 to 0.989, but all subjects demonstrated at least one coefficient greater than 0.89. These findings showed a high level of association between the MMG signals detected in the perpendicular and transverse axes. Thus, it may not be necessary to detect MMG signals in multiple axes. PMID:19926909

Beck, Travis W; Dillon, Michael A; DeFreitas, Jason M; Stock, Matt S



Separation of a mixture of independent signals using time delayed correlations  

Microsoft Academic Search

The problem of separating n linearly superimposed uncorrelated signals and determining their mixing coefficients is reduced to an eigenvalue problem which involves the simultaneous diagonalization of two symmetric matrices whose elements are measureable time delayed correlation functions. The diagonalization matrix can be determined from a cost function whose number of minima is equal to the number of degenerate solutions. Our

L. Molgedey; H. G. Schuster



Depth and structural index estimation of 2D magnetic source using correlation coefficient of analytic signal  

NASA Astrophysics Data System (ADS)

We presented using the correlation coefficient of the analytic signal of real data and the analytic signal of synthetic data generated by the assumed source to estimate the structural index and the depth of the source. First, we assumed that the causative sources are located at different locations in the underground and the structural index of the assumed source is changed from 0 to 3, and then we separately compute the correlation coefficients of the analytic signal of the measured data and the analytic signal of the anomaly generated by each assumed source, the correlation coefficient can get the maximum value when the location and structural index of the assumed source are consistent with the real source. We tested the correlation coefficient method on synthetic noise-free and noise-corrupted magnetic anomalies, and the inversion results indicate that the new method can successfully finish the inversion of magnetic data. We also applied it to measured magnetic data, and we obtain the structural index and the location of the source.

Ma, Guoqing; Li, Lili



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

ERIC Educational Resources Information Center

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

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



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

ERIC Educational Resources Information Center

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

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



Classification of Acousto-Optic Correlation Signatures of Spread Spectrum Signals Using Artificial Neural Networks.  

National Technical Information Service (NTIS)

The primary goal of this research was to determine if artificial Neural Networks (ANNs) can be trained to classify the correlation signatures of direct sequence and frequency-hopped spread-spectrum signals. Secondary goals were to determine (1) if network...

J. W. DeBerry



Spectrally-correlational properties of signals reflected by a cloud of scatterers during pulsed sounding  

Microsoft Academic Search

The correlation function and Doppler spectrum of the fluctuations of a signal reflected by a cloud of scatterers in the case of pulsed sounding are investigated. The form of the Doppler spectrum of the fluctuations is obtained as a function of the shape and duration of the sounding pulse, and likewise as a function of the realization of the wind-velocity

A. A. Zachepitskii; V. M. Mareskin



Effect of Correlation on Signal Detection in Arctic Under-Ice Noise,  

National Technical Information Service (NTIS)

Signal detection in a large segment of non-Gaussian and non-stationary Arctic under-ice noise, which contains both high power narrow-band and impulsive components, is examined. It is shown that the correlation functions of sub-segments of data change sign...

J. B. Thomas P. A. Nielsen



Correlation receiver of below-noise pulsed signals based on parametric interactions of spin waves in magnetic films  

Microsoft Academic Search

A correlation receiver capable of receiving pulsed microwave signals having amplitudes substantially below the noise level is proposed and experimentally realized. The device is based on the parametric interaction of two contra-propagating spin waves excited by the received microwave signal and the reference pulsed signal, containing information about the received signal shape, in a ferrite film waveguide. The output nonlinear

V. I. Vasyuchka; G. A. Melkov; V. A. Moiseienko; A. V. Prokopenko; A. N. Slavin



Quantum process estimation via generic two-body correlations  

SciTech Connect

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

Mohseni, M. [Research Laboratory of Electronics, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139 (United States); Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, Massachusetts 02138 (United States); Rezakhani, A. T. [Department of Chemistry and Center for Quantum Information Science and Technology, University of Southern California, Los Angeles, California 90089 (United States); Barreiro, J. T. [Department of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801 (United States); Institut fuer Experimentalphysik, Universitaet Innsbruck, Technikerstrasse 25/4, A-6020 Innsbruck (Austria); Kwiat, P. G. [Department of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801 (United States); Aspuru-Guzik, A. [Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, Massachusetts 02138 (United States)



Information retrieval and cross-correlation function analysis of random noise radar signal through dispersive media  

NASA Astrophysics Data System (ADS)

In this contribution we examine the propagation of an ultrawideband (UWB) random noise signal through dispersive media such as soil, vegetation, and water, using Fourier-based analysis. For such media, the propagated signal undergoes medium-specific impairments which degrade the received signal in a different way than the non-dispersive propagation media. Theoretically, larger penetration depths into a dispersive medium can be achieved by identifying and detecting the precursors, thereby offering significantly better signal-to-noise ratio and enhanced imaging. For a random noise signal, well defined precursors in term of peak-amplitude don't occur. The phenomenon must therefore be studied in terms of energy evolution. Additionally, the distortion undergone by the UWB random noise signal through a dispersive medium can introduce frequency-dependent uncertainty or noise in the received signal. This leads to larger degradation of the cross-correlation function (CCF), mainly in terms of sidelobe levels and main peak deformation, and consequently making the information retrieval difficult. We would further analyze one method to restore the shape and carrier frequency of the input UWB random noise signal, thereby, improving the CCF estimation.

Alejos, Ana Vazques; Dawood, Muhammad



Dual-Process Theory and Signal-Detection Theory of Recognition Memory  

Microsoft Academic Search

Two influential models of recognition memory, the unequal-variance signal-detection model and a dual-process threshold\\/detection model, accurately describe the receiver operating characteristic, but only the latter model can provide estimates of recollection and familiarity. Such estimates often accord with those provided by the remember–know procedure, and both methods are now widely used in the neuroscience literature to identify the brain correlates

John T. Wixted



Array Signal Processing and Spatial Spectral Estimation Using Data Transformation  

NASA Astrophysics Data System (ADS)

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

Hong, Wooyoung


A novel optoelectronic oscillator based on all optical signal processing  

NASA Astrophysics Data System (ADS)

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).

Li, Cheng-xin; Chen, Fu-shen; Zhang, Jia-hong; Mao, Jiu-bing



The Scientist and Engineer's Guide to Digital Signal Processing  

NSDL National Science Digital Library

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.

Smith, Steven W.



Modern Techniques in Acoustical Signal and Image Processing  

SciTech Connect

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

Candy, J V



Characterization of the Dynamical Processes in All-Optical Signal Processing Using Semiconductor Optical Amplifiers  

Microsoft Academic Search

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

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



Signal processing environment for analysis and reduction (SPEAR)  

NASA Astrophysics Data System (ADS)

The need for a high-fidelity sensor design simulation model to accurately predict the system performance envelope and to offset the escalating cost of the system development and testing is widely accepted by the defense community. This paper presents one such example of the modeling capability developed for the ballistic missile defense (BMD) application, called the signal processing environment for analysis and reduction (SPEAR) simulation. SPEAR has become a key IR sensor design and signal processing performance verification tool for the BMD Advanced Sensor Technology Program (ASTP), the Discriminating Interceptor Technology Program (DITP), and the ground based interceptor (GBI) and, where it is used for sensitivity analyses, algorithm evaluations, and performance assessments. For these programs, SPEAR provides an algorithm testing simulation to evaluate candidate signal processing options, and implement and test performance of algorithms proposed through advanced technology programs. In addition, SPEAR is used to process real world data to provide assessments of sensor performance and provide preflight predictions. The simulation has been interfaced to the synthetic scene generation model (SSGM), a community standard background and target scene generation simulation. Through this interface sensor performance can be evaluated against realistically modeled backgrounds to evaluate filtering, detection, and false alarm performance. SPEAR is a hi-fidelity passive infrared (IR) sensor and signal processing simulation for staring scanning, and hybrid sensors. It allows the user to specify the IR sensor physics including the sensor, optics, focal plane array or scan chip assembly, analog signal processor, time dependent and object dependent processing parameters and specific noise sources such as optics, jitter, fixed pattern noise, dark current, and gamma spike noise. SPEAR is an Ada/PVWAVE combination. The sensor and signal processing is written in Ada and the execution, parameter input, and function analysis are controlled with the graphical user interface (GUI) written in PVWAVE. The signal processing techniques available as options include time dependent processing techniques such as adaptive threshold detection, background estimation and removal, morphological filtering, match filtering, target signature extraction, and object dependent processing techniques such as centroiding and pulse matching. SPEAR has simulation control options to allow the user to execute and examine data per frame (mission mode) or in a statistical mode to investigate parametric sensitivities of the sensor performance. Documentation of SPEAR includes manuals on the GUI, the SPEAR application components, and guidelines for adding new algorithms and features. This paper provides a summary of key algorithm and options in SPEAR. Examples of performance analysis results are provided. The paper includes stochastic analyses of both the above- the-horizon and below-the-horizon engagements of target and background generated scenes using SSGM. Also discussed are the evaluation of radiometric measurement precision, angular measurement precision, and detection of targets of varying intensities with respect to varying sensor signal processing techniques.

Smith, Brian C.; Kinashi, Yasuhiro



The high speed low noise multi-data processing signal process circuit research of remote sensing  

NASA Astrophysics Data System (ADS)

The high speed, low noise and integration characteristic are the main technology and the main development directions on the signal process circuit of the image sensor, especially in high resolution remote sensing. With these developments, the high noise limiting circuits, high speed data transfer system and the integrated design of the signal process circuit become more and more important. Therefore the requirement of the circuit system simulation is more and more important during the system design and PCB board design process. A CCD signal process circuit system which has the high speed, low noise and several selectable operate modes function was designed and certificated in this paper, during the CCD signal process circuit system design, simulation was made which include the signal integrity and the power integrity. The important devices such as FPGA and the DDR2 device were simulated, using the power integrity simulation the sensitive power planes of the FPGA on the PCB was modified to make the circuit operate more stabilize on a higher frequency. The main clock path and the high speed data path of the PCB board were simulated with the signal integrity. All the simulation works make the signal process circuit system's image's SNR value get higher and make the circuit system could operate well on higher frequency. In the board testing process, the PCB time diagrams were listed on the testing chapter and the wave's parameter meets the request. The real time diagram and the simulated result of the PCB board was listed respectively. The CCD signal process circuit system's images' SNR (Signal Noise Ratio) value, the 14bit AFE slew rate and the data transfer frequency is listed in the paper respective.

Su, Lei; Jiang, Haibin; Dong, Wang



Analog integrated circuits design for processing physiological signals.  


Analog integrated circuits (ICs) designed for processing physiological signals are important building blocks of wearable and implantable medical devices used for health monitoring or restoring lost body functions. Due to the nature of physiological signals and the corresponding application scenarios, the ICs designed for these applications should have low power consumption, low cutoff frequency, and low input-referred noise. In this paper, techniques for designing the analog front-end circuits with these three characteristics will be reviewed, including subthreshold circuits, bulk-driven MOSFETs, floating gate MOSFETs, and log-domain circuits to reduce power consumption; methods for designing fully integrated low cutoff frequency circuits; as well as chopper stabilization (CHS) and other techniques that can be used to achieve a high signal-to-noise performance. Novel applications using these techniques will also be discussed. PMID:22275203

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



Two-point correlation properties of stochastic splitting processes  

NASA Astrophysics Data System (ADS)

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

Gabrielli, Andrea; Joyce, Michael



Signal processing for robotically assisted laser photocoagulation of the retina  

NASA Astrophysics Data System (ADS)

A new system for robotically assisted retinal surgery requires real-time signal processing of the reflectance signal from small targets on the retina. Laser photocoagulation is used extensively by ophthalmologists to treat retinal disorders such as diabetic retinopathy and retinal breaks. Currently, the procedure is performed manually and suffers from several drawbacks which a computer-assisted system could alleviate. Such a system is under development that will rapidly and safely place multiple therapeutic lesions at desired locations on the retina in a mater of seconds. This system provides real- time, motion-stabilized lesion placement for typical clinical irradiation times. A reflectance signal from a small target on the retina is used to derive high-speed tracking corrections to compensate for patient eye movement by adjusting the laser pointing angles. Another reflectance signal from a different small target on the retina is used to derive information to control the laser irradiation time which allows consistent lesion formation over any part of the retina. This paper describes the electro-optical system which dynamically measures the two reflectance signals, determines the appropriate reflectance parameters in real time, and controls laser pointing and irradiation time to meet the stated requirements.

Wright, Cameron H.; de Graaf, Peter W.; Barrett, Steven F.; Ferguson, R. D.



Ultrasonic distance and velocity measurement using a pair of LPM signals for cross-correlation method: improvement of Doppler-shift compensation and examination of Doppler velocity estimation.  


Real-time distance measurement of a moving object with high accuracy and high resolution using an ultrasonic wave is difficult due to the influence of the Doppler effect or the limit of the calculation cost of signal processing. An over-sampling signal processing method using a pair of LPM signals has been proposed for ultrasonic distance and velocity measurement of moving objects with high accuracy and high resolution. The proposed method consists of cross correlation by single-bit signal processing, high-resolution Doppler velocity estimation with wide measurement range and low-calculation-cost Doppler-shift compensation. The over-sampling cross-correlation function is obtained from cross correlation by single-bit signal processing with low calculation cost. The Doppler velocity and distance of the object are determined from the peak interval and peak form in the cross-correlation function by the proposed method of Doppler velocity estimation and Doppler-shift compensation. In this paper, the proposed method of Doppler-shift compensation is improved. Accuracy of the determined distance was improved from approximately within ±140?m in the previous method to approximately within ±10?m in computer simulations. Then, the proposed method of Doppler velocity estimation is evaluated. In computer simulations, accuracy of the determined Doppler velocity and distance were demonstrated within ±8.471mm/s and ±13.87?m. In experiments, Doppler velocities of the motorized stage could be determined within ±27.9mm/s. PMID:22560801

Hirata, Shinnosuke; Kurosawa, Minoru Kuribayashi



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

Microsoft Academic Search

The development of technology which integrates a four phase, buried-channel CCD in an existing 1.75 micron CMOS process is described. The four phase clock is employed in the integrated early vision system to minimize process complexity. Signal corruption is minimized and lateral fringing fields are enhanced by burying the channel. The CMOS process for CCD enhancement is described, which highlights

Craig L. Keast; Charles G. Sodini



Nonlinear signal processing of electroencephalograms for automated sleep monitoring  

NASA Astrophysics Data System (ADS)

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

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



A New Approach to Radio Astronomy Signal Processing: Packet Switched, FPGA-based, Upgradeable, Modular Hardware and Reusable, Platform-Independent Signal Processing Libraries  

Microsoft Academic Search

Our group seeks to revolutionize the development of radio astronomy signal processing instrumentation by designing and demonstrating a scalable, upgradeable, FPGA-based computing platform and software design methodology that targets a range of real-time radio telescope signal processing applications. This project relies on the development of a small number of modular, connectible, upgradeable hardware components and platform- independent signal processing algorithms

Aaron Parsons; Don Backer; Chen Chang; Daniel Chapman; Henry Chen; Pierre Droz; Christina de Jesus; David MacMahon; Andrew Siemion; John Wawrzynek; Dan Werthimer; Mel Wright


Maximum likelihood estimation of spatially correlated signal-dependent noise in hyperspectral images  

NASA Astrophysics Data System (ADS)

A new algorithm is described for estimating the noise model parameters in hyperspectral data when neither noise components variance nor noise spatial/spectral correlation priors are available. A maximum likelihood (ML) technique is introduced for checking the noise spatial correlation hypothesis and estimating the spatial correlation function width alongside with estimating signal-independent and signal-dependent noise components variance. The hyperspectral image is assumed to match a limited set of assumptions. A three-dimensional (3-D) fractional Brownian motion (fBm) model is introduced for describing locally the texture of the 3-D image noisy textural fragment. Nonstationarity of the useful image signal is taken into account by performing the estimation locally on a 3-D block-by-block basis. The accuracy of the proposed algorithm is first illustrated for synthetic images obtained from either pure fBm or almost noise-free AVIRIS hyperspectral images artificially degraded with spatially correlated noise. The results obtained for synthetic images demonstrate appropriate accuracy and robustness of the proposed method. Then results obtained for real life AVIRIS hyperspectral data sets confirm the noise spatial uncorrelation hypothesis for images acquired by the AVIRIS sensor. Conclusions and open problems are outlined.

Uss, Mykhail L.; Vozel, Benoit; Lukin, Vladimir V.; Chehdi, Kacem



All-optical signal processing using planar Bragg gratings  

NASA Astrophysics Data System (ADS)

All-optical signal processing offers the prospect of realizing high sampling bandwidth and overcoming many of the limitations of electronics. This work introduces the use of planar Bragg gratings in all-optical signal processing. The key fabrication technique is direct grating writing (DGW). One significant advantage of the DGW system is the small spot size of the focused laser beam used to inscribe the waveguide and grating. Rather than using the wide area exposure such as that from a phase mask, DGW uses a direct UV laser spot such that the dimensions of the UV induced structure are determined by the focal spot size. For complex grating engineering this feature is superior to the conventional phase mask techniques, allowing accurate control of the chirp, phase shifts, apodisation and other parameters to produce intricate optical response.

Sima, C.; Gates, J. C.; Rogers, H. L.; Snow, B. D.; Holmes, C.; Zervas, M. N.; Smith, P. G. R.



Systolic pocessing and an implementation for signal and image processing  

SciTech Connect

Many signal and image processing applications impose a severe demand on the I/O bandwidth and computation power of general-purpose computers. The systolic concept offers guidelines in building cost-effective systems that balance I/O with computation. The resulting simplicity and regularity of such systems leads to modular designs suitable for VLSI implementation. The authors describe a linear systolic array capable of evaluating a large class of inner-product functions used in signal and image processing. These include matrix multiplications, multidimensional convolutions using fixed or time-varying kernels, as well as various nonlinear functions of vectors. The system organization of a working prototype is also described. 11 references.

Kulkarni, A.V.; Yen, D.W.L.



Systolic design with asynchronous controls for digital-signal processing  

NASA Astrophysics Data System (ADS)

The research sponsored by this grant is focused on the development of a theoretical and technological basis for designing efficient systolic arrays for digital-signal processing algorithms. The major contributions of the research are the following: data reduction techniques via the utilization of algorithm properties; conversion of sequential input signal into input blocks by means of a spiral systolic mesh that is suitable for parallel processing and that is flexible for enabling various array dimensions; and devising a hybrid of SA and data-flow approach, making data streams independent of computations executed in each processor, thus reducing waiting time. The communication (PE) protocols resolve the data-flow conflicts created by the merging of the spiral and asynchronous systolic array architecture.

Reihani, Kamran



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

NASA Astrophysics Data System (ADS)

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.

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



Image processing of correlated data by experimental design techniques  

SciTech Connect

New classes of algorithms are developed for processing of two-dimensional image data imbedded in correlated noise. The algorithms are based on modifications of standard analysis of variance (ANOVA) techniques ensuring their proper operation in dependent noise. The approach taken in the development of procedures is deductive. First, the theory of modified ANOVA (MANOVA) techniques involving one- and two-way layouts are considered for noise models with autocorrelation matrix (ACM) formed by direct multiplication of rows and columns or tensored correlation matrices (TCM) stressing the special case of the first-order Markov process. Next, the techniques are generalized to include arbitrary, wide-sense stationary (WSS) processes. This permits dealing with diagonal masks which have ACM of a general form even for TCM. As further extension, the theory of Latin square (LS) masks is generalized to include dependent noise with TCM. This permits dealing with three different effects of m levels using only m{sup 2} observations rather than m{sup 3}. Since in many image-processing problems, replication of data is possible, the masking techniques are generalized to replicated data for which the replication is TCM dependent. For all procedures developed, algorithms are implemented which ensure real-time processing of images.

Stern, D.



Signal Processing Techniques for Data Confidentiality in OCDMA Access Networks  

Microsoft Academic Search

This chapter focuses on several imminent security applications in optical CDMA networks where the strong potentials of optical\\u000a signal processing could be leveraged. As one of the dominant technologies in wireless communications, the unique features\\u000a of CDMA have attracted wide attention in many optical network-ing areas. We explored the security properties of optical CDMA\\u000a networks enhanced by the aid of

Yue-Kai Huang; Paul Toliver; Paul R. Prucnal



Microsoft Academic Search

Aim: Computer-assisted processing of intramyocardial electrograms employing internet-based transmission to specialized service centers. Materials and methods: Implantable pacemakers provided with broad-bandwidth electrogram telemetry and using fractally coated electrodes render possible the acquisition of intramyocardial electrograms from the spontaneously beating as well as from the paced heart. These signals are transmitted via the Internet to the service center in Graz where

H. Hutten



Contributors to a multivariate statistical process control chart signal  

Microsoft Academic Search

A significant practical disadvantage of multivariate statistical process control is that it is difficult to determine which of the monitored variables is responsible for the out-of-control signal. While there have been several proposed techniques and diagnostics, most of these have disadvantages. Rather than an ad hoc selection, we use three approaches to develop a diagnostic for a chi-square chart and

George C. Runger; Frank B. Alt; Douglas C. Montgomery



Signal Processing for Young Child Speech Language Development  

Microsoft Academic Search

Speech signal processing and other man-machine interaction technologies have been developed for improved child-computer interaction for education, entertainment, as well as other applications (1, 2). However, for very young children (in the age range of 0 to 4 years old, and especially 0 to 2), such interaction is not encouraged (3, 4). Instead, parent-child interaction is highly recommended (3, 4)

Dongxin Xu; Umit Yapanel; Sharmi Gray; Jill Gilkerson; Jeff Richards; John Hansen


Attitude rate estimation by GPS Doppler signal processing  

Microsoft Academic Search

A method is presented for near-Earth spacecraft or aviation vehicle’s attitude rate estimation by using relative Doppler frequency\\u000a shift of the Global Positioning System (GPS) carrier. It comprises two GPS receiving antennas, a signal processing circuit\\u000a and an algorithm. The whole system is relatively simple, the cost and weight, as well as power consumption, are very low.

Side He; Doroslovacki Milos; Zhenyu Guo; Yufeng Zhang



Cathedral-II: A Silicon Compiler for Digital Signal Processing  

Microsoft Academic Search

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 ¿meet in the middle¿ design method that encourages a total separation

H. De Man; J. Rabaey; L. Claesen



An integrated signal processing framework for multiuser CDMA communications  

Microsoft Academic Search

The major signal processing challenges in wireless CDMA systems stem from time-varying multipath propagation effects, multi-access interference (MAI), and the complexity of the DSP algorithms. We propose a framework based on canonical multipath-Doppler coordinates for addressing these issues in an integrated fashion. The canonical coordinates are derived from a fundamental characterization of channel propagation dynamics in terms of discrete multipath-delayed

A. M. Sayeer



A digital filter chip for ECG signal processing  

Microsoft Academic Search

A VLSI implementation of a linear-phase digital filter for ECG signal processing has been designed. With a sampling rate of 100 Hz, the passband is from 0.5 Hz to 49.5 Hz with 0.5-dB ripple. The filter architecture is based on the use of recursive running-sum blocks, resulting in a very low computational complexity. Module generators have been used in the

Tommi Raita-aho; T. Saramaki; O. Vainio



Performance Evaluation and Benchmarking of Native Signal Processing  

Microsoft Academic Search

DSP processor growth is phenomenal and continues to grow rapidly, but general-purpose microprocessors have entered the multimedia and signal processing oriented stream by adding DSP functionality to the instruction set and also providing optimized assembly libraries. In this paper, we compare the performance of a general-purpose processor (Pentium II with MMX) versus a DSP processor (TI's C62xx) by evaluating the

Deependra Talla; Lizy Kurian John



Lab Exercises: Digital Signal Processing with Field Programmable Gate Arrays  

NSDL National Science Digital Library

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.

Meyer-Baese, Uwe


UniBoard: generic hardware for radio astronomy signal processing  

NASA Astrophysics Data System (ADS)

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

Hargreaves, J. E.



Signal shredding by autogenic processes in sedimentary systems  

NASA Astrophysics Data System (ADS)

Erosional and depositional landscapes evolve in response to changes in external drivers such as climate, tectonic motion, and eustatic sea level. These changes are typically imposed via time-varying boundary conditions with a wide range of time scales, and are transmitted to the landscape via changes in sediment flux. The response of landscapes is then mediated by the mechanics of sediment transport. Understanding how signals of environmental forcing are transmitted and preserved in sedimentary systems is crucial for predicting landscape response to environmental change, and for the inverse problem of interpreting Earth history from landforms and the depositional record. It is generally understood that climatic or tectonic signals can be modified - for example, damped and/or phase-shifted - as they propagate through sedimentary systems. Here we examine a much stronger effect: sediment transport can act as a noisy, nonlinear filter that destroys (“shreds”) signals of environmental forcing so that they are not merely masked but entirely lost. Signal shredding is analogous to modulated turbulence in fluid flows. We demonstrate that autogenic variations in sediment transport associated with sediment storage and release act as a kind of “morphodynamic turbulence”, with a temporal spectrum and finite-size cutoff similar to fluid turbulence. External signals are destroyed when their time and magnitude scales fall within the range of autogenic fluctuations. Sufficiently high-amplitide and/or long-period signals survive, albeit with superimposed noise. We show using several landscape models that autogenic sediment storage and release, and hence signal shredding, result from the ubiquitous presence of thresholds in sediment transport systems - for example, avalanching, landsliding, bed load transport, and river avulsion. We confirm the signal-shredding effect experimentally by imposing cyclical variations in sediment supply on a table-top rice pile. We suggest that Earth's sedimentary archives could be dominated by transport “noise” on time scales up to tens of thousands of years. This time scale range overlaps in particular with known climatic time scales, meaning that in many systems the physical signature of these signals may be lost. On the other hand, depositional patterns associated with autogenic dynamics may be relatively uninfluenced by high-frequency external processes, and hence statistically predictable.

Jerolmack, D. J.; Paola, C.; Martin, R.



Nonlinear fiber applications for ultrafast all-optical signal processing  

NASA Astrophysics Data System (ADS)

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.

Kravtsov, Konstantin


Charge-domain integrated circuits for signal processing  

NASA Astrophysics Data System (ADS)

A new class of integrated circuits called charge-domain devices has been developed for performing enhanced monolithic signal processing. All signal-processing operations are accomplished by splitting, routing, and combining charge packets, thus overcoming many of the limitations of alternative devices such as charge-coupled device (CCD) split-electrode transversal filters and switched capacitor filters. Charge manipulation techniques are described, which allow poles as well as zeroes of a transfer function to be implemented efficiently, leading to infinite impulse response monolithic filters suitable for high-frequency applications. Several test filters, including a narrow-band bandpass filter, have been demonstrated. The 8-pole bandpass filter exhibits a passband width of 1 percent of the clock frequency and over 70-dB stopband attenuation on a chip only 2.0 x 2.7 mm in size. Since only charge-coupled device delay-line-type operations are used, the device clock rate is only limited by the inherent charge transfer inefficiency. Clocking speeds of up to 15 MHz have been demonstrated using surface channel devices. These charge-domain devices are useful in applications ranging from radio IF to radar to video signal processing with a high level of integration achievable on a single charge-domain integrated circuit.

Vogelsong, T. L.; Tiemann, J. J.; Steckl, A. J.



Nonlinear signal processing using neural networks: Prediction and system modelling  

SciTech Connect

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

Lapedes, A.; Farber, R.



DSPSR: Digital Signal Processing Software for Pulsar Astronomy  

NASA Astrophysics Data System (ADS)

DSPSR is a high-performance, open-source, object-oriented, digital signal processing software library and application suite for use in radio pulsar astronomy. Written primarily in C++, the library implements an extensive range of modular algorithms that can optionally exploit both multiple-core processors and general-purpose graphics processing units. After over a decade of research and development, DSPSR is now stable and in widespread use in the community. This paper presents a detailed description of its functionality, justification of major design decisions, analysis of phase-coherent dispersion removal algorithms, and demonstration of performance on some contemporary microprocessor architectures.

van Straten, W.; Bailes, M.



DSPSR: Digital Signal Processing Software for Pulsar Astronomy  

NASA Astrophysics Data System (ADS)

dspsr is a high-performance, open-source, object-oriented, digital signal processing software library and application suite for use in radio pulsar astronomy. Written primarily in C++, the library implements an extensive range of modular algorithms that can optionally exploit both multiple-core processors and general-purpose graphics processing units. After over a decade of research and development, dspsr is now stable and in widespread use in the community. This paper presents a detailed description of its functionality, justification of major design decisions, analysis of phase-coherent dispersion removal algorithms, and demonstration of performance on some contemporary microprocessor architectures.

van Straten, W.; Bailes, M.



Power optimization in wearable biomedical systems: a signal processing perspective  

NASA Astrophysics Data System (ADS)

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

Ghasemzadeh, Hassan


Neural correlates of variations in event processing during learning in basolateral amygdala  

PubMed Central

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.

Roesch, Matthew R.; Calu, Donna J.; Esber, Guillem R.; Schoenbaum, Geoffrey



Processing the tort deterrent signal: a qualitative study.  


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

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



mfERG_LAB: Software for processing multifocal electroretinography signals.  


The multifocal electroretinography technique consists of performing sectorized light excitation of the retina and capturing the resulting evoked potential. This provides functional localized information about the state of the retinal neurons. Analysis of multifocal electroretinography signals can be used for diagnosing different types of optic neuropathies (glaucomatous, demyelinating and ischemic ethiology). In order to obtain a reliable diagnosis, it is necessary to apply advanced processing algorithms (morphological, frequency and time-frequency analysis, etc.) to the multifocal electroretinography signal. This paper presents a software application developed in MATLAB(®) (MathWorks Inc., MA) designed to perform advanced multifocal electroretinography signal analysis and classification. This intuitive application, mfERG_LAB, is used to plot the signals, apply various algorithms to them and present the data in an appropriate format. The application's computational power and modular structure make it suitable for use in clinical settings as a powerful and innovative diagnostic tool, as well as in research and teaching settings as a means of assessing new algorithms. PMID:22465639

Miguel, J M; Boquete, L; Ortega, S; Cordero, C Alén; Barea, R; Blanco, R



Neural Correlates of Impulse Control During Stop Signal Inhibition in Cocaine-Dependent Men  

Microsoft Academic Search

Altered impulse control is associated with substance use disorders, including cocaine dependence. We sought to identify the neural correlates of impulse control in abstinent male patients with cocaine dependence (PCD). Functional magnetic resonance imaging (fMRI) was conducted during a stop signal task that allowed trial-by-trial evaluation of response inhibition. Fifteen male PCD and 15 healthy control (HC) subjects, matched in

Chiang-shan Ray Li; Cong Huang; Peisi Yan; Zubin Bhagwagar; Verica Milivojevic; Rajita Sinha; C-SR Li



MRC performance for binary signals in Nakagami fading with general branch correlation  

Microsoft Academic Search

Exact expressions are derived for the performance of predetection maximal ratio combiner diversity reception with L correlated branches in Nakagami fading. Bit error rates are evaluated for both coherent and noncoherent binary phase-shift-keying and frequency-shift-keying signals, starting from the L-variate moment generating function of the random input power vector. The new formulation presented for the bit error rate, in which

Pierfrancesco Lombardo; Gennaro Fedele; Murli Mohan Rao



Classification of acousto-optic correlation signatures of spread spectrum signals using artificial neural networks  

Microsoft Academic Search

An attempt was made to determine if artificial neural networks (ANNs) can be trained to classify the correlation signatures of direct-sequence and frequency-hopped spread-spectrum signals. Secondary goals were to determine if network classification performance can be modeled with a conditional probability matrix; if the symmetry of the matrices can be controlled; and if using a majority vote rule over independently

John W. DeBerry; David M. Norman



Digital signal processing and numerical analysis for radar in geophysical applications  

NASA Astrophysics Data System (ADS)

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

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



Synchronized delta oscillations correlate with the resting-state functional MRI signal  

PubMed Central

Synchronized low-frequency spontaneous fluctuations of the functional MRI (fMRI) signal have recently been applied to investigate large-scale neuronal networks of the brain in the absence of specific task instructions. However, the underlying neural mechanisms of these fluctuations remain largely unknown. To this end, electrophysiological recordings and resting-state fMRI measurements were conducted in ?-chloralose-anesthetized rats. Using a seed-voxel analysis strategy, region-specific, anesthetic dose-dependent fMRI resting-state functional connectivity was detected in bilateral primary somatosensory cortex (S1FL) of the resting brain. Cortical electroencephalographic signals were also recorded from bilateral S1FL; a visual cortex locus served as a control site. Results demonstrate that, unlike the evoked fMRI response that correlates with power changes in the ? bands, the resting-state fMRI signal correlates with the power coherence in low-frequency bands, particularly the ? band. These data indicate that hemodynamic fMRI signal differentially registers specific electrical oscillatory frequency band activity, suggesting that fMRI may be able to distinguish the ongoing from the evoked activity of the brain.

Lu, Hanbing; Zuo, Yantao; Gu, Hong; Waltz, James A.; Zhan, Wang; Scholl, Clara A.; Rea, William; Yang, Yihong; Stein, Elliot A.



Time Reversal Signal Processing in Communications - A Feasibility Study  

SciTech Connect

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

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



Ramanujan sums for signal processing of low-frequency noise.  


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

Planat, Michel; Rosu, Haret; Perrine, Serge



Information processing and signal integration in bacterial quorum sensing  

NASA Astrophysics Data System (ADS)

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

Mehta, Pankaj



Oxytocin effects on neural correlates of self-referential processing.  


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 220-280ms (P2) during self- vs. valence-judgments. OT vs. placebo treatment tended to reduce the differential amplitude of a late positive potential at 520-1000ms (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

Liu, Yi; Sheng, Feng; Woodcock, Kate A; Han, Shihui



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


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

Patek, D R; Tompkins, W J



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

NASA Astrophysics Data System (ADS)

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.

Banik, Manik



Coherent detection and digital signal processing for fiber optic communications  

NASA Astrophysics Data System (ADS)

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

Ip, Ezra


Digital speckle correlation method based on wavelet-packet noise-reduction processing.  


Despite the advantages of being highly sensitive and nondestructive, the digital speckle correlation method (DSCM) may have difficulties in detecting tiny defects such as delaminations in multilayer ceramic capacitors. This is because the presence of background noise always complicates the data processing. We present a new algorithm, which employs the wavelet-packet noise-reduction process together with the improved DSCM, to improve data processing. Both the computational error and the noise are shown to be reduced successfully by this new algorithm. The accuracy (or precision) of the improved DSCM is increased after operation of the wavelet-packet noise-reduction process. The most important feature of this new algorithm is that it can extract a small hillock signal from a large noisy background in a DSCM deformation result. This helps to save time in the detection of tiny defects, such as delamination, in a miniaturized electronic component. PMID:18319947

Dai, X; Chan, Y C; So, A C



Biomedical signal processing (in four parts). Part 2. The frequency transforms and their inter-relationships.  


This is the second in a series of four tutorial papers on biomedical signal processing, and it concerns the relationships between commonly used frequency transforms. It begins with the Fourier series and Fourier transform for continuous time signals and extends these concepts for aperiodic discrete time data and then periodic discrete time data. The Laplace transform is discussed as an extension of the Fourier transform. The z-transform is introduced and the ideas behind the chirp-z transform are described. The equivalence between the time and frequency domains is described in terms of Parseval's theorem and the theory of convolution. The use of the FFT for fast convolution and fast correlation is described for both short recordings and long recordings that must be processed in sections. PMID:2016912

Challis, R E; Kitney, R I



Application of orthogonal ultrasonic signals and binaural processing for imaging of the environment  


Data acquisition rates in ultrasonic imaging systems are limited by the finite value of the speed of ultrasonic waves. In order to improve the imaging speed, it is proposed to perform simultaneous scanning of the environment in different directions. In order to avoid cross-talk between adjacent channels in different directions, different orthogonal signals are transmitted. Application of cross-correlation processing and non-linear iterative deconvolution enables the reliable separation of signals transmitted by different sources and reflected by multiple targets. The spatial positions of the targets are found using the data obtained after the non-linear deconvolution as the initial data for binaural or tri-aural processing. This approach has been exploited in ultrasonic sonar used for navigation of mobile robots. PMID:10829652

Kazys; Svilainis; Mazeika



Diffraction and signal processing experiments with a liquid crystal microdisplay  

NASA Astrophysics Data System (ADS)

In this work, we show some diffraction experiments performed with a liquid crystal display (LCD) that shows how useful this device can be to teach and experience diffraction optics and signal processing experiments. The LCD acts as a programmable pixelated diffractive mask. The Fourier spectrum of the image displayed in the LCD is visualized through a simple free propagation diffraction experiment. This optical system allows easy testing of different diffractive elements. As a demonstration we include experimental results with well-known diffractive elements like diffraction gratings or Fresnel lenses, and with more complicated elements like computer-generated holograms.

Martínez, José Luis; Moreno, Ignacio; Ahouzi, Esmail



Matching instrument design and signal processing for a scanning radiometer  

NASA Astrophysics Data System (ADS)

An account is given of the instrument design and signal processing features used by the 'Airborne Version of the Conical Scanning Radiometer' in order to minimize blurring and aliasing errors in radiation budget measurements. Attention is given to the interrelations among modulation transfer characteristics, optical chopping, scan patterns, and sampling rates; their effects on blurring and aliasing are then analyzed. A sophisticated algorithm was developed in order to achieve the retrieval of measured data at a chopper frequency lying below the regular Nyquist limit.

Bauche, Bernd; Hennings, Detlef


DSPSR: Digital Signal Processing Software for Pulsar Astronomy  

Microsoft Academic Search

DSPSR is a high-performance, open-source, object-oriented, digital signal\\u000aprocessing software library and application suite for use in radio pulsar\\u000aastronomy. Written primarily in C++, the library implements an extensive range\\u000aof modular algorithms that can optionally exploit both multiple-core processors\\u000aand general-purpose graphics processing units. After over a decade of research\\u000aand development, DSPSR is now stable and in widespread

W. van Straten; M. Bailes



A Random Walk into Optical Signal Processing and Integrated Optofluidics  

NASA Astrophysics Data System (ADS)

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.

Baylor, Martha-Elizabeth



Automatic signal processing of front monitor radar for tunneling machines  

SciTech Connect

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.

Sato, Toru [Kyoto Univ. (Japan). Dept. of Electronics and Communication; Takeda, Kenya [NTT Co. Ltd., Chiba (Japan); Nagamatsu, Takashi [Mitsubishi Heavy Industries, Ltd., Tokyo (Japan); Wakayama, Toshio [Mitsubishi Electric Corp., Kamakura, Kanagawa (Japan); Kimura, Iwane [Osaka Inst. of Tech., Hirakata, Osaka (Japan); Shinbo, Tetsuya [Komatsu Co. Ltd., Kanagawa (Japan)



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

NASA Astrophysics Data System (ADS)

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.

Boashash, Boualem; Boubchir, Larbi; Azemi, Ghasem



Comparison of Arithmetic Units in VLSI (Very Large Scale Integration) Signal Processing Systems.  

National Technical Information Service (NTIS)

Digital Signal Processing (DSP) is a term encompassing a variety of techniques for transforming digital samples of analog signals into samples of analog signals having more desirable characteristics. This paper is concerned only with DSP techniques which ...

H. M. Ahmed



Real-time fractal signal processing in the time domain  

NASA Astrophysics Data System (ADS)

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.

Hartmann, András; Mukli, Péter; Nagy, Zoltán; Kocsis, László; Hermán, Péter; Eke, András



Ultrawideband (UWB) impulse signal detection and processing issues  

Microsoft Academic Search

The author considers the detection, collection, and analysis of impulse-like time domain signals which meet the ultrawideband (UWB) definition. First, UWB impulse signal technical terminology and foreign work are reviewed. The fundamental collection differences between narrowband (sinusoid) and UWB (impulse-like) signals are discussed, and a comparison of the minimum detectable signal for the narrowband and UWB transient signals is presented.

Elizabeth C. Kisenwether



Bioluminescence imaging of Smad signaling in living mice shows correlation with excitotoxic neurodegeneration  

PubMed Central

The TGF-? signaling pathway is a key organizer of injury and immune responses, and recent studies suggest it fulfills critical roles in CNS function and maintenance. TGF-? receptor activation results in phosphorylation of Smad proteins, which subsequently translocate to the nucleus to regulate gene transcription by binding to Smad binding elements (SBE). Using SBE-luciferase reporter mice, we recently discovered that the brain has the highest Smad baseline activity of any major organ in the mouse, and we now demonstrate that this signal is primarily localized to pyramidal neurons of the hippocampus. In vivo excitatory stimulation with kainic acid (KA) resulted in an increase in luciferase activity and phosphorylated Smad2 (Smad2P), and nuclear translocation of Smad2P in hippocampal CA3 neurons correlated significantly with luciferase activity. Although this activation was most prominent at 24 h after KA administration in neurons, Smad2P immunoreactivity gradually increased in astrocytes and microglial cells at 3 and 5 days, consistent with reactive gliosis. Bioluminescence measured over the skull in living mice peaked at 12–72 h and correlated with the extent of microglial activation and pathological markers of neurodegeneration 5 days after injury. Treatment with the glutamate receptor antagonist MK-801 strongly reduced bioluminescence and pathology. These results show that Smad2 signaling is a sensitive marker of neuronal activation and CNS injury that can be used to monitor KA-induced neuronal degeneration. This and related mouse models may provide valuable tools to study mechanisms and treatments for neurodegeneration.

Luo, Jian; Lin, Amy H.; Masliah, Eliezer; Wyss-Coray, Tony



Neural correlates of quantity processing of numeral classifiers.  


Objective: Classifiers play an important role in describing the quantity information of objects. Few studies have been conducted to investigate the brain organization for quantity processing of classifiers. In the current study, we investigated whether activation of numeral classifiers was specific to the bilateral inferior parietal areas, which are believed to process numerical magnitude. Method: Using functional MRI, we explored the neural correlates of numeral classifiers, as compared with those of numbers, dot arrays, and nonquantity words (i.e., tool nouns). Results: Our results showed that numeral classifiers and tool nouns elicited greater activation in the left inferior frontal lobule and left middle temporal gyrus than did numbers and dot arrays, but numbers and dot arrays had greater activation in the middle frontal gyrus, precuneus, and the superior and inferior parietal lobule in the right hemisphere. No differences were found between numeral classifiers and tool nouns. Conclusion: The results suggest that quantity processing of numeral classifiers is independent of that of numbers and dot arrays, supporting the notation-dependent hypothesis of quantity processing. (PsycINFO Database Record (c) 2013 APA, all rights reserved). PMID:23937482

Cui, Jiaxin; Yu, Xiaodan; Yang, Hong; Chen, Chuansheng; Liang, Peipeng; Zhou, Xinlin



Neural correlates of lexical and sublexical processes in reading.  


The purpose of the present study was to compare the brain regions and systems that subserve lexical and sublexical processes in reading. In order to do so, three types of tasks were used: (i). silent reading of very high frequency regular words (lexical task); (ii). silent reading of nonwords (sublexical task); and, (iii). silent reading of very low frequency regular words (sublexical task). All three conditions were contrasted with a visual/phonological baseline condition. The lexical condition engaged primarily an area at the border of the left angular and supramarginal gyri. Activation found in this region suggests that this area may be involved in mapping orthographic-to-phonological whole word representations. Both sublexical conditions elicited significantly greater activation in the left inferior prefrontal gyrus. This region is thought to be associated with sublexical processes in reading such as grapheme-to-phoneme conversion, phoneme assembly and underlying verbal working memory processes. Activation in the left IFG was also associated with left superior and middle temporal activation. These areas are thought to be functionally correlated with the left IFG and to contribute to a phonologically based form of reading. The results as a whole demonstrate that lexical and sublexical processes in reading activate different regions within a complex network of brain structures. PMID:15010232

Joubert, Sven; Beauregard, Mario; Walter, Nathalie; Bourgouin, Pierre; Beaudoin, Gilles; Leroux, Jean-Maxime; Karama, Sherif; Lecours, André Roch



Characterization and matched-field processing localization of photoacoustic signals  

NASA Astrophysics Data System (ADS)

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

Yonak, Serdar Hakki



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

NASA Astrophysics Data System (ADS)

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

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



Analog signal processing for optical coherence imaging systems  

NASA Astrophysics Data System (ADS)

Optical coherence tomography (OCT) and optical coherence microscopy (OCM) are non-invasive optical coherence imaging techniques, which enable micron-scale resolution, depth resolved imaging capability. Both OCT and OCM are based on Michelson interferometer theory. They are widely used in ophthalmology, gastroenterology and dermatology, because of their high resolution, safety and low cost. OCT creates cross sectional images whereas OCM obtains en face images. In this dissertation, the design and development of three increasingly complicated analog signal processing (ASP) solutions for optical coherence imaging are presented. The first ASP solution was implemented for a time domain OCT system with a Rapid Scanning Optical Delay line (RSOD)-based optical signal modulation and logarithmic amplifier (Log amp) based demodulation. This OCT system can acquire up to 1600 A-scans per second. The measured dynamic range is 106dB at 200A-scan per second. This OCT signal processing electronics includes an off-the-shelf filter box with a Log amp circuit implemented on a PCB board. The second ASP solution was developed for an OCM system with synchronized modulation and demodulation and compensation for interferometer phase drift. This OCM acquired micron-scale resolution, high dynamic range images at acquisition speeds up to 45,000 pixels/second. This OCM ASP solution is fully custom designed on a perforated circuit board. The third ASP solution was implemented on a single 2.2 mm x 2.2 mm complementary metal oxide semiconductor (CMOS) chip. This design is expandable to a multiple channel OCT system. A single on-chip CMOS photodetector and ASP channel was used for coherent demodulation in a time domain OCT system. Cross-sectional images were acquired with a dynamic range of 76dB (limited by photodetector responsivity). When incorporated with a bump-bonded InGaAs photodiode with higher responsivity, the expected dynamic range is close to 100dB.

Xu, Wei


Brain Correlates of Mathematical Competence in Processing Mathematical Representations  

PubMed Central

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

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



Parametric design and correlational analyses help integrating fMRI and electrophysiological data during face processing.  


Face perception is typically associated with activation in the inferior occipital, superior temporal (STG), and fusiform gyri (FG) and with an occipitotemporal electrophysiological component peaking around 170 ms on the scalp, the N170. However, the relationship between the N170 and the multiple face-sensitive activations observed in neuroimaging is unclear. It has been recently shown that the amplitude of the N170 component monotonically decreases as gaussian noise is added to a picture of a face [Jemel et al., 2003]. To help clarify the sources of the N170 without a priori assumptions regarding their number and locations, ERPs and fMRI were recorded in five subjects in the same experiment, in separate sessions. We used a parametric paradigm in which the amplitude of the N170 was modulated by varying the level of noise in a picture, and identified regions where the percent signal change in fMRI correlated with the ERP data. N170 signals were observed for pictures of both cars and faces but were stronger for faces. A monotonic decrease with added noise was observed for the N170 at right hemisphere sites but was less clear on the left and occipital central sites. Correlations between fMRI signal and N170 amplitudes for faces were highly significant (P < 0.001) in bilateral fusiform gyrus and superior temporal gyrus. For cars, the strongest correlations were observed in the parahippocampal region and in the STG (P < 0.005). Besides contributing to clarify the spatiotemporal course of face processing, this study illustrates how ERP information may be used synergistically in fMRI analyses. Parametric designs may be developed further to provide some timing information on fMRI activity and help identify the generators of ERP signals. PMID:15275915

Horovitz, Silvina G; Rossion, Bruno; Skudlarski, Pawel; Gore, John C



The weak GPS signal parallel processing algorithm in dual-core based GPS software receiver  

Microsoft Academic Search

The basic GPS signal acquisition and several weak signal processing algorithms based on FFT is presented in this paper. Considering the sensitivity and the time consuming issues, a weak GPS signal parallel processing algorithm based on Duo-Core is proposed in the framework of a software GPS receiver. This method was developed for the acquisition of weak signals without a priori

Yongrong Sun; Jianfeng Miao; Wu Chen; Jianye Liu



Chemical library screening for WNK signalling inhibitors using fluorescence correlation spectroscopy.  


WNKs (with-no-lysine kinases) are the causative genes of a hereditary hypertensive disease, PHAII (pseudohypoaldosteronism type II), and form a signal cascade with OSR1 (oxidative stress-responsive 1)/SPAK (STE20/SPS1-related proline/alanine-rich protein kinase) and Slc12a (solute carrier family 12) transporters. We have shown that this signal cascade regulates blood pressure by controlling vascular tone as well as renal NaCl excretion. Therefore agents that inhibit this signal cascade could be a new class of antihypertensive drugs. Since the binding of WNK to OSR1/SPAK kinases was postulated to be important for signal transduction, we sought to discover inhibitors of WNK/SPAK binding by screening chemical compounds that disrupt the binding. For this purpose, we developed a high-throughput screening method using fluorescent correlation spectroscopy. As a result of screening 17000 compounds, we discovered two novel compounds that reproducibly disrupted the binding of WNK to SPAK. Both compounds mediated dose-dependent inhibition of hypotonicity-induced activation of WNK, namely the phosphorylation of SPAK and its downstream transporters NKCC1 (Na/K/Cl cotransporter 1) and NCC (NaCl cotransporter) in cultured cell lines. The two compounds could be the promising seeds of new types of antihypertensive drugs, and the method that we developed could be applied as a general screening method to identify compounds that disrupt the binding of two molecules. PMID:23981180

Mori, Takayasu; Kikuchi, Eriko; Watanabe, Yuko; Fujii, Shinya; Ishigami-Yuasa, Mari; Kagechika, Hiroyuki; Sohara, Eisei; Rai, Tatemitsu; Sasaki, Sei; Uchida, Shinichi



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

NASA Astrophysics Data System (ADS)

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

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



Neural correlates of feedback processing in obsessive-compulsive disorder.  


Obsessive-compulsive disorder (OCD) patients show hyperactive performance monitoring when monitoring their own actions. Hyperactive performance monitoring is related to OCD symptomatology, like the unflexibility of compulsive behaviors, and was suggested as a potential endophenotype for the disorder. However, thus far the functioning of the performance monitoring system in OCD remains unclear in processes where performance is not monitored in one's own actions internally, but through external feedback during learning. The present study investigated whether electrocortical indicators of feedback processing are hyperactive, and whether feedback-guided learning is compromised in OCD. A modified deterministic four-choice object reversal learning task was used that required recurrent feedback-based behavioral adjustment in response to changing reward contingencies. Electrophysiological correlates of feedback processing (i.e. feedback-related negativity [FRN] and P300) were measured in 25 OCD patients and 25 matched healthy comparison subjects. Deficits in behavioral adjustment were found in terms of higher error rates of OCD patients in response to negative feedback. Whereas the FRN was unchanged for reversal negative feedback, it was reduced for negative feedback that indicated that a newly selected stimulus was still incorrect. The observed FRN reduction suggests attenuated monitoring of feedback during the learning process in OCD potentially contributing to a deficit in adaptive behavior reflected in obsessive thoughts and actions. The reduction of FRN amplitudes contrasts with overactive performance monitoring of self-generated errors. Nevertheless, the findings contribute to the theoretical framework of performance monitoring, suggesting a dissociation of processing systems for actions and feedback with specific alterations of these two systems in OCD. PMID:23421527

Endrass, Tanja; Koehne, Svenja; Riesel, Anja; Kathmann, Norbert



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

NASA Astrophysics Data System (ADS)

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

Kosal, Haluk; Skoog, Ronald A.



Electrophysiological correlates of morphological processing in Chinese compound word recognition  

PubMed Central

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

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



Electrophysiological correlates of morphological processing in Chinese compound word recognition.  


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

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



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

SciTech Connect

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

Samedov, V. V. [National Research Nuclear Univ. (Moscow Engineering Physics Inst.), 31, Kashirskoye Shosse, 115409, Moscow (Russian Federation)



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

NASA Astrophysics Data System (ADS)

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

Vardhan, Harsh; Roy Mahapatra, D.



Intensity correlations and dynamical processes in cavity quantum electrodynamics  

NASA Astrophysics Data System (ADS)

Dynamical processes in a cavity quantum electrodynamical system are studied with two-level atoms in an optical cavity. The initial condition for the dynamics is either an internal or external step. The internal step is caused by the escape of a photon from the system, and the external step by a change in the driving intensity. After either step there is an oscillatory exchange of energy as the system reaches steady state. The frequency of oscillation decreases with increasing input intensity. The experimental results are compared quantitatively to theoretical calculations and to transmission spectroscopy measurements. After the external step, the output intensity oscillates to a value many times larger than the steady state. Response to the internal step is measured by photon correlations. Antibunched light with sub-Poissonian statistics is observed. Antibunched light with super-Poissonian statistics, as well as bunched light with larger correlations for non-zero times are also observed. All three effects are nonclassical. The latter two have not previously been observed, and violate the Schwarz inequality.

Mielke, Stephen Lawrence



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

NASA Astrophysics Data System (ADS)

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

Teich, Malvin C.



SPECIAL ISSUE ON OPTICAL PROCESSING OF INFORMATION: Optical signal-processing systems based on anisotropic media  

NASA Astrophysics Data System (ADS)

Partially coherent optical systems for signal processing are considered. The transfer functions are formed in these systems by interference of polarised light transmitted by an anisotropic medium. It is shown that such systems can perform various integral transformations of both optical and electric signals, in particular, two-dimensional Fourier and Fresnel transformations, as well as spectral analysis of weak light sources. It is demonstrated that such systems have the highest luminosity and vibration immunity among the systems with interference formation of transfer functions. An experimental investigation is reported of the application of these systems in the processing of signals from a linear hydroacoustic antenna array, and in measurements of the optical spectrum and of the intrinsic noise.

Kiyashko, B. V.



Tracking Radar Advanced Signal Processing and Computing for Kwajalein Atoll (KA) Application.  

National Technical Information Service (NTIS)

Two means are examined whereby the operations of KMR during mission execution may be improved through the introduction of advanced signal processing techniques. In the first approach, the addition of real time coherent signal processing technology to the ...

S. D. Cottrill



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

PubMed Central

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

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



The Vector, Signal, and Image Processing Library (VSIPL): an Open Standard for Astronomical Data Processing  

NASA Astrophysics Data System (ADS)

The Vector/Signal/Image Processing Library (VSIPL) is a DARPA initiated effort made up of industry, government and academic representatives who have defined an industry standard API for vector, signal, and image processing primitives for real-time signal processing on high performance systems. VSIPL supports a wide range of data types (int, float, complex, ...) and layouts (vectors, matrices and tensors) and is ideal for astronomical data processing. The VSIPL API is intended to serve as an open, vendor-neutral, industry standard interface. The object-based VSIPL API abstracts the memory architecture of the underlying machine by using the concept of memory blocks and views. Early experiments with VSIPL code conversions have been carried out by the High Performance Computing Program team at the UCSD. Commercially, several major vendors of signal processors are actively developing implementations. VSIPL has also been explicitly required as part of a recent Rome Labs teraflop procurement. This poster presents the VSIPL API, its functionality and the status of various implementations.

Kepner, J. V.; Janka, R. S.; Lebak, J.; Richards, M. A.



Temporally selective processing of communication signals by auditory midbrain neurons  

PubMed Central

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

Christensen-Dalsgaard, Jakob; Kelley, Darcy B.



Direct observation of the dynamic process underlying allosteric signal transmission.  


Allosteric regulation is an effective mechanism of control in biological processes. In allosteric proteins a signal originating at one site in the molecule is communicated through the protein structure to trigger a specific response at a remote site. Using NMR relaxation dispersion techniques we directly observe the dynamic process through which the KIX domain of CREB binding protein communicates allosteric information between binding sites. KIX mediates cooperativity between pairs of transcription factors through binding to two distinct interaction surfaces in an allosteric manner. We show that binding the activation domain of the mixed lineage leukemia (MLL) transcription factor to KIX induces a redistribution of the relative populations of KIX conformations toward a high-energy state in which the allosterically activated second binding site is already preformed, consistent with the Monod-Wyman-Changeux (WMC) model of allostery. The structural rearrangement process that links the two conformers and by which allosteric information is communicated occurs with a time constant of 3 ms at 27 degrees C. Our dynamic NMR data reveal that an evolutionarily conserved network of hydrophobic amino acids constitutes the pathway through which information is transmitted. PMID:19203263

Brüschweiler, Sven; Schanda, Paul; Kloiber, Karin; Brutscher, Bernhard; Kontaxis, Georg; Konrat, Robert; Tollinger, Martin



REVIEW ARTICLE: Spectrophotometric applications of digital signal processing  

NASA Astrophysics Data System (ADS)

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

Morawski, Roman Z.



Neurological Tremor: Sensors, Signal Processing and Emerging Applications  

PubMed Central

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

Grimaldi, Giuliana; Manto, Mario



A signal processing method to explore similarity in protein flexibility.  


Understanding mechanisms of protein flexibility is of great importance to structural biology. The ability to detect similarities between proteins and their patterns is vital in discovering new information about unknown protein functions. A Distance Constraint Model (DCM) provides a means to generate a variety of flexibility measures based on a given protein structure. Although information about mechanical properties of flexibility is critical for understanding protein function for a given protein, the question of whether certain characteristics are shared across homologous proteins is difficult to assess. For a proper assessment, a quantified measure of similarity is necessary. This paper begins to explore image processing techniques to quantify similarities in signals and images that characterize protein flexibility. The dataset considered here consists of three different families of proteins, with three proteins in each family. The similarities and differences found within flexibility measures across homologous proteins do not align with sequence-based evolutionary methods. PMID:21197478

Vasilache, Simina; Mirshahi, Nazanin; Ji, Soo-Yeon; Mottonen, James; Jacobs, Donald J; Najarian, Kayvan



A Signal Processing Method to Explore Similarity in Protein Flexibility  

PubMed Central

Understanding mechanisms of protein flexibility is of great importance to structural biology. The ability to detect similarities between proteins and their patterns is vital in discovering new information about unknown protein functions. A Distance Constraint Model (DCM) provides a means to generate a variety of flexibility measures based on a given protein structure. Although information about mechanical properties of flexibility is critical for understanding protein function for a given protein, the question of whether certain characteristics are shared across homologous proteins is difficult to assess. For a proper assessment, a quantified measure of similarity is necessary. This paper begins to explore image processing techniques to quantify similarities in signals and images that characterize protein flexibility. The dataset considered here consists of three different families of proteins, with three proteins in each family. The similarities and differences found within flexibility measures across homologous proteins do not align with sequence-based evolutionary methods.

Vasilache, Simina; Mirshahi, Nazanin; Ji, Soo-Yeon; Mottonen, James; Jacobs, Donald J.; Najarian, Kayvan



Two-dimensional signal processing for regional seismic event identification  

NASA Astrophysics Data System (ADS)

The objective of this research was to develop a methodology for regional seismic event identification which utilizes 2-dimensional signal processing and treats the seismogram as an image. The motivation for this research comes from the observation that the spectral features which distinguish quarry explosions from earthquakes can be seen throughout the entire seismogram. These features, which include spectral banding, are apparent in the time-frequency (TF) representation of the seismogram. We parameterized the TF representation by computing the wavenumber spectrum of the image and fitting this to a stochastic surface model developed to characterize bathymetric surfaces. Five model parameters control image features such as lineations, spatial orientation, characteristics lengths, and roughness of the surface.

Pulli, Jay J.; Dysart, Paul S.



On adaptive robustness approach to Anti-Jam signal processing  

NASA Astrophysics Data System (ADS)

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

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


Multiscale signal processing and shape analysis for an inverse SAR imaging system  

Microsoft Academic Search

The great challenge in signal processing is to devise computationally efficient and statistically optimal algorithms for estimating signals from noisy background and understanding their contents. This thesis treats the problem of multiscale signal processing and shape analysis for an Inverse Synthetic Aperture Radar (ISAR) imaging system. To address some of the limitations of conventional techniques in radar image processing, an

Yun He



PetaOp\\/Second FPGA Signal Processing for SETI and Radio Astronomy  

Microsoft Academic Search

Our group, the Center for Astronomy Signal Processing and Electronics Research (CASPER), seeks to speed the development of radio astronomy signal processing instrumentation by designing and demonstrating a scalable, upgradeable, FPGA-based computing platform and software design methodology that targets a range of realtime radio telescope signal processing applications. This project relies on a small number of modular, connectible hardware components

Aaron Parsons; Donald Backer; Chen Chang; Daniel Chapman; Henry Chen; Patrick Crescini; Christina de Jesus; C. Dick; P. Droz; D. MacMahon; K. Meder; J. Mock; V. Nagpal; B. Nikolic; A. Parsa; B. Richards; A. Siemion; J. Wawrzynek; D. Werthimer; M. Wright



PetaOp\\/Second FPGA Signal Processing for SETI and Radio Astronomy  

Microsoft Academic Search

Our group, the Center for Astronomy Signal Processing and Electronics Research (CASPER), seeks to speed the development of radio astronomy signal process- ing instrumentation by designing and demonstrating a scal- able, upgradeable, FPGA-based computing platform and software design methodology that targets a range of real- time radio telescope signal processing applications. This project relies on a small number of modular,

Aaron Parsons; Donald Backer; Chen Chang; Daniel Chapman; Henry Chen; Patrick Crescini; Christina de Jesus; Chris Dick; Pierre Droz; David MacMahon; Kirsten Meder; Jeff Mock; Vinayak Nagpal; Borivoje Nikolic; Arash Parsa; Brian Richards; Andrew Siemion; John Wawrzynek; Dan Werthimer; Melvyn Wright



Sparse multiple kernel learning for signal processing applications.  


In many signal processing applications, grouping of features during model development and the selection of a small number of relevant groups can be useful to improve the interpretability of the learned parameters. While a lot of work based on linear models has been reported to solve this problem, in the last few years, multiple kernel learning has come up as a candidate to solve this problem in nonlinear models. Since all of the multiple kernel learning algorithms to date use convex primal problem formulations, the kernel weights selected by these algorithms are not strictly the sparsest possible solution. The main reason for using a convex primal formulation is that efficient implementations of kernel-based methods invariably rely on solving the dual problem. This work proposes the use of an additional log-based concave penalty term in the primal problem to induce sparsity in terms of groups of parameters. A generalized iterative learning algorithm, which can be used with a linear combination of this concave penalty term with other penalty terms, is given for model parameter estimation in the primal space. It is then shown that a natural extension of the method to nonlinear models using the "kernel trick" results in a new algorithm, called Sparse Multiple Kernel Learning (SMKL), which generalizes group-feature selection to kernel selection. SMKL is capable of exploiting existing efficient single kernel algorithms while providing a sparser solution in terms of the number of kernels used as compared to the existing multiple kernel learning framework. A number of signal processing examples based on the use of mass spectra for cancer detection, hyperspectral imagery for land cover classification, and NIR spectra from wheat, fescue grass, and diesel are given to highlight the ability of SMKL to achieve a very high accuracy with a very few kernels. PMID:20299705

Subrahmanya, Niranjan; Shin, Yung C



Signal processing approaches to radio frequency interference (RFI) suppression  

NASA Astrophysics Data System (ADS)

Ultra-wideband radar (UWB) has been shown to be among the most powerful techniques available for underground and obscured object detection. The value of such systems is that they combine the penetration enhancement associated with VHF/UHF (and lower) frequencies with the resolution of wide absolute bandwidth. Such systems necessarily make use of much of the frequency spectrum already in heavy use by other services, such as television and mobile communications. Although this spectral overlap provides occasion for adverse consequences in both directions, to date the principal consequence has been often-severe impact on UWB radar measurements. Even in remote locations, the average interference power often exceeds receiver noise by many dB, becoming the limiting factor on system sensitivity. Nor are UWB radar designers free to overcome this interference by increasing radar power, since regulatory sanction for UWB operation will depend on maintaining sufficiently low spectral power densities to assure that other, prior, services are not appreciably degraded. Given the importance of radio frequency interference (RFI) on practical ultrawide band ground penetrating radar systems, it is important to consider how and to what extent the effects of RFI noise may be reduced. The overall problem of RFI and its impacts will be described and several signal processing approaches to removal of RFI will be discussed. These include spectral estimation and coherent subtraction algorithms and various filter approaches, which have been developed and applied by the signal processing community in other contexts. These methods will be applied to several different real-world experimental data sets, and quantitative measures of the effectiveness of each of these algorithms in removing RFI noise will be presented. Although computationally-intensive, most of the techniques to be described achieve substantial increases in S/RFI without requiring concomitant increases in radar average power.

Braunstein, Matthew; Ralston, James M.; Sparrow, David A.



Multimodal neuroimaging dissociates hemodynamic and electrophysiological correlates of error processing  

PubMed Central

Recognizing errors and adjusting responses are fundamental to adaptive behavior. The error-related negativity (ERN) and error-related functional MRI (fMRI) activation of the dorsal anterior cingulate cortex (dACC) index these processes and are thought to reflect the same neural mechanism. In the present study, we evaluated this hypothesis. Although errors elicited robust dACC activation using fMRI, combined electroencephalography and magnetoencephalography data localized the ERN to the posterior cingulate cortex (PCC). ERN amplitude correlated with fMRI activation in both the PCC and dACC, and these two regions showed coordinated activity based on functional connectivity MRI. Finally, increased microstructural integrity of the posterior cingulum bundle, as measured by diffusion tensor imaging, predicted faster error correction. These findings suggest that the PCC generates the ERN and communicates with the dACC to subserve error processing. They challenge current models that view fMRI activation of the dACC as the hemodynamic reflection of the ERN.

Agam, Yigal; Hamalainen, Matti S.; Lee, Adrian K. C.; Dyckman, Kara A.; Friedman, Jesse S.; Isom, Marlisa; Makris, Nikos; Manoach, Dara S.



The level of CD147 expression correlates with cyclophilin-induced signalling and chemotaxis  

PubMed Central

Background Previous studies identified CD147 as the chemotactic receptor on inflammatory leukocytes for extracellular cyclophilins (eCyp). However, CD147 is not known to associate with signal transducing molecules, so other transmembrane proteins, such as proteoglycans, integrins, and CD98, were suggested as receptor or co-receptor for eCyp. CD147 is ubiquitously expressed on many cell types, but relationship between the level of CD147 expression and cellular responses to eCyp has never been analyzed. Given the role of eCyp in pathogenesis of many diseases, it is important to know whether cellular responses to eCyp are regulated at the level of CD147 expression. Results Here, we manipulated CD147 expression levels on HeLa cells using RNAi and investigated the signalling and chemotactic responses to eCypA. Both Erk activation and chemotaxis correlated with the level of CD147 expression, with cells exhibiting low level expression being practically unresponsive to eCypA. Conclusions Our results provide the first demonstration of a chemotactic response of HeLa cells to eCypA, establish a correlation between the level of CD147 expression and the magnitude of cellular responses to eCypA, and indicate that CD147 may be a limiting factor in the receptor complex determining cyclophilin-induced Erk activation and cell migration.



Signal transduction via the interleukin-4 receptor and its correlation with atopy.  


IL-4 and IL-13 are unique cytokines, in that they induce IgE synthesis in B cells and TH2 type differentiation in T cells. Both cytokines exert their biological activities by binding to their functional receptors on target cells. These receptors are thought to be composed as heterodimers, both having the IL-4R alpha chain (IL-4Ralpha) as a component. Among the signal-transducing molecules of IL-4 and IL-13, Stat6, which is activated by these cytokines and recruits to IL-4Ralpha, is essential for the biological activities of these cytokines. Atopy is an inherited tendency, underlying asthma, rhinitis, and eczema, and generating high non-specific IgE and/or high specific IgE against common antigens. Based on information on the molecular mechanism of the signal transduction of IL-4 and IL-13 and on some genetic studies, IL-4Ralpha was assumed to be one gene giving rise to atopy. One polymorphism existing in the IL-4Ralpha gene, Ile50Val, is verified to correlate with atopy by both genetic and functional aspects. On the contrary, the correlation between another polymorphism on the IL-4Ralpha gene, Arg551Gln, and atopy is still controversial. The strategy used in these studies should lead to identification of other genes involved in atopy. PMID:9864378

Izuhara, K; Shirakawa, T



Variation, Signal, and Noise in Cerebellar Sensory-Motor Processing for Smooth-Pursuit Eye Movements  

PubMed Central

Neural responses are variable, yet motor performance can be quite precise. To ask how neural signal and noise are processed in the brain during sensory–motor behavior, we have evaluated the trial-by-trial variation of Purkinje cell (PC) activity in the floccular complex of the cerebellum, an intermediate stage in the neural circuit for smooth-pursuit eye movements. We find strong correlations between small trial-by-trial variations in the simple spike activity of individual PCs and the eye movements at the initiation of pursuit. The correlation is lower but still present during steady-state pursuit. Recordings from a few pairs of PCs verified the predictions of a model of the PC population, that there is a transition from highly covariant PC activity during movement initiation to more independent activity later on. Application to the data of a theoretical and computational analysis suggests that variation in pursuit initiation arises mostly from variation in visual motion signals that provide common inputs to the PC population. Variation in eye movement during steady-state pursuit can be attributed primarily to signal-dependent motor noise that arises downstream from PCs.

Medina, Javier F.; Lisberger, Stephen G.



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

Microsoft Academic Search

Phase-correlated reconstruction is commonly used in computed tomography (CT)-based cardiac imaging. Alternatively to the commonly\\u000a used ECG, the raw data-based kymogram function can be used as a synchronization signal. We used raw data of 100 consecutive\\u000a patient exams to compare the performance of kymogram function to the ECG signal. For objective validation the correlation\\u000a of the ECG and the kymogram

Dirk Ertel; Tobias Pflederer; Stephan Achenbach; Marc Kachelrieß; Peter Steffen; Willi A. Kalender



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

PubMed Central

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

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



Conjunctive processing of locomotor signals by the ventral tegmental area neuronal population.  


The ventral tegmental area (VTA) plays an essential role in reward and motivation. How the dopamine (DA) and non-DA neurons in the VTA engage in motivation-based locomotor behaviors is not well understood. We recorded activity of putative DA and non-DA neurons simultaneously in the VTA of awake mice engaged in motivated voluntary movements such as wheel running. Our results revealed that VTA non-DA neurons exhibited significant rhythmic activity that was correlated with the animal's running rhythms. Activity of putative DA neurons also correlated with the movement behavior, but to a lesser degree. More importantly, putative DA neurons exhibited significant burst activation at both onset and offset of voluntary movements. These findings suggest that VTA DA and non-DA neurons conjunctively process locomotor-related motivational signals that are associated with movement initiation, maintenance and termination. PMID:21304590

Wang, Dong V; Tsien, Joe Z



Correlation Between X-ray And Microwave (sz) Signals From The Warm-hot Intergalactic Medium  

NASA Astrophysics Data System (ADS)

A large fraction of the low redshift baryons is believed to reside in a warm-hot filamentary gas in the intergalactic medium (WHIM). In the past we have successfully used XMM-Newton data to identify and characterize the WHIM angular signature using the autocorrelation function [Galeazzi 2009, 695, 1127]. Using the output of large scale hydrodynamic simulations we have also investigated the correlation between low energy X-ray emission and SZ effect from WHIM filaments. The largest of the current SZ surveys (with the South Pole Telescope [Ruhl 2004, Proc. SPIE, 5498, 11] and the Atacama Cosmology Telescope [Kosowsky 2004, NAR 47, 939; 2006, NAR 50, 969]) are mapping hundreds of square degrees at arcminute resolution at bands in 100-300 GHz, and have started identifying clusters detected by their SZ signature alone [e.g. Staniszewski 2009, ApJ, 701,32; Hincks 2009, arXiv:0907.0461]. Although the bulk of the total luminosity in the SZ effect is associated with collapsed structures like clusters, our work indicates that a significant fraction comes from unbound objects, mostly from overdense regions, like the WHIM. Due to the unique emission mechanism, the X-ray and SZ correlation provides additional constraints on the structure of the intergalactic gas. Adopting an adiabatic, polytropic model the SZ signal goes as ne1.2, compared with the x-ray emission that goes roughly as ne2 (slightly modified by the cooling function). In this paper we will discuss the result of our investigation on the correlation between X-ray emission and SZ signals and the implications for current X-ray and SZ observatories. We will also present our preliminary applications using actual data.

Galeazzi, Massimiliano; Gupta, A.; Huffenberger, K.; Ursino, E.



Cross-correlation time-frequency analysis for multiple EMG signals in Parkinson’s disease: a wavelet approach  

Microsoft Academic Search

Using a wavelet analysis approach, it is possible to investigate better the transient and intermittent behavior of multiple electromyographic (EMG) signals during ballistic movements in Parkinsonian patients. In particular, a wavelet cross-correlation analysis on surface signals of two different shoulder muscles allows us to evidence the related unsteady and synchronization characteristics. With a suitable global parameter extracted from local wavelet

Gennaro De Michele; Stefano Sello; Maria Chiara Carboncini; Bruno Rossi; Soo-Kyung Strambi



Study of the correlation dimension of ECG signals based on MIT-BIH Arrhythmia Data Base ECGs  

Microsoft Academic Search

The correlation dimensions of random noise and electrocardiograms of both normal and sick subjects have been analyzed and compared. The noisy signal has been obtained by using the random function of a DEC VAX computer; ECG data have been obtained from the MIT-BIH Arrhythmia Data Base. It was expected that a lower dimensionality of the ECG signal would be obtained

A. Casaleggio; M. Morando; S. Pestelli; S. Ridella



Signal Processing and Characterization of the Audio Evoked Cortical Response.  

National Technical Information Service (NTIS)

The audio evoked cortical response to stimuli consisting of audio 'clicks' of varied frequency was analyzed. Analysis of the encephalogram was accomplished through the use of a computer based signal processor which used signal averaging as the primary pro...

R. E. McWey



Membrane Dynamics Correlate with Formation of Signaling Clusters during Cell Spreading  

PubMed Central

The morphology and duration of contacts between cells and adhesive surfaces play a key role in several biological processes, such as cell migration, cell differentiation, and the immune response. The interaction of receptors on the cell membrane with ligands on the adhesive surface leads to triggering of signaling pathways, which allow cytoskeletal rearrangement, and large-scale deformation of the cell membrane, which allows the cell to spread over the substrate. Despite numerous studies of cell spreading, the nanometer-scale dynamics of the membrane during formation of contacts, spreading, and initiation of signaling are not well understood. Using interference reflection microscopy, we study the kinetics of cell spreading at the micron scale, as well as the topography and fluctuations of the membrane at the nanometer scale during spreading of Jurkat T cells on antibody-coated substrates. We observed two modes of spreading, which were characterized by dramatic differences in membrane dynamics and topography. Formation of signaling clusters was closely related to the movement and morphology of the membrane in contact with the activating surface. Our results suggest that cell membrane morphology may be a critical constraint on signaling at the cell-substrate interface.

Lam Hui, King; Wang, Chenlu; Grooman, Brian; Wayt, Jessica; Upadhyaya, Arpita



Membrane dynamics correlate with formation of signaling clusters during cell spreading.  


The morphology and duration of contacts between cells and adhesive surfaces play a key role in several biological processes, such as cell migration, cell differentiation, and the immune response. The interaction of receptors on the cell membrane with ligands on the adhesive surface leads to triggering of signaling pathways, which allow cytoskeletal rearrangement, and large-scale deformation of the cell membrane, which allows the cell to spread over the substrate. Despite numerous studies of cell spreading, the nanometer-scale dynamics of the membrane during formation of contacts, spreading, and initiation of signaling are not well understood. Using interference reflection microscopy, we study the kinetics of cell spreading at the micron scale, as well as the topography and fluctuations of the membrane at the nanometer scale during spreading of Jurkat T cells on antibody-coated substrates. We observed two modes of spreading, which were characterized by dramatic differences in membrane dynamics and topography. Formation of signaling clusters was closely related to the movement and morphology of the membrane in contact with the activating surface. Our results suggest that cell membrane morphology may be a critical constraint on signaling at the cell-substrate interface. PMID:22500752

Lam Hui, King; Wang, Chenlu; Grooman, Brian; Wayt, Jessica; Upadhyaya, Arpita



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

PubMed Central

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

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



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

NASA Astrophysics Data System (ADS)

Detrended fluctuation analysis (DFA) is an improved method of classical fluctuation analysis for nonstationary