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

PubMed

Fujita, Ichiro; Doi, Takahiro

2016-06-19

Binocular disparity is detected in the primary visual cortex by a process similar to calculation of local cross-correlation between left and right retinal images. As a consequence, correlation-based neural signals convey information about false disparities as well as the true disparity. The false responses in the initial disparity detectors are eliminated at later stages in order to encode only disparities of the features correctly matched between the two eyes. For a simple stimulus configuration, a feed-forward nonlinear process can transform the correlation signal into the match signal. For human observers, depth judgement is determined by a weighted sum of the correlation and match signals rather than depending solely on the latter. The relative weight changes with spatial and temporal parameters of the stimuli, allowing adaptive recruitment of the two computations under different visual circumstances. A full transformation from correlation-based to match-based representation occurs at the neuronal population level in cortical area V4 and manifests in single-neuron responses of inferior temporal and posterior parietal cortices. Neurons in area V5/MT represent disparity in a manner intermediate between the correlation and match signals. We propose that the correlation and match signals in these areas contribute to depth perception in a weighted, parallel manner.This article is part of the themed issue 'Vision in our three-dimensional world'. © 2016 The Author(s).

Nonlinear Transfer of Signal and Noise Correlations in Cortical Networks

PubMed Central

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

2015-01-01

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

Dual-process theory and signal-detection theory of recognition memory.

PubMed

Wixted, John T

2007-01-01

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 of recollection and familiarity. However, in recent years, a substantial literature has accumulated directly contrasting the signal-detection model against the threshold/detection model, and that literature is almost unanimous in its endorsement of signal-detection theory. A dual-process version of signal-detection theory implies that individual recognition decisions are not process pure, and it suggests new ways to investigate the brain correlates of recognition memory. ((c) 2007 APA, all rights reserved).

Theory and Measurement of Signal-to-Noise Ratio in Continuous-Wave Noise Radar.

PubMed

Stec, Bronisław; Susek, Waldemar

2018-05-06

Determination of the signal power-to-noise power ratio on the input and output of reception systems is essential to the estimation of their quality and signal reception capability. This issue is especially important in the case when both signal and noise have the same characteristic as Gaussian white noise. This article considers the problem of how a signal-to-noise ratio is changed as a result of signal processing in the correlation receiver of a noise radar in order to determine the ability to detect weak features in the presence of strong clutter-type interference. These studies concern both theoretical analysis and practical measurements of a noise radar with a digital correlation receiver for 9.2 GHz bandwidth. Firstly, signals participating individually in the correlation process are defined and the terms signal and interference are ascribed to them. Further studies show that it is possible to distinguish a signal and a noise on the input and output of a correlation receiver, respectively, when all the considered noises are in the form of white noise. Considering the above, a measurement system is designed in which it is possible to represent the actual conditions of noise radar operation and power measurement of a useful noise signal and interference noise signals—in particular the power of an internal leakage signal between a transmitter and a receiver of the noise radar. The proposed measurement stands and the obtained results show that it is possible to optimize with the use of the equipment and not with the complex processing of a noise signal. The radar parameters depend on its prospective application, such as short- and medium-range radar, ground-penetrating radar, and through-the-wall detection radar.

Background Noise Reduction Using Adaptive Noise Cancellation Determined by the Cross-Correlation

NASA Technical Reports Server (NTRS)

Spalt, Taylor B.; Brooks, Thomas F.; Fuller, Christopher R.

2012-01-01

Background noise due to flow in wind tunnels contaminates desired data by decreasing the Signal-to-Noise Ratio. The use of Adaptive Noise Cancellation to remove background noise at measurement microphones is compromised when the reference sensor measures both background and desired noise. The technique proposed modifies the classical processing configuration based on the cross-correlation between the reference and primary microphone. Background noise attenuation is achieved using a cross-correlation sample width that encompasses only the background noise and a matched delay for the adaptive processing. A present limitation of the method is that a minimum time delay between the background noise and desired signal must exist in order for the correlated parts of the desired signal to be separated from the background noise in the crosscorrelation. A simulation yields primary signal recovery which can be predicted from the coherence of the background noise between the channels. Results are compared with two existing methods.

Correlative weighted stacking for seismic data in the wavelet domain

USGS Publications Warehouse

Zhang, S.; Xu, Y.; Xia, J.; ,

2004-01-01

Horizontal stacking plays a crucial role for modern seismic data processing, for it not only compresses random noise and multiple reflections, but also provides a foundational data for subsequent migration and inversion. However, a number of examples showed that random noise in adjacent traces exhibits correlation and coherence. The average stacking and weighted stacking based on the conventional correlative function all result in false events, which are caused by noise. Wavelet transform and high order statistics are very useful methods for modern signal processing. The multiresolution analysis in wavelet theory can decompose signal on difference scales, and high order correlative function can inhibit correlative noise, for which the conventional correlative function is of no use. Based on the theory of wavelet transform and high order statistics, high order correlative weighted stacking (HOCWS) technique is presented in this paper. Its essence is to stack common midpoint gathers after the normal moveout correction by weight that is calculated through high order correlative statistics in the wavelet domain. Synthetic examples demonstrate its advantages in improving the signal to noise (S/N) ration and compressing the correlative random noise.

Processing of Antenna-Array Signals on the Basis of the Interference Model Including a Rank-Deficient Correlation Matrix

NASA Astrophysics Data System (ADS)

Rodionov, A. A.; Turchin, V. I.

2017-06-01

We propose a new method of signal processing in antenna arrays, which is called the Maximum-Likelihood Signal Classification. The proposed method is based on the model in which interference includes a component with a rank-deficient correlation matrix. Using numerical simulation, we show that the proposed method allows one to ensure variance of the estimated arrival angle of the plane wave, which is close to the Cramer-Rao lower boundary and more efficient than the best-known MUSIC method. It is also shown that the proposed technique can be efficiently used for estimating the time dependence of the useful signal.

Data processing device test apparatus and method therefor

DOEpatents

Wilcox, Richard Jacob; Mulig, Jason D.; Eppes, David; Bruce, Michael R.; Bruce, Victoria J.; Ring, Rosalinda M.; Cole, Jr., Edward I.; Tangyunyong, Paiboon; Hawkins, Charles F.; Louie, Arnold Y.

2003-04-08

A method and apparatus mechanism for testing data processing devices are implemented. The test mechanism isolates critical paths by correlating a scanning microscope image with a selected speed path failure. A trigger signal having a preselected value is generated at the start of each pattern vector. The sweep of the scanning microscope is controlled by a computer, which also receives and processes the image signals returned from the microscope. The value of the trigger signal is correlated with a set of pattern lines being driven on the DUT. The trigger is either asserted or negated depending the detection of a pattern line failure and the particular line that failed. In response to the detection of the particular speed path failure being characterized, and the trigger signal, the control computer overlays a mask on the image of the device under test (DUT). The overlaid image provides a visual correlation of the failure with the structural elements of the DUT at the level of resolution of the microscope itself.

Aligning a Receiving Antenna Array to Reduce Interference

NASA Technical Reports Server (NTRS)

Jongeling, Andre P.; Rogstad, David H.

2009-01-01

A digital signal-processing algorithm has been devised as a means of aligning (as defined below) the outputs of multiple receiving radio antennas in a large array for the purpose of receiving a desired weak signal transmitted by a single distant source in the presence of an interfering signal that (1) originates at another source lying within the antenna beam and (2) occupies a frequency band significantly wider than that of the desired signal. In the original intended application of the algorithm, the desired weak signal is a spacecraft telemetry signal, the antennas are spacecraft-tracking antennas in NASA s Deep Space Network, and the source of the wide-band interfering signal is typically a radio galaxy or a planet that lies along or near the line of sight to the spacecraft. The algorithm could also afford the ability to discriminate between desired narrow-band and nearby undesired wide-band sources in related applications that include satellite and terrestrial radio communications and radio astronomy. The development of the present algorithm involved modification of a prior algorithm called SUMPLE and a predecessor called SIMPLE. SUMPLE was described in Algorithm for Aligning an Array of Receiving Radio Antennas (NPO-40574), NASA Tech Briefs Vol. 30, No. 4 (April 2006), page 54. To recapitulate: As used here, aligning signifies adjusting the delays and phases of the outputs from the various antennas so that their relatively weak replicas of the desired signal can be added coherently to increase the signal-to-noise ratio (SNR) for improved reception, as though one had a single larger antenna. Prior to the development of SUMPLE, it was common practice to effect alignment by means of a process that involves correlation of signals in pairs. SIMPLE is an example of an algorithm that effects such a process. SUMPLE also involves correlations, but the correlations are not performed in pairs. Instead, in a partly iterative process, each signal is appropriately weighted and then correlated with a composite signal equal to the sum of the other signals.

Single baseline GLONASS observations with VLBI: data processing and first results

NASA Astrophysics Data System (ADS)

Tornatore, V.; Haas, R.; Duev, D.; Pogrebenko, S.; Casey, S.; Molera Calvés, G.; Keimpema, A.

2011-07-01

Several tests to observe signals transmitted by GLONASS (GLObal NAvigation Satellite System) satellites have been performed using the geodetic VLBI (Very Long Baseline Interferometry) technique. The radio telescopes involved in these experiments were Medicina (Italy) and Onsala (Sweden), both equipped with L-band receivers. Observations at the stations were performed using the standard Mark4 VLBI data acquisition rack and Mark5A disk-based recorders. The goals of the observations were to develop and test the scheduling, signal acquisition and processing routines to verify the full tracking pipeline, foreseeing the cross-correlation of the recorded data on the baseline Onsala-Medicina. The natural radio source 3c286 was used as a calibrator before the starting of the satellite observation sessions. Delay models, including the tropospheric and ionospheric corrections, which are consistent for both far- and near-field sources are under development. Correlation of the calibrator signal has been performed using the DiFX software, while the satellite signals have been processed using the narrow band approach with the Metsaehovi software and analysed with a near-field delay model. Delay models both for the calibrator signals and the satellites signals, using the same geometrical, tropospheric and ionospheric models, are under investigation to make a correlation of the satellite signals possible.

Correlation ion mobility spectroscopy

DOEpatents

Pfeifer, Kent B [Los Lunas, NM; Rohde, Steven B [Corrales, NM

2008-08-26

Correlation ion mobility spectrometry (CIMS) uses gating modulation and correlation signal processing to improve IMS instrument performance. Closely spaced ion peaks can be resolved by adding discriminating codes to the gate and matched filtering for the received ion current signal, thereby improving sensitivity and resolution of an ion mobility spectrometer. CIMS can be used to improve the signal-to-noise ratio even for transient chemical samples. CIMS is especially advantageous for small geometry IMS drift tubes that can otherwise have poor resolution due to their small size.

Real-time spatio-temporal coherence estimation for autonomous mode identification and invariance tracking

NASA Technical Reports Server (NTRS)

Park, Han G. (Inventor); Zak, Michail (Inventor); James, Mark L. (Inventor); Mackey, Ryan M. E. (Inventor)

2003-01-01

A general method of anomaly detection from time-correlated sensor data is disclosed. Multiple time-correlated signals are received. Their cross-signal behavior is compared against a fixed library of invariants. The library is constructed during a training process, which is itself data-driven using the same time-correlated signals. The method is applicable to a broad class of problems and is designed to respond to any departure from normal operation, including faults or events that lie outside the training envelope.

ALMA Correlator Real-Time Data Processor

NASA Astrophysics Data System (ADS)

Pisano, J.; Amestica, R.; Perez, J.

2005-10-01

The design of a real-time Linux application utilizing Real-Time Application Interface (RTAI) to process real-time data from the radio astronomy correlator for the Atacama Large Millimeter Array (ALMA) is described. The correlator is a custom-built digital signal processor which computes the cross-correlation function of two digitized signal streams. ALMA will have 64 antennas with 2080 signal streams each with a sample rate of 4 giga-samples per second. The correlator's aggregate data output will be 1 gigabyte per second. The software is defined by hard deadlines with high input and processing data rates, while requiring interfaces to non real-time external computers. The designed computer system - the Correlator Data Processor or CDP, consists of a cluster of 17 SMP computers, 16 of which are compute nodes plus a master controller node all running real-time Linux kernels. Each compute node uses an RTAI kernel module to interface to a 32-bit parallel interface which accepts raw data at 64 megabytes per second in 1 megabyte chunks every 16 milliseconds. These data are transferred to tasks running on multiple CPUs in hard real-time using RTAI's LXRT facility to perform quantization corrections, data windowing, FFTs, and phase corrections for a processing rate of approximately 1 GFLOPS. Highly accurate timing signals are distributed to all seventeen computer nodes in order to synchronize them to other time-dependent devices in the observatory array. RTAI kernel tasks interface to the timing signals providing sub-millisecond timing resolution. The CDP interfaces, via the master node, to other computer systems on an external intra-net for command and control, data storage, and further data (image) processing. The master node accesses these external systems utilizing ALMA Common Software (ACS), a CORBA-based client-server software infrastructure providing logging, monitoring, data delivery, and intra-computer function invocation. The software is being developed in tandem with the correlator hardware which presents software engineering challenges as the hardware evolves. The current status of this project and future goals are also presented.

Optical Processing of Speckle Images with Bacteriorhodopsin for Pattern Recognition

NASA Technical Reports Server (NTRS)

Downie, John D.; Tucker, Deanne (Technical Monitor)

1994-01-01

Logarithmic processing of images with multiplicative noise characteristics can be utilized to transform the image into one with an additive noise distribution. This simplifies subsequent image processing steps for applications such as image restoration or correlation for pattern recognition. One particularly common form of multiplicative noise is speckle, for which the logarithmic operation not only produces additive noise, but also makes it of constant variance (signal-independent). We examine the optical transmission properties of some bacteriorhodopsin films here and find them well suited to implement such a pointwise logarithmic transformation optically in a parallel fashion. We present experimental results of the optical conversion of speckle images into transformed images with additive, signal-independent noise statistics using the real-time photochromic properties of bacteriorhodopsin. We provide an example of improved correlation performance in terms of correlation peak signal-to-noise for such a transformed speckle image.

Wavelet transform: fundamentals, applications, and implementation using acousto-optic correlators

NASA Astrophysics Data System (ADS)

DeCusatis, Casimer M.; Koay, J.; Litynski, Daniel M.; Das, Pankaj K.

1995-10-01

In recent years there has been a great deal of interest in the use of wavelets to supplement or replace conventional Fourier transform signal processing. This paper provides a review of wavelet transforms for signal processing applications, and discusses several emerging applications which benefit from the advantages of wavelets. The wavelet transform can be implemented as an acousto-optic correlator; perfect reconstruction of digital signals may also be achieved using acousto-optic finite impulse response filter banks. Acousto-optic image correlators are discussed as a potential implementation of the wavelet transform, since a 1D wavelet filter bank may be encoded as a 2D image. We discuss applications of the wavelet transform including nondestructive testing of materials, biomedical applications in the analysis of EEG signals, and interference excision in spread spectrum communication systems. Computer simulations and experimental results for these applications are also provided.

Mitochondrial correlates of signaling processes involved with the cellular response to eimeria infection in broiler chickens

USDA-ARS?s Scientific Manuscript database

Host cellular responses to coccidiosis infection are consistent with elements of apoptosis, autophagy, and necrosis. These processes are enhanced in the cell through cell-directed signaling or repressed through parasite-derived inhibitors of these processes favoring the survival of the parasite. Acr...

An Ultra-Wideband Cross-Correlation Radiometer for Mesoscopic Experiments

NASA Astrophysics Data System (ADS)

Toonen, Ryan; Haselby, Cyrus; Qin, Hua; Eriksson, Mark; Blick, Robert

2007-03-01

We have designed, built and tested a cross-correlation radiometer for detecting statistical order in the quantum fluctuations of mesoscopic experiments at sub-Kelvin temperatures. Our system utilizes a fully analog front-end--operating over the X- and Ku-bands (8 to 18 GHz)--for computing the cross-correlation function. Digital signal processing techniques are used to provide robustness against instrumentation drifts and offsets. The economized version of our instrument can measure, with sufficient correlation efficiency, noise signals having power levels as low as 10 fW. We show that, if desired, we can improve this performance by including cryogenic preamplifiers which boost the signal-to-noise ratio near the signal source. By adding a few extra components, we can measure both the real and imaginary parts of the cross-correlation function--improving the overall signal-to-noise ratio by a factor of sqrt[2]. We demonstrate the utility of our cross-correlator with noise power measurements from a quantum point contact.

Perseveration effects in detection tasks with correlated decision intervals. [applied to pilot collision avoidance

NASA Technical Reports Server (NTRS)

Gai, E. G.; Curry, R. E.

1978-01-01

An investigation of the behavior of the human decisionmaker is described for a task related to the problem of a pilot using a traffic situation display to avoid collisions. This sequential signal detection task is characterized by highly correlated signals with time varying strength. Experimental results are presented and the behavior of the observers is analyzed using the theory of Markov processes and classical signal detection theory. Mathematical models are developed which describe the main result of the experiment: that correlation in sequential signals induced perseveration in the observer response and a strong tendency to repeat their previous decision, even when they were wrong.

``Seeing'' electroencephalogram through the skull: imaging prefrontal cortex with fast optical signal

NASA Astrophysics Data System (ADS)

Medvedev, Andrei V.; Kainerstorfer, Jana M.; Borisov, Sergey V.; Gandjbakhche, Amir H.; Vanmeter, John

2010-11-01

Near-infrared spectroscopy is a novel imaging technique potentially sensitive to both brain hemodynamics (slow signal) and neuronal activity (fast optical signal, FOS). The big challenge of measuring FOS noninvasively lies in the presumably low signal-to-noise ratio. Thus, detectability of the FOS has been controversially discussed. We present reliable detection of FOS from 11 individuals concurrently with electroencephalogram (EEG) during a Go-NoGo task. Probes were placed bilaterally over prefrontal cortex. Independent component analysis (ICA) was used for artifact removal. Correlation coefficient in the best correlated FOS-EEG ICA pairs was highly significant (p < 10-8), and event-related optical signal (EROS) was found in all subjects. Several EROS components were similar to the event-related potential (ERP) components. The most robust ``optical N200'' at t = 225 ms coincided with the N200 ERP; both signals showed significant difference between targets and nontargets, and their timing correlated with subject's reaction time. Correlation between FOS and EEG even in single trials provides further evidence that at least some FOS components ``reflect'' electrical brain processes directly. The data provide evidence for the early involvement of prefrontal cortex in rapid object recognition. EROS is highly localized and can provide cost-effective imaging tools for cortical mapping of cognitive processes.

“Seeing” electroencephalogram through the skull: imaging prefrontal cortex with fast optical signal

PubMed Central

Medvedev, Andrei V.; Kainerstorfer, Jana M.; Borisov, Sergey V.; Gandjbakhche, Amir H.; VanMeter, John

2010-01-01

Near-infrared spectroscopy is a novel imaging technique potentially sensitive to both brain hemodynamics (slow signal) and neuronal activity (fast optical signal, FOS). The big challenge of measuring FOS noninvasively lies in the presumably low signal-to-noise ratio. Thus, detectability of the FOS has been controversially discussed. We present reliable detection of FOS from 11 individuals concurrently with electroencephalogram (EEG) during a Go-NoGo task. Probes were placed bilaterally over prefrontal cortex. Independent component analysis (ICA) was used for artifact removal. Correlation coefficient in the best correlated FOS–EEG ICA pairs was highly significant (p < 10−8), and event-related optical signal (EROS) was found in all subjects. Several EROS components were similar to the event-related potential (ERP) components. The most robust “optical N200” at t = 225 ms coincided with the N200 ERP; both signals showed significant difference between targets and nontargets, and their timing correlated with subject’s reaction time. Correlation between FOS and EEG even in single trials provides further evidence that at least some FOS components “reflect” electrical brain processes directly. The data provide evidence for the early involvement of prefrontal cortex in rapid object recognition. EROS is highly localized and can provide cost-effective imaging tools for cortical mapping of cognitive processes. PMID:21198150

Optical information-processing systems and architectures II; Proceedings of the Meeting, San Diego, CA, July 9-13, 1990

NASA Astrophysics Data System (ADS)

Javidi, Bahram

The present conference discusses topics in the fields of neural networks, acoustooptic signal processing, pattern recognition, phase-only processing, nonlinear signal processing, image processing, optical computing, and optical information processing. Attention is given to the optical implementation of an inner-product neural associative memory, optoelectronic associative recall via motionless-head/parallel-readout optical disk, a compact real-time acoustooptic image correlator, a multidimensional synthetic estimation filter, and a light-efficient joint transform optical correlator. Also discussed are a high-resolution spatial light modulator, compact real-time interferometric Fourier-transform processors, a fast decorrelation algorithm for permutation arrays, the optical interconnection of optical modules, and carry-free optical binary adders.

Correlation analysis of respiratory signals by using parallel coordinate plots.

PubMed

Saatci, Esra

2018-01-01

The understanding of the bonds and the relationships between the respiratory signals, i.e. the airflow, the mouth pressure, the relative temperature and the relative humidity during breathing may provide the improvement on the measurement methods of respiratory mechanics and sensor designs or the exploration of the several possible applications in the analysis of respiratory disorders. Therefore, the main objective of this study was to propose a new combination of methods in order to determine the relationship between respiratory signals as a multidimensional data. In order to reveal the coupling between the processes two very different methods were used: the well-known statistical correlation analysis (i.e. Pearson's correlation and cross-correlation coefficient) and parallel coordinate plots (PCPs). Curve bundling with the number intersections for the correlation analysis, Least Mean Square Time Delay Estimator (LMS-TDE) for the point delay detection and visual metrics for the recognition of the visual structures were proposed and utilized in PCP. The number of intersections was increased when the correlation coefficient changed from high positive to high negative correlation between the respiratory signals, especially if whole breath was processed. LMS-TDE coefficients plotted in PCP indicated well-matched point delay results to the findings in the correlation analysis. Visual inspection of PCB by visual metrics showed range, dispersions, entropy comparisons and linear and sinusoidal-like relationships between the respiratory signals. It is demonstrated that the basic correlation analysis together with the parallel coordinate plots perceptually motivates the visual metrics in the display and thus can be considered as an aid to the user analysis by providing meaningful views of the data. Copyright © 2017 Elsevier B.V. All rights reserved.

Contemporary ultrasonic signal processing approaches for nondestructive evaluation of multilayered structures

NASA Astrophysics Data System (ADS)

Zhang, Guang-Ming; Harvey, David M.

2012-03-01

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

Real-Time and Memory Correlation via Acousto-Optic Processing,

DTIC Science & Technology

1978-06-01

acousto - optic technology as an answer to these requirements appears very attractive. Three fundamental signal-processing schemes using the acousto ... optic interaction have been investigated: (i) real-time correlation and convolution, (ii) Fourier and discrete Fourier transformation, and (iii

No Quantum Realization of Extremal No-Signaling Boxes

NASA Astrophysics Data System (ADS)

Ramanathan, Ravishankar; Tuziemski, Jan; Horodecki, Michał; Horodecki, Paweł

2016-07-01

The study of quantum correlations is important for fundamental reasons as well as for quantum communication and information processing tasks. On the one hand, it is of tremendous interest to derive the correlations produced by measurements on separated composite quantum systems from within the set of all correlations obeying the no-signaling principle of relativity, by means of information-theoretic principles. On the other hand, an important ongoing research program concerns the formulation of device-independent cryptographic protocols based on quantum nonlocal correlations for the generation of secure keys, and the amplification and expansion of random bits against general no-signaling adversaries. In both these research programs, a fundamental question arises: Can any measurements on quantum states realize the correlations present in pure extremal no-signaling boxes? Here, we answer this question in full generality showing that no nontrivial (not local realistic) extremal boxes of general no-signaling theories can be realized in quantum theory. We then explore some important consequences of this fact.

SAW correlator spread spectrum receiver

DOEpatents

Brocato, Robert W

2014-04-01

A surface acoustic wave (SAW) correlator spread-spectrum (SS) receiver is disclosed which utilizes a first demodulation stage with a chip length n and a second demodulation stage with a chip length m to decode a transmitted SS signal having a code length l=n.times.m which can be very long (e.g. up to 2000 chips or more). The first demodulation stage utilizes a pair of SAW correlators which demodulate the SS signal to generate an appropriate code sequence at an intermediate frequency which can then be fed into the second demodulation stage which can be formed from another SAW correlator, or by a digital correlator. A compound SAW correlator comprising two input transducers and a single output transducer is also disclosed which can be used to form the SAW correlator SS receiver, or for use in processing long code length signals.

System for monitoring non-coincident, nonstationary process signals

DOEpatents

Gross, Kenneth C.; Wegerich, Stephan W.

2005-01-04

An improved system for monitoring non-coincident, non-stationary, process signals. The mean, variance, and length of a reference signal is defined by an automated system, followed by the identification of the leading and falling edges of a monitored signal and the length of the monitored signal. The monitored signal is compared to the reference signal, and the monitored signal is resampled in accordance with the reference signal. The reference signal is then correlated with the resampled monitored signal such that the reference signal and the resampled monitored signal are coincident in time with each other. The resampled monitored signal is then compared to the reference signal to determine whether the resampled monitored signal is within a set of predesignated operating conditions.

Energy spectrum analysis - A model of echolocation processing. [in animals

NASA Technical Reports Server (NTRS)

Johnson, R. A.; Titlebaum, E. L.

1976-01-01

The paper proposes a frequency domain approach based on energy spectrum analysis of the combination of a signal and its echoes as the processing mechanism for the echolocation process used by bats and other animals. The mechanism is a generalized wide-band one and can account for the large diversity of wide-band signals used for orientation. The coherency in the spectrum of the signal-echo combination is shown to be equivalent to correlation.

Digital Signal Processing in Acoustics--Part 2.

ERIC Educational Resources Information Center

Davies, H.; McNeill, D. J.

1986-01-01

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

Low Computational Signal Acquisition for GNSS Receivers Using a Resampling Strategy and Variable Circular Correlation Time

PubMed Central

Zhang, Yeqing; Wang, Meiling; Li, Yafeng

2018-01-01

For the objective of essentially decreasing computational complexity and time consumption of signal acquisition, this paper explores a resampling strategy and variable circular correlation time strategy specific to broadband multi-frequency GNSS receivers. In broadband GNSS receivers, the resampling strategy is established to work on conventional acquisition algorithms by resampling the main lobe of received broadband signals with a much lower frequency. Variable circular correlation time is designed to adapt to different signal strength conditions and thereby increase the operation flexibility of GNSS signal acquisition. The acquisition threshold is defined as the ratio of the highest and second highest correlation results in the search space of carrier frequency and code phase. Moreover, computational complexity of signal acquisition is formulated by amounts of multiplication and summation operations in the acquisition process. Comparative experiments and performance analysis are conducted on four sets of real GPS L2C signals with different sampling frequencies. The results indicate that the resampling strategy can effectively decrease computation and time cost by nearly 90–94% with just slight loss of acquisition sensitivity. With circular correlation time varying from 10 ms to 20 ms, the time cost of signal acquisition has increased by about 2.7–5.6% per millisecond, with most satellites acquired successfully. PMID:29495301

Low Computational Signal Acquisition for GNSS Receivers Using a Resampling Strategy and Variable Circular Correlation Time.

PubMed

Zhang, Yeqing; Wang, Meiling; Li, Yafeng

2018-02-24

For the objective of essentially decreasing computational complexity and time consumption of signal acquisition, this paper explores a resampling strategy and variable circular correlation time strategy specific to broadband multi-frequency GNSS receivers. In broadband GNSS receivers, the resampling strategy is established to work on conventional acquisition algorithms by resampling the main lobe of received broadband signals with a much lower frequency. Variable circular correlation time is designed to adapt to different signal strength conditions and thereby increase the operation flexibility of GNSS signal acquisition. The acquisition threshold is defined as the ratio of the highest and second highest correlation results in the search space of carrier frequency and code phase. Moreover, computational complexity of signal acquisition is formulated by amounts of multiplication and summation operations in the acquisition process. Comparative experiments and performance analysis are conducted on four sets of real GPS L2C signals with different sampling frequencies. The results indicate that the resampling strategy can effectively decrease computation and time cost by nearly 90-94% with just slight loss of acquisition sensitivity. With circular correlation time varying from 10 ms to 20 ms, the time cost of signal acquisition has increased by about 2.7-5.6% per millisecond, with most satellites acquired successfully.

Field-quadrature and photon-number correlations produced by parametric processes.

PubMed

McKinstrie, C J; Karlsson, M; Tong, Z

2010-09-13

In a previous paper [Opt. Express 13, 4986 (2005)], formulas were derived for the field-quadrature and photon-number variances produced by multiple-mode parametric processes. In this paper, formulas are derived for the quadrature and number correlations. The number formulas are used to analyze the properties of basic devices, such as two-mode amplifiers, attenuators and frequency convertors, and composite systems made from these devices, such as cascaded parametric amplifiers and communication links. Amplifiers generate idlers that are correlated with the amplified signals, or correlate pre-existing pairs of modes, whereas attenuators decorrelate pre-existing modes. Both types of device modify the signal-to-noise ratios (SNRs) of the modes on which they act. Amplifiers decrease or increase the mode SNRs, depending on whether they are operated in phase-insensitive (PI) or phase-sensitive (PS) manners, respectively, whereas attenuators always decrease these SNRs. Two-mode PS links are sequences of transmission fibers (attenuators) followed by two-mode PS amplifiers. Not only do these PS links have noise figures that are 6-dB lower than those of the corresponding PI links, they also produce idlers that are (almost) completely correlated with the signals. By detecting the signals and idlers, one can eliminate the effects of electronic noise in the detectors.

Investigation of charge coupled device correlation techniques

NASA Technical Reports Server (NTRS)

Lampe, D. R.; Lin, H. C.; Shutt, T. J.

1978-01-01

Analog Charge Transfer Devices (CTD's) offer unique advantages to signal processing systems, which often have large development costs, making it desirable to define those devices which can be developed for general system's use. Such devices are best identified and developed early to give system's designers some interchangeable subsystem blocks, not requiring additional individual development for each new signal processing system. The objective of this work is to describe a discrete analog signal processing device with a reasonably broad system use and to implement its design, fabrication, and testing.

Real time SAR processing

NASA Technical Reports Server (NTRS)

Premkumar, A. B.; Purviance, J. E.

1990-01-01

A simplified model for the SAR imaging problem is presented. The model is based on the geometry of the SAR system. Using this model an expression for the entire phase history of the received SAR signal is formulated. From the phase history, it is shown that the range and the azimuth coordinates for a point target image can be obtained by processing the phase information during the intrapulse and interpulse periods respectively. An architecture for a VLSI implementation for the SAR signal processor is presented which generates images in real time. The architecture uses a small number of chips, a new correlation processor, and an efficient azimuth correlation process.

On comprehensive recovery of an aftershock sequence with cross correlation

NASA Astrophysics Data System (ADS)

Kitov, I.; Bobrov, D.; Coyne, J.; Turyomurugyendo, G.

2012-04-01

We have introduced cross correlation between seismic waveforms as a technique for signal detection and automatic event building at the International Data Centre (IDC) of the Comprehensive Nuclear-Test-Ban Treaty Organization. The intuition behind signal detection is simple - small and mid-sized seismic events close in space should produce similar signals at the same seismic stations. Equivalently, these signals have to be characterized by a high cross correlation coefficient. For array stations with many individual sensors distributed over a large area, signals from events at distances beyond, say, 50 km, are subject to destructive interference when cross correlated due to changing time delays between various channels. Thus, any cross correlation coefficient above some predefined threshold can be considered as a signature of a valid signal. With a dense grid of master events (spacing between adjacent masters between 20 km and 50 km corresponds to the statistically estimated correlation distance) with high quality (signal-to-noise ratio above 10) template waveforms at primary array stations of the International Monitoring System one can detect signals from and then build natural and manmade seismic events close to the master ones. The use of cross correlation allows detecting smaller signals (sometimes below noise level) than provided by the current IDC detecting techniques. As a result it is possible to automatically build from 50% to 100% more valid seismic events than included in the Reviewed Event Bulletin (REB). We have developed a tentative pipeline for automatic processing at the IDC. It includes three major stages. Firstly, we calculate cross correlation coefficient for a given master and continuous waveforms at the same stations and carry out signal detection as based on the statistical behavior of signal-to-noise ratio of the cross correlation coefficient. Secondly, a thorough screening is performed for all obtained signals using f-k analysis and F-statistics as applied to the cross-correlation traces at individual channels of all included array stations. Thirdly, local (i.e. confined to the correlation distance around the master event) association of origin times of all qualified signals is fulfilled. These origin times are calculated from the arrival times of these signals, which are reduced to the origin times by the travel times from the master event. An aftershock sequence of a mid-size earthquake is an ideal case to test cross correlation techniques for autiomatic event building. All events should be close to the mainshock and occur within several days. Here we analyse the aftershock sequence of an earthquake in the North Atlantic Ocean with mb(IDC)=4.79. The REB includes 38 events at distances less than 150 km from the mainshock. Our ultimate goal is to excersice the complete iterative procedure to find all possible aftershocks. We start with the mainshock and recover ten aftershocks with the largest number of stations to produce an initial set of master events with the highest quality templates. Then we find all aftershocks in the REB and many additional events, which were not originally found by the IDC. Using all events found after the first iteration as master events we find new events, which are also used in the next iteration. The iterative process stops when no new events can be found. In that sense the final set of aftershocks obtained with cross correlation is a comprehensive one.

[Multi-channel in vivo recording techniques: signal processing of action potentials and local field potentials].

PubMed

Xu, Jia-Min; Wang, Ce-Qun; Lin, Long-Nian

2014-06-25

Multi-channel in vivo recording techniques are used to record ensemble neuronal activity and local field potentials (LFP) simultaneously. One of the key points for the technique is how to process these two sets of recorded neural signals properly so that data accuracy can be assured. We intend to introduce data processing approaches for action potentials and LFP based on the original data collected through multi-channel recording system. Action potential signals are high-frequency signals, hence high sampling rate of 40 kHz is normally chosen for recording. Based on waveforms of extracellularly recorded action potentials, tetrode technology combining principal component analysis can be used to discriminate neuronal spiking signals from differently spatially distributed neurons, in order to obtain accurate single neuron spiking activity. LFPs are low-frequency signals (lower than 300 Hz), hence the sampling rate of 1 kHz is used for LFPs. Digital filtering is required for LFP analysis to isolate different frequency oscillations including theta oscillation (4-12 Hz), which is dominant in active exploration and rapid-eye-movement (REM) sleep, gamma oscillation (30-80 Hz), which is accompanied by theta oscillation during cognitive processing, and high frequency ripple oscillation (100-250 Hz) in awake immobility and slow wave sleep (SWS) state in rodent hippocampus. For the obtained signals, common data post-processing methods include inter-spike interval analysis, spike auto-correlation analysis, spike cross-correlation analysis, power spectral density analysis, and spectrogram analysis.

Task effects on BOLD signal correlates of implicit syntactic processing

PubMed Central

Caplan, David

2010-01-01

BOLD signal was measured in sixteen participants who made timed font change detection judgments in visually presented sentences that varied in syntactic structure and the order of animate and inanimate nouns. Behavioral data indicated that sentences were processed to the level of syntactic structure. BOLD signal increased in visual association areas bilaterally and left supramarginal gyrus in the contrast of sentences with object- and subject-extracted relative clauses without font changes in which the animacy order of the nouns biased against the syntactically determined meaning of the sentence. This result differs from the findings in a non-word detection task (Caplan et al, 2008a), in which the same contrast led to increased BOLD signal in the left inferior frontal gyrus. The difference in areas of activation indicates that the sentences were processed differently in the two tasks. These differences were further explored in an eye tracking study using the materials in the two tasks. Issues pertaining to how parsing and interpretive operations are affected by a task that is being performed, and how this might affect BOLD signal correlates of syntactic contrasts, are discussed. PMID:20671983

Task effects on BOLD signal correlates of implicit syntactic processing.

PubMed

Caplan, David

2010-07-01

BOLD signal was measured in sixteen participants who made timed font change detection judgments in visually presented sentences that varied in syntactic structure and the order of animate and inanimate nouns. Behavioral data indicated that sentences were processed to the level of syntactic structure. BOLD signal increased in visual association areas bilaterally and left supramarginal gyrus in the contrast of sentences with object- and subject-extracted relative clauses without font changes in which the animacy order of the nouns biased against the syntactically determined meaning of the sentence. This result differs from the findings in a non-word detection task (Caplan et al, 2008a), in which the same contrast led to increased BOLD signal in the left inferior frontal gyrus. The difference in areas of activation indicates that the sentences were processed differently in the two tasks. These differences were further explored in an eye tracking study using the materials in the two tasks. Issues pertaining to how parsing and interpretive operations are affected by a task that is being performed, and how this might affect BOLD signal correlates of syntactic contrasts, are discussed.

Optical rangefinding applications using communications modulation technique

NASA Astrophysics Data System (ADS)

Caplan, William D.; Morcom, Christopher John

2010-10-01

A novel range detection technique combines optical pulse modulation patterns with signal cross-correlation to produce an accurate range estimate from low power signals. The cross-correlation peak is analyzed by a post-processing algorithm such that the phase delay is proportional to the range to target. This technique produces a stable range estimate from noisy signals. The advantage is higher accuracy obtained with relatively low optical power transmitted. The technique is useful for low cost, low power and low mass sensors suitable for tactical use. The signal coding technique allows applications including IFF and battlefield identification systems.

Ex vivo accuracy of an apex locator using digital signal processing in primary teeth.

PubMed

Leonardo, Mário Roberto; da Silva, Lea Assed Bezerra; Nelson-Filho, Paulo; da Silva, Raquel Assed Bezerra; Lucisano, Marília Pacífico

2009-01-01

The purpose of this study was to evaluate ex vivo the accuracy an electronic apex locator during root canal length determination in primary molars. One calibrated examiner determined the root canal length in 15 primary molars (total=34 root canals) with different stages of root resorption. Root canal length was measured both visually with the placement of a K-file 1 mm short of the apical foramen or the apical resorption bevel, and electronically using an electronic apex locator (Digital Signal Processing). Data were analyzed statistically using the intraclass correlation (ICC) test. Comparing the actual and electronic root canal length measurements in the primary teeth showed a high correlation (ICC=0.95). The Digital Signal Processing apex locator is useful and accurate for apex foramen location during root canal length measurement in primary molars.

Cross-correlation between EMG and center of gravity during quiet stance: theory and simulations.

PubMed

Kohn, André Fabio

2005-11-01

Several signal processing tools have been employed in the experimental study of the postural control system in humans. Among them, the cross-correlation function has been used to analyze the time relationship between signals such as the electromyogram and the horizontal projection of the center of gravity. The common finding is that the electromyogram precedes the biomechanical signal, a result that has been interpreted in different ways, for example, the existence of feedforward control or the preponderance of a velocity feedback. It is shown here, analytically and by simulation, that the cross-correlation function is dependent in a complicated way on system parameters and on noise spectra. Results similar to those found experimentally, e.g., electromyogram preceding the biomechanical signal may be obtained in a postural control model without any feedforward control and without any velocity feedback. Therefore, correct interpretations of experimentally obtained cross-correlation functions may require additional information about the system. The results extend to other biomedical applications where two signals from a closed loop system are cross-correlated.

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

PubMed Central

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

2012-01-01

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

Time Reversal Mirrors and Cross Correlation Functions in Acoustic Wave Propagation

NASA Astrophysics Data System (ADS)

Fishman, Louis; Jonsson, B. Lars G.; de Hoop, Maarten V.

2009-03-01

In time reversal acoustics (TRA), a signal is recorded by an array of transducers, time reversed, and then retransmitted into the configuration. The retransmitted signal propagates back through the same medium and retrofocuses on the source that generated the signal. If the transducer array is a single, planar (flat) surface, then this configuration is referred to as a planar, one-sided, time reversal mirror (TRM). In signal processing, for example, in active-source seismic interferometry, the measurement of the wave field at two distinct receivers, generated by a common source, is considered. Cross correlating these two observations and integrating the result over the sources yield the cross correlation function (CCF). Adopting the TRM experiments as the basic starting point and identifying the kinematically correct correspondences, it is established that the associated CCF signal processing constructions follow in a specific, infinite recording time limit. This perspective also provides for a natural rationale for selecting the Green's function components in the TRM and CCF expressions. For a planar, one-sided, TRM experiment and the corresponding CCF signal processing construction, in a three-dimensional homogeneous medium, the exact expressions are explicitly calculated, and the connecting limiting relationship verified. Finally, the TRM and CCF results are understood in terms of the underlying, governing, two-way wave equation, its corresponding time reversal invariance (TRI) symmetry, and the absence of TRI symmetry in the associated one-way wave equations, highlighting the role played by the evanescent modal contributions.

Hot topics: Signal processing in acoustics

NASA Astrophysics Data System (ADS)

Gaumond, Charles F.

2005-09-01

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

Photon correlation in single-photon frequency upconversion.

PubMed

Gu, Xiaorong; Huang, Kun; Pan, Haifeng; Wu, E; Zeng, Heping

2012-01-30

We experimentally investigated the intensity cross-correlation between the upconverted photons and the unconverted photons in the single-photon frequency upconversion process with multi-longitudinal mode pump and signal sources. In theoretical analysis, with this multi-longitudinal mode of both signal and pump sources system, the properties of the signal photons could also be maintained as in the single-mode frequency upconversion system. Experimentally, based on the conversion efficiency of 80.5%, the joint probability of simultaneously detecting at upconverted and unconverted photons showed an anti-correlation as a function of conversion efficiency which indicated the upconverted photons were one-to-one from the signal photons. While due to the coherent state of the signal photons, the intensity cross-correlation function g(2)(0) was shown to be equal to unity at any conversion efficiency, agreeing with the theoretical prediction. This study will benefit the high-speed wavelength-tunable quantum state translation or photonic quantum interface together with the mature frequency tuning or longitudinal mode selection techniques.

Analysis of cerebral vessels dynamics using experimental data with missed segments

NASA Astrophysics Data System (ADS)

Pavlova, O. N.; Abdurashitov, A. S.; Ulanova, M. V.; Shihalov, G. M.; Semyachkina-Glushkovskaya, O. V.; Pavlov, A. N.

2018-04-01

Physiological signals often contain various bad segments that occur due to artifacts, failures of the recording equipment or varying experimental conditions. The related experimental data need to be preprocessed to avoid such parts of recordings. In the case of few bad segments, they can simply be removed from the signal and its analysis is further performed. However, when there are many extracted segments, the internal structure of the analyzed physiological process may be destroyed, and it is unclear whether such signal can be used in diagnostic-related studies. In this paper we address this problem for the case of cerebral vessels dynamics. We perform analysis of simulated data in order to reveal general features of quantifying scaling features of complex signals with distinct correlation properties and show that the effects of data loss are significantly different for experimental data with long-range correlations and anti-correlations. We conclude that the cerebral vessels dynamics is significantly less sensitive to missed data fragments as compared with signals with anti-correlated statistics.

Hybrid Signal Processing Technique to Improve the Defect Estimation in Ultrasonic Non-Destructive Testing of Composite Structures

PubMed Central

Raisutis, Renaldas; Samaitis, Vykintas

2017-01-01

This work proposes a novel hybrid signal processing technique to extract information on disbond-type defects from a single B-scan in the process of non-destructive testing (NDT) of glass fiber reinforced plastic (GFRP) material using ultrasonic guided waves (GW). The selected GFRP sample has been a segment of wind turbine blade, which possessed an aerodynamic shape. Two disbond type defects having diameters of 15 mm and 25 mm were artificially constructed on its trailing edge. The experiment has been performed using the low-frequency ultrasonic system developed at the Ultrasound Institute of Kaunas University of Technology and only one side of the sample was accessed. A special configuration of the transmitting and receiving transducers fixed on a movable panel with a separation distance of 50 mm was proposed for recording the ultrasonic guided wave signals at each one-millimeter step along the scanning distance up to 500 mm. Finally, the hybrid signal processing technique comprising the valuable features of the three most promising signal processing techniques: cross-correlation, wavelet transform, and Hilbert–Huang transform has been applied to the received signals for the extraction of defects information from a single B-scan image. The wavelet transform and cross-correlation techniques have been combined in order to extract the approximated size and location of the defects and measurements of time delays. Thereafter, Hilbert–Huang transform has been applied to the wavelet transformed signal to compare the variation of instantaneous frequencies and instantaneous amplitudes of the defect-free and defective signals. PMID:29232845

Results of the Baikal Experiment on Observations of Macroscopic Nonlocal Correlations in Reverse Time

NASA Astrophysics Data System (ADS)

Korotaev, S. M.; Serdyuk, V. O.; Kiktenko, E. O.; Budnev, N. M.; Gorohov, J. V.

Although the general theory macroscopic quantum entanglement of is still in its infancy, consideration of the matter in the framework of action-at-a distance electrodynamics predicts for the random dissipative processes observability of the advanced nonlocal correlations (time reversal causality). These correlations were really revealed in our previous experiments with some large-scale heliogeophysical processes as the source ones and the lab detectors as the probe ones. Recently a new experiment has been performing on the base of Baikal Deep Water Neutrino Observatory. The thick water layer is an excellent shield against any local impacts on the detectors. The first annual series 2012/2013 has demonstrated that detector signals respond to the heliogeophysical (external) processes and causal connection of the signals directed downwards: from the Earth surface to the Baikal floor. But this nonlocal connection proved to be in reverse time. In addition advanced nonlocal correlation of the detector signal with the regional source-process: the random component of hydrological activity in the upper layer was revealed and the possibility of its forecast on nonlocal correlations was demonstrated. But the strongest macroscopic nonlocal correlations are observed at extremely low frequencies, that is at periods of several months. Therefore the above results should be verified in a longer experiment. We verify them by data of the second annual series 2013/2014 of the Baikal experiment. All the results have been confirmed, although some quantitative parameters of correlations and time reversal causal links turned out different due to nonstationarity of the source-processes. A new result is displaying of the advanced response of nonlocal correlation detector to the earthquake. This opens up the prospect of the earthquake forecast on the new physical principle, although further confirmation in the next events is certainly needed. The continuation of the Baikal experiment with expanded program is burning.

Achieving subpixel resolution with time-correlated transient signals in pixelated CdZnTe gamma-ray sensors using a focused laser beam (Conference Presentation)

NASA Astrophysics Data System (ADS)

Ocampo Giraldo, Luis A.; Bolotnikov, Aleksey E.; Camarda, Giuseppe S.; Cui, Yonggang; De Geronimo, Gianluigi; Gul, Rubi; Fried, Jack; Hossain, Anwar; Unlu, Kenan; Vernon, Emerson; Yang, Ge; James, Ralph B.

2017-05-01

High-resolution position-sensitive detectors have been proposed to correct response non-uniformities in Cadmium Zinc Telluride (CZT) crystals by virtually subdividing the detectors area into small voxels and equalizing responses from each voxel. 3D pixelated detectors coupled with multichannel readout electronics are the most advanced type of CZT devices offering many options in signal processing and enhancing detector performance. One recent innovation proposed for pixelated detectors is to use the induced (transient) signals from neighboring pixels to achieve high sub-pixel position resolution while keeping large pixel sizes. The main hurdle in achieving this goal is the relatively low signal induced on the neighboring pixels because of the electrostatic shielding effect caused by the collecting pixel. In addition, to achieve high position sensitivity one should rely on time-correlated transient signals, which means that digitized output signals must be used. We present the results of our studies to measure the amplitude of the pixel signals so that these can be used to measure positions of the interaction points. This is done with the processing of digitized correlated time signals measured from several adjacent pixels taking into account rise-time and charge-sharing effects. In these measurements we used a focused pulsed laser to generate a 10-micron beam at one milliwatt (650-nm wavelength) over the detector surface while the collecting pixel was moved in cardinal directions. The results include measurements that present the benefits of combining conventional pixel geometry with digital pulse processing for the best approach in achieving sub-pixel position resolution with the pixel dimensions of approximately 2 mm. We also present the sub-pixel resolution measurements at comparable energies from various gamma emitting isotopes.

Neural Correlates of Success and Failure Signals During Neurofeedback Learning.

PubMed

Radua, Joaquim; Stoica, Teodora; Scheinost, Dustin; Pittenger, Christopher; Hampson, Michelle

2018-05-15

Feedback-driven learning, observed across phylogeny and of clear adaptive value, is frequently operationalized in simple operant conditioning paradigms, but it can be much more complex, driven by abstract representations of success and failure. This study investigates the neural processes involved in processing success and failure during feedback learning, which are not well understood. Data analyzed were acquired during a multisession neurofeedback experiment in which ten participants were presented with, and instructed to modulate, the activity of their orbitofrontal cortex with the aim of decreasing their anxiety. We assessed the regional blood-oxygenation-level-dependent response to the individualized neurofeedback signals of success and failure across twelve functional runs acquired in two different magnetic resonance sessions in each of ten individuals. Neurofeedback signals of failure correlated early during learning with deactivation in the precuneus/posterior cingulate and neurofeedback signals of success correlated later during learning with deactivation in the medial prefrontal/anterior cingulate cortex. The intensity of the latter deactivations predicted the efficacy of the neurofeedback intervention in the reduction of anxiety. These findings indicate a role for regulation of the default mode network during feedback learning, and suggest a higher sensitivity to signals of failure during the early feedback learning and to signals of success subsequently. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.

Methods to detect, characterize, and remove motion artifact in resting state fMRI

PubMed Central

Power, Jonathan D; Mitra, Anish; Laumann, Timothy O; Snyder, Abraham Z; Schlaggar, Bradley L; Petersen, Steven E

2013-01-01

Head motion systematically alters correlations in resting state functional connectivity fMRI (RSFC). In this report we examine impact of motion on signal intensity and RSFC correlations. We find that motion-induced signal changes (1) are often complex and variable waveforms, (2) are often shared across nearly all brain voxels, and (3) often persist more than 10 seconds after motion ceases. These signal changes, both during and after motion, increase observed RSFC correlations in a distance-dependent manner. Motion-related signal changes are not removed by a variety of motion-based regressors, but are effectively reduced by global signal regression. We link several measures of data quality to motion, changes in signal intensity, and changes in RSFC correlations. We demonstrate that improvements in data quality measures during processing may represent cosmetic improvements rather than true correction of the data. We demonstrate a within-subject, censoring-based artifact removal strategy based on volume censoring that reduces group differences due to motion to chance levels. We note conditions under which group-level regressions do and do not correct motion-related effects. PMID:23994314

Analysis of digital communication signals and extraction of parameters

NASA Astrophysics Data System (ADS)

Al-Jowder, Anwar

1994-12-01

The signal classification performance of four types of electronics support measure (ESM) communications detection systems is compared from the standpoint of the unintended receiver (interceptor). Typical digital communication signals considered include binary phase shift keying (BPSK), quadrature phase shift keying (QPSK), frequency shift keying (FSK), and on-off keying (OOK). The analysis emphasizes the use of available signal processing software. Detection methods compared include broadband energy detection, FFT-based narrowband energy detection, and two correlation methods which employ the fast Fourier transform (FFT). The correlation methods utilize modified time-frequency distributions, where one of these is based on the Wigner-Ville distribution (WVD). Gaussian white noise is added to the signal to simulate various signal-to-noise ratios (SNR's).

The relationship of acquisition systems to automated stereo correlation.

USGS Publications Warehouse

Colvocoresses, A.P.

1983-01-01

Today a concerted effort is being made to expedite the mapping process through automated correlation of stereo data. Stereo correlation involves the comparison of radiance (brightness) signals or patterns recorded by sensors. Conventionally, two-dimensional area correlation is utilized but this is a rather slow and cumbersome procedure. Digital correlation can be performed in only one dimension where suitable signal patterns exist, and the one-dimensional mode is much faster. Electro-optical (EO) systems, suitable for space use, also have much greater flexibility than film systems. Thus, an EO space system can be designed which will optimize one-dimensional stereo correlation and lead toward the automation of topographic mapping.-from Author

Efficient Processing of Data for Locating Lightning Strikes

NASA Technical Reports Server (NTRS)

Medelius, Pedro J.; Starr, Stan

2003-01-01

Two algorithms have been devised to increase the efficiency of processing of data in lightning detection and ranging (LDAR) systems so as to enable the accurate location of lightning strikes in real time. In LDAR, the location of a lightning strike is calculated by solving equations for the differences among the times of arrival (DTOAs) of the lightning signals at multiple antennas as functions of the locations of the antennas and the speed of light. The most difficult part of the problem is computing the DTOAs from digitized versions of the signals received by the various antennas. One way (a time-domain approach) to determine the DTOAs is to compute cross-correlations among variously differentially delayed replicas of the digitized signals and to select, as the DTOAs, those differential delays that yield the maximum correlations. Another way (a frequency-domain approach) to determine the DTOAs involves the computation of cross-correlations among Fourier transforms of variously differentially phased replicas of the digitized signals, along with utilization of the relationship among phase difference, time delay, and frequency.

Signal processing: opportunities for superconductive circuits

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ralston, R.W.

1985-03-01

Prime motivators in the evolution of increasingly sophisticated communication and detection systems are the needs for handling ever wider signal bandwidths and higher data-processing speeds. These same needs drive the development of electronic device technology. Until recently the superconductive community has been tightly focused on digital devices for high speed computers. The purpose of this paper is to describe opportunities and challenges which exist for both analog and digital devices in a less familiar area, that of wideband signal processing. The function and purpose of analog signal-processing components, including matched filters, correlators and Fourier transformers, will be described and examplesmore » of superconductive implementations given. A canonic signal-processing system is then configured using these components and digital output circuits to highlight the important issues of dynamic range, accuracy and equivalent computation rate. (Reprints)« less

Glutamate and GABA contributions to medial prefrontal cortical activity to emotion: implications for mood disorders.

PubMed

Stan, Ana D; Schirda, Claudiu V; Bertocci, Michele A; Bebko, Genna M; Kronhaus, Dina M; Aslam, Haris A; LaBarbara, Eduard J; Tanase, Costin; Lockovich, Jeanette C; Pollock, Myrna H; Stiffler, Richelle S; Phillips, Mary L

2014-09-30

The dorsomedial prefrontal cortex (MdPFC) and anterior cingulate cortices (ACC) play a critical role in implicit emotion regulation; however the understanding of the specific neurotransmitters that mediate such role is lacking. In this study, we examined relationships between MdPFC concentrations of two neurotransmitters, glutamate and γ-amino butyric acid (GABA), and BOLD activity in ACC during performance of an implicit facial emotion-processing task. Twenty healthy volunteers, aged 20-35 years, were scanned while performing an implicit facial emotion-processing task, whereby presented facial expressions changed from neutral to one of the four emotions: happy, anger, fear, or sad. Glutamate concentrations were measured before and after the emotion-processing task in right MdPFC using magnetic resonance spectroscopy (MRS). GABA concentrations were measured in bilateral MdPFC after the emotion-processing task. Multiple regression models were run to determine the relative contribution of glutamate and GABA concentration, age, and gender to BOLD signal in ACC to each of the four emotions. Multiple regression analyses revealed a significant negative correlation between MdPFC GABA concentration and BOLD signal in subgenual ACC (p<0.05, corrected) to sad versus shape contrast. For the anger versus shape contrast, there was a significant negative correlation between age and BOLD signal in pregenual ACC (p<0.05, corrected) and a positive correlation between MdPFC glutamate concentration (pre-task) and BOLD signal in pregenual ACC (p<0.05, corrected). Our findings are the first to provide insight into relationships between MdPFC neurotransmitter concentrations and ACC BOLD signal, and could further understanding of molecular mechanisms underlying emotion processing in healthy and mood-disordered individuals. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Suprathreshold stochastic resonance in neural processing tuned by correlation.

PubMed

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

2011-07-01

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

Suprathreshold stochastic resonance in neural processing tuned by correlation

NASA Astrophysics Data System (ADS)

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

2011-07-01

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

The Analysis and Suppression of the spike noise in vibrator record

NASA Astrophysics Data System (ADS)

Jia, H.; Jiang, T.; Xu, X.; Ge, L.; Lin, J.; Yang, Z.

2013-12-01

During the seismic exploration with vibrator, seismic recording systems have often been affected by random spike noise in the background, which leads to strong data distortions as a result of the cross-correlation processing of the vibrator method. Partial or total loss of the desired seismic information is possible if no automatic spike reduction is available in the field prior to correlation of the field record. Generally speaking, original record of vibrator is uncorrelated data, in which the signal is non-wavelet form. In order to obtain the seismic record similar to explosive source, the signal of uncorrelated data needs to use the correlation algorithm to compress into wavelet form. The correlation process results in that the interference of spike in correlated data is not only being suppressed, but also being expanded. So the spike noise suppression of vibrator is indispensable. According to numerical simulation results, the effect of spike in the vibrator record is mainly affected by the amplitude and proportional points in the uncorrelated record. When the spike noise ratio in uncorrelated record reaches 1.5% and the average amplitude exceeds 200, it will make the SNR(signal-to-noise ratio) of the correlated record lower than 0dB, so that it is difficult to separate the signal. While the amplitude and ratio is determined by the intensity of background noise. Therefore, when the noise level is strong, in order to improve SNR of the seismic data, the uncorrelated record of vibrator need to take necessary steps to suppress spike noise. For the sake of reducing the influence of the spike noise, we need to make the detection and suppression of spike noise process for the uncorrelated record. Because vibrator works by inputting sweep signal into the underground long time, ideally, the peak and valley values of each trace have little change. On the basis of the peak and valley values, we can get a reference amplitude value. Then the spike can be detected and suppressed. After this process, it can reduce the effection of spike noise in the uncorrelated record to improve the SNR. At present, because the memory space of vibrator uncorrelated data is always very large, in order to reduce acquisition costs, we usually record correlated data directly. It's reasonable if there is no strong spike sneaking into uncorrelated record. However, due to the fact that the random spike in the background is not avoidable in the acquisition process, and the instantaneous input energy of the vibrator is probably smaller than spike noise, which makes the uncorrelated data contain a certain amount of spike noise, it severely reduces the acquisition quality of vibrator if there is no noise suppression module beforehand. Of course, the suppressing process of spike noise can be carried out in the field acquisition or data processing stage. In the field of vibrator acquisition system, we can use the spike noise suppression before the correlated module, so that it can directly record correlated data without the spike affection. If in the stage of data processing, it is necessary to record uncorrelated data.

Scaling Behavior in Mitochondrial Redox Fluctuations

PubMed Central

Ramanujan, V. Krishnan; Biener, Gabriel; Herman, Brian A.

2006-01-01

Scale-invariant long-range correlations have been reported in fluctuations of time-series signals originating from diverse processes such as heart beat dynamics, earthquakes, and stock market data. The common denominator of these apparently different processes is a highly nonlinear dynamics with competing forces and distinct feedback species. We report for the first time an experimental evidence for scaling behavior in NAD(P)H signal fluctuations in isolated mitochondria and intact cells isolated from the liver of a young (5-month-old) mouse. Time-series data were collected by two-photon imaging of mitochondrial NAD(P)H fluorescence and signal fluctuations were quantitatively analyzed for statistical correlations by detrended fluctuation analysis and spectral power analysis. Redox [NAD(P)H / NAD(P)+] fluctuations in isolated mitochondria and intact liver cells were found to display nonrandom, long-range correlations. These correlations are interpreted as arising due to the regulatory dynamics operative in Krebs' cycle enzyme network and electron transport chain in the mitochondria. This finding may provide a novel basis for understanding similar regulatory networks that govern the nonequilibrium properties of living cells. PMID:16565066

In vivo evaluation of mastication noise reduction for dual channel implantable microphone.

PubMed

Woo, SeongTak; Jung, EuiSung; Lim, HyungGyu; Lee, Jang Woo; Seong, Ki Woong; Won, Chul Ho; Kim, Myoung Nam; Cho, Jin Ho; Lee, Jyung Hyun

2014-01-01

Input for fully implantable hearing devices (FIHDs) is provided by an implantable microphone under the skin of the temporal bone. However, the implanted microphone can be affected when the FIHDs user chews. In this paper, a dual implantable microphone was designed that can filter out the noise from mastication. For the in vivo experiment, a fabricated microphone was implanted in a rabbit. Pure-tone sounds of 1 kHz through a standard speaker were applied to the rabbit, which was given food simultaneously. To evaluate noise reduction, the measured signals were processed using a MATLAB program based adaptive filter. To verify the proposed method, the correlation coefficients and signal to-noise ratio before and after signal processing were calculated. By comparing the results, signal-to-noise ratio and correlation coefficients are enhanced by 6.07dB and 0.529 respectively.

Design of a cathodoluminescence image generator using a Raspberry Pi coupled to a scanning electron microscope.

PubMed

Benítez, Alfredo; Santiago, Ulises; Sanchez, John E; Ponce, Arturo

2018-01-01

In this work, an innovative cathodoluminescence (CL) system is coupled to a scanning electron microscope and synchronized with a Raspberry Pi computer integrated with an innovative processing signal. The post-processing signal is based on a Python algorithm that correlates the CL and secondary electron (SE) images with a precise dwell time correction. For CL imaging, the emission signal is collected through an optical fiber and transduced to an electrical signal via a photomultiplier tube (PMT). CL Images are registered in a panchromatic mode and can be filtered using a monochromator connected between the optical fiber and the PMT to produce monochromatic CL images. The designed system has been employed to study ZnO samples prepared by electrical arc discharge and microwave methods. CL images are compared with SE images and chemical elemental mapping images to correlate the emission regions of the sample.

Design of a cathodoluminescence image generator using a Raspberry Pi coupled to a scanning electron microscope

NASA Astrophysics Data System (ADS)

Benítez, Alfredo; Santiago, Ulises; Sanchez, John E.; Ponce, Arturo

2018-01-01

In this work, an innovative cathodoluminescence (CL) system is coupled to a scanning electron microscope and synchronized with a Raspberry Pi computer integrated with an innovative processing signal. The post-processing signal is based on a Python algorithm that correlates the CL and secondary electron (SE) images with a precise dwell time correction. For CL imaging, the emission signal is collected through an optical fiber and transduced to an electrical signal via a photomultiplier tube (PMT). CL Images are registered in a panchromatic mode and can be filtered using a monochromator connected between the optical fiber and the PMT to produce monochromatic CL images. The designed system has been employed to study ZnO samples prepared by electrical arc discharge and microwave methods. CL images are compared with SE images and chemical elemental mapping images to correlate the emission regions of the sample.

Activation of parallel fiber feedback by spatially diffuse stimuli reduces signal and noise correlations via independent mechanisms in a cerebellum-like structure.

PubMed

Simmonds, Benjamin; Chacron, Maurice J

2015-01-01

Correlations between the activities of neighboring neurons are observed ubiquitously across systems and species and are dynamically regulated by several factors such as the stimulus' spatiotemporal extent as well as by the brain's internal state. Using the electrosensory system of gymnotiform weakly electric fish, we recorded the activities of pyramidal cell pairs within the electrosensory lateral line lobe (ELL) under spatially localized and diffuse stimulation. We found that both signal and noise correlations were markedly reduced (>40%) under the latter stimulation. Through a network model incorporating key anatomical features of the ELL, we reveal how activation of diffuse parallel fiber feedback from granule cells by spatially diffuse stimulation can explain both the reduction in signal as well as the reduction in noise correlations seen experimentally through independent mechanisms. First, we show that burst-timing dependent plasticity, which leads to a negative image of the stimulus and thereby reduces single neuron responses, decreases signal but not noise correlations. Second, we show trial-to-trial variability in the responses of single granule cells to sensory input reduces noise but not signal correlations. Thus, our model predicts that the same feedback pathway can simultaneously reduce both signal and noise correlations through independent mechanisms. To test this prediction experimentally, we pharmacologically inactivated parallel fiber feedback onto ELL pyramidal cells. In agreement with modeling predictions, we found that inactivation increased both signal and noise correlations but that there was no significant relationship between magnitude of the increase in signal correlations and the magnitude of the increase in noise correlations. The mechanisms reported in this study are expected to be generally applicable to the cerebellum as well as other cerebellum-like structures. We further discuss the implications of such decorrelation on the neural coding strategies used by the electrosensory and by other systems to process natural stimuli.

Reward value comparison via mutual inhibition in ventromedial prefrontal cortex

PubMed Central

Strait, Caleb E.; Blanchard, Tommy C.; Hayden, Benjamin Y.

2014-01-01

Recent theories suggest that reward-based choice reflects competition between value signals in the ventromedial prefrontal cortex (vmPFC). We tested this idea by recording vmPFC neurons while macaques performed a gambling task with asynchronous offer presentation. We found that neuronal activity shows four patterns consistent with selection via mutual inhibition. (1) Correlated tuning for probability and reward size, suggesting that vmPFC carries an integrated value signal, (2) anti-correlated tuning curves for the two options, suggesting mutual inhibition, (3) neurons rapidly come to signal the value of the chosen offer, suggesting the circuit serves to produce a choice, (4) after regressing out the effects of option values, firing rates still could predict choice – a choice probability signal. In addition, neurons signaled gamble outcomes, suggesting that vmPFC contributes to both monitoring and choice processes. These data suggest a possible mechanism for reward-based choice and endorse the centrality of vmPFC in that process. PMID:24881835

Analysis of cutting force signals by wavelet packet transform for surface roughness monitoring in CNC turning

NASA Astrophysics Data System (ADS)

García Plaza, E.; Núñez López, P. J.

2018-01-01

On-line monitoring of surface finish in machining processes has proven to be a substantial advancement over traditional post-process quality control techniques by reducing inspection times and costs and by avoiding the manufacture of defective products. This study applied techniques for processing cutting force signals based on the wavelet packet transform (WPT) method for the monitoring of surface finish in computer numerical control (CNC) turning operations. The behaviour of 40 mother wavelets was analysed using three techniques: global packet analysis (G-WPT), and the application of two packet reduction criteria: maximum energy (E-WPT) and maximum entropy (SE-WPT). The optimum signal decomposition level (Lj) was determined to eliminate noise and to obtain information correlated to surface finish. The results obtained with the G-WPT method provided an in-depth analysis of cutting force signals, and frequency ranges and signal characteristics were correlated to surface finish with excellent results in the accuracy and reliability of the predictive models. The radial and tangential cutting force components at low frequency provided most of the information for the monitoring of surface finish. The E-WPT and SE-WPT packet reduction criteria substantially reduced signal processing time, but at the expense of discarding packets with relevant information, which impoverished the results. The G-WPT method was observed to be an ideal procedure for processing cutting force signals applied to the real-time monitoring of surface finish, and was estimated to be highly accurate and reliable at a low analytical-computational cost.

Global scale stratospheric processes as measured by the infrasound IMS network

NASA Astrophysics Data System (ADS)

Le Pichon, A.; Ceranna, L.; Kechut, P.

2012-04-01

IMS infrasound array data are routinely processed at the International Data Center (IDC). The wave parameters of the detected signals are estimated with the Progressive Multi-Channel Correlation method (PMCC). This new implementation of the PMCC algorithm allows the full frequency range of interest (0.01-5 Hz) to be processed efficiently in a single computational run. We have processed continuous recordings from 41 certified IMS stations from 2005 to 2010. We show that microbaroms are the dominant source of signals and are near-continuously globally detected. The observed azimuthal seasonal trend correlates well with the variation of the effective sound speed ratio which is a proxy for the combined effects of refraction due to sound speed gradients and advection due to along-path wind on infrasound propagation. A general trend in signal backazimuth is observed between winter and summer, driven by the seasonal reversal of the stratospheric winds. Combined with propagation modeling, we show that such an analysis enables a characterization of the wind and temperature structure above the stratosphere and may provide detailed information on upper atmospheric processes (e.g., large-scale planetary waves, stratospheric warming effects). We correlate perturbations and deviations from the seasonal trend to short time-scale variability of the atmosphere. We discuss the potential benefit of long-term infrasound monitoring to infer stratospheric processes for the first time on a global scale.

Recirculating cross-correlation detector

DOEpatents

Andrews, W.H. Jr.; Roberts, M.J.

1985-01-18

A digital cross-correlation detector is provided in which two time-varying signals are correlated by repetitively comparing data samples stored in digital form to detect correlation between the two signals. The signals are sampled at a selected rate converted to digital form, and stored in separate locations in separate memories. When the memories are filled, the data samples from each memory are first fed word-by-word through a multiplier and summing circuit and each result is compared to the last in a peak memory circuit and if larger than the last is retained in the peak memory. Then the address line to leading signal memory is offset by one byte to affect one sample period delay of a known amount in that memory and the data in the two memories are then multiplied word-by-word once again and summed. If a new result is larger than a former sum, it is saved in the peak memory together with the time delay. The recirculating process continues with the address of the one memory being offset one additional byte each cycle until the address is shifted through the length of the memory. The correlation between the two signals is indicated by the peak signal stored in the peak memory together with the delay time at which the peak occurred. The circuit is faster and considerably less expensive than comparable accuracy correlation detectors.

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

PubMed

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

2012-10-15

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. Copyright © 2012 Elsevier Inc. All rights reserved.

Ultralow-Power Digital Correlator for Microwave Polarimetry

NASA Technical Reports Server (NTRS)

Piepmeier, Jeffrey R.; Hass, K. Joseph

2004-01-01

A recently developed high-speed digital correlator is especially well suited for processing readings of a passive microwave polarimeter. This circuit computes the autocorrelations of, and the cross-correlations among, data in four digital input streams representing samples of in-phase (I) and quadrature (Q) components of two intermediate-frequency (IF) signals, denoted A and B, that are generated in heterodyne reception of two microwave signals. The IF signals arriving at the correlator input terminals have been digitized to three levels (-1,0,1) at a sampling rate up to 500 MHz. Two bits (representing sign and magnitude) are needed to represent the instantaneous datum in each input channel; hence, eight bits are needed to represent the four input signals during any given cycle of the sampling clock. The accumulation (integration) time for the correlation is programmable in increments of 2(exp 8) cycles of the sampling clock, up to a maximum of 2(exp 24) cycles. The basic functionality of the correlator is embodied in 16 correlation slices, each of which contains identical logic circuits and counters (see figure). The first stage of each correlation slice is a logic gate that computes one of the desired correlations (for example, the autocorrelation of the I component of A or the negative of the cross-correlation of the I component of A and the Q component of B). The sampling of the output of the logic gate output is controlled by the sampling-clock signal, and an 8-bit counter increments in every clock cycle when the logic gate generates output. The most significant bit of the 8-bit counter is sampled by a 16-bit counter with a clock signal at 2(exp 8) the frequency of the sampling clock. The 16-bit counter is incremented every time the 8-bit counter rolls over.

Process control system using polarizing interferometer

DOEpatents

Schultz, T.J.; Kotidis, P.A.; Woodroffe, J.A.; Rostler, P.S.

1994-02-15

A system for nondestructively measuring an object and controlling industrial processes in response to the measurement is disclosed in which an impulse laser generates a plurality of sound waves over timed increments in an object. A polarizing interferometer is used to measure surface movement of the object caused by the sound waves and sensed by phase shifts in the signal beam. A photon multiplier senses the phase shift and develops an electrical signal. A signal conditioning arrangement modifies the electrical signals to generate an average signal correlated to the sound waves which in turn is correlated to a physical or metallurgical property of the object, such as temperature, which property may then be used to control the process. External, random vibrations of the workpiece are utilized to develop discernible signals which can be sensed in the interferometer by only one photon multiplier. In addition the interferometer includes an arrangement for optimizing its sensitivity so that movement attributed to various waves can be detected in opaque objects. The interferometer also includes a mechanism for sensing objects with rough surfaces which produce speckle light patterns. Finally the interferometer per se, with the addition of a second photon multiplier is capable of accurately recording beam length distance differences with only one reading. 38 figures.

Process control system using polarizing interferometer

DOEpatents

Schultz, Thomas J.; Kotidis, Petros A.; Woodroffe, Jaime A.; Rostler, Peter S.

1994-01-01

A system for non-destructively measuring an object and controlling industrial processes in response to the measurement is disclosed in which an impulse laser generates a plurality of sound waves over timed increments in an object. A polarizing interferometer is used to measure surface movement of the object caused by the sound waves and sensed by phase shifts in the signal beam. A photon multiplier senses the phase shift and develops an electrical signal. A signal conditioning arrangement modifies the electrical signals to generate an average signal correlated to the sound waves which in turn is correlated to a physical or metallurgical property of the object, such as temperature, which property may then be used to control the process. External, random vibrations of the workpiece are utilized to develop discernible signals which can be sensed in the interferometer by only one photon multiplier. In addition the interferometer includes an arrangement for optimizing its sensitivity so that movement attributed to various waves can be detected in opaque objects. The interferometer also includes a mechanism for sensing objects with rough surfaces which produce speckle light patterns. Finally the interferometer per se, with the addition of a second photon multiplier is capable of accurately recording beam length distance differences with only one reading.

A method of noise reduction in heterodyne interferometric vibration metrology by combining auto-correlation analysis and spectral filtering

NASA Astrophysics Data System (ADS)

Hao, Hongliang; Xiao, Wen; Chen, Zonghui; Ma, Lan; Pan, Feng

2018-01-01

Heterodyne interferometric vibration metrology is a useful technique for dynamic displacement and velocity measurement as it can provide a synchronous full-field output signal. With the advent of cost effective, high-speed real-time signal processing systems and software, processing of the complex signals encountered in interferometry has become more feasible. However, due to the coherent nature of the laser sources, the sequence of heterodyne interferogram are corrupted by a mixture of coherent speckle and incoherent additive noise, which can severely degrade the accuracy of the demodulated signal and the optical display. In this paper, a new heterodyne interferometric demodulation method by combining auto-correlation analysis and spectral filtering is described leading to an expression for the dynamic displacement and velocity of the object under test that is significantly more accurate in both the amplitude and frequency of the vibrating waveform. We present a mathematical model of the signals obtained from interferograms that contain both vibration information of the measured objects and the noise. A simulation of the signal demodulation process is presented and used to investigate the noise from the system and external factors. The experimental results show excellent agreement with measurements from a commercial Laser Doppler Velocimetry (LDV).

Surveillance system and method having parameter estimation and operating mode partitioning

NASA Technical Reports Server (NTRS)

Bickford, Randall L. (Inventor)

2005-01-01

A system and method for monitoring an apparatus or process asset including creating a process model comprised of a plurality of process submodels each correlative to at least one training data subset partitioned from an unpartitioned training data set and each having an operating mode associated thereto; acquiring a set of observed signal data values from the asset; determining an operating mode of the asset for the set of observed signal data values; selecting a process submodel from the process model as a function of the determined operating mode of the asset; calculating a set of estimated signal data values from the selected process submodel for the determined operating mode; and determining asset status as a function of the calculated set of estimated signal data values for providing asset surveillance and/or control.

Digital processing of array seismic recordings

USGS Publications Warehouse

Ryall, Alan; Birtill, John

1962-01-01

This technical letter contains a brief review of the operations which are involved in digital processing of array seismic recordings by the methods of velocity filtering, summation, cross-multiplication and integration, and by combinations of these operations (the "UK Method" and multiple correlation). Examples are presented of analyses by the several techniques on array recordings which were obtained by the U.S. Geological Survey during chemical and nuclear explosions in the western United States. Seismograms are synthesized using actual noise and Pn-signal recordings, such that the signal-to-noise ratio, onset time and velocity of the signal are predetermined for the synthetic record. These records are then analyzed by summation, cross-multiplication, multiple correlation and the UK technique, and the results are compared. For all of the examples presented, analysis by the non-linear techniques of multiple correlation and cross-multiplication of the traces on an array recording are preferred to analyses by the linear operations involved in summation and the UK Method.

Multi-template image matching using alpha-rooted biquaternion phase correlation with application to logo recognition

NASA Astrophysics Data System (ADS)

DelMarco, Stephen

2011-06-01

Hypercomplex approaches are seeing increased application to signal and image processing problems. The use of multicomponent hypercomplex numbers, such as quaternions, enables the simultaneous co-processing of multiple signal or image components. This joint processing capability can provide improved exploitation of the information contained in the data, thereby leading to improved performance in detection and recognition problems. In this paper, we apply hypercomplex processing techniques to the logo image recognition problem. Specifically, we develop an image matcher by generalizing classical phase correlation to the biquaternion case. We further incorporate biquaternion Fourier domain alpha-rooting enhancement to create Alpha-Rooted Biquaternion Phase Correlation (ARBPC). We present the mathematical properties which justify use of ARBPC as an image matcher. We present numerical performance results of a logo verification problem using real-world logo data, demonstrating the performance improvement obtained using the hypercomplex approach. We compare results of the hypercomplex approach to standard multi-template matching approaches.

Evaluation of arterial stiffness by finger-toe pulse wave velocity: optimization of signal processing and clinical validation.

PubMed

Obeid, Hasan; Khettab, Hakim; Marais, Louise; Hallab, Magid; Laurent, Stéphane; Boutouyrie, Pierre

2017-08-01

Carotid-femoral pulse wave velocity (PWV) (cf-PWV) is the gold standard for measuring aortic stiffness. Finger-toe PWV (ft-PWV) is a simpler noninvasive method for measuring arterial stiffness. Although the validity of the method has been previously assessed, its accuracy can be improved. ft-PWV is determined on the basis of a patented height chart for the distance and the pulse transit time (PTT) between the finger and the toe pulpar arteries signals (ft-PTT). The objective of the first study, performed in 66 patients, was to compare different algorithms (intersecting tangents, maximum of the second derivative, 10% threshold and cross-correlation) for determining the foot of the arterial pulse wave, thus the ft-PTT. The objective of the second study, performed in 101 patients, was to investigate different signal processing chains to improve the concordance of ft-PWV with the gold-standard cf-PWV. Finger-toe PWV (ft-PWV) was calculated using the four algorithms. The best correlations relating ft-PWV and cf-PWV, and relating ft-PTT and carotid-femoral PTT were obtained with the maximum of the second derivative algorithm [PWV: r = 0.56, P < 0.0001, root mean square error (RMSE) = 0.9 m/s; PTT: r = 0.61, P < 0.001, RMSE = 12 ms]. The three other algorithms showed lower correlations. The correlation between ft-PTT and carotid-femoral PTT further improved (r = 0.81, P < 0.0001, RMSE = 5.4 ms) when the maximum of the second derivative algorithm was combined with an optimized signal processing chain. Selecting the maximum of the second derivative algorithm for detecting the foot of the pressure waveform, and combining it with an optimized signal processing chain, improved the accuracy of ft-PWV measurement in the current population sample. Thus, it makes ft-PWV very promising for the simple noninvasive determination of aortic stiffness in clinical practice.

Method and apparatus for measuring flow velocity using matched filters

DOEpatents

Raptis, Apostolos C.

1983-01-01

An apparatus and method for measuring the flow velocities of individual phase flow components of a multiphase flow utilizes matched filters. Signals arising from flow noise disturbance are extracted from the flow, at upstream and downstream locations. The signals are processed through pairs of matched filters which are matched to the flow disturbance frequency characteristics of the phase flow component to be measured. The processed signals are then cross-correlated to determine the transit delay time of the phase flow component between sensing positions.

Mastication noise reduction method for fully implantable hearing aid using piezo-electric sensor.

PubMed

Na, Sung Dae; Lee, Gihyoun; Wei, Qun; Seong, Ki Woong; Cho, Jin Ho; Kim, Myoung Nam

2017-07-20

Fully implantable hearing devices (FIHDs) can be affected by generated biomechanical noise such as mastication noise. To reduce the mastication noise using a piezo-electric sensor, the mastication noise is measured with the piezo-electric sensor, and noise reduction is practiced by the energy difference. For the experiment on mastication noise, a skull model was designed using artificial skull model and a piezo-electric sensor that can measure the vibration signals better than other sensors. A 1 kHz pure-tone sound through a standard speaker was applied to the model while the lower jawbone of the model was moved in a masticatory fashion. The correlation coefficients and signal-to-noise ratio (SNR) before and after application of the proposed method were compared. It was found that the signal-to-noise ratio and correlation coefficients increased by 4.48 dB and 0.45, respectively. The mastication noise is measured by piezo-electric sensor as the mastication noise that occurred during vibration. In addition, the noise was reduced by using the proposed method in conjunction with MATLAB. In order to confirm the performance of the proposed method, the correlation coefficients and signal-to-noise ratio before and after signal processing were calculated. In the future, an implantable microphone for real-time processing will be developed.

Correlation analysis of motor current and chatter vibration in grinding using complex continuous wavelet coherence

NASA Astrophysics Data System (ADS)

Liu, Yao; Wang, Xiufeng; Lin, Jing; Zhao, Wei

2016-11-01

Motor current is an emerging and popular signal which can be used to detect machining chatter with its multiple advantages. To achieve accurate and reliable chatter detection using motor current, it is important to make clear the quantitative relationship between motor current and chatter vibration, which has not yet been studied clearly. In this study, complex continuous wavelet coherence, including cross wavelet transform and wavelet coherence, is applied to the correlation analysis of motor current and chatter vibration in grinding. Experimental results show that complex continuous wavelet coherence performs very well in demonstrating and quantifying the intense correlation between these two signals in frequency, amplitude and phase. When chatter occurs, clear correlations in frequency and amplitude in the chatter frequency band appear and the phase difference of current signal to vibration signal turns from random to stable. The phase lead of the most correlated chatter frequency is the largest. With the further development of chatter, the correlation grows up in intensity and expands to higher order chatter frequency band. The analyzing results confirm that there is a consistent correlation between motor current and vibration signals in the grinding chatter process. However, to achieve accurate and reliable chatter detection using motor current, the frequency response bandwidth of current loop of the feed drive system must be wide enough to response chatter effectively.

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

PubMed

Elo, Hannu; Kuure, Matti; Pelttari, Eila

2015-03-06

Certain substituted salicylaldehydes are potent antibacterial and antifungal agents and some of them merit consideration as potential chemotherapeutic agents against Candida infections, but their mechanism of action has remained obscure. We report here a distinct correlation between broadening of the NMR signal of the hydroxyl proton of salicylaldehydes and their activity against several types of bacteria and fungi. When proton NMR spectra of the compounds were determined using hexadeuterodimethylsulfoxide as solvent and the height of the OH proton signal was measured, using the signal of the aldehyde proton as an internal standard, it was discovered that a prerequisite of potent antimicrobial activity is that the proton signal is either unobservable or relatively very low, i.e. that it is extremely broadened. Thus, none of the congeners whose OH proton signal was high were potent antimicrobial agents. Some congeners that gave a very low OH signal were, however, essentially inactive against the microbes, indicating that although drastic broadening of the OH signal appears to be a prerequisite, also other (so far unknown) factors are needed for high antimicrobial activity. Because broadening of the hydroxyl proton signal is related to the speed of the proton exchange process(es) involving that proton, proton exchange may be involved in the mechanism of action of the compounds. Further studies are needed to analyze the relative importance of different factors (such as electronic effects, strength of the internal hydrogen bond, co-planarity of the ring and the formyl group) that determine the rates of those processes. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Real-Time EEG Signal Enhancement Using Canonical Correlation Analysis and Gaussian Mixture Clustering

PubMed Central

Huang, Chih-Sheng; Yang, Wen-Yu; Chuang, Chun-Hsiang; Wang, Yu-Kai

2018-01-01

Electroencephalogram (EEG) signals are usually contaminated with various artifacts, such as signal associated with muscle activity, eye movement, and body motion, which have a noncerebral origin. The amplitude of such artifacts is larger than that of the electrical activity of the brain, so they mask the cortical signals of interest, resulting in biased analysis and interpretation. Several blind source separation methods have been developed to remove artifacts from the EEG recordings. However, the iterative process for measuring separation within multichannel recordings is computationally intractable. Moreover, manually excluding the artifact components requires a time-consuming offline process. This work proposes a real-time artifact removal algorithm that is based on canonical correlation analysis (CCA), feature extraction, and the Gaussian mixture model (GMM) to improve the quality of EEG signals. The CCA was used to decompose EEG signals into components followed by feature extraction to extract representative features and GMM to cluster these features into groups to recognize and remove artifacts. The feasibility of the proposed algorithm was demonstrated by effectively removing artifacts caused by blinks, head/body movement, and chewing from EEG recordings while preserving the temporal and spectral characteristics of the signals that are important to cognitive research. PMID:29599950

An open-loop system design for deep space signal processing applications

NASA Astrophysics Data System (ADS)

Tang, Jifei; Xia, Lanhua; Mahapatra, Rabi

2018-06-01

A novel open-loop system design with high performance is proposed for space positioning and navigation signal processing. Divided by functions, the system has four modules, bandwidth selectable data recorder, narrowband signal analyzer, time-delay difference of arrival estimator and ANFIS supplement processor. A hardware-software co-design approach is made to accelerate computing capability and improve system efficiency. Embedded with the proposed signal processing algorithms, the designed system is capable of handling tasks with high accuracy over long period of continuous measurements. The experiment results show the Doppler frequency tracking root mean square error during 3 h observation is 0.0128 Hz, while the TDOA residue analysis in correlation power spectrum is 0.1166 rad.

Signal Processing Studies of a Simulated Laser Doppler Velocimetry-Based Acoustic Sensor

DTIC Science & Technology

1990-10-17

investigated using spectral correlation methods. Results indicate that it may be possible to extend demonstrated LDV-based acoustic sensor sensitivities using higher order processing techniques. (Author)

Signal processing: opportunities for superconductive circuits

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ralston, R.W.

1985-03-01

Prime motivators in the evolution of increasingly sophisticated communication and detection systems are the needs for handling ever wider signal bandwidths and higher data processing speeds. These same needs drive the development of electronic device technology. Until recently the superconductive community has been tightly focused on digital devices for high speed computers. The purpose of this paper is to describe opportunities and challenges which exist for both analog and digital devices in a less familiar area, that of wideband signal processing. The function and purpose of analog signal-processing components, including matched filters, correlators and Fourier transformers, will be described andmore » examples of superconductive implementations given. A canonic signal-processing system is then configured using these components in combination with analog/digital converters and digital output circuits to highlight the important issues of dynamic range, accuracy and equivalent computation rate. Superconductive circuits hold promise for processing signals of 10-GHz bandwidth. Signal processing systems, however, can be properly designed and implemented only through a synergistic combination of the talents of device physicists, circuit designers, algorithm architects and system engineers. An immediate challenge to the applied superconductivity community is to begin sharing ideas with these other researchers.« less

Signal Processing for Determining Water Height in Steam Pipes with Dynamic Surface Conditions

NASA Technical Reports Server (NTRS)

Lih, Shyh-Shiuh; Lee, Hyeong Jae; Bar-Cohen, Yoseph

2015-01-01

An enhanced signal processing method based on the filtered Hilbert envelope of the auto-correlation function of the wave signal has been developed to monitor the height of condensed water through the steel wall of steam pipes with dynamic surface conditions. The developed signal processing algorithm can also be used to estimate the thickness of the pipe to determine the cut-off frequency for the low pass filter frequency of the Hilbert Envelope. Testing and analysis results by using the developed technique for dynamic surface conditions are presented. A multiple array of transducers setup and methodology are proposed for both the pulse-echo and pitch-catch signals to monitor the fluctuation of the water height due to disturbance, water flow, and other anomaly conditions.

Analysis of the sleep quality of elderly people using biomedical signals.

PubMed

Moreno-Alsasua, L; Garcia-Zapirain, B; Mendez-Zorrilla, A

2015-01-01

This paper presents a technical solution that analyses sleep signals captured by biomedical sensors to find possible disorders during rest. Specifically, the method evaluates electrooculogram (EOG) signals, skin conductance (GSR), air flow (AS), and body temperature. Next, a quantitative sleep quality analysis determines significant changes in the biological signals, and any similarities between them in a given time period. Filtering techniques such as the Fourier transform method and IIR filters process the signal and identify significant variations. Once these changes have been identified, all significant data is compared and a quantitative and statistical analysis is carried out to determine the level of a person's rest. To evaluate the correlation and significant differences, a statistical analysis has been calculated showing correlation between EOG and AS signals (p=0,005), EOG, and GSR signals (p=0,037) and, finally, the EOG and Body temperature (p=0,04). Doctors could use this information to monitor changes within a patient.

Quantifying two-dimensional nonstationary signal with power-law correlations by detrended fluctuation analysis

NASA Astrophysics Data System (ADS)

Fan, Qingju; Wu, Yonghong

2015-08-01

In this paper, we develop a new method for the multifractal characterization of two-dimensional nonstationary signal, which is based on the detrended fluctuation analysis (DFA). By applying to two artificially generated signals of two-component ARFIMA process and binomial multifractal model, we show that the new method can reliably determine the multifractal scaling behavior of two-dimensional signal. We also illustrate the applications of this method in finance and physiology. The analyzing results exhibit that the two-dimensional signals under investigation are power-law correlations, and the electricity market consists of electricity price and trading volume is multifractal, while the two-dimensional EEG signal in sleep recorded for a single patient is weak multifractal. The new method based on the detrended fluctuation analysis may add diagnostic power to existing statistical methods.

A UWB Radar Signal Processing Platform for Real-Time Human Respiratory Feature Extraction Based on Four-Segment Linear Waveform Model.

PubMed

Hsieh, Chi-Hsuan; Chiu, Yu-Fang; Shen, Yi-Hsiang; Chu, Ta-Shun; Huang, Yuan-Hao

2016-02-01

This paper presents an ultra-wideband (UWB) impulse-radio radar signal processing platform used to analyze human respiratory features. Conventional radar systems used in human detection only analyze human respiration rates or the response of a target. However, additional respiratory signal information is available that has not been explored using radar detection. The authors previously proposed a modified raised cosine waveform (MRCW) respiration model and an iterative correlation search algorithm that could acquire additional respiratory features such as the inspiration and expiration speeds, respiration intensity, and respiration holding ratio. To realize real-time respiratory feature extraction by using the proposed UWB signal processing platform, this paper proposes a new four-segment linear waveform (FSLW) respiration model. This model offers a superior fit to the measured respiration signal compared with the MRCW model and decreases the computational complexity of feature extraction. In addition, an early-terminated iterative correlation search algorithm is presented, substantially decreasing the computational complexity and yielding negligible performance degradation. These extracted features can be considered the compressed signals used to decrease the amount of data storage required for use in long-term medical monitoring systems and can also be used in clinical diagnosis. The proposed respiratory feature extraction algorithm was designed and implemented using the proposed UWB radar signal processing platform including a radar front-end chip and an FPGA chip. The proposed radar system can detect human respiration rates at 0.1 to 1 Hz and facilitates the real-time analysis of the respiratory features of each respiration period.

Method and apparatus for improving resolution in spectrometers processing output steps from non-ideal signal sources

DOEpatents

Warburton, William K.; Momayezi, Michael

2006-06-20

A method and apparatus for processing step-like output signals (primary signals) generated by non-ideal, for example, nominally single-pole ("N-1P ") devices. An exemplary method includes creating a set of secondary signals by directing the primary signal along a plurality of signal paths to a signal summation point, summing the secondary signals reaching the signal summation point after propagating along the signal paths to provide a summed signal, performing a filtering or delaying operation in at least one of said signal paths so that the secondary signals reaching said summing point have a defined time correlation with respect to one another, applying a set of weighting coefficients to the secondary signals propagating along said signal paths, and performing a capturing operation after any filtering or delaying operations so as to provide a weighted signal sum value as a measure of the integrated area Q_gT of the input signal.

Fiber fault location utilizing traffic signal in optical network.

PubMed

Zhao, Tong; Wang, Anbang; Wang, Yuncai; Zhang, Mingjiang; Chang, Xiaoming; Xiong, Lijuan; Hao, Yi

2013-10-07

We propose and experimentally demonstrate a method for fault location in optical communication network. This method utilizes the traffic signal transmitted across the network as probe signal, and then locates the fault by correlation technique. Compared with conventional techniques, our method has a simple structure and low operation expenditure, because no additional device is used, such as light source, modulator and signal generator. The correlation detection in this method overcomes the tradeoff between spatial resolution and measurement range in pulse ranging technique. Moreover, signal extraction process can improve the location result considerably. Experimental results show that we achieve a spatial resolution of 8 cm and detection range of over 23 km with -8-dBm mean launched power in optical network based on synchronous digital hierarchy protocols.

Gravitational wave searches with pulsar timing arrays: Cancellation of clock and ephemeris noises

NASA Astrophysics Data System (ADS)

Tinto, Massimo

2018-04-01

We propose a data processing technique to cancel monopole and dipole noise sources (such as clock and ephemeris noises, respectively) in pulsar timing array searches for gravitational radiation. These noises are the dominant sources of correlated timing fluctuations in the lower-part (≈10-9-10-8 Hz ) of the gravitational wave band accessible by pulsar timing experiments. After deriving the expressions that reconstruct these noises from the timing data, we estimate the gravitational wave sensitivity of our proposed processing technique to single-source signals to be at least one order of magnitude higher than that achievable by directly processing the timing data from an equal-size array. Since arrays can generate pairs of clock and ephemeris-free timing combinations that are no longer affected by correlated noises, we implement with them the cross-correlation statistic to search for an isotropic stochastic gravitational wave background. We find the resulting optimal signal-to-noise ratio to be more than one order of magnitude larger than that obtainable by correlating pairs of timing data from arrays of equal size.

Acoustic Signal Processing in Photorefractive Optical Systems.

NASA Astrophysics Data System (ADS)

Zhou, Gan

This thesis discusses applications of the photorefractive effect in the context of acoustic signal processing. The devices and systems presented here illustrate the ideas and optical principles involved in holographic processing of acoustic information. The interest in optical processing stems from the similarities between holographic optical systems and contemporary models for massively parallel computation, in particular, neural networks. An initial step in acoustic processing is the transformation of acoustic signals into relevant optical forms. A fiber-optic transducer with photorefractive readout transforms acoustic signals into optical images corresponding to their short-time spectrum. The device analyzes complex sound signals and interfaces them with conventional optical correlators. The transducer consists of 130 multimode optical fibers sampling the spectral range of 100 Hz to 5 kHz logarithmically. A physical model of the human cochlea can help us understand some characteristics of human acoustic transduction and signal representation. We construct a life-sized cochlear model using elastic membranes coupled with two fluid-filled chambers, and use a photorefractive novelty filter to investigate its response. The detection sensitivity is determined to be 0.3 angstroms per root Hz at 2 kHz. Qualitative agreement is found between the model response and physiological data. Delay lines map time-domain signals into space -domain and permit holographic processing of temporal information. A parallel optical delay line using dynamic beam coupling in a rotating photorefractive crystal is presented. We experimentally demonstrate a 64 channel device with 0.5 seconds of time-delay and 167 Hz bandwidth. Acoustic signal recognition is described in a photorefractive system implementing the time-delay neural network model. The system consists of a photorefractive optical delay-line and a holographic correlator programmed in a LiNbO_3 crystal. We demonstrate the recognition of synthesized chirps as well as spoken words. A photorefractive ring resonator containing an optical delay line can learn temporal information through self-organization. We experimentally investigate a system that learns by itself and picks out the most-frequently -presented signals from the input. We also give results demonstrating the separation of two orthogonal temporal signals into two competing ring resonators.

A canonical correlation analysis based EMG classification algorithm for eliminating electrode shift effect.

PubMed

Zhe Fan; Zhong Wang; Guanglin Li; Ruomei Wang

2016-08-01

Motion classification system based on surface Electromyography (sEMG) pattern recognition has achieved good results in experimental condition. But it is still a challenge for clinical implement and practical application. Many factors contribute to the difficulty of clinical use of the EMG based dexterous control. The most obvious and important is the noise in the EMG signal caused by electrode shift, muscle fatigue, motion artifact, inherent instability of signal and biological signals such as Electrocardiogram. In this paper, a novel method based on Canonical Correlation Analysis (CCA) was developed to eliminate the reduction of classification accuracy caused by electrode shift. The average classification accuracy of our method were above 95% for the healthy subjects. In the process, we validated the influence of electrode shift on motion classification accuracy and discovered the strong correlation with correlation coefficient of >0.9 between shift position data and normal position data.

New instrument for on-line viscosity measurement of fermentation media.

PubMed

Picque, D; Corrieu, G

1988-01-01

In an attempt to resolve the difficult problem of on-line determination of the viscosity of non-Newtonian fermentation media, the authors have used a vibrating rod sensor mounted on a bioreactor. The sensor signal decreases nonlinearly with increased apparent viscosity. Electronic filtering of the signal damps the interfering effect of aeration and mechanical agitation. Sensor drift is very low (0.03% of measured value per hour). On the rheological level the sensor is primarily an empirical tool that must be specifically calibrated for each fermentation process. Once this is accomplished, it becomes possible to establish linear or second-degree correlations between the electrical signal from the sensor and the essential parameters of the fermentation process in question (pH of a fermented milk during acidification, concentration of extra cellular polysaccharide). In addition, by applying the power law to describe the rheological behavior of fermentation media, we observe a second-order polynomial correlation between the sensor signal and the behavior index (n).

Full-field wrist pulse signal acquisition and analysis by 3D Digital Image Correlation

NASA Astrophysics Data System (ADS)

Xue, Yuan; Su, Yong; Zhang, Chi; Xu, Xiaohai; Gao, Zeren; Wu, Shangquan; Zhang, Qingchuan; Wu, Xiaoping

2017-11-01

Pulse diagnosis is an essential part in four basic diagnostic methods (inspection, listening, inquiring and palpation) in traditional Chinese medicine, which depends on longtime training and rich experience, so computerized pulse acquisition has been proposed and studied to ensure the objectivity. To imitate the process that doctors using three fingertips with different pressures to feel fluctuations in certain areas containing three acupoints, we established a five dimensional pulse signal acquisition system adopting a non-contacting optical metrology method, 3D digital image correlation, to record the full-field displacements of skin fluctuations under different pressures. The system realizes real-time full-field vibration mode observation with 10 FPS. The maximum sample frequency is 472 Hz for detailed post-processing. After acquisition, the signals are analyzed according to the amplitude, pressure, and pulse wave velocity. The proposed system provides a novel optical approach for digitalizing pulse diagnosis and massive pulse signal data acquisition for various types of patients.

The high frequency characteristics of laser reflection and visible light during solid state disk laser welding

NASA Astrophysics Data System (ADS)

Gao, Xiangdong; You, Deyong; Katayama, Seiji

2015-07-01

Optical properties are related to weld quality during laser welding. Visible light radiation generated from optical-induced plasma and laser reflection is considered a key element reflecting weld quality. An in-depth analysis of the high-frequency component of optical signals is conducted. A combination of a photoelectric sensor and an optical filter helped to obtain visible light reflection and laser reflection in the welding process. Two groups of optical signals were sampled at a high sampling rate (250 kHz) using an oscilloscope. Frequencies in the ranges 1-10 kHz and 10-125 kHz were investigated respectively. Experimental results showed that there was an obvious correlation between the high-frequency signal and the laser power, while the high-frequency signal was not sensitive to changes in welding speed. In particular, when the defocus position was changed, only a high frequency of the visible light signal was observed, while the high frequency of the laser reflection signal remained unchanged. The basic correlation between optical features and welding status during the laser welding process is specified, which helps to provide a new research focus for investigating the stability of welding status.

The VLBA correlator: Real-time in the distributed era

NASA Technical Reports Server (NTRS)

Wells, D. C.

1992-01-01

The correlator is the signal processing engine of the Very Long Baseline Array (VLBA). Radio signals are recorded on special wideband (128 Mb/s) digital recorders at the 10 telescopes, with sampling times controlled by hydrogen maser clocks. The magnetic tapes are shipped to the Array Operations Center in Socorro, New Mexico, where they are played back simultaneously into the correlator. Real-time software and firmware controls the playback drives to achieve synchronization, compute models of the wavefront delay, control the numerous modules of the correlator, and record FITS files of the fringe visibilities at the back-end of the correlator. In addition to the more than 3000 custom VLSI chips which handle the massive data flow of the signal processing, the correlator contains a total of more than 100 programmable computers, 8-, 16- and 32-bit CPUs. Code is downloaded into front-end CPU's dependent on operating mode. Low-level code is assembly language, high-level code is C running under a RT OS. We use VxWorks on Motorola MVME147 CPU's. Code development is on a complex of SPARC workstations connected to the RT CPU's by Ethernet. The overall management of the correlation process is dependent on a database management system. We use Ingres running on a Sparcstation-2. We transfer logging information from the database of the VLBA Monitor and Control System to our database using Ingres/NET. Job scripts are computed and are transferred to the real-time computers using NFS, and correlation job execution logs and status flow back by the route. Operator status and control displays use windows on workstations, interfaced to the real-time processes by network protocols. The extensive network protocol support provided by VxWorks is invaluable. The VLBA Correlator's dependence on network protocols is an example of the radical transformation of the real-time world over the past five years. Real-time is becoming more like conventional computing. Paradoxically, 'conventional' computing is also adopting practices from the real-time world: semaphores, shared memory, light-weight threads, and concurrency. This appears to be a convergence of thinking.

Error reduction study employing a pseudo-random binary sequence for use in acoustic pyrometry of gases

NASA Astrophysics Data System (ADS)

Ewan, B. C. R.; Ireland, S. N.

2000-12-01

Acoustic pyrometry uses the temperature dependence of sound speed in materials to measure temperature. This is normally achieved by measuring the transit time for a sound signal over a known path length and applying the material relation between temperature and velocity to extract an "average" temperature. Sources of error associated with the measurement of mean transit time are discussed in implementing the technique in gases, one of the principal causes being background noise in typical industrial environments. A number of transmitted signal and processing strategies which can be used in the area are examined and the expected error in mean transit time associated with each technique is quantified. Transmitted signals included pulses, pure frequencies, chirps, and pseudorandom binary sequences (prbs), while processing involves edge detection and correlation. Errors arise through the misinterpretation of the positions of edge arrival or correlation peaks due to instantaneous deviations associated with background noise and these become more severe as signal to noise amplitude ratios decrease. Population errors in the mean transit time are estimated for the different measurement strategies and it is concluded that PRBS combined with correlation can provide the lowest errors when operating in high noise environments. The operation of an instrument based on PRBS transmitted signals is described and test results under controlled noise conditions are presented. These confirm the value of the strategy and demonstrate that measurements can be made with signal to noise amplitude ratios down to 0.5.

Method and apparatus for measuring flow velocity using matched filters

DOEpatents

Raptis, A.C.

1983-09-06

An apparatus and method for measuring the flow velocities of individual phase flow components of a multiphase flow utilizes matched filters. Signals arising from flow noise disturbance are extracted from the flow, at upstream and downstream locations. The signals are processed through pairs of matched filters which are matched to the flow disturbance frequency characteristics of the phase flow component to be measured. The processed signals are then cross-correlated to determine the transit delay time of the phase flow component between sensing positions. 8 figs.

Detrended fluctuation analysis made flexible to detect range of cross-correlated fluctuations

NASA Astrophysics Data System (ADS)

Kwapień, Jarosław; Oświecimka, Paweł; DroŻdŻ, Stanisław

2015-11-01

The detrended cross-correlation coefficient ρDCCA has recently been proposed to quantify the strength of cross-correlations on different temporal scales in bivariate, nonstationary time series. It is based on the detrended cross-correlation and detrended fluctuation analyses (DCCA and DFA, respectively) and can be viewed as an analog of the Pearson coefficient in the case of the fluctuation analysis. The coefficient ρDCCA works well in many practical situations but by construction its applicability is limited to detection of whether two signals are generally cross-correlated, without the possibility to obtain information on the amplitude of fluctuations that are responsible for those cross-correlations. In order to introduce some related flexibility, here we propose an extension of ρDCCA that exploits the multifractal versions of DFA and DCCA: multifractal detrended fluctuation analysis and multifractal detrended cross-correlation analysis, respectively. The resulting new coefficient ρq not only is able to quantify the strength of correlations but also allows one to identify the range of detrended fluctuation amplitudes that are correlated in two signals under study. We show how the coefficient ρq works in practical situations by applying it to stochastic time series representing processes with long memory: autoregressive and multiplicative ones. Such processes are often used to model signals recorded from complex systems and complex physical phenomena like turbulence, so we are convinced that this new measure can successfully be applied in time-series analysis. In particular, we present an example of such application to highly complex empirical data from financial markets. The present formulation can straightforwardly be extended to multivariate data in terms of the q -dependent counterpart of the correlation matrices and then to the network representation.

A Novel Multilayer Correlation Maximization Model for Improving CCA-Based Frequency Recognition in SSVEP Brain-Computer Interface.

PubMed

Jiao, Yong; Zhang, Yu; Wang, Yu; Wang, Bei; Jin, Jing; Wang, Xingyu

2018-05-01

Multiset canonical correlation analysis (MsetCCA) has been successfully applied to optimize the reference signals by extracting common features from multiple sets of electroencephalogram (EEG) for steady-state visual evoked potential (SSVEP) recognition in brain-computer interface application. To avoid extracting the possible noise components as common features, this study proposes a sophisticated extension of MsetCCA, called multilayer correlation maximization (MCM) model for further improving SSVEP recognition accuracy. MCM combines advantages of both CCA and MsetCCA by carrying out three layers of correlation maximization processes. The first layer is to extract the stimulus frequency-related information in using CCA between EEG samples and sine-cosine reference signals. The second layer is to learn reference signals by extracting the common features with MsetCCA. The third layer is to re-optimize the reference signals set in using CCA with sine-cosine reference signals again. Experimental study is implemented to validate effectiveness of the proposed MCM model in comparison with the standard CCA and MsetCCA algorithms. Superior performance of MCM demonstrates its promising potential for the development of an improved SSVEP-based brain-computer interface.

Laser anemometry for hot flows

NASA Astrophysics Data System (ADS)

Kugler, P.; Langer, G.

1987-07-01

The fundamental principles, instrumentation, and practical operation of LDA and laser-transit-anemometry systems for measuring velocity profiles and the degree of turbulence in high-temperature flows are reviewed and illustrated with diagrams, drawings and graphs of typical data. Consideration is given to counter, tracker, spectrum-analyzer and correlation methods of LDA signal processing; multichannel analyzer and cross correlation methods for LTA data; LTA results for a small liquid fuel rocket motor; and experiments demonstrating the feasibility of an optoacoustic demodulation scheme for LDA signals from unsteady flows.

Implementation of a noise reduction circuit for spaceflight IR spectrometers

NASA Technical Reports Server (NTRS)

Ramirez, L.; Hickok, R.; Pain, B.; Staller, C.

1992-01-01

The paper discusses the implementation and analysis of a correlated triple sampling circuit using analog subtractor/integrators. The software and test setup for noise measurements are also described. The correlation circuitry is part of the signal chain for a 256-element InSb line array used in the Visible and Infrared Mapping Spectrometer. Using a focal-plane array (FPA) simulator, system noise measurements of 0.7 DN are obtained. A test setup for FPA/SPE (signal processing electronics) characterization along with noise measurements is demonstrated.

Optimized signal detection and analysis methods for in vivo photoacoustic flow cytometry

NASA Astrophysics Data System (ADS)

Wang, Qiyan; Zhou, Quanyu; Yang, Ping; Wang, Xiaoling; Niu, Zhenyu; Suo, Yuanzhen; He, Hao; Gao, Wenyuan; Tang, Shuo; Wei, Xunbin

2017-02-01

Melanoma is known as a malignant tumor of melanocytes, which usually appear in the blood circulation at the metastasis stage of cancer. Thus the detection of circulating melanoma cells is useful for early diagnosis and therapy of cancer. Here we have developed an in vivo photoacoustic flow cytometry (PAFC) based on the photoacoustic effect to detect melanoma cells. However, the raw signals we obtain from the target cells contain noises such as environmental sonic noises and electronic noises. Therefore we apply correlation comparison and feature separation methods to the detection and verification of the in vivo signals. Due to similar shape and structure of cells, the photoacoustic signals usually have similar vibration mode. By analyzing the correlations and the signal features in time domain and frequency domain, we are able to provide a method for separating photoacoustic signals generated by target cells from background noises. The method introduced here has proved to optimize the signal acquisition and signal processing, which can improve the detection accuracy in PAFC.

Processes Affecting Variability of Fluorescence Signals from Benthic Targets in Shallow Waters

DTIC Science & Technology

1997-09-30

processes in the Department of Chemistry at Brookhaven National Laboratory. The model organisms used are primarily cultured zooxanthellae obtained from...and closed (Fm) photosystem II reaction centers in the zooxanthellae isolated from the fire coral, Montipora. The short lifetime curve corresponds...individual zooxanthellae strains, is highly correlated Figure 2. The correlation between the average fluorescence lifetimes, calculated from a four

Eddy current technique for predicting burst pressure

DOEpatents

Petri, Mark C.; Kupperman, David S.; Morman, James A.; Reifman, Jaques; Wei, Thomas Y. C.

2003-01-01

A signal processing technique which correlates eddy current inspection data from a tube having a critical tubing defect with a range of predicted burst pressures for the tube is provided. The method can directly correlate the raw eddy current inspection data representing the critical tubing defect with the range of burst pressures using a regression technique, preferably an artificial neural network. Alternatively, the technique deconvolves the raw eddy current inspection data into a set of undistorted signals, each of which represents a separate defect of the tube. The undistorted defect signal which represents the critical tubing defect is related to a range of burst pressures utilizing a regression technique.

Noise reduction methods for nucleic acid and macromolecule sequencing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schuller, Ivan K.; Di Ventra, Massimiliano; Balatsky, Alexander

Methods, systems, and devices are disclosed for processing macromolecule sequencing data with substantial noise reduction. In one aspect, a method for reducing noise in a sequential measurement of a macromolecule comprising serial subunits includes cross-correlating multiple measured signals of a physical property of subunits of interest of the macromolecule, the multiple measured signals including the time data associated with the measurement of the signal, to remove or at least reduce signal noise that is not in the same frequency and in phase with the systematic signal contribution of the measured signals.

Processing methods for photoacoustic Doppler flowmetry with a clinical ultrasound scanner

NASA Astrophysics Data System (ADS)

Bücking, Thore M.; van den Berg, Pim J.; Balabani, Stavroula; Steenbergen, Wiendelt; Beard, Paul C.; Brunker, Joanna

2018-02-01

Photoacoustic flowmetry (PAF) based on time-domain cross correlation of photoacoustic signals is a promising technique for deep tissue measurement of blood flow velocity. Signal processing has previously been developed for single element transducers. Here, the processing methods for acoustic resolution PAF using a clinical ultrasound transducer array are developed and validated using a 64-element transducer array with a -6 dB detection band of 11 to 17 MHz. Measurements were performed on a flow phantom consisting of a tube (580 μm inner diameter) perfused with human blood flowing at physiological speeds ranging from 3 to 25 mm / s. The processing pipeline comprised: image reconstruction, filtering, displacement detection, and masking. High-pass filtering and background subtraction were found to be key preprocessing steps to enable accurate flow velocity estimates, which were calculated using a cross-correlation based method. In addition, the regions of interest in the calculated velocity maps were defined using a masking approach based on the amplitude of the cross-correlation functions. These developments enabled blood flow measurements using a transducer array, bringing PAF one step closer to clinical applicability.

A VLSI implementation for synthetic aperture radar image processing

NASA Technical Reports Server (NTRS)

Premkumar, A.; Purviance, J.

1990-01-01

A simple physical model for the Synthetic Aperture Radar (SAR) is presented. This model explains the one dimensional and two dimensional nature of the received SAR signal in the range and azimuth directions. A time domain correlator, its algorithm, and features are explained. The correlator is ideally suited for VLSI implementation. A real time SAR architecture using these correlators is proposed. In the proposed architecture, the received SAR data is processed using one dimensional correlators for determining the range while two dimensional correlators are used to determine the azimuth of a target. The architecture uses only three different types of custom VLSI chips and a small amount of memory.

New methods of multimode fiber interferometer signal processing

NASA Astrophysics Data System (ADS)

Vitrik, Oleg B.; Kulchin, Yuri N.; Maxaev, Oleg G.; Kirichenko, Oleg V.; Kamenev, Oleg T.; Petrov, Yuri S.

1995-06-01

New methods of multimode fiber interferometers signal processing are suggested. For scheme of single fiber multimode interferometers with two excited modes, the method based on using of special fiber unit is developed. This unit provides the modes interaction and further sum optical field filtering. As a result the amplitude of output signal is modulated by external influence on interferometer. The stabilization of interferometer sensitivity is achieved by using additional special modulation of output signal. For scheme of single fiber multimode interferometers with excitation of wide mode spectrum, the signal of intermode interference is registered by photodiode matrix and then special electronic unit performs correlation processing. For elimination of temperature destabilization, the registered signal is adopted to multimode interferometers optical signal temperature changes. The achieved parameters for double mode scheme: temporary stability--0.6% per hour, sensitivity to interferometer length deviations--3,2 nm; for multimode scheme: temperature stability--(0.5%)/(K), temporary nonstability--0.2% per hour, sensitivity to interferometer length deviations--20 nm, dynamic range--35 dB.

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

NASA Astrophysics Data System (ADS)

Volman, Vladislav; Levine, Herbert

2009-09-01

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

Detecting modulated signals in modulated noise: (II) neural thresholds in the songbird forebrain.

PubMed

Bee, Mark A; Buschermöhle, Michael; Klump, Georg M

2007-10-01

Sounds in the real world fluctuate in amplitude. The vertebrate auditory system exploits patterns of amplitude fluctuations to improve signal detection in noise. One experimental paradigm demonstrating these general effects has been used in psychophysical studies of 'comodulation detection difference' (CDD). The CDD effect refers to the fact that thresholds for detecting a modulated, narrowband noise signal are lower when the envelopes of flanking bands of modulated noise are comodulated with each other, but fluctuate independently of the signal compared with conditions in which the envelopes of the signal and flanking bands are all comodulated. Here, we report results from a study of the neural correlates of CDD in European starlings (Sturnus vulgaris). We manipulated: (i) the envelope correlations between a narrowband noise signal and a masker comprised of six flanking bands of noise; (ii) the signal onset delay relative to masker onset; (iii) signal duration; and (iv) masker spectrum level. Masked detection thresholds were determined from neural responses using signal detection theory. Across conditions, the magnitude of neural CDD ranged between 2 and 8 dB, which is similar to that reported in a companion psychophysical study of starlings [U. Langemann & G.M. Klump (2007) Eur. J. Neurosci., 26, 1969-1978]. We found little evidence to suggest that neural CDD resulted from the across-channel processing of auditory grouping cues related to common envelope fluctuations and synchronous onsets between the signal and flanking bands. We discuss a within-channel model of peripheral processing that explains many of our results.

GNSS Space-Time Interference Mitigation and Attitude Determination in the Presence of Interference Signals

PubMed Central

Daneshmand, Saeed; Jahromi, Ali Jafarnia; Broumandan, Ali; Lachapelle, Gérard

2015-01-01

The use of Space-Time Processing (STP) in Global Navigation Satellite System (GNSS) applications is gaining significant attention due to its effectiveness for both narrowband and wideband interference suppression. However, the resulting distortion and bias on the cross correlation functions due to space-time filtering is a major limitation of this technique. Employing the steering vector of the GNSS signals in the filter structure can significantly reduce the distortion on cross correlation functions and lead to more accurate pseudorange measurements. This paper proposes a two-stage interference mitigation approach in which the first stage estimates an interference-free subspace before the acquisition and tracking phases and projects all received signals into this subspace. The next stage estimates array attitude parameters based on detecting and employing GNSS signals that are less distorted due to the projection process. Attitude parameters enable the receiver to estimate the steering vector of each satellite signal and use it in the novel distortionless STP filter to significantly reduce distortion and maximize Signal-to-Noise Ratio (SNR). GPS signals were collected using a six-element antenna array under open sky conditions to first calibrate the antenna array. Simulated interfering signals were then added to the digitized samples in software to verify the applicability of the proposed receiver structure and assess its performance for several interference scenarios. PMID:26016909

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

NASA Technical Reports Server (NTRS)

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

2000-01-01

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

GNSS space-time interference mitigation and attitude determination in the presence of interference signals.

PubMed

Daneshmand, Saeed; Jahromi, Ali Jafarnia; Broumandan, Ali; Lachapelle, Gérard

2015-05-26

The use of Space-Time Processing (STP) in Global Navigation Satellite System (GNSS) applications is gaining significant attention due to its effectiveness for both narrowband and wideband interference suppression. However, the resulting distortion and bias on the cross correlation functions due to space-time filtering is a major limitation of this technique. Employing the steering vector of the GNSS signals in the filter structure can significantly reduce the distortion on cross correlation functions and lead to more accurate pseudorange measurements. This paper proposes a two-stage interference mitigation approach in which the first stage estimates an interference-free subspace before the acquisition and tracking phases and projects all received signals into this subspace. The next stage estimates array attitude parameters based on detecting and employing GNSS signals that are less distorted due to the projection process. Attitude parameters enable the receiver to estimate the steering vector of each satellite signal and use it in the novel distortionless STP filter to significantly reduce distortion and maximize Signal-to-Noise Ratio (SNR). GPS signals were collected using a six-element antenna array under open sky conditions to first calibrate the antenna array. Simulated interfering signals were then added to the digitized samples in software to verify the applicability of the proposed receiver structure and assess its performance for several interference scenarios.

Instantaneous phase estimation to measure weak velocity variations: application to noise correlation on seismic data at the exploration scale

NASA Astrophysics Data System (ADS)

Corciulo, M.; Roux, P.; Campillo, M.; Dubucq, D.

2010-12-01

Passive imaging from noise cross-correlation is a consolidated analysis applied at continental and regional scale whereas its use at local scale for seismic exploration purposes is still uncertain. The development of passive imaging by cross-correlation analysis is based on the extraction of the Green’s function from seismic noise data. In a completely random field in time and space, the cross-correlation permits to retrieve the complete Green’s function whatever the complexity of the medium. At the exploration scale and at frequency above 2 Hz, the noise sources are not ideally distributed around the stations which strongly affect the extraction of the direct arrivals from the noise cross-correlation process. In order to overcome this problem, the coda waves extracted from noise correlation could be useful. Coda waves describe long and scattered paths sampling the medium in different ways such that they become sensitive to weak velocity variations without being dependent on the noise source distribution. Indeed, scatters in the medium behave as a set of secondary noise sources which randomize the spatial distribution of noise sources contributing to the coda waves in the correlation process. We developed a new technique to measure weak velocity changes based on the computation of the local phase variations (instantaneous phase variation or IPV) of the cross-correlated signals. This newly-developed technique takes advantage from the doublet and stretching techniques classically used to monitor weak velocity variation from coda waves. We apply IPV to data acquired in Northern America (Canada) on a 1-km side square seismic network laid out by 397 stations. Data used to study temporal variations are cross-correlated signals computed on 10-minutes ambient noise in the frequency band 2-5 Hz. As the data set was acquired over five days, about 660 files are processed to perform a complete temporal analysis for each stations pair. The IPV permits to estimate the phase shift all over the signal length without any assumption on the medium velocity. The instantaneous phase is computed using the Hilbert transform of the signal. For each stations pair, we measure the phase difference between successive correlation functions calculated for 10 minutes of ambient noise. We then fit the instantaneous phase shift using a first-order polynomial function. The measure of the velocity variation corresponds to the slope of this fit. Compared to other techniques, the advantage of IPV is a very fast procedure which efficiently provides the measure of velocity variation on large data sets. Both experimental results and numerical tests on synthetic signals will be presented to assess the reliability of the IPV technique, with comparison to the doublet and stretching methods.

Dynamic shaping of dopamine signals during probabilistic Pavlovian conditioning.

PubMed

Hart, Andrew S; Clark, Jeremy J; Phillips, Paul E M

2015-01-01

Cue- and reward-evoked phasic dopamine activity during Pavlovian and operant conditioning paradigms is well correlated with reward-prediction errors from formal reinforcement learning models, which feature teaching signals in the form of discrepancies between actual and expected reward outcomes. Additionally, in learning tasks where conditioned cues probabilistically predict rewards, dopamine neurons show sustained cue-evoked responses that are correlated with the variance of reward and are maximal to cues predicting rewards with a probability of 0.5. Therefore, it has been suggested that sustained dopamine activity after cue presentation encodes the uncertainty of impending reward delivery. In the current study we examined the acquisition and maintenance of these neural correlates using fast-scan cyclic voltammetry in rats implanted with carbon fiber electrodes in the nucleus accumbens core during probabilistic Pavlovian conditioning. The advantage of this technique is that we can sample from the same animal and recording location throughout learning with single trial resolution. We report that dopamine release in the nucleus accumbens core contains correlates of both expected value and variance. A quantitative analysis of these signals throughout learning, and during the ongoing updating process after learning in probabilistic conditions, demonstrates that these correlates are dynamically encoded during these phases. Peak CS-evoked responses are correlated with expected value and predominate during early learning while a variance-correlated sustained CS signal develops during the post-asymptotic updating phase. Copyright © 2014 Elsevier Inc. All rights reserved.

On the influence of noise correlations in measurement data on basis image noise in dual-energylike x-ray imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Roessl, Ewald; Ziegler, Andy; Proksa, Roland

2007-03-15

In conventional dual-energy systems, two transmission measurements with distinct spectral characteristics are performed. These measurements are used to obtain the line integrals of two basis material densities. Usually, the measurement process is such that the two measured signals can be treated as independent and therefore uncorrelated. Recently, however, a readout system for x-ray detectors has been introduced for which this is no longer the case. The readout electronics is designed to obtain simultaneous measurements of the total number of photons N and the total energy E they deposit in the sensor material. Practically, this is realized by a signal replicationmore » and separate counting and integrating processing units. Since the quantities N and E are (electronically) derived from one and the same physical sensor signal, they are statistically correlated. Nevertheless, the pair N and E can be used to perform a dual-energy processing following the well-known approach by Alvarez and Macovski. Formally, this means that N is to be identified with the first dual-energy measurement M{sub 1} and E with the second measurement M{sub 2}. In the presence of input correlations between M{sub 1}=N and M{sub 2}=E, however, the corresponding analytic expressions for the basis image noise have to be modified. The main observation made in this paper is that for positively correlated data, as is the case for the simultaneous counting and integrating device mentioned above, the basis image noise is suppressed through the influence of the covariance between the two signals. We extend the previously published relations for the basis image noise to the case where the original measurements are not independent and illustrate the importance of the input correlations by comparing dual-energy basis image noise resulting from the device mentioned above and a device measuring the photon numbers and the deposited energies consecutively.« less

Novel sonar signal processing tool using Shannon entropy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Quazi, A.H.

1996-06-01

Traditionally, conventional signal processing extracts information from sonar signals using amplitude, signal energy or frequency domain quantities obtained using spectral analysis techniques. The object is to investigate an alternate approach which is entirely different than that of traditional signal processing. This alternate approach is to utilize the Shannon entropy as a tool for the processing of sonar signals with emphasis on detection, classification, and localization leading to superior sonar system performance. Traditionally, sonar signals are processed coherently, semi-coherently, and incoherently, depending upon the a priori knowledge of the signals and noise. Here, the detection, classification, and localization technique will bemore » 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.}« less

Laser pulse coded signal frequency measuring device based on DSP and CPLD

NASA Astrophysics Data System (ADS)

Zhang, Hai-bo; Cao, Li-hua; Geng, Ai-hui; Li, Yan; Guo, Ru-hai; Wang, Ting-feng

2011-06-01

Laser pulse code is an anti-jamming measures used in semi-active laser guided weapons. On account of the laser-guided signals adopting pulse coding mode and the weak signal processing, it need complex calculations in the frequency measurement process according to the laser pulse code signal time correlation to meet the request in optoelectronic countermeasures in semi-active laser guided weapons. To ensure accurately completing frequency measurement in a short time, it needed to carry out self-related process with the pulse arrival time series composed of pulse arrival time, calculate the signal repetition period, and then identify the letter type to achieve signal decoding from determining the time value, number and rank number in a signal cycle by Using CPLD and DSP for signal processing chip, designing a laser-guided signal frequency measurement in the pulse frequency measurement device, improving the signal processing capability through the appropriate software algorithms. In this article, we introduced the principle of frequency measurement of the device, described the hardware components of the device, the system works and software, analyzed the impact of some system factors on the accuracy of the measurement. The experimental results indicated that this system improve the accuracy of the measurement under the premise of volume, real-time, anti-interference, low power of the laser pulse frequency measuring device. The practicality of the design, reliability has been demonstrated from the experimental point of view.

Multiplexing in the primate motion pathway.

PubMed

Huk, Alexander C

2012-06-01

This article begins by reviewing recent work on 3D motion processing in the primate visual system. Some of these results suggest that 3D motion signals may be processed in the same circuitry already known to compute 2D motion signals. Such "multiplexing" has implications for the study of visual cortical circuits and neural signals. A more explicit appreciation of multiplexing--and the computations required for demultiplexing--may enrich the study of the visual system by emphasizing the importance of a structured and balanced "encoding/decoding" framework. In addition to providing a fresh perspective on how successive stages of visual processing might be approached, multiplexing also raises caveats about the value of "neural correlates" for understanding neural computation.

Correlator data analysis for the array feed compensation system

NASA Technical Reports Server (NTRS)

Iijima, B.; Fort, D.; Vilnrotter, V.

1994-01-01

The real-time array feed compensation system is currently being evaluated at DSS 13. This system recovers signal-to-noise ratio (SNR) loss due to mechanical antenna deformations by using an array of seven Ka-band (33.7-GHz) horns to collect the defocused signal fields. The received signals are downconverted and digitized, in-phase and quadrature samples are generated, and combining weights are applied before the samples are recombined. It is shown that when optimum combining weights are employed, the SNR of the combined signal approaches the sum of the channel SNR's. The optimum combining weights are estimated directly from the signals in each channel by the Real-Time Block 2 (RTB2) correlator; since it was designed for very-long-baseline interferometer (VLBI) applications, it can process broadband signals as well as tones to extract the required weight estimates. The estimation algorithms for the optimum combining weights are described for tones and broadband sources. Data recorded in correlator output files can also be used off-line to estimate combiner performance by estimating the SNR in each channel, which was done for data taken during a Jupiter track at DSS 13.

Seismic signal processing on heterogeneous supercomputers

NASA Astrophysics Data System (ADS)

Gokhberg, Alexey; Ermert, Laura; Fichtner, Andreas

2015-04-01

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

Intensity-based masking: A tool to improve functional connectivity results of resting-state fMRI.

PubMed

Peer, Michael; Abboud, Sami; Hertz, Uri; Amedi, Amir; Arzy, Shahar

2016-07-01

Seed-based functional connectivity (FC) of resting-state functional MRI data is a widely used methodology, enabling the identification of functional brain networks in health and disease. Based on signal correlations across the brain, FC measures are highly sensitive to noise. A somewhat neglected source of noise is the fMRI signal attenuation found in cortical regions in close vicinity to sinuses and air cavities, mainly in the orbitofrontal, anterior frontal and inferior temporal cortices. BOLD signal recorded at these regions suffers from dropout due to susceptibility artifacts, resulting in an attenuated signal with reduced signal-to-noise ratio in as many as 10% of cortical voxels. Nevertheless, signal attenuation is largely overlooked during FC analysis. Here we first demonstrate that signal attenuation can significantly influence FC measures by introducing false functional correlations and diminishing existing correlations between brain regions. We then propose a method for the detection and removal of the attenuated signal ("intensity-based masking") by fitting a Gaussian-based model to the signal intensity distribution and calculating an intensity threshold tailored per subject. Finally, we apply our method on real-world data, showing that it diminishes false correlations caused by signal dropout, and significantly improves the ability to detect functional networks in single subjects. Furthermore, we show that our method increases inter-subject similarity in FC, enabling reliable distinction of different functional networks. We propose to include the intensity-based masking method as a common practice in the pre-processing of seed-based functional connectivity analysis, and provide software tools for the computation of intensity-based masks on fMRI data. Hum Brain Mapp 37:2407-2418, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Apparatus for measuring surface movement of an object that is subjected to external vibrations

DOEpatents

Kotidis, Petros A.; Woodroffe, Jaime A.; Rostler, Peter S.

1997-01-01

A system for non-destructively measuring an object and controlling industrial processes in response to the measurement is disclosed in which an impulse laser generates a plurality of sound waves over timed increments in an object. A polarizing interferometer is used to measure surface movement of the object caused by the sound waves and sensed by phase shifts in the signal beam. A photon multiplier senses the phase shift and develops an electrical signal. A signal conditioning arrangement modifies the electrical signals to generate an average signal correlated to the sound waves which in turn is correlated to a physical or metallurgical property of the object, such as temperature, which property may then be used to control the process. External, random vibrations of the workpiece are utilized to develop discernible signals which can be sensed in the interferometer by only one photon multiplier. In addition the interferometer includes an arrangement for optimizing its sensitivity so that movement attributed to various waves can be detected in opaque objects. The interferometer also includes a mechanism for sensing objects with rough surfaces which produce speckle light patterns. Finally the interferometer per se, with the addition of a second photon multiplier is capable of accurately recording beam length distance differences with only one reading.

Furnace control apparatus using polarizing interferometer

DOEpatents

Schultz, Thomas J.; Kotidis, Petros A.; Woodroffe, Jaime A.; Rostler, Peter S.

1995-01-01

A system for non-destructively measuring an object and controlling industrial processes in response to the measurement is disclosed in which an impulse laser generates a plurality of sound waves over timed increments in an object. A polarizing interferometer is used to measure surface movement of the object caused by the sound waves and sensed by phase shifts in the signal beam. A photon multiplier senses the phase shift and develops an electrical signal. A signal conditioning arrangement modifies the electrical signals to generate an average signal correlated to the sound waves which in turn is correlated to a physical or metallurgical property of the object, such as temperature, which property may then be used to control the process. External, random vibrations of the workpiece are utilized to develop discernible signals which can be sensed in the interferometer by only one photon multiplier. In addition the interferometer includes an arrangement for optimizing its sensitivity so that movement attributed to various waves can be detected in opaque objects. The interferometer also includes a mechanism for sensing objects with rough surfaces which produce speckle light patterns. Finally the interferometer per se, with the addition of a second photon multiplier is capable of accurately recording beam length distance differences with only one reading.

Polarizing optical interferometer having a dual use optical element

DOEpatents

Kotidis, P.A.; Woodroffe, J.A.; Rostler, P.S.

1995-04-04

A system for nondestructively measuring an object and controlling industrial processes in response to the measurement is disclosed in which an impulse laser generates a plurality of sound waves over timed increments in an object. A polarizing interferometer is used to measure surface movement of the object caused by the sound waves and sensed by phase shifts in the signal beam. A photon multiplier senses the phase shift and develops an electrical signal. A signal conditioning arrangement modifies the electrical signals to generate an average signal correlated to the sound waves which in turn is correlated to a physical or metallurgical property of the object, such as temperature, which property may then be used to control the process. External, random vibrations of the workpiece are utilized to develop discernible signals which can be sensed in the interferometer by only one photon multiplier. In addition the interferometer includes an arrangement for optimizing its sensitivity so that movement attributed to various waves can be detected in opaque objects. The interferometer also includes a mechanism for sensing objects with rough surfaces which produce speckle light patterns. Finally the interferometer per se, with the addition of a second photon multiplier is capable of accurately recording beam length distance differences with only one reading. 38 figures.

Polarizing optical interferometer having a dual use optical element

DOEpatents

Kotidis, Petros A.; Woodroffe, Jaime A.; Rostler, Peter S.

1995-01-01

A system for non-destructively measuring an object and controlling industrial processes in response to the measurement is disclosed in which an impulse laser generates a plurality of sound waves over timed increments in an object. A polarizing interferometer is used to measure surface movement of the object caused by the sound waves and sensed by phase shifts in the signal beam. A photon multiplier senses the phase shift and develops an electrical signal. A signal conditioning arrangement modifies the electrical signals to generate an average signal correlated to the sound waves which in turn is correlated to a physical or metallurgical property of the object, such as temperature, which property may then be used to control the process. External, random vibrations of the workpiece are utilized to develop discernible signals which can be sensed in the interferometer by only one photon multiplier. In addition the interferometer includes an arrangement for optimizing its sensitivity so that movement attributed to various waves can be detected in opaque objects. The interferometer also includes a mechanism for sensing objects with rough surfaces which produce speckle light patterns. Finally the interferometer per se, with the addition of a second photon multiplier is capable of accurately recording beam length distance differences with only one reading.

Furnace control apparatus using polarizing interferometer

DOEpatents

Schultz, T.J.; Kotidis, P.A.; Woodroffe, J.A.; Rostler, P.S.

1995-03-28

A system for nondestructively measuring an object and controlling industrial processes in response to the measurement is disclosed in which an impulse laser generates a plurality of sound waves over timed increments in an object. A polarizing interferometer is used to measure surface movement of the object caused by the sound waves and sensed by phase shifts in the signal beam. A photon multiplier senses the phase shift and develops an electrical signal. A signal conditioning arrangement modifies the electrical signals to generate an average signal correlated to the sound waves which in turn is correlated to a physical or metallurgical property of the object, such as temperature, which property may then be used to control the process. External, random vibrations of the workpiece are utilized to develop discernible signals which can be sensed in the interferometer by only one photon multiplier. In addition the interferometer includes an arrangement for optimizing its sensitivity so that movement attributed to various waves can be detected in opaque objects. The interferometer also includes a mechanism for sensing objects with rough surfaces which produce speckle light patterns. Finally the interferometer per se, with the addition of a second photon multiplier is capable of accurately recording beam length distance differences with only one reading. 38 figures.

Method and apparatus for measuring surface movement of a solid object that is subjected to external vibrations

DOEpatents

Schultz, Thomas J.; Kotidis, Petros A.; Woodroffe, Jaime A.; Rostler, Peter S.

1995-01-01

A system for non-destructively measuring an object and controlling industrial processes in response to the measurement is disclosed in which an impulse laser generates a plurality of sound waves over timed increments in an object. A polarizing interferometer is used to measure surface movement of the object caused by the sound waves and sensed by phase shifts in the signal beam. A photon multiplier senses the phase shift and develops an electrical signal. A signal conditioning arrangement modifies the electrical signals to generate an average signal correlated to the sound waves which in turn is correlated to a physical or metallurgical property of the object, such as temperature, which property may then be used to control the process. External, random vibrations of the workpiece are utilized to develop discernible signals which can be sensed in the interferometer by only one photon multiplier. In addition the interferometer includes an arrangement for optimizing its sensitivity so that movement attributed to various waves can be detected in opaque objects. The interferometer also includes a mechanism for sensing objects with rough surfaces which produce speckle light patterns. Finally the interferometer per se, with the addition of a second photon multiplier is capable of accurately recording beam length distance differences with only one reading.

Method and apparatus for measuring surface movement of an object using a polarizing interfeometer

DOEpatents

Schultz, Thomas J.; Kotidis, Petros A.; Woodroffe, Jaime A.; Rostler, Peter S.

1995-01-01

A system for non-destructively measuring an object and controlling industrial processes in response to the measurement is disclosed in which an impulse laser generates a plurality of sound waves over timed increments in an object. A polarizing interferometer is used to measure surface movement of the object caused by the sound waves and sensed by phase shifts in the signal beam. A photon multiplier senses the phase shift and develops an electrical signal. A signal conditioning arrangement modifies the electrical signals to generate an average signal correlated to the sound waves which in turn is correlated to a physical or metallurgical property of the object, such as temperature, which property may then be used to control the process. External, random vibrations of the workpiece are utilized to develop discernible signals which can be sensed in the interferometer by only one photon multiplier. In addition the interferometer includes an arrangement for optimizing its sensitivity so that movement attributed to various waves can be detected in opaque objects. The interferometer also includes a mechanism for sensing objects with rough surfaces which produce speckle light patterns. Finally the interferometer per se, with the addition of a second photon multiplier is capable of accurately recording beam length distance differences with only one reading.

Method and apparatus for measuring surface movement of an object using a polarizing interferometer

DOEpatents

Schultz, T.J.; Kotidis, P.A.; Woodroffe, J.A.; Rostler, P.S.

1995-05-09

A system for non-destructively measuring an object and controlling industrial processes in response to the measurement is disclosed in which an impulse laser generates a plurality of sound waves over timed increments in an object. A polarizing interferometer is used to measure surface movement of the object caused by the sound waves and sensed by phase shifts in the signal beam. A photon multiplier senses the phase shift and develops an electrical signal. A signal conditioning arrangement modifies the electrical signals to generate an average signal correlated to the sound waves which in turn is correlated to a physical or metallurgical property of the object, such as temperature, which property may then be used to control the process. External, random vibrations of the workpiece are utilized to develop discernible signals which can be sensed in the interferometer by only one photon multiplier. In addition the interferometer includes an arrangement for optimizing its sensitivity so that movement attributed to various waves can be detected in opaque objects. The interferometer also includes a mechanism for sensing objects with rough surfaces which produce speckle light patterns. Finally the interferometer per se, with the addition of a second photon multiplier is capable of accurately recording beam length distance differences with only one reading. 38 figs.

Method and apparatus for measuring surface movement of a solid object that is subjected to external vibrations

DOEpatents

Schultz, T.J.; Kotidis, P.A.; Woodroffe, J.A.; Rostler, P.S.

1995-04-25

A system for non-destructively measuring an object and controlling industrial processes in response to the measurement is disclosed in which an impulse laser generates a plurality of sound waves over timed increments in an object. A polarizing interferometer is used to measure surface movement of the object caused by the sound waves and sensed by phase shifts in the signal beam. A photon multiplier senses the phase shift and develops an electrical signal. A signal conditioning arrangement modifies the electrical signals to generate an average signal correlated to the sound waves which in turn is correlated to a physical or metallurgical property of the object, such as temperature, which property may then be used to control the process. External, random vibrations of the workpiece are utilized to develop discernible signals which can be sensed in the interferometer by only one photon multiplier. In addition the interferometer includes an arrangement for optimizing its sensitivity so that movement attributed to various waves can be detected in opaque objects. The interferometer also includes a mechanism for sensing objects with rough surfaces which produce speckle light patterns. Finally the interferometer per se, with the addition of a second photon multiplier is capable of accurately recording beam length distance differences with only one reading. 38 figs.

Apparatus for measuring surface movement of an object that is subjected to external vibrations

DOEpatents

Kotidis, P.A.; Woodroffe, J.A.; Rostler, P.S.

1997-04-22

A system for non-destructively measuring an object and controlling industrial processes in response to the measurement is disclosed in which an impulse laser generates a plurality of sound waves over timed increments in an object. A polarizing interferometer is used to measure surface movement of the object caused by the sound waves and sensed by phase shifts in the signal beam. A photon multiplier senses the phase shift and develops an electrical signal. A signal conditioning arrangement modifies the electrical signals to generate an average signal correlated to the sound waves which in turn is correlated to a physical or metallurgical property of the object, such as temperature, which property may then be used to control the process. External, random vibrations of the workpiece are utilized to develop discernible signals which can be sensed in the interferometer by only one photon multiplier. In addition the interferometer includes an arrangement for optimizing its sensitivity so that movement attributed to various waves can be detected in opaque objects. The interferometer also includes a mechanism for sensing objects with rough surfaces which produce speckle light patterns. Finally the interferometer per se, with the addition of a second photon multiplier is capable of accurately recording beam length distance differences with only one reading. 38 figs.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Candy, J. V.

Chirp signals have evolved primarily from radar/sonar signal processing applications specifically attempting to estimate the location of a target in surveillance/tracking volume. The chirp, which is essentially a sinusoidal signal whose phase changes instantaneously at each time sample, has an interesting property in that its correlation approximates an impulse function. It is well-known that a matched-filter detector in radar/sonar estimates the target range by cross-correlating a replicant of the transmitted chirp with the measurement data reflected from the target back to the radar/sonar receiver yielding a maximum peak corresponding to the echo time and therefore enabling the desired range estimate.more » In this application, we perform the same operation as a radar or sonar system, that is, we transmit a “chirp-like pulse” into the target medium and attempt to first detect its presence and second estimate its location or range. Our problem is complicated by the presence of disturbance signals from surrounding broadcast stations as well as extraneous sources of interference in our frequency bands and of course the ever present random noise from instrumentation. First, we discuss the chirp signal itself and illustrate its inherent properties and then develop a model-based processing scheme enabling both the detection and estimation of the signal from noisy measurement data.« less

Computer Vision for Artificially Intelligent Robotic Systems

NASA Astrophysics Data System (ADS)

Ma, Chialo; Ma, Yung-Lung

1987-04-01

In this paper An Acoustic Imaging Recognition System (AIRS) will be introduced which is installed on an Intelligent Robotic System and can recognize different type of Hand tools' by Dynamic pattern recognition. The dynamic pattern recognition is approached by look up table method in this case, the method can save a lot of calculation time and it is practicable. The Acoustic Imaging Recognition System (AIRS) is consist of four parts -- position control unit, pulse-echo signal processing unit, pattern recognition unit and main control unit. The position control of AIRS can rotate an angle of ±5 degree Horizental and Vertical seperately, the purpose of rotation is to find the maximum reflection intensity area, from the distance, angles and intensity of the target we can decide the characteristic of this target, of course all the decision is target, of course all the decision is processed bye the main control unit. In Pulse-Echo Signal Process Unit, we ultilize the correlation method, to overcome the limitation of short burst of ultrasonic, because the Correlation system can transmit large time bandwidth signals and obtain their resolution and increased intensity through pulse compression in the correlation receiver. The output of correlator is sampled and transfer into digital data by u law coding method, and this data together with delay time T, angle information OH, eV will be sent into main control unit for further analysis. The recognition process in this paper, we use dynamic look up table method, in this method at first we shall set up serval recognition pattern table and then the new pattern scanned by Transducer array will be devided into serval stages and compare with the sampling table. The comparison is implemented by dynamic programing and Markovian process. All the hardware control signals, such as optimum delay time for correlator receiver, horizental and vertical rotation angle for transducer plate, are controlled by the Main Control Unit, the Main Control Unit also handles the pattern recognition process. The distance from the target to the transducer plate is limitted by the power and beam angle of transducer elements, in this AIRS Model, we use a narrow beam transducer and it's input voltage is 50V p-p. A RobOt equipped with AIRS can not only measure the distance from the target but also recognize a three dimensional image of target from the image lab of Robot memory. Indexitems, Accoustic System, Supersonic transducer, Dynamic programming, Look-up-table, Image process, pattern Recognition, Quad Tree, Quadappoach.

Improved Performance Characteristics For Indium Antimonide Photovoltaic Detector Arrays Using A FET-Switched Multiplexing Technique

NASA Astrophysics Data System (ADS)

Ma, Yung-Lung; Ma, Chialo

1987-03-01

In this paper An Acoustic Imaging Recognition System (AIRS) will be introduced which is installed on an Intelligent Robotic System and can recognize different type of Hand tools' by Dynamic pattern recognition. The dynamic pattern recognition is approached by look up table method in this case, the method can save a lot of calculation time and it is practicable. The Acoustic Imaging Recognition System (AIRS) is consist of four parts _ position control unit, pulse-echo signal processing unit, pattern recognition unit and main control unit. The position control of AIRS can rotate an angle of ±5 degree Horizental and Vertical seperately, the purpose of rotation is to find the maximum reflection intensity area, from the distance, angles and intensity of the target we can decide the characteristic of this target, of course all the decision is target, of course all the decision is processed by the main control unit. In Pulse-Echo Signal Process Unit, we utilize the correlation method, to overcome the limitation of short burst of ultrasonic, because the Correlation system can transmit large time bandwidth signals and obtain their resolution and increased intensity through pulse compression in the correlation receiver. The output of correlator is sampled and transfer into digital data by p law coding method, and this data together with delay time T, angle information eH, eV will be sent into main control unit for further analysis. The recognition process in this paper, we use dynamic look up table method, in this method at first we shall set up serval recognition pattern table and then the new pattern scanned by Transducer array will be devided into serval stages and compare with the sampling table. The comparison is implemented by dynamic programing and Markovian process. All the hardware control signals, such as optimum delay time for correlator receiver, horizental and vertical rotation angle for transducer plate, are controlled by the Main Control Unit, the Main Control Unit also handles the pattern recognition process. The distance from the target to the transducer plate is limitted by the power and beam angle of transducer elements, in this AIRS Models, we use a narrow beam transducer and it's input voltage is 50V p-p. A Robot equipped with AIRS can not only measure the distance from the target but also recognize a three dimensional image of target from the image lab of Robot memory. Indexitems, Accoustic System, Supersonic transducer, Dynamic programming, Look-up-table, Image process, pattern Recognition, Quad Tree, Quadappoach.

A comparative analysis of frequency modulation threshold extension techniques

NASA Technical Reports Server (NTRS)

Arndt, G. D.; Loch, F. J.

1970-01-01

FM threshold extension for system performance improvement, comparing impulse noise elimination, correlation detection and delta modulation signal processing techniques implemented at demodulator output

Noise shaping in populations of coupled model neurons.

PubMed

Mar, D J; Chow, C C; Gerstner, W; Adams, R W; Collins, J J

1999-08-31

Biological information-processing systems, such as populations of sensory and motor neurons, may use correlations between the firings of individual elements to obtain lower noise levels and a systemwide performance improvement in the dynamic range or the signal-to-noise ratio. Here, we implement such correlations in networks of coupled integrate-and-fire neurons using inhibitory coupling and demonstrate that this can improve the system dynamic range and the signal-to-noise ratio in a population rate code. The improvement can surpass that expected for simple averaging of uncorrelated elements. A theory that predicts the resulting power spectrum is developed in terms of a stochastic point-process model in which the instantaneous population firing rate is modulated by the coupling between elements.

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

NASA Astrophysics Data System (ADS)

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

2006-06-01

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

Application of the wavelet packet transform to vibration signals for surface roughness monitoring in CNC turning operations

NASA Astrophysics Data System (ADS)

García Plaza, E.; Núñez López, P. J.

2018-01-01

The wavelet packet transform method decomposes a time signal into several independent time-frequency signals called packets. This enables the temporary location of transient events occurring during the monitoring of the cutting processes, which is advantageous in monitoring condition and fault diagnosis. This paper proposes the monitoring of surface roughness using a single low cost sensor that is easily implemented in numerical control machine tools in order to make on-line decisions on workpiece surface finish quality. Packet feature extraction in vibration signals was applied to correlate the sensor signals to measured surface roughness. For the successful application of the WPT method, mother wavelets, packet decomposition level, and appropriate packet selection methods should be considered, but are poorly understood aspects in the literature. In this novel contribution, forty mother wavelets, optimal decomposition level, and packet reduction methods were analysed, as well as identifying the effective frequency range providing the best packet feature extraction for monitoring surface finish. The results show that mother wavelet biorthogonal 4.4 in decomposition level L3 with the fusion of the orthogonal vibration components (ax + ay + az) were the best option in the vibration signal and surface roughness correlation. The best packets were found in the medium-high frequency DDA (6250-9375 Hz) and high frequency ADA (9375-12500 Hz) ranges, and the feed acceleration component ay was the primary source of information. The packet reduction methods forfeited packets with relevant features to the signal, leading to poor results for the prediction of surface roughness. WPT is a robust vibration signal processing method for the monitoring of surface roughness using a single sensor without other information sources, satisfactory results were obtained in comparison to other processing methods with a low computational cost.

Investigation of signal models and methods for evaluating structures of processing telecommunication information exchange systems under acoustic noise conditions

NASA Astrophysics Data System (ADS)

Kropotov, Y. A.; Belov, A. A.; Proskuryakov, A. Y.; Kolpakov, A. A.

2018-05-01

The paper considers models and methods for estimating signals during the transmission of information messages in telecommunication systems of audio exchange. One-dimensional probability distribution functions that can be used to isolate useful signals, and acoustic noise interference are presented. An approach to the estimation of the correlation and spectral functions of the parameters of acoustic signals is proposed, based on the parametric representation of acoustic signals and the components of the noise components. The paper suggests an approach to improving the efficiency of interference cancellation and highlighting the necessary information when processing signals from telecommunications systems. In this case, the suppression of acoustic noise is based on the methods of adaptive filtering and adaptive compensation. The work also describes the models of echo signals and the structure of subscriber devices in operational command telecommunications systems.

Statistical analysis and digital processing of the Mössbauer spectra

NASA Astrophysics Data System (ADS)

Prochazka, Roman; Tucek, Pavel; Tucek, Jiri; Marek, Jaroslav; Mashlan, Miroslav; Pechousek, Jiri

2010-02-01

This work is focused on using the statistical methods and development of the filtration procedures for signal processing in Mössbauer spectroscopy. Statistical tools for noise filtering in the measured spectra are used in many scientific areas. The use of a pure statistical approach in accumulated Mössbauer spectra filtration is described. In Mössbauer spectroscopy, the noise can be considered as a Poisson statistical process with a Gaussian distribution for high numbers of observations. This noise is a superposition of the non-resonant photons counting with electronic noise (from γ-ray detection and discrimination units), and the velocity system quality that can be characterized by the velocity nonlinearities. The possibility of a noise-reducing process using a new design of statistical filter procedure is described. This mathematical procedure improves the signal-to-noise ratio and thus makes it easier to determine the hyperfine parameters of the given Mössbauer spectra. The filter procedure is based on a periodogram method that makes it possible to assign the statistically important components in the spectral domain. The significance level for these components is then feedback-controlled using the correlation coefficient test results. The estimation of the theoretical correlation coefficient level which corresponds to the spectrum resolution is performed. Correlation coefficient test is based on comparison of the theoretical and the experimental correlation coefficients given by the Spearman method. The correctness of this solution was analyzed by a series of statistical tests and confirmed by many spectra measured with increasing statistical quality for a given sample (absorber). The effect of this filter procedure depends on the signal-to-noise ratio and the applicability of this method has binding conditions.

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

PubMed

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

2015-06-01

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

Ultrasonic Signal Processing for Structural Health Monitoring

NASA Astrophysics Data System (ADS)

Michaels, Jennifer E.; Michaels, Thomas E.

2004-02-01

Permanently mounted ultrasonic sensors are a key component of systems under development for structural health monitoring. Signal processing plays a critical role in the viability of such systems due to the difficulty in interpreting signals received from structures of complex geometry. This paper describes a differential feature-based approach to classifying signal changes as either "environmental" or "structural". Data are presented from piezoelectric discs bonded to an aluminum specimen subjected to both environmental changes and introduction of artificial defects. The classifier developed as part of this study was able to correctly identify artificial defects that were not part of the initial training and evaluation data sets. Central to the success of the classifier was the use of the Short Time Cross Correlation to measure coherency between the signal and reference as a function of time.

Automatic Methods in Image Processing and Their Relevance to Map-Making.

DTIC Science & Technology

1981-02-11

23b) and ECfg ) = DC1 1 reIc (5-24) Is an example, let the image function f be white noise so that Cf( ) = s, ,), the Dirac impulse . Then (5-24...based on image and correlator models which describe the behavior of correlation processors under condi- tions of low image contrast or signal-to- noise ...71 Sensor Noise ......................... 74 Self Noise .7.................. 6 Ma chine Noise ................ 81 Fixed Point Processing

Age-Dependent Relationships between Prefrontal Cortex Activation and Processing Efficiency

PubMed Central

Motes, Michael A.; Biswal, Bharat B.; Rypma, Bart

2012-01-01

fMRI was used in the present study to examine the neural basis for age-related differences in processing efficiency, particularly targeting prefrontal cortex (PFC). During scanning, older and younger participants completed a processing efficiency task in which they determined on each trial whether a symbol-number pair appeared in a simultaneously presented array of nine symbol-number pairs. Estimates of task-related BOLD signal-change were obtained for each participant. These estimates were then correlated with the participants’ performance on the task. For younger participants, BOLD signal-change within PFC decreased with better performance, but for older participants, BOLD signal-change within PFC increased with better performance. The results support the hypothesis that the availability and use of PFC resources mediates age-related changes in processing efficiency. PMID:22792129

Age-Dependent Relationships between Prefrontal Cortex Activation and Processing Efficiency.

PubMed

Motes, Michael A; Biswal, Bharat B; Rypma, Bart

2011-01-01

fMRI was used in the present study to examine the neural basis for age-related differences in processing efficiency, particularly targeting prefrontal cortex (PFC). During scanning, older and younger participants completed a processing efficiency task in which they determined on each trial whether a symbol-number pair appeared in a simultaneously presented array of nine symbol-number pairs. Estimates of task-related BOLD signal-change were obtained for each participant. These estimates were then correlated with the participants' performance on the task. For younger participants, BOLD signal-change within PFC decreased with better performance, but for older participants, BOLD signal-change within PFC increased with better performance. The results support the hypothesis that the availability and use of PFC resources mediates age-related changes in processing efficiency.

Computer algorithm for analyzing and processing borehole strainmeter data

USGS Publications Warehouse

Langbein, John O.

2010-01-01

The newly installed Plate Boundary Observatory (PBO) strainmeters record signals from tectonic activity, Earth tides, and atmospheric pressure. Important information about tectonic processes may occur at amplitudes at and below tidal strains and pressure loading. If incorrect assumptions are made regarding the background noise in the strain data, then the estimates of tectonic signal amplitudes may be incorrect. Furthermore, the use of simplifying assumptions that data are uncorrelated can lead to incorrect results and pressure loading and tides may not be completely removed from the raw data. Instead, any algorithm used to process strainmeter data must incorporate the strong temporal correlations that are inherent with these data. The technique described here uses least squares but employs data covariance that describes the temporal correlation of strainmeter data. There are several advantages to this method since many parameters are estimated simultaneously. These parameters include: (1) functional terms that describe the underlying error model, (2) the tidal terms, (3) the pressure loading term(s), (4) amplitudes of offsets, either those from earthquakes or from the instrument, (5) rate and changes in rate, and (6) the amplitudes and time constants of either logarithmic or exponential curves that can characterize postseismic deformation or diffusion of fluids near the strainmeter. With the proper error model, realistic estimates of the standard errors of the various parameters are obtained; this is especially critical in determining the statistical significance of a suspected, tectonic strain signal. The program also provides a method of tracking the various adjustments required to process strainmeter data. In addition, the program provides several plots to assist with identifying either tectonic signals or other signals that may need to be removed before any geophysical signal can be identified.

A Small Leak Detection Method Based on VMD Adaptive De-Noising and Ambiguity Correlation Classification Intended for Natural Gas Pipelines.

PubMed

Xiao, Qiyang; Li, Jian; Bai, Zhiliang; Sun, Jiedi; Zhou, Nan; Zeng, Zhoumo

2016-12-13

In this study, a small leak detection method based on variational mode decomposition (VMD) and ambiguity correlation classification (ACC) is proposed. The signals acquired from sensors were decomposed using the VMD, and numerous components were obtained. According to the probability density function (PDF), an adaptive de-noising algorithm based on VMD is proposed for noise component processing and de-noised components reconstruction. Furthermore, the ambiguity function image was employed for analysis of the reconstructed signals. Based on the correlation coefficient, ACC is proposed to detect the small leak of pipeline. The analysis of pipeline leakage signals, using 1 mm and 2 mm leaks, has shown that proposed detection method can detect a small leak accurately and effectively. Moreover, the experimental results have shown that the proposed method achieved better performances than support vector machine (SVM) and back propagation neural network (BP) methods.

A Small Leak Detection Method Based on VMD Adaptive De-Noising and Ambiguity Correlation Classification Intended for Natural Gas Pipelines

PubMed Central

Xiao, Qiyang; Li, Jian; Bai, Zhiliang; Sun, Jiedi; Zhou, Nan; Zeng, Zhoumo

2016-01-01

In this study, a small leak detection method based on variational mode decomposition (VMD) and ambiguity correlation classification (ACC) is proposed. The signals acquired from sensors were decomposed using the VMD, and numerous components were obtained. According to the probability density function (PDF), an adaptive de-noising algorithm based on VMD is proposed for noise component processing and de-noised components reconstruction. Furthermore, the ambiguity function image was employed for analysis of the reconstructed signals. Based on the correlation coefficient, ACC is proposed to detect the small leak of pipeline. The analysis of pipeline leakage signals, using 1 mm and 2 mm leaks, has shown that proposed detection method can detect a small leak accurately and effectively. Moreover, the experimental results have shown that the proposed method achieved better performances than support vector machine (SVM) and back propagation neural network (BP) methods. PMID:27983577

Costas loop lock detection in the advanced receiver

NASA Technical Reports Server (NTRS)

Mileant, A.; Hinedi, S.

1989-01-01

The advanced receiver currently being developed uses a Costas digital loop to demodulate the subcarrier. Previous analyses of lock detector algorithms for Costas loops have ignored the effects of the inherent correlation between the samples of the phase-error process. Accounting for this correlation is necessary to achieve the desired lock-detection probability for a given false-alarm rate. Both analysis and simulations are used to quantify the effects of phase correlation on lock detection for the square-law and the absolute-value type detectors. Results are obtained which depict the lock-detection probability as a function of loop signal-to-noise ratio for a given false-alarm rate. The mathematical model and computer simulation show that the square-law detector experiences less degradation due to phase jitter than the absolute-value detector and that the degradation in detector signal-to-noise ratio is more pronounced for square-wave than for sine-wave signals.

High Frequency Sampling of TTL Pulses on a Raspberry Pi for Diffuse Correlation Spectroscopy Applications.

PubMed

Tivnan, Matthew; Gurjar, Rajan; Wolf, David E; Vishwanath, Karthik

2015-08-12

Diffuse Correlation Spectroscopy (DCS) is a well-established optical technique that has been used for non-invasive measurement of blood flow in tissues. Instrumentation for DCS includes a correlation device that computes the temporal intensity autocorrelation of a coherent laser source after it has undergone diffuse scattering through a turbid medium. Typically, the signal acquisition and its autocorrelation are performed by a correlation board. These boards have dedicated hardware to acquire and compute intensity autocorrelations of rapidly varying input signal and usually are quite expensive. Here we show that a Raspberry Pi minicomputer can acquire and store a rapidly varying time-signal with high fidelity. We show that this signal collected by a Raspberry Pi device can be processed numerically to yield intensity autocorrelations well suited for DCS applications. DCS measurements made using the Raspberry Pi device were compared to those acquired using a commercial hardware autocorrelation board to investigate the stability, performance, and accuracy of the data acquired in controlled experiments. This paper represents a first step toward lowering the instrumentation cost of a DCS system and may offer the potential to make DCS become more widely used in biomedical applications.

High Frequency Sampling of TTL Pulses on a Raspberry Pi for Diffuse Correlation Spectroscopy Applications

PubMed Central

Tivnan, Matthew; Gurjar, Rajan; Wolf, David E.; Vishwanath, Karthik

2015-01-01

Diffuse Correlation Spectroscopy (DCS) is a well-established optical technique that has been used for non-invasive measurement of blood flow in tissues. Instrumentation for DCS includes a correlation device that computes the temporal intensity autocorrelation of a coherent laser source after it has undergone diffuse scattering through a turbid medium. Typically, the signal acquisition and its autocorrelation are performed by a correlation board. These boards have dedicated hardware to acquire and compute intensity autocorrelations of rapidly varying input signal and usually are quite expensive. Here we show that a Raspberry Pi minicomputer can acquire and store a rapidly varying time-signal with high fidelity. We show that this signal collected by a Raspberry Pi device can be processed numerically to yield intensity autocorrelations well suited for DCS applications. DCS measurements made using the Raspberry Pi device were compared to those acquired using a commercial hardware autocorrelation board to investigate the stability, performance, and accuracy of the data acquired in controlled experiments. This paper represents a first step toward lowering the instrumentation cost of a DCS system and may offer the potential to make DCS become more widely used in biomedical applications. PMID:26274961

Mixed Signal Learning by Spike Correlation Propagation in Feedback Inhibitory Circuits

PubMed Central

Hiratani, Naoki; Fukai, Tomoki

2015-01-01

The brain can learn and detect mixed input signals masked by various types of noise, and spike-timing-dependent plasticity (STDP) is the candidate synaptic level mechanism. Because sensory inputs typically have spike correlation, and local circuits have dense feedback connections, input spikes cause the propagation of spike correlation in lateral circuits; however, it is largely unknown how this secondary correlation generated by lateral circuits influences learning processes through STDP, or whether it is beneficial to achieve efficient spike-based learning from uncertain stimuli. To explore the answers to these questions, we construct models of feedforward networks with lateral inhibitory circuits and study how propagated correlation influences STDP learning, and what kind of learning algorithm such circuits achieve. We derive analytical conditions at which neurons detect minor signals with STDP, and show that depending on the origin of the noise, different correlation timescales are useful for learning. In particular, we show that non-precise spike correlation is beneficial for learning in the presence of cross-talk noise. We also show that by considering excitatory and inhibitory STDP at lateral connections, the circuit can acquire a lateral structure optimal for signal detection. In addition, we demonstrate that the model performs blind source separation in a manner similar to the sequential sampling approximation of the Bayesian independent component analysis algorithm. Our results provide a basic understanding of STDP learning in feedback circuits by integrating analyses from both dynamical systems and information theory. PMID:25910189

Within-Subject Correlation Analysis to Detect Functional Areas Associated With Response Inhibition.

PubMed

Yamasaki, Tomoko; Ogawa, Akitoshi; Osada, Takahiro; Jimura, Koji; Konishi, Seiki

2018-01-01

Functional areas in fMRI studies are often detected by brain-behavior correlation, calculating across-subject correlation between the behavioral index and the brain activity related to a function of interest. Within-subject correlation analysis is also employed in a single subject level, which utilizes cognitive fluctuations in a shorter time period by correlating the behavioral index with the brain activity across trials. In the present study, the within-subject analysis was applied to the stop-signal task, a standard task to probe response inhibition, where efficiency of response inhibition can be evaluated by the stop-signal reaction time (SSRT). Since the SSRT is estimated, by definition, not in a trial basis but from pooled trials, the correlation across runs was calculated between the SSRT and the brain activity related to response inhibition. The within-subject correlation revealed negative correlations in the anterior cingulate cortex and the cerebellum. Moreover, the dissociation pattern was observed in the within-subject analysis when earlier vs. later parts of the runs were analyzed: negative correlation was dominant in earlier runs, whereas positive correlation was dominant in later runs. Regions of interest analyses revealed that the negative correlation in the anterior cingulate cortex, but not in the cerebellum, was dominant in earlier runs, suggesting multiple mechanisms associated with inhibitory processes that fluctuate on a run-by-run basis. These results indicate that the within-subject analysis compliments the across-subject analysis by highlighting different aspects of cognitive/affective processes related to response inhibition.

Neural Correlates and Mechanisms of Spatial Release From Masking: Single-Unit and Population Responses in the Inferior Colliculus

PubMed Central

Lane, Courtney C.; Delgutte, Bertrand

2007-01-01

Spatial release from masking (SRM), a factor in listening in noisy environments, is the improvement in auditory signal detection obtained when a signal is separated in space from a masker. To study the neural mechanisms of SRM, we recorded from single units in the inferior colliculus (IC) of barbiturate-anesthetized cats, focusing on low-frequency neurons sensitive to interaural time differences. The stimulus was a broadband chirp train with a 40-Hz repetition rate in continuous broadband noise, and the unit responses were measured for several signal and masker (virtual) locations. Masked thresholds (the lowest signal-to-noise ratio, SNR, for which the signal could be detected for 75% of the stimulus presentations) changed systematically with signal and masker location. Single-unit thresholds did not necessarily improve with signal and masker separation; instead, they tended to reflect the units’ azimuth preference. Both how the signal was detected (through a rate increase or decrease) and how the noise masked the signal response (suppressive or excitatory masking) changed with signal and masker azimuth, consistent with a cross-correlator model of binaural processing. However, additional processing, perhaps related to the signal’s amplitude modulation rate, appeared to influence the units’ responses. The population masked thresholds (the most sensitive unit’s threshold at each signal and masker location) did improve with signal and masker separation as a result of the variety of azimuth preferences in our unit sample. The population thresholds were similar to human behavioral thresholds in both SNR value and shape, indicating that these units may provide a neural substrate for low-frequency SRM. PMID:15857966

Attenuation of harmonic noise in vibroseis data using Simulated Annealing

NASA Astrophysics Data System (ADS)

Sharma, S. P.; Tildy, Peter; Iranpour, Kambiz; Scholtz, Peter

2009-04-01

Processing of high productivity vibroseis seismic data (such as slip-sweep acquisition records) suffers from the well known disadvantage of harmonic distortion. Harmonic distortions are observed after cross-correlation of the recorded seismic signal with the pilot sweep and affect the signals in negative time (before the actual strong reflection event). Weak reflection events of the earlier sweeps falling in the negative time window of the cross-correlation sequence are being masked by harmonic distortions. Though the amplitude of the harmonic distortion is small (up to 10-20 %) compared to the fundamental amplitude of the reflection events, but it is significant enough to mask weak reflected signals. Elimination of harmonic noise due to source signal distortion from the cross-correlated seismic trace is a challenging task since the application of vibratory sources started and it still needs improvement. An approach has been worked out that minimizes the level of harmonic distortion by designing the signal similar to the harmonic distortion. An arbitrary length filter is optimized using the Simulated Annealing global optimization approach to design a harmonic signal. The approach deals with the convolution of a ratio trace (ratio of the harmonics with respect to the fundamental sweep) with the correlated "positive time" recorded signal and an arbitrary filter. Synthetic data study has revealed that this procedure of designing a signal similar to the desired harmonics using convolution of a suitable filter with theoretical ratio of harmonics with fundamental sweep helps in reducing the problem of harmonic distortion. Once we generate a similar signal for a vibroseis source using an optimized filter, then, this filter could be used to generate harmonics, which can be subtracted from the main cross-correlated trace to get the better, undistorted image of the subsurface. Designing the predicted harmonics to reduce the energy in the trace by considering weak reflection and observed harmonics together yields the desired result (resolution of weak reflected signal from the harmonic distortion). As optimization steps proceeds forward it is possible to observe from the difference plots of desired and predicted harmonics how weak reflections evolved from the harmonic distortion gradually during later iterations of global optimization. The procedure is applied in resolving weak reflections from a number of traces considered together. For a more precise design of harmonics SA procedure needs longer computation time which is impractical to deal with voluminous seismic data. However, the objective of resolving weak reflection signal in the strong harmonic noise can be achieved with fast computation using faster cooling schedule and less number of iterations and number of moves in simulated annealing procedure. This process could help in reducing the harmonics distortion and achieving the objective of resolving the lost weak reflection events in the cross-correlated seismic traces. Acknowledgements: The research was supported under the European Marie Curie Host Fellowships for Transfer of Knowledge (TOK) Development Host Scheme (contract no. MTKD-CT-2006-042537).

Rapid and Robust Cross-Correlation-Based Seismic Phase Identification Using an Approximate Nearest Neighbor Method

NASA Astrophysics Data System (ADS)

Tibi, R.; Young, C. J.; Gonzales, A.; Ballard, S.; Encarnacao, A. V.

2016-12-01

The matched filtering technique involving the cross-correlation of a waveform of interest with archived signals from a template library has proven to be a powerful tool for detecting events in regions with repeating seismicity. However, waveform correlation is computationally expensive, and therefore impractical for large template sets unless dedicated distributed computing hardware and software are used. In this study, we introduce an Approximate Nearest Neighbor (ANN) approach that enables the use of very large template libraries for waveform correlation without requiring a complex distributed computing system. Our method begins with a projection into a reduced dimensionality space based on correlation with a randomized subset of the full template archive. Searching for a specified number of nearest neighbors is accomplished by using randomized K-dimensional trees. We used the approach to search for matches to each of 2700 analyst-reviewed signal detections reported for May 2010 for the IMS station MKAR. The template library in this case consists of a dataset of more than 200,000 analyst-reviewed signal detections for the same station from 2002-2014 (excluding May 2010). Of these signal detections, 60% are teleseismic first P, and 15% regional phases (Pn, Pg, Sn, and Lg). The analyses performed on a standard desktop computer shows that the proposed approach performs the search of the large template libraries about 20 times faster than the standard full linear search, while achieving recall rates greater than 80%, with the recall rate increasing for higher correlation values. To decide whether to confirm a match, we use a hybrid method involving a cluster approach for queries with two or more matches, and correlation score for single matches. Of the signal detections that passed our confirmation process, 52% were teleseismic first P, and 30% were regional phases.

A new class of random processes with application to helicopter noise

NASA Technical Reports Server (NTRS)

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

1989-01-01

The concept of dividing random processes into classes (e.g., stationary, locally stationary, periodically correlated, and harmonizable) has long been employed. A new class of random processes is introduced which includes many of these processes as well as other interesting processes which fall into none of the above classes. Such random processes are denoted as linearly correlated. This class is shown to include the familiar stationary and periodically correlated processes as well as many other, both harmonizable and non-harmonizable, nonstationary processes. When a process is linearly correlated for all t and harmonizable, its two-dimensional power spectral density S(x) (omega 1, omega 2) is shown to take a particularly simple form, being non-zero only on lines such that omega 1 to omega 2 = + or - r(k) where the r(k's) are (not necessarily equally spaced) roots of a characteristic function. The relationship of such processes to the class of stationary processes is examined. In addition, the application of such processes in the analysis of typical helicopter noise signals is described.

A new class of random processes with application to helicopter noise

NASA Technical Reports Server (NTRS)

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

1989-01-01

The concept of dividing random processes into classes (e.g., stationary, locally stationary, periodically correlated, and harmonizable) has long been employed. A new class of random processes is introduced which includes many of these processes as well as other interesting processes which fall into none of the above classes. Such random processes are denoted as linearly correlated. This class is shown to include the familiar stationary and periodically correlated processes as well as many other, both harmonizable and non-harmonizable, nonstationary processes. When a process is linearly correlated for all t and harmonizable, its two-dimensional power spectral density S(x)(omega 1, omega 2) is shown to take a particularly simple form, being non-zero only on lines such that omega 1 to omega 2 = + or - r(k) where the r(k's) are (not necessarily equally spaced) roots of a characteristic function. The relationship of such processes to the class of stationary processes is examined. In addition, the application of such processes in the analysis of typical helicopter noise signals is described.

Ambient Noise Correlation Amplitudes and Local Site Response

NASA Astrophysics Data System (ADS)

Bowden, D. C.; Tsai, V. C.; Lin, F. C.

2014-12-01

We investigate amplitudes from ambient noise cross correlations in a spatially dense array. Our study of wave propagation effects and ambient noise is focused on the Long Beach Array, with more than 5000 single component geophones in an area of about 100 square kilometers, providing high resolution imaging of shallow crustal features. The method allows for observations of ground properties like site response and attenuation, which can well supplement traditional velocity models and simulations for seismic hazard. Traditional ambient noise cross correlations have proven to be an effective means of measuring velocity information about surface waves, but the amplitudes of such signals in traditional processing are often distorted. We discuss a method of signal processing which preserves relative amplitudes of signals within an array, and the subsequent processing to track wave motion across the array. Previous work showed promising correlation to known local structure, but did not represent a thorough application of tomographic methods. Now we extend the methodology to more robustly consider wavefront focusing and defocusing, interference with higher modes, and discuss the differing effects of local site response, attenuation, and scattering. Application of Helmholtz tomography and determination of local site amplification has previously been demonstrated using earthquake data on the continental scale with USArray, but the exploitation of the ambient noise field is required both for the higher frequencies needed by seismic hazard studies and for the short deployment time of a Long Beach scale array. We outline both the successes and shortcomings of the methodology, and show how it can be extended for use on future arrays.

Decomposing decision components in the Stop-signal task: A model-based approach to individual differences in inhibitory control

PubMed Central

White, Corey N.; Congdon, Eliza; Mumford, Jeanette A.; Karlsgodt, Katherine H.; Sabb, Fred W.; Freimer, Nelson B.; London, Edythe D.; Cannon, Tyrone D.; Bilder, Robert M.; Poldrack, Russell A.

2014-01-01

The Stop-signal task (SST), in which participants must inhibit prepotent responses, has been used to identify neural systems that vary with individual differences in inhibitory control. To explore how these differences relate to other aspects of decision-making, a drift diffusion model of simple decisions was fitted to SST data from Go trials to extract measures of caution, motor execution time, and stimulus processing speed for each of 123 participants. These values were used to probe fMRI data to explore individual differences in neural activation. Faster processing of the Go stimulus correlated with greater activation in the right frontal pole for both Go and Stop trials. On Stop trials stimulus processing speed also correlated with regions implicated in inhibitory control, including the right inferior frontal gyrus, medial frontal gyrus, and basal ganglia. Individual differences in motor execution time correlated with activation of the right parietal cortex. These findings suggest a robust relationship between the speed of stimulus processing and inhibitory processing at the neural level. This model-based approach provides novel insight into the interrelationships among decision components involved in inhibitory control, and raises interesting questions about strategic adjustments in performance and inhibitory deficits associated with psychopathology. PMID:24405185

Turbulent Statistics From Time-Resolved PIV Measurements of a Jet Using Empirical Mode Decomposition

NASA Technical Reports Server (NTRS)

Dahl, Milo D.

2013-01-01

Empirical mode decomposition is an adaptive signal processing method that when applied to a broadband signal, such as that generated by turbulence, acts as a set of band-pass filters. This process was applied to data from time-resolved, particle image velocimetry measurements of subsonic jets prior to computing the second-order, two-point, space-time correlations from which turbulent phase velocities and length and time scales could be determined. The application of this method to large sets of simultaneous time histories is new. In this initial study, the results are relevant to acoustic analogy source models for jet noise prediction. The high frequency portion of the results could provide the turbulent values for subgrid scale models for noise that is missed in large-eddy simulations. The results are also used to infer that the cross-correlations between different components of the decomposed signals at two points in space, neglected in this initial study, are important.

Turbulent Statistics from Time-Resolved PIV Measurements of a Jet Using Empirical Mode Decomposition

NASA Technical Reports Server (NTRS)

Dahl, Milo D.

2012-01-01

Empirical mode decomposition is an adaptive signal processing method that when applied to a broadband signal, such as that generated by turbulence, acts as a set of band-pass filters. This process was applied to data from time-resolved, particle image velocimetry measurements of subsonic jets prior to computing the second-order, two-point, space-time correlations from which turbulent phase velocities and length and time scales could be determined. The application of this method to large sets of simultaneous time histories is new. In this initial study, the results are relevant to acoustic analogy source models for jet noise prediction. The high frequency portion of the results could provide the turbulent values for subgrid scale models for noise that is missed in large-eddy simulations. The results are also used to infer that the cross-correlations between different components of the decomposed signals at two points in space, neglected in this initial study, are important.

Pipeline Processing with an Iterative, Context-based Detection Model

DTIC Science & Technology

2014-04-19

stripping the incoming data stream of repeating and irrelevant signals prior to running primary detectors , adaptive beamforming and matched field processing...framework, pattern detectors , correlation detectors , subspace detectors , matched field detectors , nuclear explosion monitoring 16. SECURITY CLASSIFICATION...10 5. Teleseismic paths from earthquakes in

Ventromedial prefrontal cortex activity and pathological worry in generalised anxiety disorder.

PubMed

Via, E; Fullana, M A; Goldberg, X; Tinoco-González, D; Martínez-Zalacaín, I; Soriano-Mas, C; Davey, C G; Menchón, J M; Straube, B; Kircher, T; Pujol, J; Cardoner, N; Harrison, B J

2018-05-09

Pathological worry is a hallmark feature of generalised anxiety disorder (GAD), associated with dysfunctional emotional processing. The ventromedial prefrontal cortex (vmPFC) is involved in the regulation of such processes, but the link between vmPFC emotional responses and pathological v. adaptive worry has not yet been examined.AimsTo study the association between worry and vmPFC activity evoked by the processing of learned safety and threat signals. In total, 27 unmedicated patients with GAD and 56 healthy controls (HC) underwent a differential fear conditioning paradigm during functional magnetic resonance imaging. Compared to HC, the GAD group demonstrated reduced vmPFC activation to safety signals and no safety-threat processing differentiation. This response was positively correlated with worry severity in GAD, whereas the same variables showed a negative and weak correlation in HC. Poor vmPFC safety-threat differentiation might characterise GAD, and its distinctive association with GAD worries suggests a neural-based qualitative difference between healthy and pathological worries.Declaration of interestNone.

Differences in neural activity when processing emotional arousal and valence in autism spectrum disorders.

PubMed

Tseng, Angela; Wang, Zhishun; Huo, Yuankai; Goh, Suzanne; Russell, James A; Peterson, Bradley S

2016-02-01

Individuals with autism spectrum disorders (ASD) often have difficulty recognizing and interpreting facial expressions of emotion, which may impair their ability to navigate and communicate successfully in their social, interpersonal environments. Characterizing specific differences between individuals with ASD and their typically developing (TD) counterparts in the neural activity subserving their experience of emotional faces may provide distinct targets for ASD interventions. Thus we used functional magnetic resonance imaging (fMRI) and a parametric experimental design to identify brain regions in which neural activity correlated with ratings of arousal and valence for a broad range of emotional faces. Participants (51 ASD, 84 TD) were group-matched by age, sex, IQ, race, and socioeconomic status. Using task-related change in blood-oxygen-level-dependent (BOLD) fMRI signal as a measure, and covarying for age, sex, FSIQ, and ADOS scores, we detected significant differences across diagnostic groups in the neural activity subserving the dimension of arousal but not valence. BOLD-signal in TD participants correlated inversely with ratings of arousal in regions associated primarily with attentional functions, whereas BOLD-signal in ASD participants correlated positively with arousal ratings in regions commonly associated with impulse control and default-mode activity. Only minor differences were detected between groups in the BOLD signal correlates of valence ratings. Our findings provide unique insight into the emotional experiences of individuals with ASD. Although behavioral responses to face-stimuli were comparable across diagnostic groups, the corresponding neural activity for our ASD and TD groups differed dramatically. The near absence of group differences for valence correlates and the presence of strong group differences for arousal correlates suggest that individuals with ASD are not atypical in all aspects of emotion-processing. Studying these similarities and differences may help us to understand the origins of divergent interpersonal emotional experience in persons with ASD. Hum Brain Mapp 37:443-461, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Differences in Neural Activity when Processing Emotional Arousal and Valence in Autism Spectrum Disorders

PubMed Central

Tseng, Angela; Wang, Zhishun; Huo, Yuankai; Goh, Suzanne; Russell, James A.; Peterson, Bradley S.

2016-01-01

Individuals with autism spectrum disorders (ASD) often have difficulty recognizing and interpreting facial expressions of emotion, which may impair their ability to navigate and communicate successfully in their social, interpersonal environments. Characterizing specific differences between individuals with ASD and their typically-developing (TD) counterparts in the neural activity subserving their experience of emotional faces may provide distinct targets for ASD interventions. Thus we used functional magnetic resonance imaging (fMRI) and a parametric experimental design to identify brain regions in which neural activity correlated with ratings of arousal and valence for a broad range of emotional faces. Participants (51 ASD, 84 TD) were group-matched by age, sex, IQ, race, and socioeconomic status. Using task-related change in blood-oxygen-level-dependent (BOLD) fMRI signal as a measure, and covarying for age, sex, FSIQ, and ADOS scores, we detected significant differences across diagnostic groups in the neural activity subserving the dimension of arousal but not valence. BOLD-signal in TD participants correlated inversely with ratings of arousal in regions associated primarily with attentional functions, whereas BOLD-signal in ASD participants correlated positively with arousal ratings in regions commonly associated with impulse control and default-mode activity. Only minor differences were detected between groups in the BOLD signal correlates of valence ratings. Our findings provide unique insight into the emotional experiences of individuals with ASD. Although behavioral responses to face-stimuli were comparable across diagnostic groups, the corresponding neural activity for our ASD and TD groups differed dramatically. The near absence of group differences for valence correlates and the presence of strong group differences for arousal correlates suggest that individuals with ASD are not atypical in all aspects of emotion-processing. Studying these similarities and differences may help us to understand the origins of divergent interpersonal emotional experience in persons with ASD. PMID:26526072

Using bivariate signal analysis to characterize the epileptic focus: the benefit of surrogates.

PubMed

Andrzejak, R G; Chicharro, D; Lehnertz, K; Mormann, F

2011-04-01

The disease epilepsy is related to hypersynchronous activity of networks of neurons. While acute epileptic seizures are the most extreme manifestation of this hypersynchronous activity, an elevated level of interdependence of neuronal dynamics is thought to persist also during the seizure-free interval. In multichannel recordings from brain areas involved in the epileptic process, this interdependence can be reflected in an increased linear cross correlation but also in signal properties of higher order. Bivariate time series analysis comprises a variety of approaches, each with different degrees of sensitivity and specificity for interdependencies reflected in lower- or higher-order properties of pairs of simultaneously recorded signals. Here we investigate which approach is best suited to detect putatively elevated interdependence levels in signals recorded from brain areas involved in the epileptic process. For this purpose, we use the linear cross correlation that is sensitive to lower-order signatures of interdependence, a nonlinear interdependence measure that integrates both lower- and higher-order properties, and a surrogate-corrected nonlinear interdependence measure that aims to specifically characterize higher-order properties. We analyze intracranial electroencephalographic recordings of the seizure-free interval from 29 patients with an epileptic focus located in the medial temporal lobe. Our results show that all three approaches detect higher levels of interdependence for signals recorded from the brain hemisphere containing the epileptic focus as compared to signals recorded from the opposite hemisphere. For the linear cross correlation, however, these differences are not significant. For the nonlinear interdependence measure, results are significant but only of moderate accuracy with regard to the discriminative power for the focal and nonfocal hemispheres. The highest significance and accuracy is obtained for the surrogate-corrected nonlinear interdependence measure.

Using bivariate signal analysis to characterize the epileptic focus: The benefit of surrogates

NASA Astrophysics Data System (ADS)

Andrzejak, R. G.; Chicharro, D.; Lehnertz, K.; Mormann, F.

2011-04-01

The disease epilepsy is related to hypersynchronous activity of networks of neurons. While acute epileptic seizures are the most extreme manifestation of this hypersynchronous activity, an elevated level of interdependence of neuronal dynamics is thought to persist also during the seizure-free interval. In multichannel recordings from brain areas involved in the epileptic process, this interdependence can be reflected in an increased linear cross correlation but also in signal properties of higher order. Bivariate time series analysis comprises a variety of approaches, each with different degrees of sensitivity and specificity for interdependencies reflected in lower- or higher-order properties of pairs of simultaneously recorded signals. Here we investigate which approach is best suited to detect putatively elevated interdependence levels in signals recorded from brain areas involved in the epileptic process. For this purpose, we use the linear cross correlation that is sensitive to lower-order signatures of interdependence, a nonlinear interdependence measure that integrates both lower- and higher-order properties, and a surrogate-corrected nonlinear interdependence measure that aims to specifically characterize higher-order properties. We analyze intracranial electroencephalographic recordings of the seizure-free interval from 29 patients with an epileptic focus located in the medial temporal lobe. Our results show that all three approaches detect higher levels of interdependence for signals recorded from the brain hemisphere containing the epileptic focus as compared to signals recorded from the opposite hemisphere. For the linear cross correlation, however, these differences are not significant. For the nonlinear interdependence measure, results are significant but only of moderate accuracy with regard to the discriminative power for the focal and nonfocal hemispheres. The highest significance and accuracy is obtained for the surrogate-corrected nonlinear interdependence measure.

Cyclostationarity approach for monitoring chatter and tool wear in high speed milling

NASA Astrophysics Data System (ADS)

Lamraoui, M.; Thomas, M.; El Badaoui, M.

2014-02-01

Detection of chatter and tool wear is crucial in the machining process and their monitoring is a key issue, for: (1) insuring better surface quality, (2) increasing productivity and (3) protecting both machines and safe workpiece. This paper presents an investigation of chatter and tool wear using the cyclostationary method to process the vibrations signals acquired from high speed milling. Experimental cutting tests were achieved on slot milling operation of aluminum alloy. The experimental set-up is designed for acquisition of accelerometer signals and encoding information picked up from an encoder. The encoder signal is used for re-sampling accelerometers signals in angular domain using a specific algorithm that was developed in LASPI laboratory. The use of cyclostationary on accelerometer signals has been applied for monitoring chatter and tool wear in high speed milling. The cyclostationarity appears on average properties (first order) of signals, on the energetic properties (second order) and it generates spectral lines at cyclic frequencies in spectral correlation. Angular power and kurtosis are used to analyze chatter phenomena. The formation of chatter is characterized by unstable, chaotic motion of the tool and strong anomalous fluctuations of cutting forces. Results show that stable machining generates only very few cyclostationary components of second order while chatter is strongly correlated to cyclostationary components of second order. By machining in the unstable region, chatter results in flat angular kurtosis and flat angular power, such as a pseudo (white) random signal with flat spectrum. Results reveal that spectral correlation and Wigner Ville spectrum or integrated Wigner Ville issued from second-order cyclostationary are an efficient parameter for the early diagnosis of faults in high speed machining, such as chatter, tool wear and bearings, compared to traditional stationary methods. Wigner Ville representation of the residual signal shows that the energy corresponding to the tooth passing decreases when chatter phenomenon occurs. The effect of the tool wear and the number of broken teeth on the excitation of structure resonances appears in Wigner Ville presentation.

Nonparametric Simulation of Signal Transduction Networks with Semi-Synchronized Update

PubMed Central

Nassiri, Isar; Masoudi-Nejad, Ali; Jalili, Mahdi; Moeini, Ali

2012-01-01

Simulating signal transduction in cellular signaling networks provides predictions of network dynamics by quantifying the changes in concentration and activity-level of the individual proteins. Since numerical values of kinetic parameters might be difficult to obtain, it is imperative to develop non-parametric approaches that combine the connectivity of a network with the response of individual proteins to signals which travel through the network. The activity levels of signaling proteins computed through existing non-parametric modeling tools do not show significant correlations with the observed values in experimental results. In this work we developed a non-parametric computational framework to describe the profile of the evolving process and the time course of the proportion of active form of molecules in the signal transduction networks. The model is also capable of incorporating perturbations. The model was validated on four signaling networks showing that it can effectively uncover the activity levels and trends of response during signal transduction process. PMID:22737250

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tang, Yanmei; Li, Xinli; Bai, Yan

The measurement of multiphase flow parameters is of great importance in a wide range of industries. In the measurement of multiphase, the signals from the sensors are extremely weak and often buried in strong background noise. It is thus desirable to develop effective signal processing techniques that can detect the weak signal from the sensor outputs. In this paper, two methods, i.e., lock-in-amplifier (LIA) and improved Duffing chaotic oscillator are compared to detect and process the weak signal. For sinusoidal signal buried in noise, the correlation detection with sinusoidal reference signal is simulated by using LIA. The improved Duffing chaoticmore » oscillator method, which based on the Wigner transformation, can restore the signal waveform and detect the frequency. Two methods are combined to detect and extract the weak signal. Simulation results show the effectiveness and accuracy of the proposed improved method. The comparative analysis shows that the improved Duffing chaotic oscillator method can restrain noise strongly since it is sensitive to initial conditions.« less

Parmeterization of spectra

NASA Technical Reports Server (NTRS)

Cornish, C. R.

1983-01-01

Following reception and analog to digital conversion (A/D) conversion, atmospheric radar backscatter echoes need to be processed so as to obtain desired information about atmospheric processes and to eliminate or minimize contaminating contributions from other sources. Various signal processing techniques have been implemented at mesosphere-stratosphere-troposphere (MST) radar facilities to estimate parameters of interest from received spectra. Such estimation techniques need to be both accurate and sufficiently efficient to be within the capabilities of the particular data-processing system. The various techniques used to parameterize the spectra of received signals are reviewed herein. Noise estimation, electromagnetic interference, data smoothing, correlation, and the Doppler effect are among the specific points addressed.

Low-cost TDRSS communications for NASA's long duration balloon project

NASA Technical Reports Server (NTRS)

Israel, David J.

1993-01-01

A new transponder and RF ground support equipment for the NASA Tracking and Data Relay Satellite System (TDRSS) intended to support long duration scientific balloon flights in Antarctica are described. The new balloon class transponder features a highly integrated spread spectrum receiver design based on programmable charge coupled device (CCD) correlators and digital signal processing chips. The correlator chip is a Lincoln Labs 4ABC with four CCD channels. The balloon transponder is capable of reporting an estimate of its input bit error rate using digital signal processing. The TDRSS user RF test set is based on a set of RF ground support equipment capable of providing both the RF communications and direct control and monitoring necessary for transponder testing and a two-way RF link for preflight testing.

Physiological correlates of mental workload

NASA Technical Reports Server (NTRS)

Zacharias, G. L.

1980-01-01

A literature review was conducted to assess the basis of and techniques for physiological assessment of mental workload. The study findings reviewed had shortcomings involving one or more of the following basic problems: (1) physiologic arousal can be easily driven by nonworkload factors, confounding any proposed metric; (2) the profound absence of underlying physiologic models has promulgated a multiplicity of seemingly arbitrary signal processing techniques; (3) the unspecified multidimensional nature of physiological "state" has given rise to a broad spectrum of competing noncommensurate metrics; and (4) the lack of an adequate definition of workload compels physiologic correlations to suffer either from the vagueness of implicit workload measures or from the variance of explicit subjective assessments. Using specific studies as examples, two basic signal processing/data reduction techniques in current use, time and ensemble averaging are discussed.

Neural Correlation Is Stimulus Modulated by Feedforward Inhibitory Circuitry

PubMed Central

Middleton, Jason W.; Omar, Cyrus; Doiron, Brent; Simons, Daniel J.

2012-01-01

Correlated variability of neural spiking activity has important consequences for signal processing. How incoming sensory signals shape correlations of population responses remains unclear. Cross-correlations between spiking of different neurons may be particularly consequential in sparsely firing neural populations such as those found in layer 2/3 of sensory cortex. In rat whisker barrel cortex, we found that pairs of excitatory layer 2/3 neurons exhibit similarly low levels of spike count correlation during both spontaneous and sensory-evoked states. The spontaneous activity of excitatory–inhibitory neuron pairs is positively correlated, while sensory stimuli actively decorrelate joint responses. Computational modeling shows how threshold nonlinearities and local inhibition form the basis of a general decorrelating mechanism. We show that inhibitory population activity maintains low correlations in excitatory populations, especially during periods of sensory-evoked coactivation. The role of feedforward inhibition has been previously described in the context of trial-averaged phenomena. Our findings reveal a novel role for inhibition to shape correlations of neural variability and thereby prevent excessive correlations in the face of feedforward sensory-evoked activation. PMID:22238086

The neural basis of functional neuroimaging signal with positron and single-photon emission tomography.

PubMed

Sestini, S

2007-07-01

Functional imaging techniques such as positron and single-photon emission tomography exploit the relationship between neural activity, energy demand and cerebral blood flow to functionally map the brain. Despite the fact that neurobiological processes are not completely understood, several results have revealed the signals that trigger the metabolic and vascular changes accompanying variations in neural activity. Advances in this field have demonstrated that release of the major excitatory neurotransmitter glutamate initiates diverse signaling processes between neurons, astrocytes and blood perfusion, and that this signaling is crucial for the occurrence of brain imaging signals. Better understanding of the neural sites of energy consumption and the temporal correlation between energy demand, energy consumption and associated cerebrovascular hemodynamics gives novel insight into the potential of these imaging tools in the study of metabolic neurodegenerative disorders.

FIBRE AND INTEGRATED OPTICS. OPTICAL PROCESSING OF INFORMATION: Method for optical data processing based on a two-pulse photon echo

NASA Astrophysics Data System (ADS)

Zakharov, S. M.; Manykin, Eduard A.

1995-02-01

The principles of optical processing based on dynamic spatial—temporal properties of two-pulse photon echo signals are considered. The properties of a resonant medium as an on-line filter of temporal and spatial frequencies are discussed. These properties are due to the sensitivity of such a medium to the Fourier spectrum of the second exiting pulse. Degeneracy of quantum resonant systems, demonstrated by the coherent response dependence on the square of the amplitude of the second pulse, can be used for 'simultaneous' correlation processing of optical 'signals'. Various methods for the processing of the Fourier optical image are discussed.

Multi-Fault Diagnosis of Rolling Bearings via Adaptive Projection Intrinsically Transformed Multivariate Empirical Mode Decomposition and High Order Singular Value Decomposition

PubMed Central

Lv, Yong; Song, Gangbing

2018-01-01

Rolling bearings are important components in rotary machinery systems. In the field of multi-fault diagnosis of rolling bearings, the vibration signal collected from single channels tends to miss some fault characteristic information. Using multiple sensors to collect signals at different locations on the machine to obtain multivariate signal can remedy this problem. The adverse effect of a power imbalance between the various channels is inevitable, and unfavorable for multivariate signal processing. As a useful, multivariate signal processing method, Adaptive-projection has intrinsically transformed multivariate empirical mode decomposition (APIT-MEMD), and exhibits better performance than MEMD by adopting adaptive projection strategy in order to alleviate power imbalances. The filter bank properties of APIT-MEMD are also adopted to enable more accurate and stable intrinsic mode functions (IMFs), and to ease mode mixing problems in multi-fault frequency extractions. By aligning IMF sets into a third order tensor, high order singular value decomposition (HOSVD) can be employed to estimate the fault number. The fault correlation factor (FCF) analysis is used to conduct correlation analysis, in order to determine effective IMFs; the characteristic frequencies of multi-faults can then be extracted. Numerical simulations and the application of multi-fault situation can demonstrate that the proposed method is promising in multi-fault diagnoses of multivariate rolling bearing signal. PMID:29659510

Multi-Fault Diagnosis of Rolling Bearings via Adaptive Projection Intrinsically Transformed Multivariate Empirical Mode Decomposition and High Order Singular Value Decomposition.

PubMed

Yuan, Rui; Lv, Yong; Song, Gangbing

2018-04-16

Rolling bearings are important components in rotary machinery systems. In the field of multi-fault diagnosis of rolling bearings, the vibration signal collected from single channels tends to miss some fault characteristic information. Using multiple sensors to collect signals at different locations on the machine to obtain multivariate signal can remedy this problem. The adverse effect of a power imbalance between the various channels is inevitable, and unfavorable for multivariate signal processing. As a useful, multivariate signal processing method, Adaptive-projection has intrinsically transformed multivariate empirical mode decomposition (APIT-MEMD), and exhibits better performance than MEMD by adopting adaptive projection strategy in order to alleviate power imbalances. The filter bank properties of APIT-MEMD are also adopted to enable more accurate and stable intrinsic mode functions (IMFs), and to ease mode mixing problems in multi-fault frequency extractions. By aligning IMF sets into a third order tensor, high order singular value decomposition (HOSVD) can be employed to estimate the fault number. The fault correlation factor (FCF) analysis is used to conduct correlation analysis, in order to determine effective IMFs; the characteristic frequencies of multi-faults can then be extracted. Numerical simulations and the application of multi-fault situation can demonstrate that the proposed method is promising in multi-fault diagnoses of multivariate rolling bearing signal.

A MUSIC-based method for SSVEP signal processing.

PubMed

Chen, Kun; Liu, Quan; Ai, Qingsong; Zhou, Zude; Xie, Sheng Quan; Meng, Wei

2016-03-01

The research on brain computer interfaces (BCIs) has become a hotspot in recent years because it offers benefit to disabled people to communicate with the outside world. Steady state visual evoked potential (SSVEP)-based BCIs are more widely used because of higher signal to noise ratio and greater information transfer rate compared with other BCI techniques. In this paper, a multiple signal classification based method was proposed for multi-dimensional SSVEP feature extraction. 2-second data epochs from four electrodes achieved excellent accuracy rates including idle state detection. In some asynchronous mode experiments, the recognition accuracy reached up to 100%. The experimental results showed that the proposed method attained good frequency resolution. In most situations, the recognition accuracy was higher than canonical correlation analysis, which is a typical method for multi-channel SSVEP signal processing. Also, a virtual keyboard was successfully controlled by different subjects in an unshielded environment, which proved the feasibility of the proposed method for multi-dimensional SSVEP signal processing in practical applications.

Association between glutamate/glutamine and blood oxygen level dependent signal in the left dorsolateral prefrontal region during verbal working memory.

PubMed

Vijayakumari, Anupa A; Thomas, Bejoy; Menon, Ramshekhar N; Kesavadas, Chandrasekharan

2018-04-11

Functional MRI (fMRI) has provided much insight into the changes in the neuronal activity on the basis of blood oxygen level dependent (BOLD) phenomenon. The dynamic changes in the metabolites can be detected using functional proton magnetic resonance spectroscopy (H-fMRS). The strategy of combining fMRI and H-fMRS would facilitate the understanding of the neurochemical interpretation of the BOLD signal. The dorsolateral prefrontal region is critically involved in the processing of working memory (WM), as demonstrated by the studies involving the neuroimaging, neuropsychological, and electrophysiological experiments. In this study, we tested the association between BOLD signal and changes in brain metabolites in the left dorsolateral prefrontal region using N-back verbal WM task. We used single-voxel task-based H-MRS acquired in the left dorsolateral prefrontal region and fMRI during the performance of N-back verbal WM task to investigate the association between changes in metabolites and BOLD response in 10 healthy participants. The correlation between changes in metabolites and percent signal change was examined by the Pearson correlation. The Pearson correlation analysis revealed a significant positive correlation between the BOLD signal and glutamate/glutamine in the left dorsolateral prefrontal region during the verbal WM. Our finding suggests that glutamate/glutamine cycle plays a critical role in the neuronal activation as reflected by the changes in the BOLD response.

Multi-ball and one-ball geolocation and location verification

NASA Astrophysics Data System (ADS)

Nelson, D. J.; Townsend, J. L.

2017-05-01

We present analysis methods that may be used to geolocate emitters using one or more moving receivers. While some of the methods we present may apply to a broader class of signals, our primary interest is locating and tracking ships from short pulsed transmissions, such as the maritime Automatic Identification System (AIS.) The AIS signal is difficult to process and track since the pulse duration is only 25 milliseconds, and the pulses may only be transmitted every six to ten seconds. Several fundamental problems are addressed, including demodulation of AIS/GMSK signals, verification of the emitter location, accurate frequency and delay estimation and identification of pulse trains from the same emitter. In particular, we present several new correlation methods, including cross-cross correlation that greatly improves correlation accuracy over conventional methods and cross- TDOA and cross-FDOA functions that make it possible to estimate time and frequency delay without the need of computing a two dimensional cross-ambiguity surface. By isolating pulses from the same emitter and accurately tracking the received signal frequency, we are able to accurately estimate the emitter location from the received Doppler characteristics.

Response inhibition, preattentive processing, and sex difference in young children: an event-related potential study.

PubMed

Liu, Tongran; Xiao, Tong; Shi, Jiannong

2013-02-13

Response inhibition and preattentive processing are two important cognitive abilities for child development, and the current study adopted both behavioral and electrophysiological protocols to examine whether young children's response inhibition correlated with their preattentive processing. A Go/Nogo task was used to explore young children's response inhibition performances and an Oddball task with event-related potential recordings was used to measure their preattentive processing. The behavioral results showed that girls committed significantly fewer commission error rates, which showed that girls had stronger inhibition control abilities than boys. Girls also achieved higher d' scores in the Go/Nogo task, which indicated that they were more sensitive to the stimulus signals than boys. Although the electrophysiological results of preattentive processing did not show any sex differences, the correlation patterns between children's response inhibition and preattentive processing were different between these two groups: the neural response speed of preattentive processing (mismatch negativity peak latency) negatively correlated with girls' commission error rates and positively correlated with boys' correct hit rates. The current findings supported that the preattentive processing correlated with human inhibition control performances, and further showed that girls' better inhibition responses might be because of the influence of their preattentive processing.

The 1976 Helios and Pioneer solar conjunctions-continuing corroboration of the link between Doppler noise and integrated signal path electron density

NASA Technical Reports Server (NTRS)

Berman, A. L.; Wackley, J. A.; Rockwell, S. T.

1976-01-01

Observed Doppler noise (rms phase jitter) from the 1976 solar conjunctions of the Helios 1 and 2 and the Pioneer 10 and 11 spacecraft was processed with a recently developed Doppler noise model ISEDB. Good agreement is obtained between the observed data and the model. Correlation is shown between deviations from the ISEDB model and sunspot activity, but it is insufficient to be modeled. Correlation is also shown between ISEDB model deviations for (spacecraft) signal paths on the same side of the sun.

Contrast Responsivity in MT+ Correlates with Phonological Awareness and Reading Measures in Children

PubMed Central

Ben-Shachar, Michal; Dougherty, Robert F.; Deutsch, Gayle K.; Wandell, Brian A.

2007-01-01

There are several independent sets of findings concerning the neural basis of reading. One set demonstrates a powerful relationship between phonological processing and reading skills. Another set reveals a relationship between visual responses in the motion pathways and reading skills. It is widely assumed that these two findings are unrelated. We tested the hypothesis that phonological awareness is related to motion responsivity in children’s MT+. We measured BOLD signals to drifting gratings as a function of contrast. Subjects were 35 children ages 7–12y with a wide range of reading skills. Contrast responsivity in MT+, but not V1, was correlated with phonological awareness and to a lesser extent with two other measures of reading. No correlation was found between MT+ signals and rapid naming, age or general IQ measures. These results establish an important link between visual and phonological processing in children and suggest that MT+ responsivity is a marker for healthy reading development. PMID:17689981

Spin-echo based diagonal peak suppression in solid-state MAS NMR homonuclear chemical shift correlation spectra

NASA Astrophysics Data System (ADS)

Wang, Kaiyu; Zhang, Zhiyong; Ding, Xiaoyan; Tian, Fang; Huang, Yuqing; Chen, Zhong; Fu, Riqiang

2018-02-01

The feasibility of using the spin-echo based diagonal peak suppression method in solid-state MAS NMR homonuclear chemical shift correlation experiments is demonstrated. A complete phase cycling is designed in such a way that in the indirect dimension only the spin diffused signals are evolved, while all signals not involved in polarization transfer are refocused for cancellation. A data processing procedure is further introduced to reconstruct this acquired spectrum into a conventional two-dimensional homonuclear chemical shift correlation spectrum. A uniformly 13C, 15N labeled Fmoc-valine sample and the transmembrane domain of a human protein, LR11 (sorLA), in native Escherichia coli membranes have been used to illustrate the capability of the proposed method in comparison with standard 13C-13C chemical shift correlation experiments.

Digital signal processor and processing method for GPS receivers

NASA Technical Reports Server (NTRS)

Thomas, Jr., Jess B. (Inventor)

1989-01-01

A digital signal processor and processing method therefor for use in receivers of the NAVSTAR/GLOBAL POSITIONING SYSTEM (GPS) employs a digital carrier down-converter, digital code correlator and digital tracking processor. The digital carrier down-converter and code correlator consists of an all-digital, minimum bit implementation that utilizes digital chip and phase advancers, providing exceptional control and accuracy in feedback phase and in feedback delay. Roundoff and commensurability errors can be reduced to extremely small values (e.g., less than 100 nanochips and 100 nanocycles roundoff errors and 0.1 millichip and 1 millicycle commensurability errors). The digital tracking processor bases the fast feedback for phase and for group delay in the C/A, P.sub.1, and P.sub.2 channels on the L.sub.1 C/A carrier phase thereby maintaining lock at lower signal-to-noise ratios, reducing errors in feedback delays, reducing the frequency of cycle slips and in some cases obviating the need for quadrature processing in the P channels. Simple and reliable methods are employed for data bit synchronization, data bit removal and cycle counting. Improved precision in averaged output delay values is provided by carrier-aided data-compression techniques. The signal processor employs purely digital operations in the sense that exactly the same carrier phase and group delay measurements are obtained, to the last decimal place, every time the same sampled data (i.e., exactly the same bits) are processed.

Exploring the stochastic dynamics of correlated movement of receptor proteins in plasma membranes in vivo

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Jung Y., E-mail: jyhuang@faculty.nctu.edu.tw; Lin, Chien Y.

Ligand-induced receptor dimerization plays a crucial role in the signaling process of living cells. In this study, we developed a theoretical model and performed single-molecule tracking to explore the correlated diffusion processes of liganded epidermal growth factor receptors prior to dimer formation. We disclosed that both an attractive potential between liganded receptor proteins in proximity and correlated fluctuations in the local environments of the proteins play an important role to produce the observed correlated movement of the receptors. This result can serve as the foundation to shed light on the way in which receptor functions are regulated in plasma membranesmore » in vivo.« less

Characteristic of a Digital Correlation Radiometer Back End with Finite Wordlength

NASA Technical Reports Server (NTRS)

Biswas, Sayak K.; Hyde, David W.; James, Mark W.; Cecil, Daniel J.

2017-01-01

The performance characteristic of a digital correlation radiometer signal processing back end (DBE) is analyzed using a simulator. The particular design studied here corresponds to the airborne Hurricane Imaging radiometer which was jointly developed by the NASA Marshall Space Flight Center, University of Michigan, University of Central Florida and NOAA. Laboratory and flight test data is found to be in accord with the simulation results. Overall design seems to be optimum for the typical input signal dynamic range. It was found that the performance of the digital kurtosis could be improved by lowering the DBE input power level. An unusual scaling between digital correlation channels observed in the instrument data is confirmed to be a DBE characteristic.

Flies and humans share a motion estimation strategy that exploits natural scene statistics

PubMed Central

Clark, Damon A.; Fitzgerald, James E.; Ales, Justin M.; Gohl, Daryl M.; Silies, Marion A.; Norcia, Anthony M.; Clandinin, Thomas R.

2014-01-01

Sighted animals extract motion information from visual scenes by processing spatiotemporal patterns of light falling on the retina. The dominant models for motion estimation exploit intensity correlations only between pairs of points in space and time. Moving natural scenes, however, contain more complex correlations. Here we show that fly and human visual systems encode the combined direction and contrast polarity of moving edges using triple correlations that enhance motion estimation in natural environments. Both species extract triple correlations with neural substrates tuned for light or dark edges, and sensitivity to specific triple correlations is retained even as light and dark edge motion signals are combined. Thus, both species separately process light and dark image contrasts to capture motion signatures that can improve estimation accuracy. This striking convergence argues that statistical structures in natural scenes have profoundly affected visual processing, driving a common computational strategy over 500 million years of evolution. PMID:24390225

The ALMA correlator

NASA Astrophysics Data System (ADS)

Escoffier, R. P.; Comoretto, G.; Webber, J. C.; Baudry, A.; Broadwell, C. M.; Greenberg, J. H.; Treacy, R. R.; Cais, P.; Quertier, B.; Camino, P.; Bos, A.; Gunst, A. W.

2007-02-01

Aims: The Atacama Large Millimeter Array (ALMA) is an international astronomy facility to be used for detecting and imaging all types of astronomical sources at millimeter and submillimeter wavelengths at a 5000-m elevation site in the Atacama Desert of Chile. Our main aims are: describe the correlator sub-system which is that part of the ALMA system that combines the signal from up to 64 remote individual radio antennas and forms them into a single instrument; emphasize the high spectral resolution and the configuration flexibility available with the ALMA correlator. Methods: The main digital signal processing features and a block diagram of the correlator being constructed for the ALMA radio astronomy observatory are presented. Tables of observing modes and spectral resolutions offered by the correlator system are given together with some examples of multi-resolution spectral modes. Results: The correlator is delivered by quadrants and the first quadrant is being tested while most of the other printed circuit cards required by the system have been produced. In its final version the ALMA correlator will process the outputs of up to 64 antennas using an instantaneous bandwidth of 8 GHz in each of two polarizations per antenna. In the frequency division mode, unrivalled spectral flexibility together with very high resolution (3.8 kHz) and up to 8192 spectral points are achieved. In the time division mode high time resolution is available with minimum data dump rates of 16 ms for all cross-products.

Weak correlations between hemodynamic signals and ongoing neural activity during the resting state

PubMed Central

Winder, Aaron T.; Echagarruga, Christina; Zhang, Qingguang; Drew, Patrick J.

2017-01-01

Spontaneous fluctuations in hemodynamic signals in the absence of a task or overt stimulation are used to infer neural activity. We tested this coupling by simultaneously measuring neural activity and changes in cerebral blood volume (CBV) in the somatosensory cortex of awake, head-fixed mice during periods of true rest, and during whisker stimulation and volitional whisking. Here we show that neurovascular coupling was similar across states, and large spontaneous CBV changes in the absence of sensory input were driven by volitional whisker and body movements. Hemodynamic signals during periods of rest were weakly correlated with neural activity. Spontaneous fluctuations in CBV and vessel diameter persisted when local neural spiking and glutamatergic input was blocked, and during blockade of noradrenergic receptors, suggesting a non-neuronal origin for spontaneous CBV fluctuations. Spontaneous hemodynamic signals reflect a combination of behavior, local neural activity, and putatively non-neural processes. PMID:29184204

Weak correlations between hemodynamic signals and ongoing neural activity during the resting state.

PubMed

Winder, Aaron T; Echagarruga, Christina; Zhang, Qingguang; Drew, Patrick J

2017-12-01

Spontaneous fluctuations in hemodynamic signals in the absence of a task or overt stimulation are used to infer neural activity. We tested this coupling by simultaneously measuring neural activity and changes in cerebral blood volume (CBV) in the somatosensory cortex of awake, head-fixed mice during periods of true rest and during whisker stimulation and volitional whisking. We found that neurovascular coupling was similar across states and that large, spontaneous CBV changes in the absence of sensory input were driven by volitional whisker and body movements. Hemodynamic signals during periods of rest were weakly correlated with neural activity. Spontaneous fluctuations in CBV and vessel diameter persisted when local neural spiking and glutamatergic input were blocked, as well as during blockade of noradrenergic receptors, suggesting a non-neuronal origin for spontaneous CBV fluctuations. Spontaneous hemodynamic signals reflect a combination of behavior, local neural activity, and putatively non-neural processes.

Using multiple-accumulator CMACs to improve efficiency of the X part of an input-buffered FX correlator

NASA Astrophysics Data System (ADS)

Lapshev, Stepan; Hasan, S. M. Rezaul

2017-04-01

This paper presents the approach of using complex multiplier-accumulators (CMACs) with multiple accumulators to reduce the total number of memory operations in an input-buffered architecture for the X part of an FX correlator. A processing unit of this architecture uses an array of CMACs that are reused for different groups of baselines. The disadvantage of processing correlations in this way is that each input data sample has to be read multiple times from the memory because each input signal is used in many of these baseline groups. While a one-accumulator CMAC cannot switch to a different baseline until it is finished integrating the current one, a multiple-accumulator CMAC can. Thus, the array of multiple-accumulator CMACs can switch between processing different baselines that share some input signals at any moment to reuse the current data in the processing buffers. In this way significant reductions in the number of memory read operations are achieved with only a few accumulators per CMAC. For example, for a large number of input signals three-accumulator CMACs reduce the total number of memory operations by more than a third. Simulated energy measurements of four VLSI designs in a high-performance 28 nm CMOS technology are presented in this paper to demonstrate that using multiple accumulators can also lead to reduced power dissipation of the processing array. Using three accumulators as opposed to one has been found to reduce the overall energy of 8-bit CMACs by 1.4% through the reduction of the switching activity within their circuits, which is in addition to a more than 30% reduction in the memory.

Cell-Cell Contact Area Affects Notch Signaling and Notch-Dependent Patterning.

PubMed

Shaya, Oren; Binshtok, Udi; Hersch, Micha; Rivkin, Dmitri; Weinreb, Sheila; Amir-Zilberstein, Liat; Khamaisi, Bassma; Oppenheim, Olya; Desai, Ravi A; Goodyear, Richard J; Richardson, Guy P; Chen, Christopher S; Sprinzak, David

2017-03-13

During development, cells undergo dramatic changes in their morphology. By affecting contact geometry, these morphological changes could influence cellular communication. However, it has remained unclear whether and how signaling depends on contact geometry. This question is particularly relevant for Notch signaling, which coordinates neighboring cell fates through direct cell-cell signaling. Using micropatterning with a receptor trans-endocytosis assay, we show that signaling between pairs of cells correlates with their contact area. This relationship extends across contact diameters ranging from micrometers to tens of micrometers. Mathematical modeling predicts that dependence of signaling on contact area can bias cellular differentiation in Notch-mediated lateral inhibition processes, such that smaller cells are more likely to differentiate into signal-producing cells. Consistent with this prediction, analysis of developing chick inner ear revealed that ligand-producing hair cell precursors have smaller apical footprints than non-hair cells. Together, these results highlight the influence of cell morphology on fate determination processes. Copyright © 2017 Elsevier Inc. All rights reserved.

Cell-cell contact area affects Notch signaling and Notch-dependent patterning

PubMed Central

Shaya, Oren; Binshtok, Udi; Hersch, Micha; Rivkin, Dmitri; Weinreb, Sheila; Amir-Zilberstein, Liat; Khamaisi, Bassma; Oppenheim, Olya; Desai, Ravi A.; Goodyear, Richard J.; Richardson, Guy P.; Chen, Christopher S.; Sprinzak, David

2017-01-01

Summary During development, cells undergo dramatic changes in their morphology. By affecting contact geometry, these morphological changes could influence cellular communication. However, it has remained unclear whether and how signaling depends on contact geometry. This question is particularly relevant for Notch signaling, which coordinates neighboring cell fates through direct cell-cell signaling. Using micropatterning with a receptor trans-endocytosis assay, we show that signaling between pairs of cells correlates with their contact area. This relationship extends across contact diameters ranging from microns to tens of microns. Mathematical modeling predicts that dependence of signaling on contact area can bias cellular differentiation in Notch-mediated lateral inhibition processes, such that smaller cells are more likely to differentiate into signal-producing cells. Consistent with this prediction, analysis of developing chick inner ear revealed that ligand-producing hair cell precursors have smaller apical footprints than non-hair cells. Together, these results highlight the influence of cell morphology on fate determination processes. PMID:28292428

High efficiency processing for reduced amplitude zones detection in the HRECG signal

NASA Astrophysics Data System (ADS)

Dugarte, N.; Álvarez, A.; Balacco, J.; Mercado, G.; Gonzalez, A.; Dugarte, E.; Olivares, A.

2016-04-01

Summary - This article presents part of a more detailed research proposed in the medium to long term, with the intention of establishing a new philosophy of electrocardiogram surface analysis. This research aims to find indicators of cardiovascular disease in its early stage that may go unnoticed with conventional electrocardiography. This paper reports the development of a software processing which collect some existing techniques and incorporates novel methods for detection of reduced amplitude zones (RAZ) in high resolution electrocardiographic signal (HRECG).The algorithm consists of three stages, an efficient processing for QRS detection, averaging filter using correlation techniques and a step for RAZ detecting. Preliminary results show the efficiency of system and point to incorporation of techniques new using signal analysis with involving 12 leads.

Intelligent approach for analysis of respiratory signals and oxygen saturation in the sleep apnea/hypopnea syndrome.

PubMed

Moret-Bonillo, Vicente; Alvarez-Estévez, Diego; Fernández-Leal, Angel; Hernández-Pereira, Elena

2014-01-01

This work deals with the development of an intelligent approach for clinical decision making in the diagnosis of the Sleep Apnea/Hypopnea Syndrome, SAHS, from the analysis of respiratory signals and oxygen saturation in arterial blood, SaO2. In order to accomplish the task the proposed approach makes use of different artificial intelligence techniques and reasoning processes being able to deal with imprecise data. These reasoning processes are based on fuzzy logic and on temporal analysis of the information. The developed approach also takes into account the possibility of artifacts in the monitored signals. Detection and characterization of signal artifacts allows detection of false positives. Identification of relevant diagnostic patterns and temporal correlation of events is performed through the implementation of temporal constraints.

Intelligent Approach for Analysis of Respiratory Signals and Oxygen Saturation in the Sleep Apnea/Hypopnea Syndrome

PubMed Central

Moret-Bonillo, Vicente; Alvarez-Estévez, Diego; Fernández-Leal, Angel; Hernández-Pereira, Elena

2014-01-01

This work deals with the development of an intelligent approach for clinical decision making in the diagnosis of the Sleep Apnea/Hypopnea Syndrome, SAHS, from the analysis of respiratory signals and oxygen saturation in arterial blood, SaO2. In order to accomplish the task the proposed approach makes use of different artificial intelligence techniques and reasoning processes being able to deal with imprecise data. These reasoning processes are based on fuzzy logic and on temporal analysis of the information. The developed approach also takes into account the possibility of artifacts in the monitored signals. Detection and characterization of signal artifacts allows detection of false positives. Identification of relevant diagnostic patterns and temporal correlation of events is performed through the implementation of temporal constraints. PMID:25035712

A space-based classification system for RF transients

NASA Astrophysics Data System (ADS)

Moore, K. R.; Call, D.; Johnson, S.; Payne, T.; Ford, W.; Spencer, K.; Wilkerson, J. F.; Baumgart, C.

The FORTE (Fast On-Orbit Recording of Transient Events) small satellite is scheduled for launch in mid 1995. The mission is to measure and classify VHF (30-300 MHz) electromagnetic pulses, primarily due to lightning, within a high noise environment dominated by continuous wave carriers such as TV and FM stations. The FORTE Event Classifier will use specialized hardware to implement signal processing and neural network algorithms that perform onboard classification of RF transients and carriers. Lightning events will also be characterized with optical data telemetered to the ground. A primary mission science goal is to develop a comprehensive understanding of the correlation between the optical flash and the VHF emissions from lightning. By combining FORTE measurements with ground measurements and/or active transmitters, other science issues can be addressed. Examples include the correlation of global precipitation rates with lightning flash rates and location, the effects of large scale structures within the ionosphere (such as traveling ionospheric disturbances and horizontal gradients in the total electron content) on the propagation of broad bandwidth RF signals, and various areas of lightning physics. Event classification is a key feature of the FORTE mission. Neural networks are promising candidates for this application. The authors describe the proposed FORTE Event Classifier flight system, which consists of a commercially available digital signal processing board and a custom board, and discuss work on signal processing and neural network algorithms.

Histopathologic correlation of magnetic resonance imaging signal patterns in a spinal cord injury model.

PubMed

Weirich, S D; Cotler, H B; Narayana, P A; Hazle, J D; Jackson, E F; Coupe, K J; McDonald, C L; Langford, L A; Harris, J H

1990-07-01

Magnetic resonance imaging (MRI) provides a noninvasive method of monitoring the pathologic response to spinal cord injury. Specific MR signal intensity patterns appear to correlate with degrees of improvement in the neurologic status in spinal cord injury patients. Histologic correlation of two types of MR signal intensity patterns are confirmed in the current study using a rat animal model. Adult male Sprague-Dawley rats underwent spinal cord trauma at the midthoracic level using a weight-dropping technique. After laminectomy, 5- and 10-gm brass weights were dropped from designated heights onto a 0.1-gm impounder placed on the exposed dura. Animals allowed to regain consciousness demonstrated variable recovery of hind limb paraplegia. Magnetic resonance images were obtained from 2 hours to 1 week after injury using a 2-tesla MRI/spectrometer. Sacrifice under anesthesia was performed by perfusive fixation; spinal columns were excised en bloc, embedded, sectioned, and observed with the compound light microscope. Magnetic resonance axial images obtained during the time sequence after injury demonstrate a distinct correlation between MR signal intensity patterns and the histologic appearance of the spinal cord. Magnetic resonance imaging delineates the pathologic processes resulting from acute spinal cord injury and can be used to differentiate the type of injury and prognosis.

Determining Polarities Of Distant Lightning Strokes

NASA Technical Reports Server (NTRS)

Blakeslee, Richard J.; Brook, Marx

1990-01-01

Method for determining polarities of lightning strokes more than 400 km away. Two features of signal from each stroke correlated. New method based on fact each stroke observed thus far for which polarity determined unambiguously, initial polarity of tail same as polarity of initial deflection before initial-deflection signal altered by propagation effects. Receiving station equipped with electric-field-change antenna coupled to charge amplifier having time constant of order of 1 to 10 seconds. Output of amplifier fed to signal-processing circuitry, which determines initial polarity of tail.

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

PubMed

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

2004-08-01

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.

Chaotic time series analysis of vision evoked EEG

NASA Astrophysics Data System (ADS)

Zhang, Ningning; Wang, Hong

2010-01-01

To investigate the human brain activities for aesthetic processing, beautiful woman face picture and ugly buffoon face picture were applied. Twelve subjects were assigned the aesthetic processing task while the electroencephalogram (EEG) was recorded. Event-related brain potential (ERP) was required from the 32 scalp electrodes and the ugly buffoon picture produced larger amplitudes for the N1, P2, N2, and late slow wave components. Average ERP from the ugly buffoon picture were larger than that from the beautiful woman picture. The ERP signals shows that the ugly buffoon elite higher emotion waves than the beautiful woman face, because some expression is on the face of the buffoon. Then, chaos time series analysis was carried out to calculate the largest Lyapunov exponent using small data set method and the correlation dimension using G-P algorithm. The results show that the largest Lyapunov exponents of the ERP signals are greater than zero, which indicate that the ERP signals may be chaotic. The correlations dimensions coming from the beautiful woman picture are larger than that from the ugly buffoon picture. The comparison of the correlations dimensions shows that the beautiful face can excite the brain nerve cells. The research in the paper is a persuasive proof to the opinion that cerebrum's work is chaotic under some picture stimuli.

Spread spectrum communication link using surface wave devices

NASA Technical Reports Server (NTRS)

Hunsinger, B. J.; Fugit, B. B.

1971-01-01

A fast lock-up, 8-MHz bandwidth 8,000 bit per second data rate spread spectrum communication link breadboard is described that is implemented using surface wave devices as the primary signal generators and signal processing elements. It uses surface wave tapped delay lines in the transmitter to generate the signals and in the receiver to detect them. The breadboard provides a measured processing gain for Gaussian noise of 31.5 dB which is within one dB of the theoretical optimum. This development demonstrates that spread spectrum receivers implemented with surface wave devices have sensitivities and complexities comparable to those of serial correlation receivers, but synchronization search times which are two to three orders of magnitude smaller.

Dynamic Vehicle Detection via the Use of Magnetic Field Sensors

PubMed Central

Markevicius, Vytautas; Navikas, Dangirutis; Zilys, Mindaugas; Andriukaitis, Darius; Valinevicius, Algimantas; Cepenas, Mindaugas

2016-01-01

The vehicle detection process plays the key role in determining the success of intelligent transport management system solutions. The measurement of distortions of the Earth’s magnetic field using magnetic field sensors served as the basis for designing a solution aimed at vehicle detection. In accordance with the results obtained from research into process modeling and experimentally testing all the relevant hypotheses an algorithm for vehicle detection using the state criteria was proposed. Aiming to evaluate all of the possibilities, as well as pros and cons of the use of anisotropic magnetoresistance (AMR) sensors in the transport flow control process, we have performed a series of experiments with various vehicles (or different series) from several car manufacturers. A comparison of 12 selected methods, based on either the process of determining the peak signal values and their concurrence in time whilst calculating the delay, or by measuring the cross-correlation of these signals, was carried out. It was established that the relative error can be minimized via the Z component cross-correlation and Kz criterion cross-correlation methods. The average relative error of vehicle speed determination in the best case did not exceed 1.5% when the distance between sensors was set to 2 m. PMID:26797615

V-FASTR: THE VLBA FAST RADIO TRANSIENTS EXPERIMENT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wayth, Randall B.; Tingay, Steven J.; Brisken, Walter F.

2011-07-10

Recent discoveries of dispersed, non-periodic impulsive radio signals with single-dish radio telescopes have sparked significant interest in exploring the relatively uncharted space of fast transient radio signals. Here we describe V-FASTR, an experiment to perform a blind search for fast transient radio signals using the Very Long Baseline Array (VLBA). The experiment runs entirely in a commensal mode, alongside normal VLBA observations and operations. It is made possible by the features and flexibility of the DiFX software correlator that is used to process VLBA data. Using the VLBA for this type of experiment offers significant advantages over single-dish experiments, includingmore » a larger field of view, the ability to easily distinguish local radio-frequency interference from real signals, and the possibility to localize detected events on the sky to milliarcsecond accuracy. We describe our software pipeline, which accepts short integration ({approx} ms) spectrometer data from each antenna in real time during correlation and performs an incoherent dedispersion separately for each antenna, over a range of trial dispersion measures. The dedispersed data are processed by a sophisticated detector and candidate events are recorded. At the end of the correlation, small snippets of the raw data at the time of the events are stored for further analysis. We present the results of our event detection pipeline from some test observations of the pulsars B0329+54 and B0531+21 (the Crab pulsar).« less

Acousto-Optic Processing of 2-D Signals Using Temporal and Spatial Integration.

DTIC Science & Technology

1983-05-31

Documents includes data on: Architectures; Coherence Properties of Pulsed Laser Diodes; Acousto - optic device data; Dynamic Range Issues; Image correlation; Synthetic aperture radar; 2-D Fourier transform; and Moments.

Video-signal improvement using comb filtering techniques.

NASA Technical Reports Server (NTRS)

Arndt, G. D.; Stuber, F. M.; Panneton, R. J.

1973-01-01

Significant improvement in the signal-to-noise performance of television signals has been obtained through the application of comb filtering techniques. This improvement is achieved by removing the inherent redundancy in the television signal through linear prediction and by utilizing the unique noise-rejection characteristics of the receiver comb filter. Theoretical and experimental results describe the signal-to-noise ratio and picture-quality improvement obtained through the use of baseband comb filters and the implementation of a comb network as the loop filter in a phase-lock-loop demodulator. Attention is given to the fact that noise becomes correlated when processed by the receiver comb filter.

Auditory conflict and congruence in frontotemporal dementia.

PubMed

Clark, Camilla N; Nicholas, Jennifer M; Agustus, Jennifer L; Hardy, Christopher J D; Russell, Lucy L; Brotherhood, Emilie V; Dick, Katrina M; Marshall, Charles R; Mummery, Catherine J; Rohrer, Jonathan D; Warren, Jason D

2017-09-01

Impaired analysis of signal conflict and congruence may contribute to diverse socio-emotional symptoms in frontotemporal dementias, however the underlying mechanisms have not been defined. Here we addressed this issue in patients with behavioural variant frontotemporal dementia (bvFTD; n = 19) and semantic dementia (SD; n = 10) relative to healthy older individuals (n = 20). We created auditory scenes in which semantic and emotional congruity of constituent sounds were independently probed; associated tasks controlled for auditory perceptual similarity, scene parsing and semantic competence. Neuroanatomical correlates of auditory congruity processing were assessed using voxel-based morphometry. Relative to healthy controls, both the bvFTD and SD groups had impaired semantic and emotional congruity processing (after taking auditory control task performance into account) and reduced affective integration of sounds into scenes. Grey matter correlates of auditory semantic congruity processing were identified in distributed regions encompassing prefrontal, parieto-temporal and insular areas and correlates of auditory emotional congruity in partly overlapping temporal, insular and striatal regions. Our findings suggest that decoding of auditory signal relatedness may probe a generic cognitive mechanism and neural architecture underpinning frontotemporal dementia syndromes. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Nonlinear circuits for naturalistic visual motion estimation

PubMed Central

Fitzgerald, James E; Clark, Damon A

2015-01-01

Many animals use visual signals to estimate motion. Canonical models suppose that animals estimate motion by cross-correlating pairs of spatiotemporally separated visual signals, but recent experiments indicate that humans and flies perceive motion from higher-order correlations that signify motion in natural environments. Here we show how biologically plausible processing motifs in neural circuits could be tuned to extract this information. We emphasize how known aspects of Drosophila's visual circuitry could embody this tuning and predict fly behavior. We find that segregating motion signals into ON/OFF channels can enhance estimation accuracy by accounting for natural light/dark asymmetries. Furthermore, a diversity of inputs to motion detecting neurons can provide access to more complex higher-order correlations. Collectively, these results illustrate how non-canonical computations improve motion estimation with naturalistic inputs. This argues that the complexity of the fly's motion computations, implemented in its elaborate circuits, represents a valuable feature of its visual motion estimator. DOI: http://dx.doi.org/10.7554/eLife.09123.001 PMID:26499494

Low-frequency interaural cross correlation discrimination in stereophonic reproduction of musical tones

NASA Astrophysics Data System (ADS)

Kim, Sungyoung; Martens, William L.

2005-04-01

By industry standard (ITU-R. Recommendation BS.775-1), multichannel stereophonic signals within the frequency range of up to 80 or 120 Hz may be mixed and delivered via a single driver (e.g., a subwoofer) without significant impairment of stereophonic sound quality. The assumption that stereophonic information within such low-frequency content is not significant was tested by measuring discrimination thresholds for changes in interaural cross-correlation (IACC) within spectral bands containing the lowest frequency components of low-pitch musical tones. Performances were recorded for three different musical instruments playing single notes ranging in fundamental frequency from 41 Hz to 110 Hz. The recordings, made using a multichannel microphone array composed of five DPA 4006 pressure microphones, were processed to produce a set of stimuli that varied in interaural cross-correlation (IACC) within a low-frequency band, but were otherwise identical in a higher-frequency band. This correlation processing was designed to have minimal effect upon other psychoacoustic variables such as loudness and timbre. The results show that changes in interaural cross correlation (IACC) within low-frequency bands of low-pitch musical tones are most easily discriminated when decorrelated signals are presented via subwoofers positioned at extreme lateral angles (far from the median plane). [Work supported by VRQ.

Remote detection of weak aftershocks of the DPRK underground explosions using waveform cross correlation

NASA Astrophysics Data System (ADS)

Le Bras, R.; Rozhkov, M.; Bobrov, D.; Kitov, I. O.; Sanina, I.

2017-12-01

Association of weak seismic signals generated by low-magnitude aftershocks of the DPRK underground tests into event hypotheses represent a challenge for routine automatic and interactive processing at the International Data Centre (IDC) of the Comprehensive Nuclear-Test-Ban Treaty Organization, due to the relatively low station density of the International Monitoring System (IMS) seismic network. Since 2011, as an alternative, the IDC has been testing various prototype techniques of signal detection and event creation based on waveform cross correlation. Using signals measured by seismic stations of the IMS from DPRK explosions as waveform templates, the IDC detected several small (estimated mb between 2.2 and 3.6) seismic events after two DPRK tests conducted on September 9, 2016 and September 3, 2017. The obtained detections were associated with reliable event hypothesis and then used to locate these events relative to the epicenters of the DPRK explosions. We observe high similarity of the detected signals with the corresponding waveform templates. The newly found signals also correlate well between themselves. In addition, the values of the signal-to-noise ratios (SNR) estimated using the traces of cross correlation coefficients, increase with template length (from 5 s to 150 s), providing strong evidence in favour of their spatial closeness, which allows interpreting them as explosion aftershocks. We estimated the relative magnitudes of all aftershocks using the ratio of RMS amplitudes of the master and slave signal in the cross correlation windows characterized by the highest SNR. Additional waveform data from regional non-IMS stations MDJ and SEHB provide independent validation of these aftershock hypotheses. Since waveform templates from any single master event may be sub-efficient at some stations, we have also developed a method of joint usage of the DPRK and the biggest aftershocks templates to build more robust event hypotheses.

Low power, compact charge coupled device signal processing system

NASA Technical Reports Server (NTRS)

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

1980-01-01

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

Method and apparatus for determining position using global positioning satellites

NASA Technical Reports Server (NTRS)

Ward, John (Inventor); Ward, William S. (Inventor)

1998-01-01

A global positioning satellite receiver having an antenna for receiving a L1 signal from a satellite. The L1 signal is processed by a preamplifier stage including a band pass filter and a low noise amplifier and output as a radio frequency (RF) signal. A mixer receives and de-spreads the RF signal in response to a pseudo-random noise code, i.e., Gold code, generated by an internal pseudo-random noise code generator. A microprocessor enters a code tracking loop, such that during the code tracking loop, it addresses the pseudo-random code generator to cause the pseudo-random code generator to sequentially output pseudo-random codes corresponding to satellite codes used to spread the L1 signal, until correlation occurs. When an output of the mixer is indicative of the occurrence of correlation between the RF signal and the generated pseudo-random codes, the microprocessor enters an operational state which slows the receiver code sequence to stay locked with the satellite code sequence. The output of the mixer is provided to a detector which, in turn, controls certain routines of the microprocessor. The microprocessor will output pseudo range information according to an interrupt routine in response detection of correlation. The pseudo range information is to be telemetered to a ground station which determines the position of the global positioning satellite receiver.

Bayesian Inference for Signal-Based Seismic Monitoring

NASA Astrophysics Data System (ADS)

Moore, D.

2015-12-01

Traditional seismic monitoring systems rely on discrete detections produced by station processing software, discarding significant information present in the original recorded signal. SIG-VISA (Signal-based Vertically Integrated Seismic Analysis) is a system for global seismic monitoring through Bayesian inference on seismic signals. By modeling signals directly, our forward model is able to incorporate a rich representation of the physics underlying the signal generation process, including source mechanisms, wave propagation, and station response. This allows inference in the model to recover the qualitative behavior of recent geophysical methods including waveform matching and double-differencing, all as part of a unified Bayesian monitoring system that simultaneously detects and locates events from a global network of stations. We demonstrate recent progress in scaling up SIG-VISA to efficiently process the data stream of global signals recorded by the International Monitoring System (IMS), including comparisons against existing processing methods that show increased sensitivity from our signal-based model and in particular the ability to locate events (including aftershock sequences that can tax analyst processing) precisely from waveform correlation effects. We also provide a Bayesian analysis of an alleged low-magnitude event near the DPRK test site in May 2010 [1] [2], investigating whether such an event could plausibly be detected through automated processing in a signal-based monitoring system. [1] Zhang, Miao and Wen, Lianxing. "Seismological Evidence for a Low-Yield Nuclear Test on 12 May 2010 in North Korea". Seismological Research Letters, January/February 2015. [2] Richards, Paul. "A Seismic Event in North Korea on 12 May 2010". CTBTO SnT 2015 oral presentation, video at https://video-archive.ctbto.org/index.php/kmc/preview/partner_id/103/uiconf_id/4421629/entry_id/0_ymmtpps0/delivery/http

Adaptive Spatial Filter Based on Similarity Indices to Preserve the Neural Information on EEG Signals during On-Line Processing

PubMed Central

Villa-Parra, Ana Cecilia; Bastos-Filho, Teodiano; López-Delis, Alberto; Frizera-Neto, Anselmo; Krishnan, Sridhar

2017-01-01

This work presents a new on-line adaptive filter, which is based on a similarity analysis between standard electrode locations, in order to reduce artifacts and common interferences throughout electroencephalography (EEG) signals, but preserving the useful information. Standard deviation and Concordance Correlation Coefficient (CCC) between target electrodes and its correspondent neighbor electrodes are analyzed on sliding windows to select those neighbors that are highly correlated. Afterwards, a model based on CCC is applied to provide higher values of weight to those correlated electrodes with lower similarity to the target electrode. The approach was applied to brain computer-interfaces (BCIs) based on Canonical Correlation Analysis (CCA) to recognize 40 targets of steady-state visual evoked potential (SSVEP), providing an accuracy (ACC) of 86.44 ± 2.81%. In addition, also using this approach, features of low frequency were selected in the pre-processing stage of another BCI to recognize gait planning. In this case, the recognition was significantly (p<0.01) improved for most of the subjects (ACC≥74.79%), when compared with other BCIs based on Common Spatial Pattern, Filter Bank-Common Spatial Pattern, and Riemannian Geometry. PMID:29186848

Recharge signal identification based on groundwater level observations.

PubMed

Yu, Hwa-Lung; Chu, Hone-Jay

2012-10-01

This study applied a method of the rotated empirical orthogonal functions to directly decompose the space-time groundwater level variations and determine the potential recharge zones by investigating the correlation between the identified groundwater signals and the observed local rainfall records. The approach is used to analyze the spatiotemporal process of piezometric heads estimated by Bayesian maximum entropy method from monthly observations of 45 wells in 1999-2007 located in the Pingtung Plain of Taiwan. From the results, the primary potential recharge area is located at the proximal fan areas where the recharge process accounts for 88% of the spatiotemporal variations of piezometric heads in the study area. The decomposition of groundwater levels associated with rainfall can provide information on the recharge process since rainfall is an important contributor to groundwater recharge in semi-arid regions. Correlation analysis shows that the identified recharge closely associates with the temporal variation of the local precipitation with a delay of 1-2 months in the study area.

Introspective Minds: Using ALE Meta-Analyses to Study Commonalities in the Neural Correlates of Emotional Processing, Social & Unconstrained Cognition

PubMed Central

Schilbach, Leonhard; Bzdok, Danilo; Timmermans, Bert; Fox, Peter T.; Laird, Angela R.; Vogeley, Kai; Eickhoff, Simon B.

2012-01-01

Previous research suggests overlap between brain regions that show task-induced deactivations and those activated during the performance of social-cognitive tasks. Here, we present results of quantitative meta-analyses of neuroimaging studies, which confirm a statistical convergence in the neural correlates of social and resting state cognition. Based on the idea that both social and unconstrained cognition might be characterized by introspective processes, which are also thought to be highly relevant for emotional experiences, a third meta-analysis was performed investigating studies on emotional processing. By using conjunction analyses across all three sets of studies, we can demonstrate significant overlap of task-related signal change in dorso-medial prefrontal and medial parietal cortex, brain regions that have, indeed, recently been linked to introspective abilities. Our findings, therefore, provide evidence for the existence of a core neural network, which shows task-related signal change during socio-emotional tasks and during resting states. PMID:22319593

Love and the commitment problem in romantic relations and friendship.

PubMed

Gonzaga, G C; Keltner, D; Londahl, E A; Smith, M D

2001-08-01

On the basis of the proposition that love promotes commitment, the authors predicted that love would motivate approach, have a distinct signal, and correlate with commitment-enhancing processes when relationships are threatened. The authors studied romantic partners and adolescent opposite-sex friends during interactions that elicited love and threatened the bond. As expected, the experience of love correlated with approach-related states (desire, sympathy). Providing evidence for a nonverbal display of love, four affiliation cues (head nods, Duchenne smiles, gesticulation, forward leans) correlated with self-reports and partner estimates of love. Finally, the experience and display of love correlated with commitment-enhancing processes (e.g., constructive conflict resolution, perceived trust) when the relationship was threatened. Discussion focused on love, positive emotion, and relationships.

Photorefractive Integrators and Correlators

DTIC Science & Technology

1992-12-01

The use of photorefractive crystals as optically addressed time integrating spatial light modulators in acousto - optic signal processing applications...adaptive acousto - optic processor. These results demonstrated the feasibility of using photorefractives for such applications.... Photorefractive, Acousto - optic processor.

Theory and simulations of covariance mapping in multiple dimensions for data analysis in high-event-rate experiments

NASA Astrophysics Data System (ADS)

Zhaunerchyk, V.; Frasinski, L. J.; Eland, J. H. D.; Feifel, R.

2014-05-01

Multidimensional covariance analysis and its validity for correlation of processes leading to multiple products are investigated from a theoretical point of view. The need to correct for false correlations induced by experimental parameters which fluctuate from shot to shot, such as the intensity of self-amplified spontaneous emission x-ray free-electron laser pulses, is emphasized. Threefold covariance analysis based on simple extension of the two-variable formulation is shown to be valid for variables exhibiting Poisson statistics. In this case, false correlations arising from fluctuations in an unstable experimental parameter that scale linearly with signals can be eliminated by threefold partial covariance analysis, as defined here. Fourfold covariance based on the same simple extension is found to be invalid in general. Where fluctuations in an unstable parameter induce nonlinear signal variations, a technique of contingent covariance analysis is proposed here to suppress false correlations. In this paper we also show a method to eliminate false correlations associated with fluctuations of several unstable experimental parameters.

Achromatical Optical Correlator

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin; Liu, Hua-Kuang

1989-01-01

Signal-to-noise ratio exceeds that of monochromatic correlator. Achromatical optical correlator uses multiple-pinhole diffraction of dispersed white light to form superposed multiple correlations of input and reference images in output plane. Set of matched spatial filters made by multiple-exposure holographic process, each exposure using suitably-scaled input image and suitable angle of reference beam. Recording-aperture mask translated to appropriate horizontal position for each exposure. Noncoherent illumination suitable for applications involving recognition of color and determination of scale. When fully developed achromatical correlators will be useful for recognition of patterns; for example, in industrial inspection and search for selected features in aerial photographs.

Exploring Large-Scale Cross-Correlation for Teleseismic and Regional Seismic Event Characterization

NASA Astrophysics Data System (ADS)

Dodge, Doug; Walter, William; Myers, Steve; Ford, Sean; Harris, Dave; Ruppert, Stan; Buttler, Dave; Hauk, Terri

2013-04-01

The decrease in costs of both digital storage space and computation power invites new methods of seismic data processing. At Lawrence Livermore National Laboratory(LLNL) we operate a growing research database of seismic events and waveforms for nuclear explosion monitoring and other applications. Currently the LLNL database contains several million events associated with tens of millions of waveforms at thousands of stations. We are making use of this database to explore the power of seismic waveform correlation to quantify signal similarities, to discover new events not in catalogs, and to more accurately locate events and identify source types. Building on the very efficient correlation methodologies of Harris and Dodge (2011) we computed the waveform correlation for event pairs in the LLNL database in two ways. First we performed entire waveform cross-correlation over seven distinct frequency bands. The correlation coefficient exceeds 0.6 for more than 40 million waveform pairs for several hundred thousand events at more than a thousand stations. These correlations reveal clusters of mining events and aftershock sequences, which can be used to readily identify and locate events. Second we determine relative pick times by correlating signals in time windows for distinct seismic phases. These correlated picks are then used to perform very high accuracy event relocations. We are examining the percentage of events that correlate as a function of magnitude and observing station distance in selected high seismicity regions. Combining these empirical results and those using synthetic data, we are working to quantify relationships between correlation and event pair separation (in epicenter and depth) as well as mechanism differences. Our exploration of these techniques on a large seismic database is in process and we will report on our findings in more detail at the meeting.

Exploring Large-Scale Cross-Correlation for Teleseismic and Regional Seismic Event Characterization

NASA Astrophysics Data System (ADS)

Dodge, D.; Walter, W. R.; Myers, S. C.; Ford, S. R.; Harris, D.; Ruppert, S.; Buttler, D.; Hauk, T. F.

2012-12-01

The decrease in costs of both digital storage space and computation power invites new methods of seismic data processing. At Lawrence Livermore National Laboratory (LLNL) we operate a growing research database of seismic events and waveforms for nuclear explosion monitoring and other applications. Currently the LLNL database contains several million events associated with tens of millions of waveforms at thousands of stations. We are making use of this database to explore the power of seismic waveform correlation to quantify signal similarities, to discover new events not in catalogs, and to more accurately locate events and identify source types. Building on the very efficient correlation methodologies of Harris and Dodge (2011) we computed the waveform correlation for event pairs in the LLNL database in two ways. First we performed entire waveform cross-correlation over seven distinct frequency bands. The correlation coefficient exceeds 0.6 for more than 40 million waveform pairs for several hundred thousand events at more than a thousand stations. These correlations reveal clusters of mining events and aftershock sequences, which can be used to readily identify and locate events. Second we determine relative pick times by correlating signals in time windows for distinct seismic phases. These correlated picks are then used to perform very high accuracy event relocations. We are examining the percentage of events that correlate as a function of magnitude and observing station distance in selected high seismicity regions. Combining these empirical results and those using synthetic data, we are working to quantify relationships between correlation and event pair separation (in epicenter and depth) as well as mechanism differences. Our exploration of these techniques on a large seismic database is in process and we will report on our findings in more detail at the meeting.

Large-N correlator systems for low frequency radio astronomy

NASA Astrophysics Data System (ADS)

Foster, Griffin

Low frequency radio astronomy has entered a second golden age driven by the development of a new class of large-N interferometric arrays. The low frequency array (LOFAR) and a number of redshifted HI Epoch of Reionization (EoR) arrays are currently undergoing commission and regularly observing. Future arrays of unprecedented sensitivity and resolutions at low frequencies, such as the square kilometer array (SKA) and the hydrogen epoch of reionization array (HERA), are in development. The combination of advancements in specialized field programmable gate array (FPGA) hardware for signal processing, computing and graphics processing unit (GPU) resources, and new imaging and calibration algorithms has opened up the oft underused radio band below 300 MHz. These interferometric arrays require efficient implementation of digital signal processing (DSP) hardware to compute the baseline correlations. FPGA technology provides an optimal platform to develop new correlators. The significant growth in data rates from these systems requires automated software to reduce the correlations in real time before storing the data products to disk. Low frequency, widefield observations introduce a number of unique calibration and imaging challenges. The efficient implementation of FX correlators using FPGA hardware is presented. Two correlators have been developed, one for the 32 element BEST-2 array at Medicina Observatory and the other for the 96 element LOFAR station at Chilbolton Observatory. In addition, calibration and imaging software has been developed for each system which makes use of the radio interferometry measurement equation (RIME) to derive calibrations. A process for generating sky maps from widefield LOFAR station observations is presented. Shapelets, a method of modelling extended structures such as resolved sources and beam patterns has been adapted for radio astronomy use to further improve system calibration. Scaling of computing technology allows for the development of larger correlator systems, which in turn allows for improvements in sensitivity and resolution. This requires new calibration techniques which account for a broad range of systematic effects.

Differences in electrosensory anatomy and social behavior in an area of sympatry between two species of mormyrid electric fishes.

PubMed

Carlson, Bruce A

2016-01-01

Sensory systems play a key role in social behavior by mediating the detection and analysis of communication signals. In mormyrid fishes, electric signals are processed within a dedicated sensory pathway, providing a unique opportunity to relate sensory biology to social behavior. Evolutionary changes within this pathway led to new perceptual abilities that have been linked to increased rates of signal evolution and species diversification in a lineage called 'clade A'. Previous field observations suggest that clade-A species tend to be solitary and territorial, whereas non-clade-A species tend to be clustered in high densities suggestive of schooling or shoaling. To explore behavioral differences between species in these lineages in greater detail, I studied population densities, social interactions, and electric signaling in two mormyrid species, Gnathonemus victoriae (clade A) and Petrocephalus degeni (non-clade A), from Lwamunda Swamp, Uganda. Petrocephalus degeni was found at higher population densities, but intraspecific diversity in electric signal waveform was greater in G. victoriae. In the laboratory, G. victoriae exhibited strong shelter-seeking behavior and competition for shelter, whereas P. degeni were more likely to abandon shelter in the presence of conspecifics as well as electric mimics of signaling conspecifics. In other words, P. degeni exhibited social affiliation whereas G. victoriae exhibited social competition. Further, P. degeni showed correlated electric signaling behavior whereas G. victoriae showed anti-correlated signaling behavior. These findings extend previous reports of social spacing, territoriality, and habitat preference among mormyrid species, suggesting that evolutionary divergence in electrosensory processing relates to differences in social behavior. © 2016. Published by The Company of Biologists Ltd.

Dissociable brain mechanisms underlying the conscious and unconscious control of behavior.

PubMed

van Gaal, Simon; Lamme, Victor A F; Fahrenfort, Johannes J; Ridderinkhof, K Richard

2011-01-01

Cognitive control allows humans to overrule and inhibit habitual responses to optimize performance in challenging situations. Contradicting traditional views, recent studies suggest that cognitive control processes can be initiated unconsciously. To further capture the relation between consciousness and cognitive control, we studied the dynamics of inhibitory control processes when triggered consciously versus unconsciously in a modified version of the stop task. Attempts to inhibit an imminent response were often successful after unmasked (visible) stop signals. Masked (invisible) stop signals rarely succeeded in instigating overt inhibition but did trigger slowing down of response times. Masked stop signals elicited a sequence of distinct ERP components that were also observed on unmasked stop signals. The N2 component correlated with the efficiency of inhibitory control when elicited by unmasked stop signals and with the magnitude of slowdown when elicited by masked stop signals. Thus, the N2 likely reflects the initiation of inhibitory control, irrespective of conscious awareness. The P3 component was much reduced in amplitude and duration on masked versus unmasked stop trials. These patterns of differences and similarities between conscious and unconscious cognitive control processes are discussed in a framework that differentiates between feedforward and feedback connections in yielding conscious experience.

Analog computation of auto and cross-correlation functions

NASA Technical Reports Server (NTRS)

1974-01-01

For analysis of the data obtained from the cross beam systems it was deemed desirable to compute the auto- and cross-correlation functions by both digital and analog methods to provide a cross-check of the analysis methods and an indication as to which of the two methods would be most suitable for routine use in the analysis of such data. It is the purpose of this appendix to provide a concise description of the equipment and procedures used for the electronic analog analysis of the cross beam data. A block diagram showing the signal processing and computation set-up used for most of the analog data analysis is provided. The data obtained at the field test sites were recorded on magnetic tape using wide-band FM recording techniques. The data as recorded were band-pass filtered by electronic signal processing in the data acquisition systems.

Hemodynamic and electrophysiological signals of conflict processing in the Chinese-character Stroop task: a simultaneous near-infrared spectroscopy and event-related potential study

NASA Astrophysics Data System (ADS)

Zhai, Jiahuan; Li, Ting; Zhang, Zhongxing; Gong, Hui

2009-09-01

A dual-modality method combining continuous-wave near-infrared spectroscopy (NIRS) and event-related potentials (ERPs) was developed for the Chinese-character color-word Stroop task, which included congruent, incongruent, and neutral stimuli. Sixteen native Chinese speakers participated in this study. Hemodynamic and electrophysiological signals in the prefrontal cortex (PFC) were monitored simultaneously by NIRS and ERP. The hemodynamic signals were represented by relative changes in oxy-, deoxy-, and total hemoglobin concentration, whereas the electrophysiological signals were characterized by the parameters P450, N500, and P600. Both types of signals measured at four regions of the PFC were analyzed and compared spatially and temporally among the three different stimuli. We found that P600 signals correlated significantly with the hemodynamic parameters, suggesting that the PFC executes conflict-solving function. Additionally, we observed that the change in deoxy-Hb concentration showed higher sensitivity in response to the Stroop task than other hemodynamic signals. Correlation between NIRS and ERP signals revealed that the vascular response reflects the cumulative effect of neural activities. Taken together, our findings demonstrate that this new dual-modality method is a useful approach to obtaining more information during cognitive and physiological studies.

Hemodynamic and electrophysiological signals of conflict processing in the Chinese-character Stroop task: a simultaneous near-infrared spectroscopy and event-related potential study.

PubMed

Zhai, Jiahuan; Li, Ting; Zhang, Zhongxing; Gong, Hui

2009-01-01

A dual-modality method combining continuous-wave near-infrared spectroscopy (NIRS) and event-related potentials (ERPs) was developed for the Chinese-character color-word Stroop task, which included congruent, incongruent, and neutral stimuli. Sixteen native Chinese speakers participated in this study. Hemodynamic and electrophysiological signals in the prefrontal cortex (PFC) were monitored simultaneously by NIRS and ERP. The hemodynamic signals were represented by relative changes in oxy-, deoxy-, and total hemoglobin concentration, whereas the electrophysiological signals were characterized by the parameters P450, N500, and P600. Both types of signals measured at four regions of the PFC were analyzed and compared spatially and temporally among the three different stimuli. We found that P600 signals correlated significantly with the hemodynamic parameters, suggesting that the PFC executes conflict-solving function. Additionally, we observed that the change in deoxy-Hb concentration showed higher sensitivity in response to the Stroop task than other hemodynamic signals. Correlation between NIRS and ERP signals revealed that the vascular response reflects the cumulative effect of neural activities. Taken together, our findings demonstrate that this new dual-modality method is a useful approach to obtaining more information during cognitive and physiological studies.

A biological inspired fuzzy adaptive window median filter (FAWMF) for enhancing DNA signal processing.

PubMed

Ahmad, Muneer; Jung, Low Tan; Bhuiyan, Al-Amin

2017-10-01

Digital signal processing techniques commonly employ fixed length window filters to process the signal contents. DNA signals differ in characteristics from common digital signals since they carry nucleotides as contents. The nucleotides own genetic code context and fuzzy behaviors due to their special structure and order in DNA strand. Employing conventional fixed length window filters for DNA signal processing produce spectral leakage and hence results in signal noise. A biological context aware adaptive window filter is required to process the DNA signals. This paper introduces a biological inspired fuzzy adaptive window median filter (FAWMF) which computes the fuzzy membership strength of nucleotides in each slide of window and filters nucleotides based on median filtering with a combination of s-shaped and z-shaped filters. Since coding regions cause 3-base periodicity by an unbalanced nucleotides' distribution producing a relatively high bias for nucleotides' usage, such fundamental characteristic of nucleotides has been exploited in FAWMF to suppress the signal noise. Along with adaptive response of FAWMF, a strong correlation between median nucleotides and the Π shaped filter was observed which produced enhanced discrimination between coding and non-coding regions contrary to fixed length conventional window filters. The proposed FAWMF attains a significant enhancement in coding regions identification i.e. 40% to 125% as compared to other conventional window filters tested over more than 250 benchmarked and randomly taken DNA datasets of different organisms. This study proves that conventional fixed length window filters applied to DNA signals do not achieve significant results since the nucleotides carry genetic code context. The proposed FAWMF algorithm is adaptive and outperforms significantly to process DNA signal contents. The algorithm applied to variety of DNA datasets produced noteworthy discrimination between coding and non-coding regions contrary to fixed window length conventional filters. Copyright © 2017 Elsevier B.V. All rights reserved.

Understanding volatility correlation behavior with a magnitude cross-correlation function

NASA Astrophysics Data System (ADS)

Jun, Woo Cheol; Oh, Gabjin; Kim, Seunghwan

2006-06-01

We propose an approach for analyzing the basic relation between correlation properties of the original signal and its magnitude fluctuations by decomposing the original signal into its positive and negative fluctuation components. We use this relation to understand the following phenomenon found in many naturally occurring time series: the magnitude of the signal exhibits long-range correlation, whereas the original signal is short-range correlated. The applications of our approach to heart rate variability signals and high-frequency foreign exchange rates reveal that the difference between the correlation properties of the original signal and its magnitude fluctuations is induced by the time organization structure of the correlation function between the magnitude fluctuations of positive and negative components. We show that this correlation function can be described well by a stretched-exponential function and is related to the nonlinearity and the multifractal structure of the signals.

Understanding volatility correlation behavior with a magnitude cross-correlation function.

PubMed

Jun, Woo Cheol; Oh, Gabjin; Kim, Seunghwan

2006-06-01

We propose an approach for analyzing the basic relation between correlation properties of the original signal and its magnitude fluctuations by decomposing the original signal into its positive and negative fluctuation components. We use this relation to understand the following phenomenon found in many naturally occurring time series: the magnitude of the signal exhibits long-range correlation, whereas the original signal is short-range correlated. The applications of our approach to heart rate variability signals and high-frequency foreign exchange rates reveal that the difference between the correlation properties of the original signal and its magnitude fluctuations is induced by the time organization structure of the correlation function between the magnitude fluctuations of positive and negative components. We show that this correlation function can be described well by a stretched-exponential function and is related to the nonlinearity and the multifractal structure of the signals.

The Origins of Individual Differences in How Learning Is Expressed in Rats: A General-Process Perspective

PubMed Central

2016-01-01

Laboratory rats can exhibit marked, qualitative individual differences in the form of acquired behaviors. For example, when exposed to a signal-reinforcer relationship some rats show marked and consistent changes in sign-tracking (interacting with the signal; e.g., a lever) and others show marked and consistent changes in goal-tracking (interacting with the location of the predicted reinforcer; e.g., the food well). Here, stable individual differences in rats’ sign-tracking and goal-tracking emerged over the course of training, but these differences did not generalize across different signal-reinforcer relationships (Experiment 1). This selectivity suggests that individual differences in sign- and goal-tracking reflect differences in the value placed on individual reinforcers. Two findings provide direct support for this interpretation: the palatability of a reinforcer (as measured by an analysis of lick-cluster size) was positively correlated with goal-tracking (and negatively correlated with sign-tracking); and sating rats with a reinforcer affected goal-tracking but not sign-tracking (Experiment 2). These results indicate that the observed individual differences in sign- and goal-tracking behavior arise from the interaction between the palatability or value of the reinforcer and processes of association as opposed to dispositional differences (e.g., in sensory processes, “temperament,” or response repertoire). PMID:27732045

Speech Intelligibility Predicted from Neural Entrainment of the Speech Envelope.

PubMed

Vanthornhout, Jonas; Decruy, Lien; Wouters, Jan; Simon, Jonathan Z; Francart, Tom

2018-04-01

Speech intelligibility is currently measured by scoring how well a person can identify a speech signal. The results of such behavioral measures reflect neural processing of the speech signal, but are also influenced by language processing, motivation, and memory. Very often, electrophysiological measures of hearing give insight in the neural processing of sound. However, in most methods, non-speech stimuli are used, making it hard to relate the results to behavioral measures of speech intelligibility. The use of natural running speech as a stimulus in electrophysiological measures of hearing is a paradigm shift which allows to bridge the gap between behavioral and electrophysiological measures. Here, by decoding the speech envelope from the electroencephalogram, and correlating it with the stimulus envelope, we demonstrate an electrophysiological measure of neural processing of running speech. We show that behaviorally measured speech intelligibility is strongly correlated with our electrophysiological measure. Our results pave the way towards an objective and automatic way of assessing neural processing of speech presented through auditory prostheses, reducing confounds such as attention and cognitive capabilities. We anticipate that our electrophysiological measure will allow better differential diagnosis of the auditory system, and will allow the development of closed-loop auditory prostheses that automatically adapt to individual users.

Solitary chemosensory cells and bitter taste receptor signaling in human sinonasal mucosa.

PubMed

Barham, Henry P; Cooper, Sarah E; Anderson, Catherine B; Tizzano, Marco; Kingdom, Todd T; Finger, Tom E; Kinnamon, Sue C; Ramakrishnan, Vijay R

2013-06-01

Solitary chemosensory cells (SCCs) are specialized cells in the respiratory epithelium that respond to noxious chemicals including bacterial signaling molecules. SCCs express components of bitter taste transduction including the taste receptor type 2 (TAS2R) bitter taste receptors and downstream signaling effectors: α-Gustducin, phospholipase Cβ2 (PLCβ2), and transient receptor potential cation channel subfamily M member 5 (TRPM5). When activated, SCCs evoke neurogenic reflexes, resulting in local inflammation. The purpose of this study was to test for the presence SCCs in human sinonasal epithelium, and to test for a correlation with inflammatory disease processes such as allergic rhinitis and chronic rhinosinusitis. Patient demographics and biopsies of human sinonasal mucosa were obtained from control patients (n = 7) and those with allergic rhinitis and/or chronic rhinosinusitis (n = 15). Reverse transcription polymerase chain reaction (RT-PCR), quantitative PCR (qPCR), and immunohistochemistry were used to determine whether expression of signaling effectors was altered in diseased patients. RT-PCR demonstrated that bitter taste receptors TAS2R4, TAS2R14, and TAS2R46, and downstream signaling effectors α-Gustducin, PLCβ2, and TRPM5 are expressed in the inferior turbinate, middle turbinate, septum, and uncinate of both control and diseased patients. PLCβ2/TRPM5-immunoreactive SCCs were identified in the sinonasal mucosa of both control and diseased patients. qPCR showed similar expression of α-Gustducin and TRPM5 in the uncinate process of control and diseased groups, and there was no correlation between level of expression and 22-item Sino-Nasal Outcomes Test (SNOT-22) or pain scores. SCCs are present in human sinonasal mucosa in functionally relevant areas. Expression level of signaling effectors was similar in control and diseased patients and did not correlate with measures of pain and inflammation. Further study into these pathways may provide insight into nasal inflammatory diseases and may offer potential therapeutic targets. © 2013 ARS-AAOA, LLC.

Multi-Beam Radio Frequency (RF) Aperture Arrays Using Multiplierless Approximate Fast Fourier Transform (FFT)

DTIC Science & Technology

2017-08-01

filtering, correlation and radio- astronomy . In this report approximate transforms that closely follow the DFT have been studied and found. The approximate...communications, data networks, sensor networks, cognitive radio, radar and beamforming, imaging, filtering, correlation and radio- astronomy . FFTs efficiently...public release; distribution is unlimited. 4.3 Digital Hardware and Design Architectures Collaboration for Astronomy Signal Processing and Electronics

Mutual information identifies spurious Hurst phenomena in resting state EEG and fMRI data

NASA Astrophysics Data System (ADS)

von Wegner, Frederic; Laufs, Helmut; Tagliazucchi, Enzo

2018-02-01

Long-range memory in time series is often quantified by the Hurst exponent H , a measure of the signal's variance across several time scales. We analyze neurophysiological time series from electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) resting state experiments with two standard Hurst exponent estimators and with the time-lagged mutual information function applied to discretized versions of the signals. A confidence interval for the mutual information function is obtained from surrogate Markov processes with equilibrium distribution and transition matrix identical to the underlying signal. For EEG signals, we construct an additional mutual information confidence interval from a short-range correlated, tenth-order autoregressive model. We reproduce the previously described Hurst phenomenon (H >0.5 ) in the analytical amplitude of alpha frequency band oscillations, in EEG microstate sequences, and in fMRI signals, but we show that the Hurst phenomenon occurs without long-range memory in the information-theoretical sense. We find that the mutual information function of neurophysiological data behaves differently from fractional Gaussian noise (fGn), for which the Hurst phenomenon is a sufficient condition to prove long-range memory. Two other well-characterized, short-range correlated stochastic processes (Ornstein-Uhlenbeck, Cox-Ingersoll-Ross) also yield H >0.5 , whereas their mutual information functions lie within the Markovian confidence intervals, similar to neural signals. In these processes, which do not have long-range memory by construction, a spurious Hurst phenomenon occurs due to slow relaxation times and heteroscedasticity (time-varying conditional variance). In summary, we find that mutual information correctly distinguishes long-range from short-range dependence in the theoretical and experimental cases discussed. Our results also suggest that the stationary fGn process is not sufficient to describe neural data, which seem to belong to a more general class of stochastic processes, in which multiscale variance effects produce Hurst phenomena without long-range dependence. In our experimental data, the Hurst phenomenon and long-range memory appear as different system properties that should be estimated and interpreted independently.

Conflict anticipation in alcohol dependence - A model-based fMRI study of stop signal task.

PubMed

Hu, Sien; Ide, Jaime S; Zhang, Sheng; Sinha, Rajita; Li, Chiang-Shan R

2015-01-01

Our previous work characterized altered cerebral activations during cognitive control in individuals with alcohol dependence (AD). A hallmark of cognitive control is the ability to anticipate changes and adjust behavior accordingly. Here, we employed a Bayesian model to describe trial-by-trial anticipation of the stop signal and modeled fMRI signals of conflict anticipation in a stop signal task. Our goal is to characterize the neural correlates of conflict anticipation and its relationship to response inhibition and alcohol consumption in AD. Twenty-four AD and 70 age and gender matched healthy control individuals (HC) participated in the study. fMRI data were pre-processed and modeled with SPM8. We modeled fMRI signals at trial onset with individual events parametrically modulated by estimated probability of the stop signal, p(Stop), and compared regional responses to conflict anticipation between AD and HC. To address the link to response inhibition, we regressed whole-brain responses to conflict anticipation against the stop signal reaction time (SSRT). Compared to HC (54/70), fewer AD (11/24) showed a significant sequential effect - a correlation between p(Stop) and RT during go trials - and the magnitude of sequential effect is diminished, suggesting a deficit in proactive control. Parametric analyses showed decreased learning rate and over-estimated prior mean of the stop signal in AD. In fMRI, both HC and AD responded to p(Stop) in bilateral inferior parietal cortex and anterior pre-supplementary motor area, although the magnitude of response increased in AD. In contrast, HC but not AD showed deactivation of the perigenual anterior cingulate cortex (pgACC). Furthermore, deactivation of the pgACC to increasing p(Stop) is positively correlated with the SSRT in HC but not AD. Recent alcohol consumption is correlated with increased activation of the thalamus and cerebellum in AD during conflict anticipation. The current results highlight altered proactive control that may serve as an additional behavioral and neural marker of alcohol dependence.

Measuring temporal stability of positron emission tomography standardized uptake value bias using long-lived sources in a multicenter network.

PubMed

Byrd, Darrin; Christopfel, Rebecca; Arabasz, Grae; Catana, Ciprian; Karp, Joel; Lodge, Martin A; Laymon, Charles; Moros, Eduardo G; Budzevich, Mikalai; Nehmeh, Sadek; Scheuermann, Joshua; Sunderland, John; Zhang, Jun; Kinahan, Paul

2018-01-01

Positron emission tomography (PET) is a quantitative imaging modality, but the computation of standardized uptake values (SUVs) requires several instruments to be correctly calibrated. Variability in the calibration process may lead to unreliable quantitation. Sealed source kits containing traceable amounts of [Formula: see text] were used to measure signal stability for 19 PET scanners at nine hospitals in the National Cancer Institute's Quantitative Imaging Network. Repeated measurements of the sources were performed on PET scanners and in dose calibrators. The measured scanner and dose calibrator signal biases were used to compute the bias in SUVs at multiple time points for each site over a 14-month period. Estimation of absolute SUV accuracy was confounded by bias from the solid phantoms' physical properties. On average, the intrascanner coefficient of variation for SUV measurements was 3.5%. Over the entire length of the study, single-scanner SUV values varied over a range of 11%. Dose calibrator bias was not correlated with scanner bias. Calibration factors from the image metadata were nearly as variable as scanner signal, and were correlated with signal for many scanners. SUVs often showed low intrascanner variability between successive measurements but were also prone to shifts in apparent bias, possibly in part due to scanner recalibrations that are part of regular scanner quality control. Biases of key factors in the computation of SUVs were not correlated and their temporal variations did not cancel out of the computation. Long-lived sources and image metadata may provide a check on the recalibration process.

Spectroscopic techniques to study the immune response in human saliva

NASA Astrophysics Data System (ADS)

Nepomnyashchaya, E.; Savchenko, E.; Velichko, E.; Bogomaz, T.; Aksenov, E.

2018-01-01

Studies of the immune response dynamics by means of spectroscopic techniques, i.e., laser correlation spectroscopy and fluorescence spectroscopy, are described. The laser correlation spectroscopy is aimed at measuring sizes of particles in biological fluids. The fluorescence spectroscopy allows studying of the conformational and other structural changings in immune complex. We have developed a new scheme of a laser correlation spectrometer and an original signal processing algorithm. We have suggested a new fluorescence detection scheme based on a prism and an integrating pin diode. The developed system based on the spectroscopic techniques allows studies of complex process in human saliva and opens some prospects for an individual treatment of immune diseases.

Degree Correlations Optimize Neuronal Network Sensitivity to Sub-Threshold Stimuli

PubMed Central

Schmeltzer, Christian; Kihara, Alexandre Hiroaki; Sokolov, Igor Michailovitsch; Rüdiger, Sten

2015-01-01

Information processing in the brain crucially depends on the topology of the neuronal connections. We investigate how the topology influences the response of a population of leaky integrate-and-fire neurons to a stimulus. We devise a method to calculate firing rates from a self-consistent system of equations taking into account the degree distribution and degree correlations in the network. We show that assortative degree correlations strongly improve the sensitivity for weak stimuli and propose that such networks possess an advantage in signal processing. We moreover find that there exists an optimum in assortativity at an intermediate level leading to a maximum in input/output mutual information. PMID:26115374

Single-trial analysis of the neural correlates of speech quality perception.

PubMed

Porbadnigk, Anne K; Treder, Matthias S; Blankertz, Benjamin; Antons, Jan-Niklas; Schleicher, Robert; Möller, Sebastian; Curio, Gabriel; Müller, Klaus-Robert

2013-10-01

Assessing speech quality perception is a challenge typically addressed in behavioral and opinion-seeking experiments. Only recently, neuroimaging methods were introduced, which were used to study the neural processing of quality at group level. However, our electroencephalography (EEG) studies show that the neural correlates of quality perception are highly individual. Therefore, it became necessary to establish dedicated machine learning methods for decoding subject-specific effects. The effectiveness of our methods is shown by the data of an EEG study that investigates how the quality of spoken vowels is processed neurally. Participants were asked to indicate whether they had perceived a degradation of quality (signal-correlated noise) in vowels, presented in an oddball paradigm. We find that the P3 amplitude is attenuated with increasing noise. Single-trial analysis allows one to show that this is partly due to an increasing jitter of the P3 component. A novel classification approach helps to detect trials with presumably non-conscious processing at the threshold of perception. We show that this approach uncovers a non-trivial confounder between neural hits and neural misses. The combined use of EEG signals and machine learning methods results in a significant 'neural' gain in sensitivity (in processing quality loss) when compared to standard behavioral evaluation; averaged over 11 subjects, this amounts to a relative improvement in sensitivity of 35%.

Reduced functional connectivity to the frontal cortex during processing of social cues in autism spectrum disorder.

PubMed

Hoffmann, Elgin; Brück, Carolin; Kreifelts, Benjamin; Ethofer, Thomas; Wildgruber, Dirk

2016-08-01

People diagnosed with autism spectrum disorder (ASD) characteristically present with severe difficulties in interpreting every-day social signals. Currently it is assumed that these difficulties might have neurobiological correlates in alterations in activation as well as in connectivity in and between regions of the social perception network suggested to govern the processing of social cues. In this study, we conducted functional magnetic resonance imaging (fMRI)-based activation and connectivity analyses focusing on face-, voice-, and audiovisual-processing brain regions as the most important subareas of the social perception network. Results revealed alterations in connectivity among regions involved in the processing of social stimuli in ASD subjects compared to typically developed (TD) controls-specifically, a reduced connectivity between the left temporal voice area (TVA) and the superior and medial frontal gyrus. Alterations in connectivity, moreover, were correlated with the severity of autistic traits: correlation analysis indicated that the connectivity between the left TVA and the limbic lobe, anterior cingulate and the medial frontal gyrus as well as between the right TVA and the frontal lobe, anterior cingulate, limbic lobe and the caudate decreased with increasing symptom severity. As these frontal regions are understood to play an important role in interpreting and mentalizing social signals, the observed underconnectivity might be construed as playing a role in social impairments in ASD.

Simultaneous measurement of time-domain fNIRS and physiological signals during a cognitive task

NASA Astrophysics Data System (ADS)

Jelzow, A.; Tachtsidis, I.; Kirilina, E.; Niessing, M.; Brühl, R.; Wabnitz, H.; Heine, A.; Ittermann, B.; Macdonald, R.

2011-07-01

Functional near-infrared spectroscopy (fNIRS) is a commonly used technique to measure the cerebral vascular response related to brain activation. It is known that systemic physiological processes, either independent or correlated with the stimulation task, can influence the optical signal making its interpretation challenging. The aim of the present work is to investigate the impact of task-evoked changes in the systemic physiology on fNIRS measurements for a cognitive paradigm. For this purpose we carried out simultaneous measurements of time-domain fNIRS on the forehead and systemic physiological signals, i.e. mean blood pressure, heart rate, respiration, galvanic skin response, scalp blood flow (flux) and red blood cell (RBC) concentration changes. We performed measurements on 15 healthy volunteers during a semantic continuous performance task (CPT). The optical data was analyzed in terms of depth-selective moments of distributions of times of flight of photons through the tissue. In addition, cerebral activation was localized by a subsequent fMRI experiment on the same subject population using the same task. We observed strong non-cerebral task-evoked changes in concentration changes of oxygenated hemoglobin in the forehead. We investigated the temporal behavior and mutual correlations between hemoglobin changes and the systemic processes. Mean blood pressure (BP), galvanic skin response (GSR) and heart rate exhibited significant changes during the activation period, whereby BP and GSR showed the highest correlation with optical measurements.

Radiation-hardened fast acquisition/weak signal tracking system and method

NASA Technical Reports Server (NTRS)

Winternitz, Luke (Inventor); Boegner, Gregory J. (Inventor); Sirotzky, Steve (Inventor)

2009-01-01

A global positioning system (GPS) receiver and method of acquiring and tracking GPS signals comprises an antenna adapted to receive GPS signals; an analog radio frequency device operatively connected to the antenna and adapted to convert the GPS signals from an analog format to a digital format; a plurality of GPS signal tracking correlators operatively connected to the analog RF device; a GPS signal acquisition component operatively connected to the analog RF device and the plurality of GPS signal tracking correlators, wherein the GPS signal acquisition component is adapted to calculate a maximum vector on a databit correlation grid; and a microprocessor operatively connected to the plurality of GPS signal tracking correlators and the GPS signal acquisition component, wherein the microprocessor is adapted to compare the maximum vector with a predetermined correlation threshold to allow the GPS signal to be fully acquired and tracked.

Radioastronomic signal processing cores for the SKA radio telescope

NASA Astrophysics Data System (ADS)

Comorett, G.; Chiarucc, S.; Belli, C.

Modern radio telescopes require the processing of wideband signals, with sample rates from tens of MHz to tens of GHz, and are composed from hundreds up to a million of individual antennas. Digital signal processing of these signals include digital receivers (the digital equivalent of the heterodyne receiver), beamformers, channelizers, spectrometers. FPGAs present the advantage of providing a relatively low power consumption, relative to GPUs or dedicated computers, a wide signal data path, and high interconnectivity. Efficient algorithms have been developed for these applications. Here we will review some of the signal processing cores developed for the SKA telescope. The LFAA beamformer/channelizer architecture is based on an oversampling channelizer, where the channelizer output sampling rate and channel spacing can be set independently. This is useful where an overlap between adjacent channels is required to provide an uniform spectral coverage. The architecture allows for an efficient and distributed channelization scheme, with a final resolution corresponding to a million of spectral channels, minimum leakage and high out-of-band rejection. An optimized filter design procedure is used to provide an equiripple response with a very large number of spectral channels. A wideband digital receiver has been designed in order to select the processed bandwidth of the SKA Mid receiver. The receiver extracts a 2.5 MHz bandwidth form a 14 GHz input bandwidth. The design allows for non-integer ratios between the input and output sampling rates, with a resource usage comparable to that of a conventional decimating digital receiver. Finally, some considerations on quantization of radioastronomic signals are presented. Due to the stochastic nature of the signal, quantization using few data bits is possible. Good accuracies and dynamic range are possible even with 2-3 bits, but the nonlinearity in the correlation process must be corrected in post-processing. With at least 6 bits it is possible to have a very linear response of the instrument, with nonlinear terms below 80 dB, providing the signal amplitude is kept within bounds.

Global scale stratospheric processes as measured by the infrasound IMS network

NASA Astrophysics Data System (ADS)

Le Pichon, A.; Ceranna, L.; Kechut, P.

2012-12-01

IMS infrasound array data are routinely processed at the International Data Center (IDC). The wave parameters of the detected signals are estimated with the Progressive Multi-Channel Correlation method (PMCC). We have processed continuous recordings from 41 certified IMS stations from 2005 to 2010 in the 0.01-5 Hz frequency band using a new implementation of the PMCC algorithm. Microbaroms are the dominant source of signals near-continuously and globally detected. The observed azimuthal seasonal trend correlates well with the variation of the effective sound speed ratio (Veff-ratio) which is a proxy for the combined effects of refraction due to sound speed gradients and advection due to along-path stratospheric wind on infrasound propagation. Systematic correlations between infrasound parameters (e.g. number of detections, amplitude) and Veff-ratio calculated at different ranges of altitudes are performed. Combined with propagation modeling, we show that such an analysis enables a characterization of the wind and temperature structure above the stratosphere and may provide detailed information on upper atmospheric processes (e.g., large-scale planetary waves, stratospheric warming effects) from the seasonal trend to short time scale variability. We discuss the potential benefit of long-term infrasound monitoring to infer stratospheric processes for the first time on a global scale. This study suggests poorly resolved stratospheric wind fluctuations at low latitude regions with strengths of horizontal wind structures underestimated by at least ~10 m/s. It is expected that this correlation between infrasound observations and the state-of-the-art atmospheric specifications will allow to statistically quantify the spatial and temporal resolutions of the wind structures at different ranges of altitudes, latitudes and time scales.

Signal extraction and wave field separation in tunnel seismic prediction by independent component analysis

NASA Astrophysics Data System (ADS)

Yue, Y.; Jiang, T.; Zhou, Q.

2017-12-01

In order to ensure the rationality and the safety of tunnel excavation, the advanced geological prediction has been become an indispensable step in tunneling. However, the extraction of signal and the separation of P and S waves directly influence the accuracy of geological prediction. Generally, the raw data collected in TSP system is low quality because of the numerous disturb factors in tunnel projects, such as the power interference and machine vibration interference. It's difficult for traditional method (band-pass filtering) to remove interference effectively as well as bring little loss to signal. The power interference, machine vibration interference and the signal are original variables and x, y, z component as observation signals, each component of the representation is a linear combination of the original variables, which satisfy applicable conditions of independent component analysis (ICA). We perform finite-difference simulations of elastic wave propagation to synthetic a tunnel seismic reflection record. The method of ICA was adopted to process the three-component data, and the results show that extract the estimates of signal and the signals are highly correlated (the coefficient correlation is up to more than 0.93). In addition, the estimates of interference that separated from ICA and the interference signals are also highly correlated, and the coefficient correlation is up to more than 0.99. Thus, simulation results showed that the ICA is an ideal method for extracting high quality data from mixed signals. For the separation of P and S waves, the conventional separation techniques are based on physical characteristics of wave propagation, which require knowledge of the near-surface P and S waves velocities and density. Whereas the ICA approach is entirely based on statistical differences between P and S waves, and the statistical technique does not require a priori information. The concrete results of the wave field separation will be presented in the meeting. In summary, we can safely draw the conclusion that ICA can not only extract high quality data from the mixed signals, but also can separate P and S waves effectively.

A contactless approach for respiratory gating in PET using continuous-wave radar

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ersepke, Thomas, E-mail: Thomas.Ersepke@rub.de; Büther, Florian; Heß, Mirco

Purpose: Respiratory gating is commonly used to reduce motion artifacts in positron emission tomography (PET). Clinically established methods for respiratory gating in PET require contact to the patient or a direct optical line between the sensor and the patient’s torso and time consuming preparation. In this work, a contactless method for capturing a respiratory signal during PET is presented based on continuous-wave radar. Methods: The proposed method relies on the principle of emitting an electromagnetic wave and detecting the phase shift of the reflected wave, modulated due to the respiratory movement of the patient’s torso. A 24 GHz carrier frequencymore » was chosen allowing wave propagation through plastic and clothing with high reflections at the skin surface. A detector module and signal processing algorithms were developed to extract a quantitative respiratory signal. The sensor was validated using a high precision linear table. During volunteer measurements and [{sup 18}F] FDG PET scans, the radar sensor was positioned inside the scanner bore of a PET/computed tomography scanner. As reference, pressure belt (one volunteer), depth camera-based (two volunteers, two patients), and PET data-driven (six patients) signals were acquired simultaneously and the signal correlation was quantified. Results: The developed system demonstrated a high measurement accuracy for movement detection within the submillimeter range. With the proposed method, small displacements of 25 μm could be detected, not considerably influenced by clothing or blankets. From the patient studies, the extracted respiratory radar signals revealed high correlation (Pearson correlation coefficient) to those derived from the external pressure belt and depth camera signals (r = 0.69–0.99) and moderate correlation to those of the internal data-driven signals (r = 0.53–0.70). In some cases, a cardiac signal could be visualized, due to the representation of the mechanical heart motion on the skin. Conclusions: Accurate respiratory signals were obtained successfully by the proposed method with high spatial and temporal resolution. By working without contact and passing through clothing and blankets, this approach minimizes preparation time and increases the convenience of the patient during the scan.« less

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

NASA Astrophysics Data System (ADS)

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

2014-11-01

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

Reconstruction of pulse noisy images via stochastic resonance

PubMed Central

Han, Jing; Liu, Hongjun; Sun, Qibing; Huang, Nan

2015-01-01

We investigate a practical technology for reconstructing nanosecond pulse noisy images via stochastic resonance, which is based on the modulation instability. A theoretical model of this method for optical pulse signal is built to effectively recover the pulse image. The nanosecond noise-hidden images grow at the expense of noise during the stochastic resonance process in a photorefractive medium. The properties of output images are mainly determined by the input signal-to-noise intensity ratio, the applied voltage across the medium, and the correlation length of noise background. A high cross-correlation gain is obtained by optimizing these parameters. This provides a potential method for detecting low-level or hidden pulse images in various imaging applications. PMID:26067911

[A modified speech enhancement algorithm for electronic cochlear implant and its digital signal processing realization].

PubMed

Wang, Yulin; Tian, Xuelong

2014-08-01

In order to improve the speech quality and auditory perceptiveness of electronic cochlear implant under strong noise background, a speech enhancement system used for electronic cochlear implant front-end was constructed. Taking digital signal processing (DSP) as the core, the system combines its multi-channel buffered serial port (McBSP) data transmission channel with extended audio interface chip TLV320AIC10, so speech signal acquisition and output with high speed are realized. Meanwhile, due to the traditional speech enhancement method which has the problems as bad adaptability, slow convergence speed and big steady-state error, versiera function and de-correlation principle were used to improve the existing adaptive filtering algorithm, which effectively enhanced the quality of voice communications. Test results verified the stability of the system and the de-noising performance of the algorithm, and it also proved that they could provide clearer speech signals for the deaf or tinnitus patients.

Global Assessment of New GRACE Mascons Solutions for Hydrologic Applications

NASA Astrophysics Data System (ADS)

Save, H.; Zhang, Z.; Scanlon, B. R.; Wiese, D. N.; Landerer, F. W.; Long, D.; Longuevergne, L.; Chen, J.

2016-12-01

Advances in GRACE (Gravity Recovery and Climate Experiment) satellite data processing using new mass concentration (mascon) solutions have greatly increased the spatial localization and amplitude of recovered total Terrestrial Water Storage (TWS) signals; however, limited testing has been conduct on land hydrologic applications. In this study we compared TWS anomalies from (1) Center for Space Research mascons (CSR-M) solution with (2) NASA JPL mascon (JPL-M) solution, and with (3) a CSR gridded spherical harmonic rescaled (sf) solution from Tellus (CSRT-GSH.sf) in 176 river basins covering 80% of the global land area. There is good correspondence in TWS anomalies from mascons (CSR-M and JPL-M) and SH solutions based on high correlations between time series (rank correlation coefficients mostly >0.9). The long-term trends in basin TWS anomalies represent a relatively small signal (up to ±20 mm/yr) with differences among GRACE solutions and inter-basin variability increasing with decreasing basin size. Long-term TWS declines are greatest in (semi)arid and irrigated basins. Annual and semiannual signals have much larger amplitudes (up to ±250 mm). There is generally good agreement among GRACE solutions, increasing confidence in seasonal fluctuations from GRACE data. Rescaling spherical harmonics to restore lost signal increases agreement with mascons solutions for long-term trends and seasonal fluctuations. There are many advantages to using GRACE mascons solutions relative to SH solutions, such as reduced leakage from land to ocean increasing signal amplitude, and constraining results by applying geophysical data during processing with little or no post-processing requirements, making mascons more user friendly for non-geodetic users. This inter-comparison of various GRACE solutions should allow hydrologists to better select suitable GRACE products for hydrologic applications.

Carbon nanotube based respiratory gated micro-CT imaging of a murine model of lung tumors with optical imaging correlation

NASA Astrophysics Data System (ADS)

Burk, Laurel M.; Lee, Yueh Z.; Heathcote, Samuel; Wang, Ko-han; Kim, William Y.; Lu, Jianping; Zhou, Otto

2011-03-01

Current optical imaging techniques can successfully measure tumor load in murine models of lung carcinoma but lack structural detail. We demonstrate that respiratory gated micro-CT imaging of such models gives information about structure and correlates with tumor load measurements by optical methods. Four mice with multifocal, Kras-induced tumors expressing firefly luciferase were imaged against four controls using both optical imaging and respiratory gated micro-CT. CT images of anesthetized animals were acquired with a custom CNT-based system using 30 ms x-ray pulses during peak inspiration; respiration motion was tracked with a pressure sensor beneath each animal's abdomen. Optical imaging based on the Luc+ signal correlating with tumor load was performed on a Xenogen IVIS Kinetix. Micro-CT images were post-processed using Osirix, measuring lung volume with region growing. Diameters of the largest three tumors were measured. Relationships between tumor size, lung volumes, and optical signal were compared. CT images and optical signals were obtained for all animals at two time points. In all lobes of the Kras+ mice in all images, tumors were visible; the smallest to be readily identified measured approximately 300 microns diameter. CT-derived tumor volumes and optical signals related linearly, with r=0.94 for all animals. When derived for only tumor bearing animals, r=0.3. The trend of each individual animal's optical signal tracked correctly based on the CT volumes. Interestingly, lung volumes also correlated positively with optical imaging data and tumor volume burden, suggesting active remodeling.

Aberrant functioning of the putamen links delusions, antipsychotic drug dose, and compromised connectivity in first episode psychosis--Preliminary fMRI findings.

PubMed

Raij, Tuukka T; Mäntylä, Teemu; Kieseppä, Tuula; Suvisaari, Jaana

2015-08-30

The dopamine theory proposes the relationship of delusions to aberrant signaling in striatal circuitries that can be normalized with dopamine D2 receptor-blocking drugs. Localization of such circuitries, as well as their upstream and downstream signaling, remains poorly known. We collected functional magnetic resonance images from first-episode psychosis patients and controls during an audiovisual movie. Final analyses included 20 patients and 20 controls; another sample of 10 patients and 10 controls was used to calculate a comparison signal-time course. We identified putamen circuitry in which the signal aberrance (poor correlation with the comparison signal time course) was predicted by the dopamine theory, being greater in patients than controls; correlating positively with delusion scores; and correlating negatively with antipsychotic-equivalent dosage. In Granger causality analysis, patients showed a compromised contribution of the cortical salience network to the putamen and compromised contribution of the putamen to the default mode network. Results were corrected for multiple comparisons at the cluster level with primary voxel-wise threshold p < 0.005 for the salience network contribution, but liberal primary threshold p < 0.05 was used in other group comparisons. If replicated in larger studies, these findings may help unify and extend current hypotheses on dopaminergic dysfunction, salience processing and pathogenesis of delusions. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Extraction of body waves from seismic ambient noise

NASA Astrophysics Data System (ADS)

Kim, Eun Mi; Kang, Tae Seob; Kim, Tae Sung

2014-05-01

Ambient noise cross-correlation is used in seismology to obtain the part of the surface waves and applied to the theoretical researches and various experiments. Obtaining the part of body waves from the ambient noise correlation is difficult to recognize because of the feature decreasing body waves along the travel path. However, the travel times of body waves detected from temporal and spacial events occurrence involve uncertainty of the epicenter and accompany temporal-spacial restriction. On the other hand, ambient noise is always occurred and is obtained at the all stations. So it can be applied to research of the internal earth when the case of extracting the body waves using the cross-correlation is possible. This study shows that body waves can be observed by analyzing the ambient noise recorded seismic data in South Korea. Using 42 broad-band three components stations located on the South Korea. The data removed the mean and trend are filtered high-frequency band(0.5-2Hz). The noise correlations were calculated for all combinations of radial, transverse and veltical components, which required rotation of the horizontal components for each station pair according to the azimuth at each station of the great-circle between the two stations. Removing the part of broad-band signals effected by occurring event, the part of standard deviations more than three times are removed. And it applied spectral whitening to reduce effects of the surface waves. After data processing, all ambient noise signals are cross-correlated and temporal stacked. We found the signals propagating from one station to another station, this signals can be interpreted as the body waves distinguished surface travel-time in high-frequency band.From this analysis, we can extract the body waves using ambient noise cross correlation of continuous data at the stations.

Uniform, optimal signal processing of mapped deep-sequencing data.

PubMed

Kumar, Vibhor; Muratani, Masafumi; Rayan, Nirmala Arul; Kraus, Petra; Lufkin, Thomas; Ng, Huck Hui; Prabhakar, Shyam

2013-07-01

Despite their apparent diversity, many problems in the analysis of high-throughput sequencing data are merely special cases of two general problems, signal detection and signal estimation. Here we adapt formally optimal solutions from signal processing theory to analyze signals of DNA sequence reads mapped to a genome. We describe DFilter, a detection algorithm that identifies regulatory features in ChIP-seq, DNase-seq and FAIRE-seq data more accurately than assay-specific algorithms. We also describe EFilter, an estimation algorithm that accurately predicts mRNA levels from as few as 1-2 histone profiles (R ∼0.9). Notably, the presence of regulatory motifs in promoters correlates more with histone modifications than with mRNA levels, suggesting that histone profiles are more predictive of cis-regulatory mechanisms. We show by applying DFilter and EFilter to embryonic forebrain ChIP-seq data that regulatory protein identification and functional annotation are feasible despite tissue heterogeneity. The mathematical formalism underlying our tools facilitates integrative analysis of data from virtually any sequencing-based functional profile.

Status of the development of Brazilian Decimetric Array (BDA)

NASA Astrophysics Data System (ADS)

Sawant, Hanumant; Fernandes, Francisco; Chellasamy, Ebenezer; Cecatto, Jose R.; Costa, D. Joaquim; Sirothia, Sandeep Kumar; Subramanian, Koovapady

BDA will consists of 38 antennas of 4 meters diameter, capable of operating at frequency range of (1.2-1.7, 2.8 and 5.6) GHz. The array will be spread over the distances 2 x 1 km in a T shape with longest base line in E-W direction, having spatial resolution of ~10 sec of arc at 5.6 GHz. The visibility data can be processed to provide two dimensional images at a time resolution of 100 ms (or higher). In the second phase of the BDA, almost all systems of the 26 antennas are installed. LO of 10 MHz is send from receiver room to each receiver located in the each antenna tower. This receiver operates in the frequency range of 1-6 GHz and converts received signal to 70 MHz. Fiber optical system is partially installed in tower converts 70 MHz signal to optical signal and send to receiver room with low loss and phase compensation of 100 ps, where it is converted back to 70 MHz and processed to give output of 0-5 MHz bandpass and further processed by the correlator. Tracking system, with Dual feed back facility has tracking accuracy of +/- 3 arc minutes. All safety features are installed, with on line offset adjustment. Data logging and event logging for future investigations are available. Tracking system was tested for one month with 8 hours tracking and results of these will also be presented. Field programmable Gate Array based complex correlator system capable of producing all four Stokes parameters was designed and developed for correlating base band outputs from 38 antennas. The correlator produces delay and fringe corrected, visibility correlations between any two signal channels of the same polarizations from any given pair of antennas, providing visibility data. Fringes using this system have been obtained for baseline combinations of 12 fully installed antennas. Simulations of the UV coverage and imaging were carried out for the full synthesis observations of sources at different configurations and various declinations in -70 to +23 degrees range. The current system can image the Sun with spatial resolution of 3.40 x 4.54 arc min at 1.4 GHz. Results of the each of the above systems along with the observed fringes from the FPGA based complex correlator system from non redundant 12 antennas in two dimensions will be presented. BDA phase II will be operational shortly.

Weak Long-Range Correlated Motions in a Surface Patch of Ubiquitin Involved in Molecular Recognition

PubMed Central

2011-01-01

Long-range correlated motions in proteins are candidate mechanisms for processes that require information transfer across protein structures, such as allostery and signal transduction. However, the observation of backbone correlations between distant residues has remained elusive, and only local correlations have been revealed using residual dipolar couplings measured by NMR spectroscopy. In this work, we experimentally identified and characterized collective motions spanning four β-strands separated by up to 15 Å in ubiquitin. The observed correlations link molecular recognition sites and result from concerted conformational changes that are in part mediated by the hydrogen-bonding network. PMID:21634390

SERS as a tool for in vitro toxicology.

PubMed

Fisher, Kate M; McLeish, Jennifer A; Jamieson, Lauren E; Jiang, Jing; Hopgood, James R; McLaughlin, Stephen; Donaldson, Ken; Campbell, Colin J

2016-06-23

Measuring markers of stress such as pH and redox potential are important when studying toxicology in in vitro models because they are markers of oxidative stress, apoptosis and viability. While surface enhanced Raman spectroscopy is ideally suited to the measurement of redox potential and pH in live cells, the time-intensive nature and perceived difficulty in signal analysis and interpretation can be a barrier to its broad uptake by the biological community. In this paper we detail the development of signal processing and analysis algorithms that allow SERS spectra to be automatically processed so that the output of the processing is a pH or redox potential value. By automating signal processing we were able to carry out a comparative evaluation of the toxicology of silver and zinc oxide nanoparticles and correlate our findings with qPCR analysis. The combination of these two analytical techniques sheds light on the differences in toxicology between these two materials from the perspective of oxidative stress.

SPECIAL ISSUE ON OPTICAL PROCESSING OF INFORMATION: Realisation of video-frequency filters on the basis of a new mode of operation of an acousto-optical correlator with spatial integration

NASA Astrophysics Data System (ADS)

Ushakov, V. N.

1995-10-01

A video-frequency acousto-optical correlator with spatial integration, which widens the functional capabilities of correlation-type acousto-optical processors, is described. The correlator is based on a two-dimensional reference transparency and it can filter arbitrary video signals of spectral width limited by the pass band of an acousto-optical modulator. The calculated pulse characteristic is governed by the structure of the reference transparency. A procedure for the synthesis of this transparency is considered and experimental results are reported.

Process observation in fiber laser-based selective laser melting

NASA Astrophysics Data System (ADS)

Thombansen, Ulrich; Gatej, Alexander; Pereira, Milton

2015-01-01

The process observation in selective laser melting (SLM) focuses on observing the interaction point where the powder is processed. To provide process relevant information, signals have to be acquired that are resolved in both time and space. Especially in high-power SLM, where more than 1 kW of laser power is used, processing speeds of several meters per second are required for a high-quality processing results. Therefore, an implementation of a suitable process observation system has to acquire a large amount of spatially resolved data at low sampling speeds or it has to restrict the acquisition to a predefined area at a high sampling speed. In any case, it is vitally important to synchronously record the laser beam position and the acquired signal. This is a prerequisite that allows the recorded data become information. Today, most SLM systems employ f-theta lenses to focus the processing laser beam onto the powder bed. This report describes the drawbacks that result for process observation and suggests a variable retro-focus system which solves these issues. The beam quality of fiber lasers delivers the processing laser beam to the powder bed at relevant focus diameters, which is a key prerequisite for this solution to be viable. The optical train we present here couples the processing laser beam and the process observation coaxially, ensuring consistent alignment of interaction zone and observed area. With respect to signal processing, we have developed a solution that synchronously acquires signals from a pyrometer and the position of the laser beam by sampling the data with a field programmable gate array. The relevance of the acquired signals has been validated by the scanning of a sample filament. Experiments with grooved samples show a correlation between different powder thicknesses and the acquired signals at relevant processing parameters. This basic work takes a first step toward self-optimization of the manufacturing process in SLM. It enables the addition of cognitive functions to the manufacturing system to the extent that the system could track its own process. The results are based on analyzing and redesigning the optical train, in combination with a real-time signal acquisition system which provides a solution to certain technological barriers.

An interaural-correlation-based approach that accounts for a wide variety of binaural detection data.

PubMed

Bernstein, Leslie R; Trahiotis, Constantine

2017-02-01

Interaural cross-correlation-based models of binaural processing have accounted successfully for a wide variety of binaural phenomena, including binaural detection, binaural discrimination, and measures of extents of laterality based on interaural temporal disparities, interaural intensitive disparities, and their combination. This report focuses on quantitative accounts of data obtained from binaural detection experiments published over five decades. Particular emphasis is placed on stimulus contexts for which commonly used correlation-based approaches fail to provide adequate explanations of the data. One such context concerns binaural detection of signals masked by certain noises that are narrow-band and/or interaurally partially correlated. It is shown that a cross-correlation-based model that includes stages of peripheral auditory processing can, when coupled with an appropriate decision variable, account well for a wide variety of classic and recently published binaural detection data including those that have, heretofore, proven to be problematic.

Impulse-induced optimum signal amplification in scale-free networks.

PubMed

Martínez, Pedro J; Chacón, Ricardo

2016-04-01

Optimizing information transmission across a network is an essential task for controlling and manipulating generic information-processing systems. Here, we show how topological amplification effects in scale-free networks of signaling devices are optimally enhanced when the impulse transmitted by periodic external signals (time integral over two consecutive zeros) is maximum. This is demonstrated theoretically by means of a star-like network of overdamped bistable systems subjected to generic zero-mean periodic signals and confirmed numerically by simulations of scale-free networks of such systems. Our results show that the enhancer effect of increasing values of the signal's impulse is due to a correlative increase of the energy transmitted by the periodic signals, while it is found to be resonant-like with respect to the topology-induced amplification mechanism.

Molecular Pathways for Immune Recognition of Preproinsulin Signal Peptide in Type 1 Diabetes.

PubMed

Kronenberg-Versteeg, Deborah; Eichmann, Martin; Russell, Mark A; de Ru, Arnoud; Hehn, Beate; Yusuf, Norkhairin; van Veelen, Peter A; Richardson, Sarah J; Morgan, Noel G; Lemberg, Marius K; Peakman, Mark

2018-04-01

The signal peptide region of preproinsulin (PPI) contains epitopes targeted by HLA-A-restricted (HLA-A0201, A2402) cytotoxic T cells as part of the pathogenesis of β-cell destruction in type 1 diabetes. We extended the discovery of the PPI epitope to disease-associated HLA-B*1801 and HLA-B*3906 (risk) and HLA-A*1101 and HLA-B*3801 (protective) alleles, revealing that four of six alleles present epitopes derived from the signal peptide region. During cotranslational translocation of PPI, its signal peptide is cleaved and retained within the endoplasmic reticulum (ER) membrane, implying it is processed for immune recognition outside of the canonical proteasome-directed pathway. Using in vitro translocation assays with specific inhibitors and gene knockout in PPI-expressing target cells, we show that PPI signal peptide antigen processing requires signal peptide peptidase (SPP). The intramembrane protease SPP generates cytoplasm-proximal epitopes, which are transporter associated with antigen processing (TAP), ER-luminal epitopes, which are TAP independent, each presented by different HLA class I molecules and N-terminal trimmed by ER aminopeptidase 1 for optimal presentation. In vivo, TAP expression is significantly upregulated and correlated with HLA class I hyperexpression in insulin-containing islets of patients with type 1 diabetes. Thus, PPI signal peptide epitopes are processed by SPP and loaded for HLA-guided immune recognition via pathways that are enhanced during disease pathogenesis. © 2018 by the American Diabetes Association.

Portable multiplicity counter

DOEpatents

Newell, Matthew R [Los Alamos, NM; Jones, David Carl [Los Alamos, NM

2009-09-01

A portable multiplicity counter has signal input circuitry, processing circuitry and a user/computer interface disposed in a housing. The processing circuitry, which can comprise a microcontroller integrated circuit operably coupled to shift register circuitry implemented in a field programmable gate array, is configured to be operable via the user/computer interface to count input signal pluses receivable at said signal input circuitry and record time correlations thereof in a total counting mode, coincidence counting mode and/or a multiplicity counting mode. The user/computer interface can be for example an LCD display/keypad and/or a USB interface. The counter can include a battery pack for powering the counter and low/high voltage power supplies for biasing external detectors so that the counter can be configured as a hand-held device for counting neutron events.

High resolution signal-processing method for extrinsic Fabry-Perot interferometric sensors

NASA Astrophysics Data System (ADS)

Xie, Jiehui; Wang, Fuyin; Pan, Yao; Wang, Junjie; Hu, Zhengliang; Hu, Yongming

2015-03-01

In this paper, a signal-processing method for optical fiber extrinsic Fabry-Perot interferometric sensors is presented. It achieves both high resolution and absolute measurement of the dynamic change of cavity length with low sampling points in wavelength domain. In order to improve the demodulation accuracy, the reflected interference spectrum is cleared by Discrete Wavelet Transform and adjusted by the Hilbert transform. Then the cavity length is interrogated by the cross correlation algorithm. The continuous tests show the resolution of cavity length is only 36.7 pm. Moreover, the corresponding resolution of cavity length is only 1 pm on the low frequency range below 420 Hz, and the corresponding power spectrum shows the possibility of detecting the ultra-low frequency signals based on spectra detection.

Surface Acoustic Wave Tag-Based Coherence Multiplexing

NASA Technical Reports Server (NTRS)

Youngquist, Robert C. (Inventor); Malocha, Donald (Inventor); Saldanha, Nancy (Inventor)

2016-01-01

A surface acoustic wave (SAW)-based coherence multiplexing system includes SAW tags each including a SAW transducer, a first SAW reflector positioned a first distance from the SAW transducer and a second SAW reflector positioned a second distance from the SAW transducer. A transceiver including a wireless transmitter has a signal source providing a source signal and circuitry for transmitting interrogation pulses including a first and a second interrogation pulse toward the SAW tags, and a wireless receiver for receiving and processing response signals from the SAW tags. The receiver receives scrambled signals including a convolution of the wideband interrogation pulses with response signals from the SAW tags and includes a computing device which implements an algorithm that correlates the interrogation pulses or the source signal before transmitting against the scrambled signals to generate tag responses for each of the SAW tags.

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

NASA Technical Reports Server (NTRS)

Prokop, Norman; Krasowski, Michael

2013-01-01

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

Synthetic aperture radar and digital processing: An introduction

NASA Technical Reports Server (NTRS)

Dicenzo, A.

1981-01-01

A tutorial on synthetic aperture radar (SAR) is presented with emphasis on digital data collection and processing. Background information on waveform frequency and phase notation, mixing, Q conversion, sampling and cross correlation operations is included for clarity. The fate of a SAR signal from transmission to processed image is traced in detail, using the model of a single bright point target against a dark background. Some of the principal problems connected with SAR processing are also discussed.

[Oligonucleotide derivatives in the nucleic acid hybridization analysis. II. Isothermal signal amplification in process of DNA analysis by minisequencing].

PubMed

Dmitrienko, E V; Khomiakova, E A; Pyshnaia; Bragin, A G; Vedernikov, V E; Pyshnyĭ, D V

2010-01-01

The isothermal amplification of reporter signal via limited probe extension (minisequencing) upon hybridization of nucleic acids has been studied. The intensity of reporter signal has been shown to increase due to enzymatic labeling of multiple probes upon consecutive hybridization with one DNA template both in homophase and heterophase assays using various kinds of detection signal: radioisotope label, fluorescent label, and enzyme-linked assay. The kinetic scheme of the process has been proposed and kinetic parameters for each step have been determined. The signal intensity has been shown to correlate with physicochemical characteristics of both complexes: probe/DNA and product/DNA. The maximum intensity has been observed at minimal difference between the thermodynamic stability of these complexes, provided the reaction temperature has been adjusted near their melting temperature values; rising or lowering the reaction temperature reduces the amount of reporting product. The signal intensity has been shown to decrease significantly upon hybridization with the DNA template containing single-nucleotide mismatches. Limited probe extension assay is useful not only for detection of DNA template but also for its quantitative characterization.

Continuous detection of weak sensory signals in afferent spike trains: the role of anti-correlated interspike intervals in detection performance.

PubMed

Goense, J B M; Ratnam, R

2003-10-01

An important problem in sensory processing is deciding whether fluctuating neural activity encodes a stimulus or is due to variability in baseline activity. Neurons that subserve detection must examine incoming spike trains continuously, and quickly and reliably differentiate signals from baseline activity. Here we demonstrate that a neural integrator can perform continuous signal detection, with performance exceeding that of trial-based procedures, where spike counts in signal- and baseline windows are compared. The procedure was applied to data from electrosensory afferents of weakly electric fish (Apteronotus leptorhynchus), where weak perturbations generated by small prey add approximately 1 spike to a baseline of approximately 300 spikes s(-1). The hypothetical postsynaptic neuron, modeling an electrosensory lateral line lobe cell, could detect an added spike within 10-15 ms, achieving near ideal detection performance (80-95%) at false alarm rates of 1-2 Hz, while trial-based testing resulted in only 30-35% correct detections at that false alarm rate. The performance improvement was due to anti-correlations in the afferent spike train, which reduced both the amplitude and duration of fluctuations in postsynaptic membrane activity, and so decreased the number of false alarms. Anti-correlations can be exploited to improve detection performance only if there is memory of prior decisions.

A digital-receiver for the MurchisonWidefield Array

NASA Astrophysics Data System (ADS)

Prabu, Thiagaraj; Srivani, K. S.; Roshi, D. Anish; Kamini, P. A.; Madhavi, S.; Emrich, David; Crosse, Brian; Williams, Andrew J.; Waterson, Mark; Deshpande, Avinash A.; Shankar, N. Udaya; Subrahmanyan, Ravi; Briggs, Frank H.; Goeke, Robert F.; Tingay, Steven J.; Johnston-Hollitt, Melanie; R, Gopalakrishna M.; Morgan, Edward H.; Pathikulangara, Joseph; Bunton, John D.; Hampson, Grant; Williams, Christopher; Ord, Stephen M.; Wayth, Randall B.; Kumar, Deepak; Morales, Miguel F.; deSouza, Ludi; Kratzenberg, Eric; Pallot, D.; McWhirter, Russell; Hazelton, Bryna J.; Arcus, Wayne; Barnes, David G.; Bernardi, Gianni; Booler, T.; Bowman, Judd D.; Cappallo, Roger J.; Corey, Brian E.; Greenhill, Lincoln J.; Herne, David; Hewitt, Jacqueline N.; Kaplan, David L.; Kasper, Justin C.; Kincaid, Barton B.; Koenig, Ronald; Lonsdale, Colin J.; Lynch, Mervyn J.; Mitchell, Daniel A.; Oberoi, Divya; Remillard, Ronald A.; Rogers, Alan E.; Salah, Joseph E.; Sault, Robert J.; Stevens, Jamie B.; Tremblay, S.; Webster, Rachel L.; Whitney, Alan R.; Wyithe, Stuart B.

2015-03-01

An FPGA-based digital-receiver has been developed for a low-frequency imaging radio interferometer, the Murchison Widefield Array (MWA). The MWA, located at the Murchison Radio-astronomy Observatory (MRO) in Western Australia, consists of 128 dual-polarized aperture-array elements (tiles) operating between 80 and 300 MHz, with a total processed bandwidth of 30.72 MHz for each polarization. Radio-frequency signals from the tiles are amplified and band limited using analog signal conditioning units; sampled and channelized by digital-receivers. The signals from eight tiles are processed by a single digital-receiver, thus requiring 16 digital-receivers for the MWA. The main function of the digital-receivers is to digitize the broad-band signals from each tile, channelize them to form the sky-band, and transport it through optical fibers to a centrally located correlator for further processing. The digital-receiver firmware also implements functions to measure the signal power, perform power equalization across the band, detect interference-like events, and invoke diagnostic modes. The digital-receiver is controlled by high-level programs running on a single-board-computer. This paper presents the digital-receiver design, implementation, current status, and plans for future enhancements.

Effects of correlated noise on the full-spectrum combining and complex-symbol combining arraying techniques

NASA Technical Reports Server (NTRS)

Vazirani, P.

1995-01-01

The process of combining telemetry signals received at multiple antennas, commonly referred to as arraying, can be used to improve communication link performance in the Deep Space Network (DSN). By coherently adding telemetry from multiple receiving sites, arraying produces an enhancement in signal-to-noise ratio (SNR) over that achievable with any single antenna in the array. A number of different techniques for arraying have been proposed and their performances analyzed in past literature. These analyses have compared different arraying schemes under the assumption that the signals contain additive white Gaussian noise (AWGN) and that the noise observed at distinct antennas is independent. In situations where an unwanted background body is visible to multiple antennas in the array, however, the assumption of independent noises is no longer applicable. A planet with significant radiation emissions in the frequency band of interest can be one such source of correlated noise. For example, during much of Galileo's tour of Jupiter, the planet will contribute significantly to the total system noise at various ground stations. This article analyzes the effects of correlated noise on two arraying schemes currently being considered for DSN applications: full-spectrum combining (FSC) and complex-symbol combining (CSC). A framework is presented for characterizing the correlated noise based on physical parameters, and the impact of the noise correlation on the array performance is assessed for each scheme.

Divided versus selective attention: evidence for common processing mechanisms

PubMed Central

Hahn, Britta; Wolkenberg, Frank A.; Ross, Thomas J.; Myers, Carol S.; Heishman, Stephen J.; Stein, Dan J.; Kurup, Pradeep K.; Stein, Elliot A.

2008-01-01

The current study revisited the question of whether there are brain mechanisms specific to divided attention that differ from those used in selective attention. Increased neuronal activity required to simultaneously process two stimulus dimensions as compared with each separate dimension has often been observed, but rarely has activity induced by a divided attention condition exceeded the sum of activity induced by the component tasks. Healthy participants performed a selective-divided attention paradigm while undergoing functional Magnetic Resonance Imaging (fMRI). The task required participants to make a same-different judgment about either one of two simultaneously presented stimulus dimensions, or about both dimensions. Performance accuracy was equated between tasks by dynamically adjusting the stimulus display time. Blood Oxygenation Level Dependent (BOLD) signal differences between tasks were identified by whole-brain voxel-wise comparisons and by region-specific analyses of all areas modulated by the divided attention task (DIV). No region displayed greater activation or deactivation by DIV than the sum of signal change by the two selective attention tasks. Instead, regional activity followed the tasks’ processing demands as reflected by reaction time. Only a left cerebellar region displayed a correlation between participants’ BOLD signal intensity and reaction time that was selective for DIV. The correlation was positive, reflecting slower responding with greater activation. Overall, the findings do not support the existence of functional brain activity specific to DIV. Increased activity appears to reflect additional processing demands by introducing a secondary task, but those demands do not appear to qualitatively differ from processes of selective attention. PMID:18479670

Divided versus selective attention: evidence for common processing mechanisms.

PubMed

Hahn, Britta; Wolkenberg, Frank A; Ross, Thomas J; Myers, Carol S; Heishman, Stephen J; Stein, Dan J; Kurup, Pradeep K; Stein, Elliot A

2008-06-18

The current study revisited the question of whether there are brain mechanisms specific to divided attention that differ from those used in selective attention. Increased neuronal activity required to simultaneously process two stimulus dimensions as compared with each separate dimension has often been observed, but rarely has activity induced by a divided attention condition exceeded the sum of activity induced by the component tasks. Healthy participants performed a selective-divided attention paradigm while undergoing functional Magnetic Resonance Imaging (fMRI). The task required participants to make a same-different judgment about either one of two simultaneously presented stimulus dimensions, or about both dimensions. Performance accuracy was equated between tasks by dynamically adjusting the stimulus display time. Blood Oxygenation Level Dependent (BOLD) signal differences between tasks were identified by whole-brain voxel-wise comparisons and by region-specific analyses of all areas modulated by the divided attention task (DIV). No region displayed greater activation or deactivation by DIV than the sum of signal change by the two selective attention tasks. Instead, regional activity followed the tasks' processing demands as reflected by reaction time. Only a left cerebellar region displayed a correlation between participants' BOLD signal intensity and reaction time that was selective for DIV. The correlation was positive, reflecting slower responding with greater activation. Overall, the findings do not support the existence of functional brain activity specific to DIV. Increased activity appears to reflect additional processing demands by introducing a secondary task, but those demands do not appear to qualitatively differ from processes of selective attention.

Behavioural and neuroanatomical correlates of auditory speech analysis in primary progressive aphasias.

PubMed

Hardy, Chris J D; Agustus, Jennifer L; Marshall, Charles R; Clark, Camilla N; Russell, Lucy L; Bond, Rebecca L; Brotherhood, Emilie V; Thomas, David L; Crutch, Sebastian J; Rohrer, Jonathan D; Warren, Jason D

2017-07-27

Non-verbal auditory impairment is increasingly recognised in the primary progressive aphasias (PPAs) but its relationship to speech processing and brain substrates has not been defined. Here we addressed these issues in patients representing the non-fluent variant (nfvPPA) and semantic variant (svPPA) syndromes of PPA. We studied 19 patients with PPA in relation to 19 healthy older individuals. We manipulated three key auditory parameters-temporal regularity, phonemic spectral structure and prosodic predictability (an index of fundamental information content, or entropy)-in sequences of spoken syllables. The ability of participants to process these parameters was assessed using two-alternative, forced-choice tasks and neuroanatomical associations of task performance were assessed using voxel-based morphometry of patients' brain magnetic resonance images. Relative to healthy controls, both the nfvPPA and svPPA groups had impaired processing of phonemic spectral structure and signal predictability while the nfvPPA group additionally had impaired processing of temporal regularity in speech signals. Task performance correlated with standard disease severity and neurolinguistic measures. Across the patient cohort, performance on the temporal regularity task was associated with grey matter in the left supplementary motor area and right caudate, performance on the phoneme processing task was associated with grey matter in the left supramarginal gyrus, and performance on the prosodic predictability task was associated with grey matter in the right putamen. Our findings suggest that PPA syndromes may be underpinned by more generic deficits of auditory signal analysis, with a distributed cortico-subcortical neuraoanatomical substrate extending beyond the canonical language network. This has implications for syndrome classification and biomarker development.

Using a pulsed laser beam to investigate the feasibility of sub-pixel position resolution with time-correlated transient signals in 3D pixelated CdZnTe detectors

DOE PAGES

Giraldo, L. Ocampo; Bolotnikov, A. E.; Camarda, G. S.; ...

2017-04-20

For this study, we evaluated the X-Y position resolution achievable in 3D pixelated detectors by processing the signal waveforms readout from neighboring pixels. In these measurements we used a focused light beam, down to 10 μm, generated by a ~1 mW pulsed laser (650 nm) to carry out raster scans over selected 3×3 pixel areas, while recording the charge signals from the 9 pixels and the cathode using two synchronized digital oscilloscopes.

A study of FM threshold extension techniques

NASA Technical Reports Server (NTRS)

Arndt, G. D.; Loch, F. J.

1972-01-01

The characteristics of three postdetection threshold extension techniques are evaluated with respect to the ability of such techniques to improve the performance of a phase lock loop demodulator. These techniques include impulse-noise elimination, signal correlation for the detection of impulse noise, and delta modulation signal processing. Experimental results from signal to noise ratio data and bit error rate data indicate that a 2- to 3-decibel threshold extension is readily achievable by using the various techniques. This threshold improvement is in addition to the threshold extension that is usually achieved through the use of a phase lock loop demodulator.

Analysis of radiometric signal in sedimentating suspension flow in open channel

NASA Astrophysics Data System (ADS)

Zych, Marcin; Hanus, Robert; Petryka, Leszek; Świsulski, Dariusz; Doktor, Marek; Mastej, Wojciech

2015-05-01

The article discusses issues related to the estimation of the sedimentating solid particles average flow velocity in an open channel using radiometric methods. Due to the composition of the compound, which formed water and diatomite, received data have a very weak signal to noise ratio. In the process analysis the known determining of the solid phase transportation time delay the classical cross-correlation function is the most reliable method. The use of advanced frequency analysis based on mutual spectral density function and wavelet transform of recorded signals allows a reduction of the noise contribution.

Performance highlights of the ALMA correlators

NASA Astrophysics Data System (ADS)

Baudry, Alain; Lacasse, Richard; Escoffier, Ray; Webber, John; Greenberg, Joseph; Platt, Laurence; Treacy, Robert; Saez, Alejandro F.; Cais, Philippe; Comoretto, Giovanni; Quertier, Benjamin; Okumura, Sachiko K.; Kamazaki, Takeshi; Chikada, Yoshihiro; Watanabe, Manabu; Okuda, Takeshi; Kurono, Yasutake; Iguchi, Satoru

2012-09-01

Two large correlators have been constructed to combine the signals captured by the ALMA antennas deployed on the Atacama Desert in Chile at an elevation of 5050 meters. The Baseline correlator was fabricated by a NRAO/European team to process up to 64 antennas for 16 GHz bandwidth in two polarizations and another correlator, the Atacama Compact Array (ACA) correlator, was fabricated by a Japanese team to process up to 16 antennas. Both correlators meet the same specifications except for the number of processed antennas. The main architectural differences between these two large machines will be underlined. Selected features of the Baseline and ACA correlators as well as the main technical challenges met by the designers will be briefly discussed. The Baseline correlator is the largest correlator ever built for radio astronomy. Its digital hybrid architecture provides a wide variety of observing modes including the ability to divide each input baseband into 32 frequency-mobile sub-bands for high spectral resolution and to be operated as a conventional 'lag' correlator for high time resolution. The various observing modes offered by the ALMA correlators to the science community for 'Early Science' are presented, as well as future observing modes. Coherently phasing the array to provide VLBI maps of extremely compact sources is another feature of the ALMA correlators. Finally, the status and availability of these large machines will be presented.

[INVITED] Evaluation of process observation features for laser metal welding

NASA Astrophysics Data System (ADS)

Tenner, Felix; Klämpfl, Florian; Nagulin, Konstantin Yu.; Schmidt, Michael

2016-06-01

In the present study we show how fast the fluid dynamics change when changing the laser power for different feed rates during laser metal welding. By the use of two high-speed cameras and a data acquisition system we conclude how fast we have to image the process to measure the fluid dynamics with a very high certainty. Our experiments show that not all process features which can be measured during laser welding do represent the process behavior similarly well. Despite the good visibility of the vapor plume the monitoring of its movement is less suitable as an input signal for a closed-loop control. The features measured inside the keyhole show a good correlation with changes of process parameters. Due to its low noise, the area of the keyhole opening is well suited as an input signal for a closed-loop control of the process.

27-day variation in solar-terrestrial parameters: Global characteristics and an origin based approach of the signals

NASA Astrophysics Data System (ADS)

Poblet, Facundo L.; Azpilicueta, Francisco

2018-05-01

The Earth and the near interplanetary medium are affected by the Sun in different ways. Those processes generated in the Sun that induce perturbations into the Magnetosphere-Ionosphere system are called geoeffective processes and show a wide range of temporal variations, like the 11-year solar cycle (long term variations), the variation of ∼27 days (recurrent variations), solar storms enduring for some days, particle acceleration events lasting for some hours, etc. In this article, the periodicity of ∼27 days associated with the solar synodic rotation period is investigated. The work is mainly focused on studying the resulting 27-day periodic signal in the magnetic activity, by the analysis of the horizontal component of the magnetic field registered on a set of 103 magnetic observatories distributed around the world. For this a new method to isolate the periodicity of interest has been developed consisting of two main steps: the first one consists of removing the linear trend corresponding to every calendar year from the data series, and the second one of removing from the resulting series a smoothed version of it obtained by applying a 30-day moving average. The result at the end of this process is a data series in which all the signal with periods larger than 30 days are canceled. The most important characteristics observed in the resulting signals are two main amplitude modulations: the first and most prominent related to the 11-year solar cycle and the second one with a semiannual pattern. In addition, the amplitude of the signal shows a dependence on the geomagnetic latitude of the observatory with a significant discontinuity at approx. ±60°. The processing scheme was also applied to other parameters that are widely used to characterize the energy transfer from the Sun to the Earth: F10.7 and Mg II indices and the ionospheric vertical total electron content (vTEC) were considered for radiative interactions; and the solar wind velocity for the non-radiative interactions between the solar wind and the magnetosphere. The 27-day signal obtained in the magnetic activity was compared with the signals found in the other parameters resulting in a series of cross-correlations curves with maximum correlation between 3 and 5 days of delays for the radiative and between 0 and 1 days of delay for the non-radiative parameters. This result supports the idea that the physical process responsible for the 27-day signal in the magnetic activity is related to the solar wind and not to the solar electromagnetic radiation.

Searching for Correlated Radio Transients & Gravitational Wave Bursts

NASA Astrophysics Data System (ADS)

Kavic, Michael; Shawhan, P. S.; Yancey, C.; Cutchin, S.; Simonetti, J. H.; Bear, B.; Tsai, J.

2013-01-01

We will discuss an ongoing multi-messenger search for transient radio pulses and gravitational wave bursts. This work is being conducted jointly by the Long Wavelength Array (LWA) and the LIGO Scientific Collaboration (LSC). A variety of astrophysical sources can produce simultaneous emission of gravitational waves and coherent low-frequency electromagnetic radiation. The primary common source motivating this work is the merger of neutron star binaries for which the LWA and LSC instruments have comparable sensitivity. Additional common sources include supernovae, long timescale GRBs and cosmic string cusp events. Data taken by both instruments can be compared to search for correlated signals. Identification of correlated signals can be used to increase the sensitivity of both instruments. We will summarize the coincident observations which have already been conducted and outline plans for future work. We will describe the process being used for synthesizing these data set and present preliminary results.

Time irreversibility and intrinsics revealing of series with complex network approach

NASA Astrophysics Data System (ADS)

Xiong, Hui; Shang, Pengjian; Xia, Jianan; Wang, Jing

2018-06-01

In this work, we analyze time series on the basis of the visibility graph algorithm that maps the original series into a graph. By taking into account the all-round information carried by the signals, the time irreversibility and fractal behavior of series are evaluated from a complex network perspective, and considered signals are further classified from different aspects. The reliability of the proposed analysis is supported by numerical simulations on synthesized uncorrelated random noise, short-term correlated chaotic systems and long-term correlated fractal processes, and by the empirical analysis on daily closing prices of eleven worldwide stock indices. Obtained results suggest that finite size has a significant effect on the evaluation, and that there might be no direct relation between the time irreversibility and long-range correlation of series. Similarity and dissimilarity between stock indices are also indicated from respective regional and global perspectives, showing the existence of multiple features of underlying systems.

Correlation of surface site formation to nanoisland growth in the electrochemical roughening of Pt(111)

NASA Astrophysics Data System (ADS)

Jacobse, Leon; Huang, Yi-Fan; Koper, Marc T. M.; Rost, Marcel J.

2018-03-01

Platinum plays a central role in a variety of electrochemical devices and its practical use depends on the prevention of electrode degradation. However, understanding the underlying atomic processes under conditions of repeated oxidation and reduction inducing irreversible surface structure changes has proved challenging. Here, we examine the correlation between the evolution of the electrochemical signal of Pt(111) and its surface roughening by simultaneously performing cyclic voltammetry and in situ electrochemical scanning tunnelling microscopy (EC-STM). We identify a `nucleation and early growth' regime of nanoisland formation, and a `late growth' regime after island coalescence, which continues up to at least 170 cycles. The correlation analysis shows that each step site that is created in the `late growth' regime contributes equally strongly to both the electrochemical and the roughness evolution. In contrast, in the `nucleation and early growth' regime, created step sites contribute to the roughness, but not to the electrochemical signal.

Signal Digitizer and Cross-Correlation Application Specific Integrated Circuit

NASA Technical Reports Server (NTRS)

Baranauskas, Gytis (Inventor); Lim, Boon H. (Inventor); Baranauskas, Dalius (Inventor); Zelenin, Denis (Inventor); Kangaslahti, Pekka (Inventor); Tanner, Alan B. (Inventor)

2017-01-01

According to one embodiment, a cross-correlator comprises a plurality of analog front ends (AFEs), a cross-correlation circuit and a data serializer. Each of the AFEs comprises a variable gain amplifier (VGA) and a corresponding analog-to-digital converter (ADC) in which the VGA receives and modifies a unique analog signal associates with a measured analog radio frequency (RF) signal and the ADC produces digital data associated with the modified analog signal. Communicatively coupled to the AFEs, the cross-correlation circuit performs a cross-correlation operation on the digital data produced from different measured analog RF signals. The data serializer is communicatively coupled to the summing and cross-correlating matrix and continuously outputs a prescribed amount of the correlated digital data.

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

NASA Technical Reports Server (NTRS)

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

2013-01-01

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

Multi-purpose ECG telemetry system.

PubMed

Marouf, Mohamed; Vukomanovic, Goran; Saranovac, Lazar; Bozic, Miroslav

2017-06-19

The Electrocardiogram ECG is one of the most important non-invasive tools for cardiac diseases diagnosis. Taking advantage of the developed telecommunication infrastructure, several approaches that address the development of telemetry cardiac devices were introduced recently. Telemetry ECG devices allow easy and fast ECG monitoring of patients with suspected cardiac issues. Choosing the right device with the desired working mode, signal quality, and the device cost are still the main obstacles to massive usage of these devices. In this paper, we introduce design, implementation, and validation of a multi-purpose telemetry system for recording, transmission, and interpretation of ECG signals in different recording modes. The system consists of an ECG device, a cloud-based analysis pipeline, and accompanied mobile applications for physicians and patients. The proposed ECG device's mechanical design allows laypersons to easily record post-event short-term ECG signals, using dry electrodes without any preparation. Moreover, patients can use the device to record long-term signals in loop and holter modes, using wet electrodes. In order to overcome the problem of signal quality fluctuation due to using different electrodes types and different placements on subject's chest, customized ECG signal processing and interpretation pipeline is presented for each working mode. We present the evaluation of the novel short-term recorder design. Recording of an ECG signal was performed for 391 patients using a standard 12-leads golden standard ECG and the proposed patient-activated short-term post-event recorder. In the validation phase, a sample of validation signals followed peer review process wherein two experts annotated the signals in terms of signal acceptability for diagnosis.We found that 96% of signals allow detecting arrhythmia and other signal's abnormal changes. Additionally, we compared and presented the correlation coefficient and the automatic QRS delineation results of both short-term post-event recorder and 12-leads golden standard ECG recorder. The proposed multi-purpose ECG device allows physicians to choose the working mode of the same device according to the patient status. The proposed device was designed to allow patients to manage the technical requirements of both working modes. Post-event short-term ECG recording using the proposed design provide physicians reliable three ECG leads with direct symptom-rhythm correlation.

No-signaling, perfect bipartite dichotomic correlations and local randomness

DOE Office of Scientific and Technical Information (OSTI.GOV)

Seevinck, M. P.

2011-03-28

The no-signaling constraint on bi-partite correlations is reviewed. It is shown that in order to obtain non-trivial Bell-type inequalities that discern no-signaling correlations from more general ones, one must go beyond considering expectation values of products of observables only. A new set of nontrivial no-signaling inequalities is derived which have a remarkably close resemblance to the CHSH inequality, yet are fundamentally different. A set of inequalities by Roy and Singh and Avis et al., which is claimed to be useful for discerning no-signaling correlations, is shown to be trivially satisfied by any correlation whatsoever. Finally, using the set of newlymore » 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.« less

Common Randomness Principles of Secrecy

ERIC Educational Resources Information Center

Tyagi, Himanshu

2013-01-01

This dissertation concerns the secure processing of distributed data by multiple terminals, using interactive public communication among themselves, in order to accomplish a given computational task. In the setting of a probabilistic multiterminal source model in which several terminals observe correlated random signals, we analyze secure…

Infrasonic wave accompanying a crack opening during the 2015 Hakone eruption

NASA Astrophysics Data System (ADS)

Yukutake, Yohei; Ichihara, Mie; Honda, Ryou

2018-03-01

To understand the initial process of the phreatic eruption of the Hakone volcano from June 29 to July 01, 2015, we analyzed infrasound data using the cross-correlation between infrasound and vertical ground velocity and compared the results of our analysis to the crustal deformation detected by tiltmeters and broadband seismometers. An infrasound signal and vertical ground motion due to an infrasound wave coupled to the ground were detected simultaneously with the opening of a crack source beneath the Owakudani geothermal region during the 2-min time period after 07:32 JST on June 29, 2015 (JST = UTC + 8 h). Given that the upper end of the open crack was approximately 150 m beneath the surface, the time for the direct emission of highly pressurized fluid from the upper end of the open crack to the surface should have exceeded the duration of the inflation owing to the hydraulic diffusivity in the porous media. Therefore, the infrasound signal coincident with the opening of the crack may reflect a sudden emission of volcanic gas resulting from the rapid vaporization of pre-existing groundwater beneath Owakudani because of the transfer of the volumetric strain change from the deformation source. We also noticed a correlation pattern corresponding to discrete impulsive infrasound signals during vent formation, which occurred several hours to 2 days after the opening of the crack. In particular, we noted that the sudden emission of vapor coincided with the inflation of the shallow pressure source, whereas the eruptive burst events accompanied by the largest vent formation were delayed by approximately 2 days. Furthermore, we demonstrated that the correlation method is a useful tool in detecting small infrasound signals and provides important information regarding the initial processes of the eruption.[Figure not available: see fulltext.

Fractal properties of background noise and target signal enhancement using CSEM data

NASA Astrophysics Data System (ADS)

Benavides, Alfonso; Everett, Mark E.; Pierce, Carl; Nguyen, Cam

2003-09-01

Controlled-source electromagnetic (CSEM) spatial profiles and 2-D conductivity maps were obtained on the Brazos Valley, TX floodplain to study the fractal statistics of geological signals and effects of man-made conductive targets using Geonics EM34, EM31 and EM63. Using target-free areas, a consistent power-law power spectrum (|A(k)| ~ k ^-β) for the profiles was found with β values typical of fractional Brownian motion (fBm). This means that the spatial variation of conductivity does not correspond to Gaussian statistics, where there are spatial correlations at different scales. The presence of targets tends to flatten the power-law power spectrum (PS) at small wavenumbers. Detection and localization of targets can be achieved using short-time Fourier transform (STFT). The presence of targets is enhanced because the signal energy is spread to higher wavenumbers (small scale numbers) in the positions occupied by the targets. In the case of poor spatial sampling or small amount of data, the information available from the power spectrum is not enough to separate spatial correlations from target signatures. Advantages are gained by using the spatial correlations of the fBm in order to reject the background response, and to enhance the signals from highly conductive targets. This approach was tested for the EM31 using a pre-processing step that combines apparent conductivity readings from two perpendicular transmitter-receiver orientations at each station. The response obtained using time-domain CSEM is influence to a lesser degree by geological noise and the target response can be processed to recover target features. The homotopy method is proposed to solve the inverse problem using a set of possible target models and a dynamic library of responses used to optimize the starting model.

DRD2 genotype-based variation of default mode network activity and of its relationship with striatal DAT binding.

PubMed

Sambataro, Fabio; Fazio, Leonardo; Taurisano, Paolo; Gelao, Barbara; Porcelli, Annamaria; Mancini, Marina; Sinibaldi, Lorenzo; Ursini, Gianluca; Masellis, Rita; Caforio, Grazia; Di Giorgio, Annabella; Niccoli-Asabella, Artor; Popolizio, Teresa; Blasi, Giuseppe; Bertolino, Alessandro

2013-01-01

The default mode network (DMN) comprises a set of brain regions with "increased" activity during rest relative to cognitive processing. Activity in the DMN is associated with functional connections with the striatum and dopamine (DA) levels in this brain region. A functional single-nucleotide polymorphism within the dopamine D2 receptor gene (DRD2, rs1076560 G > T) shifts splicing of the 2 D2 isoforms, D2 short and D2 long, and has been associated with striatal DA signaling as well as with cognitive processing. However, the effects of this polymorphism on DMN have not been explored. The aim of this study was to evaluate the effects of rs1076560 on DMN and striatal connectivity and on their relationship with striatal DA signaling. Twenty-eight subjects genotyped for rs1076560 underwent functional magnetic resonance imaging during a working memory task and 123 55 I-Fluoropropyl-2-beta-carbomethoxy-3-beta(4-iodophenyl) nortropan Single Photon Emission Computed Tomography ([(123)I]-FP-CIT SPECT) imaging (a measure of dopamine transporter [DAT] binding). Spatial group-independent component (IC) analysis was used to identify DMN and striatal ICs. Within the anterior DMN IC, GG subjects had relatively greater connectivity in medial prefrontal cortex (MPFC), which was directly correlated with striatal DAT binding. Within the posterior DMN IC, GG subjects had reduced connectivity in posterior cingulate relative to T carriers. Additionally, rs1076560 genotype predicted connectivity differences within a striatal network, and these changes were correlated with connectivity in MPFC and posterior cingulate within the DMN. These results suggest that genetically determined D2 receptor signaling is associated with DMN connectivity and that these changes are correlated with striatal function and presynaptic DA signaling.

DRD2 Genotype-Based Variation of Default Mode Network Activity and of Its Relationship With Striatal DAT Binding

PubMed Central

Sambataro, Fabio; Fazio, Leonardo; Taurisano, Paolo; Gelao, Barbara; Porcelli, Annamaria; Mancini, Marina; Sinibaldi, Lorenzo; Ursini, Gianluca; Masellis, Rita; Caforio, Grazia; Di Giorgio, Annabella; Niccoli-Asabella, Artor; Popolizio, Teresa; Blasi, Giuseppe; Bertolino, Alessandro

2013-01-01

The default mode network (DMN) comprises a set of brain regions with “increased” activity during rest relative to cognitive processing. Activity in the DMN is associated with functional connections with the striatum and dopamine (DA) levels in this brain region. A functional single-nucleotide polymorphism within the dopamine D2 receptor gene (DRD2, rs1076560 G > T) shifts splicing of the 2 D2 isoforms, D2 short and D2 long, and has been associated with striatal DA signaling as well as with cognitive processing. However, the effects of this polymorphism on DMN have not been explored. The aim of this study was to evaluate the effects of rs1076560 on DMN and striatal connectivity and on their relationship with striatal DA signaling. Twenty-eight subjects genotyped for rs1076560 underwent functional magnetic resonance imaging during a working memory task and 123 55 I-Fluoropropyl-2-beta-carbomethoxy-3-beta(4-iodophenyl) nortropan Single Photon Emission Computed Tomography ([123I]-FP-CIT SPECT) imaging (a measure of dopamine transporter [DAT] binding). Spatial group-independent component (IC) analysis was used to identify DMN and striatal ICs. Within the anterior DMN IC, GG subjects had relatively greater connectivity in medial prefrontal cortex (MPFC), which was directly correlated with striatal DAT binding. Within the posterior DMN IC, GG subjects had reduced connectivity in posterior cingulate relative to T carriers. Additionally, rs1076560 genotype predicted connectivity differences within a striatal network, and these changes were correlated with connectivity in MPFC and posterior cingulate within the DMN. These results suggest that genetically determined D2 receptor signaling is associated with DMN connectivity and that these changes are correlated with striatal function and presynaptic DA signaling. PMID:21976709

Range Measurement as Practiced in the Deep Space Network

NASA Technical Reports Server (NTRS)

Berner, Jeff B.; Bryant, Scott H.; Kinman, Peter W.

2007-01-01

Range measurements are used to improve the trajectory models of spacecraft tracked by the Deep Space Network. The unique challenge of deep-space ranging is that the two-way delay is long, typically many minutes, and the signal-to-noise ratio is small. Accurate measurements are made under these circumstances by means of long correlations that incorporate Doppler rate-aiding. This processing is done with commercial digital signal processors, providing a flexibility in signal design that can accommodate both the traditional sequential ranging signal and pseudonoise range codes. Accurate range determination requires the calibration of the delay within the tracking station. Measurements with a standard deviation of 1 m have been made.

Signal processing for distributed sensor concept: DISCO

NASA Astrophysics Data System (ADS)

Rafailov, Michael K.

2007-04-01

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

Fluctuations of pol I and fibrillarin contents of the nucleoli.

PubMed

Hornáček, M; Kováčik, L; Mazel, T; Cmarko, D; Bártová, E; Raška, I; Smirnov, E

2017-07-04

Nucleoli are formed on the basis of ribosomal DNA (rDNA) clusters called Nucleolus Organizer Regions (NORs). Each NOR contains multiple genes coding for RNAs of the ribosomal particles. The prominent components of the nucleolar ultrastructure, fibrillar centers (FC) and dense fibrillar components (DFC), together compose FC/DFC units. These units are centers of rDNA transcription by RNA polymerase I (pol I), as well as the early processing events, in which an essential role belongs to fibrillarin. Each FC/DFC unit probably corresponds to a single transcriptionally active gene. In this work, we transfected human-derived cells with GFP-RPA43 (subunit of pol I) and RFP-fibrillarin. Following changes of the fluorescent signals in individual FC/DFC units, we found two kinds of kinetics: 1) the rapid fluctuations with periods of 2-3 min, when the pol I and fibrillarin signals oscillated in anti-phase manner, and the intensities of pol I in the neighboring FC/DFC units did not correlate. 2) fluctuations with periods of 10 to 60 min, in which pol I and fibrillarin signals measured in the same unit did not correlate, but pol I signals in the units belonging to different nucleoli were synchronized. Our data indicate that a complex pulsing activity of transcription as well as early processing is common for ribosomal genes.

Nonlinear correlations impair quantification of episodic memory by mesial temporal BOLD activity.

PubMed

Klamer, Silke; Zeltner, Lena; Erb, Michael; Klose, Uwe; Wagner, Kathrin; Frings, Lars; Groen, Georg; Veil, Cornelia; Rona, Sabine; Lerche, Holger; Milian, Monika

2013-07-01

Episodic memory processes can be investigated using different functional MRI (fMRI) paradigms. The purpose of the present study was to examine correlations between neuropsychological memory test scores and BOLD signal changes during fMRI scanning using three different memory tasks. Twenty-eight right-handed healthy subjects underwent three paradigms, (a) a word pair, (b) a space-labyrinth, and (c) a face-name association paradigm. These paradigms were compared for their value in memory quantification and lateralization by calculating correlations between the BOLD signals in the mesial temporal lobe and behavioral data derived from a neuropsychological test battery. As expected, group analysis showed left-sided activation for the verbal, a tendency to right-sided activation for the spatial, and bilateral activation for the face-name paradigm. No linear correlations were observed between neuropsychological data and activation in the temporo-mesial region. However, we found significant u-shaped correlations between behavioral memory performance and activation in both the verbal and the face-name paradigms, that is, BOLD signal changes were greater not only among participants who performed best on the neuropsychological tests, but also among the poorest performers. The figural learning task did not correlate with the activations in the space-labyrinth paradigm at all. We interpreted the u-shaped correlations to be due to compensatory hippocampal activations associated with low performance when people try unsuccessfully to remember presented items. Because activation levels did not linearly increase with memory performance, the latter cannot be quantified by fMRI alone, but only be used in conjunction with neuropsychological testing. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Bradys Hot Springs Ambient Noise Correlation Functions (Initial Waveforms)

DOE Data Explorer

Eric Matzel

2015-07-01

These files are ambient noise correlation (ANC) functions calculated for 11 days of continuous seismic data recorded by the Lawrence Berkeley network in the Brady geothermal field. These are SAC formatted seismic waveforms. The stations included are BPB04, BPB05, BPB07, BPB08, BPRT1, BPRT2, BPRT3, BPRT5, BRB10, BRP01, BRP02, BRP03, BRP04, BPR06, and BRP09 The original data were cut into hour long traces and processed by differentiating, removing the mean, removing the trend, applying a 1% taper, whitening, removing the mean and trend again, and converting to single bit traces. The data were then correlated with those from other stations and stacked. The resulting files were then named according to the convention: STA1.STA2.CHAN1_CHAN2.NHOURS.stacked.sac The days included are from records during 2013 (julian days, 200,220-229). The ANC correlations were calculated on the raw data traces (without instrument corrections applied) to assess the quality of the signal as a function of frequency throughout the network. The data were recorded at 500 Hz. We observe high quality signals 30 Hz on all traces, and measurable signal up to 80 Hz on a subset of the traces.

Audio signal analysis for tool wear monitoring in sheet metal stamping

NASA Astrophysics Data System (ADS)

Ubhayaratne, Indivarie; Pereira, Michael P.; Xiang, Yong; Rolfe, Bernard F.

2017-02-01

Stamping tool wear can significantly degrade product quality, and hence, online tool condition monitoring is a timely need in many manufacturing industries. Even though a large amount of research has been conducted employing different sensor signals, there is still an unmet demand for a low-cost easy to set up condition monitoring system. Audio signal analysis is a simple method that has the potential to meet this demand, but has not been previously used for stamping process monitoring. Hence, this paper studies the existence and the significance of the correlation between emitted sound signals and the wear state of sheet metal stamping tools. The corrupting sources generated by the tooling of the stamping press and surrounding machinery have higher amplitudes compared to that of the sound emitted by the stamping operation itself. Therefore, a newly developed semi-blind signal extraction technique was employed as a pre-processing technique to mitigate the contribution of these corrupting sources. The spectral analysis results of the raw and extracted signals demonstrate a significant qualitative relationship between wear progression and the emitted sound signature. This study lays the basis for employing low-cost audio signal analysis in the development of a real-time industrial tool condition monitoring system.

Coherent broadband sonar signal processing with the environmentally corrected matched filter

NASA Astrophysics Data System (ADS)

Camin, Henry John, III

The matched filter is the standard approach for coherently processing active sonar signals, where knowledge of the transmitted waveform is used in the detection and parameter estimation of received echoes. Matched filtering broadband signals provides higher levels of range resolution and reverberation noise suppression than can be realized through narrowband processing. Since theoretical processing gains are proportional to the signal bandwidth, it is typically desirable to utilize the widest band signals possible. However, as signal bandwidth increases, so do environmental effects that tend to decrease correlation between the received echo and the transmitted waveform. This is especially true for ultra wideband signals, where the bandwidth exceeds an octave or approximately 70% fractional bandwidth. This loss of coherence often results in processing gains and range resolution much lower than theoretically predicted. Wiener filtering, commonly used in image processing to improve distorted and noisy photos, is investigated in this dissertation as an approach to correct for these environmental effects. This improved signal processing, Environmentally Corrected Matched Filter (ECMF), first uses a Wiener filter to estimate the environmental transfer function and then again to correct the received signal using this estimate. This process can be viewed as a smarter inverse or whitening filter that adjusts behavior according to the signal to noise ratio across the spectrum. Though the ECMF is independent of bandwidth, it is expected that ultra wideband signals will see the largest improvement, since they tend to be more impacted by environmental effects. The development of the ECMF and demonstration of improved parameter estimation with its use are the primary emphases in this dissertation. Additionally, several new contributions to the field of sonar signal processing made in conjunction with the development of the ECMF are described. A new, nondimensional wideband ambiguity function is presented as a way to view the behavior of the matched filter with and without the decorrelating environmental effects; a new, integrated phase broadband angle estimation method is developed and compared to existing methods; and a new, asymptotic offset phase angle variance model is presented. Several data sets are used to demonstrate these new contributions. High fidelity Sonar Simulation Toolset (SST) synthetic data is used to characterize the theoretical performance. Two in-water data sets were used to verify assumptions that were made during the development of the ECMF. Finally, a newly collected in-air data set containing ultra wideband signals was used in lieu of a cost prohibitive underwater experiment to demonstrate the effectiveness of the ECMF at improving parameter estimates.

Rapid encoding of relationships between spatially remote motion signals.

PubMed

Maruya, Kazushi; Holcombe, Alex O; Nishida, Shin'ya

2013-02-06

For visual processing, the temporal correlation of remote local motion signals is a strong cue to detect meaningful large-scale structures in the retinal image, because related points are likely to move together regardless of their spatial separation. While the processing of multi-element motion patterns involved in biological motion and optic flow has been studied intensively, the encoding of simpler pairwise relationships between remote motion signals remains poorly understood. We investigated this process by measuring the temporal rate limit for perceiving the relationship of two motion directions presented at the same time at different spatial locations. Compared to luminance or orientation, motion comparison was more rapid. Performance remained very high even when interstimulus separation was increased up to 100°. Motion comparison also remained rapid regardless of whether the two motion directions were similar to or different from each other. The exception was a dramatic slowing when the elements formed an orthogonal "T," in which two motions do not perceptually group together. Motion presented at task-irrelevant positions did not reduce performance, suggesting that the rapid motion comparison could not be ascribed to global optic flow processing. Our findings reveal the existence and unique nature of specialized processing that encodes long-range relationships between motion signals for quick appreciation of global dynamic scene structure.

Optimal Signal Filtration in Optical Sensors with Natural Squeezing of Vacuum Noises

NASA Technical Reports Server (NTRS)

Gusev, A. V.; Kulagin, V. V.

1996-01-01

The structure of optimal receiver is discussed for optical sensor measuring a small displacement of probe mass. Due to nonlinear interaction of the field and the mirror, a reflected wave is in squeezed state (natural squeezing), two quadratures of which are correlated and therefore one can increase signal-to-noise ratio and overcome the SQL. A measurement procedure realizing such correlation processing of two quadratures is clarified. The required combination of quadratures can be produced via mixing of pump field reflected from the mirror with local oscillator phase modulated field in duel-detector homodyne scheme. Such measurement procedure could be useful not only for resonant bar gravitational detector but for laser longbase interferometric detectors as well.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, TK; Ewald, A; Schultz, T

2014-06-01

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

Research on Ship-Radiated Noise Denoising Using Secondary Variational Mode Decomposition and Correlation Coefficient.

PubMed

Li, Yuxing; Li, Yaan; Chen, Xiao; Yu, Jing

2017-12-26

As the sound signal of ships obtained by sensors contains other many significant characteristics of ships and called ship-radiated noise (SN), research into a denoising algorithm and its application has obtained great significance. Using the advantage of variational mode decomposition (VMD) combined with the correlation coefficient for denoising, a hybrid secondary denoising algorithm is proposed using secondary VMD combined with a correlation coefficient (CC). First, different kinds of simulation signals are decomposed into several bandwidth-limited intrinsic mode functions (IMFs) using VMD, where the decomposition number by VMD is equal to the number by empirical mode decomposition (EMD); then, the CCs between the IMFs and the simulation signal are calculated respectively. The noise IMFs are identified by the CC threshold and the rest of the IMFs are reconstructed in order to realize the first denoising process. Finally, secondary denoising of the simulation signal can be accomplished by repeating the above steps of decomposition, screening and reconstruction. The final denoising result is determined according to the CC threshold. The denoising effect is compared under the different signal-to-noise ratio and the time of decomposition by VMD. Experimental results show the validity of the proposed denoising algorithm using secondary VMD (2VMD) combined with CC compared to EMD denoising, ensemble EMD (EEMD) denoising, VMD denoising and cubic VMD (3VMD) denoising, as well as two denoising algorithms presented recently. The proposed denoising algorithm is applied to feature extraction and classification for SN signals, which can effectively improve the recognition rate of different kinds of ships.

Spectral responses of gravel beaches to tidal signals

NASA Astrophysics Data System (ADS)

Geng, Xiaolong; Boufadel, Michel C.

2017-01-01

Tides have been recognized as a major driving forcing affecting coastal aquifer system, and deterministic modeling has been very effective in elucidating mechanisms caused by tides. However, such modeling does not lend itself to capture embedded information in the signal, and rather focuses on the primary processes. Here, using yearlong data sets measured at beaches in Alaska Prince William Sound, we performed spectral and correlation analyses to identify temporal behavior of pore-water pressure, temperature and salinity. We found that the response of the beach system was characterized by fluctuations of embedded diurnal, semidiurnal, terdiurnal and quarterdiurnal tidal components. Hydrodynamic dispersion of salinity and temperature, and the thermal conductivity greatly affected pore water signals. Spectral analyses revealed a faster dissipation of the semi-diurnal component with respect to the diurnal components. Correlation functions showed that salinity had a relatively short memory of the tidal signal when inland freshwater recharge was large. In contrast, the signature of the tidal signal on pore-water temperature persisted for longer times, up to a week. We also found that heterogeneity greatly affected beach response. The response varied from a simple linear mapping in the frequency domain to complete modulation and masking of the input frequencies.

Fiber-distributed Ultra-wideband noise radar with steerable power spectrum and colorless base station.

PubMed

Zheng, Jianyu; Wang, Hui; Fu, Jianbin; Wei, Li; Pan, Shilong; Wang, Lixian; Liu, Jianguo; Zhu, Ninghua

2014-03-10

A fiber-distributed Ultra-wideband (UWB) noise radar was achieved, which consists of a chaotic UWB noise source based on optoelectronic oscillator (OEO), a fiber-distributed transmission link, a colorless base station (BS), and a cross-correlation processing module. Due to a polarization modulation based microwave photonic filter and an electrical UWB pass-band filter embedded in the feedback loop of the OEO, the power spectrum of chaotic UWB signal could be shaped and notch-filtered to avoid the spectrum-overlay-induced interference to the narrow band signals. Meanwhile, the wavelength-reusing could be implemented in the BS by means of the distributed polarization modulation-to-intensity modulation conversion. The experimental comparison for range finding was carried out as the chaotic UWB signal was notch-filtered at 5.2 GHz and 7.8 GHz or not. Measured results indicate that space resolution with cm-level could be realized after 3-km fiber transmission thanks to the excellent self-correlation property of the UWB noise signal provided by the OEO. The performance deterioration of the radar raised by the energy loss of the notch-filtered noise signal was negligible.

Quantitative prediction of perceptual decisions during near-threshold fear detection

NASA Astrophysics Data System (ADS)

Pessoa, Luiz; Padmala, Srikanth

2005-04-01

A fundamental goal of cognitive neuroscience is to explain how mental decisions originate from basic neural mechanisms. The goal of the present study was to investigate the neural correlates of perceptual decisions in the context of emotional perception. To probe this question, we investigated how fluctuations in functional MRI (fMRI) signals were correlated with behavioral choice during a near-threshold fear detection task. fMRI signals predicted behavioral choice independently of stimulus properties and task accuracy in a network of brain regions linked to emotional processing: posterior cingulate cortex, medial prefrontal cortex, right inferior frontal gyrus, and left insula. We quantified the link between fMRI signals and behavioral choice in a whole-brain analysis by determining choice probabilities by means of signal-detection theory methods. Our results demonstrate that voxel-wise fMRI signals can reliably predict behavioral choice in a quantitative fashion (choice probabilities ranged from 0.63 to 0.78) at levels comparable to neuronal data. We suggest that the conscious decision that a fearful face has been seen is represented across a network of interconnected brain regions that prepare the organism to appropriately handle emotionally challenging stimuli and that regulate the associated emotional response. decision making | emotion | functional MRI

Discrimination between spin-dependent charge transport and spin-dependent recombination in π-conjugated polymers by correlated current and electroluminescence-detected magnetic resonance

NASA Astrophysics Data System (ADS)

Kavand, Marzieh; Baird, Douglas; van Schooten, Kipp; Malissa, Hans; Lupton, John M.; Boehme, Christoph

2016-08-01

Spin-dependent processes play a crucial role in organic electronic devices. Spin coherence can give rise to spin mixing due to a number of processes such as hyperfine coupling, and leads to a range of magnetic field effects. However, it is not straightforward to differentiate between pure single-carrier spin-dependent transport processes which control the current and therefore the electroluminescence, and spin-dependent electron-hole recombination which determines the electroluminescence yield and in turn modulates the current. We therefore investigate the correlation between the dynamics of spin-dependent electric current and spin-dependent electroluminescence in two derivatives of the conjugated polymer poly(phenylene-vinylene) using simultaneously measured pulsed electrically detected (pEDMR) and optically detected (pODMR) magnetic resonance spectroscopy. This experimental approach requires careful analysis of the transient response functions under optical and electrical detection. At room temperature and under bipolar charge-carrier injection conditions, a correlation of the pEDMR and the pODMR signals is observed, consistent with the hypothesis that the recombination currents involve spin-dependent electronic transitions. This observation is inconsistent with the hypothesis that these signals are caused by spin-dependent charge-carrier transport. These results therefore provide no evidence that supports earlier claims that spin-dependent transport plays a role for room-temperature magnetoresistance effects. At low temperatures, however, the correlation between pEDMR and pODMR is weakened, demonstrating that more than one spin-dependent process influences the optoelectronic materials' properties. This conclusion is consistent with prior studies of half-field resonances that were attributed to spin-dependent triplet exciton recombination, which becomes significant at low temperatures when the triplet lifetime increases.

Improving Global Mass Flux Solutions from Gravity Recovery and Climate Experiment (GRACE) Through Forward Modeling and Continuous Time Correlation

NASA Technical Reports Server (NTRS)

Sabaka, T. J.; Rowlands, D. D.; Luthcke, S. B.; Boy, J.-P.

2010-01-01

We describe Earth's mass flux from April 2003 through November 2008 by deriving a time series of mas cons on a global 2deg x 2deg equal-area grid at 10 day intervals. We estimate the mass flux directly from K band range rate (KBRR) data provided by the Gravity Recovery and Climate Experiment (GRACE) mission. Using regularized least squares, we take into account the underlying process dynamics through continuous space and time-correlated constraints. In addition, we place the mascon approach in the context of other filtering techniques, showing its equivalence to anisotropic, nonsymmetric filtering, least squares collocation, and Kalman smoothing. We produce mascon time series from KBRR data that have and have not been corrected (forward modeled) for hydrological processes and fmd that the former produce superior results in oceanic areas by minimizing signal leakage from strong sources on land. By exploiting the structure of the spatiotemporal constraints, we are able to use a much more efficient (in storage and computation) inversion algorithm based upon the conjugate gradient method. This allows us to apply continuous rather than piecewise continuous time-correlated constraints, which we show via global maps and comparisons with ocean-bottom pressure gauges, to produce time series with reduced random variance and full systematic signal. Finally, we present a preferred global model, a hybrid whose oceanic portions are derived using forward modeling of hydrology but whose land portions are not, and thus represent a pure GRACE-derived signal.

Research on signal demodulation technology of Mach-Zehnder optical fiber sensor vibration system

NASA Astrophysics Data System (ADS)

Liu, Juncheng; Cheng, Pengshen; Hu, Tong

2017-08-01

Mach-Zehnder (M-Z) interferometer is frequently used in optical fiber vibration system. And signal demodulation technology plays an important role in the signal processing of M-Z optical fiber vibration system. In order to accurately get the phase information of the vibration signals, the signal demodulation technique based on M-Z interference principle is studied. In this paper, by analyzing the principles of 3 × 3 fiber coupler homodyne demodulation method and phase-generating carrier (PGC) technology, the advantages and disadvantages of the two demodulation methods for different vibration signal are presented. Then the method of judging signal strength is proposed. The correlation between the demodulation effects and strength of the perturbation signals is analyzed. Finally, the simulation experiments are carried out to compare the demodulation effects of the two demodulation methods, the results demonstrate that PGC demodulation technology has great advantages in weak signals, and the 3 × 3 fiber coupler is more suitable for strong signals.

Investigating the neural bases for intra-subject cognitive efficiency changes using functional magnetic resonance imaging

PubMed Central

Rao, Neena K.; Motes, Michael A.; Rypma, Bart

2014-01-01

Several fMRI studies have examined brain regions mediating inter-subject variability in cognitive efficiency, but none have examined regions mediating intra-subject variability in efficiency. Thus, the present study was designed to identify brain regions involved in intra-subject variability in cognitive efficiency via participant-level correlations between trial-level reaction time (RT) and trial-level fMRI BOLD percent signal change on a processing speed task. On each trial, participants indicated whether a digit-symbol probe-pair was present or absent in an array of nine digit-symbol probe-pairs while fMRI data were collected. Deconvolution analyses, using RT time-series models (derived from the proportional scaling of an event-related hemodynamic response function model by trial-level RT), were used to evaluate relationships between trial-level RTs and BOLD percent signal change. Although task-related patterns of activation and deactivation were observed in regions including bilateral occipital, bilateral parietal, portions of the medial wall such as the precuneus, default mode network regions including anterior cingulate, posterior cingulate, bilateral temporal, right cerebellum, and right cuneus, RT-BOLD correlations were observed in a more circumscribed set of regions. Positive RT-BOLD correlations, where fast RTs were associated with lower BOLD percent signal change, were observed in regions including bilateral occipital, bilateral parietal, and the precuneus. RT-BOLD correlations were not observed in the default mode network indicating a smaller set of regions associated with intra-subject variability in cognitive efficiency. The results are discussed in terms of a distributed area of regions that mediate variability in the cognitive efficiency that might underlie processing speed differences between individuals. PMID:25374527

Investigating the neural bases for intra-subject cognitive efficiency changes using functional magnetic resonance imaging.

PubMed

Rao, Neena K; Motes, Michael A; Rypma, Bart

2014-01-01

Several fMRI studies have examined brain regions mediating inter-subject variability in cognitive efficiency, but none have examined regions mediating intra-subject variability in efficiency. Thus, the present study was designed to identify brain regions involved in intra-subject variability in cognitive efficiency via participant-level correlations between trial-level reaction time (RT) and trial-level fMRI BOLD percent signal change on a processing speed task. On each trial, participants indicated whether a digit-symbol probe-pair was present or absent in an array of nine digit-symbol probe-pairs while fMRI data were collected. Deconvolution analyses, using RT time-series models (derived from the proportional scaling of an event-related hemodynamic response function model by trial-level RT), were used to evaluate relationships between trial-level RTs and BOLD percent signal change. Although task-related patterns of activation and deactivation were observed in regions including bilateral occipital, bilateral parietal, portions of the medial wall such as the precuneus, default mode network regions including anterior cingulate, posterior cingulate, bilateral temporal, right cerebellum, and right cuneus, RT-BOLD correlations were observed in a more circumscribed set of regions. Positive RT-BOLD correlations, where fast RTs were associated with lower BOLD percent signal change, were observed in regions including bilateral occipital, bilateral parietal, and the precuneus. RT-BOLD correlations were not observed in the default mode network indicating a smaller set of regions associated with intra-subject variability in cognitive efficiency. The results are discussed in terms of a distributed area of regions that mediate variability in the cognitive efficiency that might underlie processing speed differences between individuals.

Neural Correlates of Temporal Complexity and Synchrony during Audiovisual Correspondence Detection.

PubMed

Baumann, Oliver; Vromen, Joyce M G; Cheung, Allen; McFadyen, Jessica; Ren, Yudan; Guo, Christine C

2018-01-01

We often perceive real-life objects as multisensory cues through space and time. A key challenge for audiovisual integration is to match neural signals that not only originate from different sensory modalities but also that typically reach the observer at slightly different times. In humans, complex, unpredictable audiovisual streams lead to higher levels of perceptual coherence than predictable, rhythmic streams. In addition, perceptual coherence for complex signals seems less affected by increased asynchrony between visual and auditory modalities than for simple signals. Here, we used functional magnetic resonance imaging to determine the human neural correlates of audiovisual signals with different levels of temporal complexity and synchrony. Our study demonstrated that greater perceptual asynchrony and lower signal complexity impaired performance in an audiovisual coherence-matching task. Differences in asynchrony and complexity were also underpinned by a partially different set of brain regions. In particular, our results suggest that, while regions in the dorsolateral prefrontal cortex (DLPFC) were modulated by differences in memory load due to stimulus asynchrony, areas traditionally thought to be involved in speech production and recognition, such as the inferior frontal and superior temporal cortex, were modulated by the temporal complexity of the audiovisual signals. Our results, therefore, indicate specific processing roles for different subregions of the fronto-temporal cortex during audiovisual coherence detection.

Neural Correlates of Temporal Complexity and Synchrony during Audiovisual Correspondence Detection

PubMed Central

Ren, Yudan

2018-01-01

Abstract We often perceive real-life objects as multisensory cues through space and time. A key challenge for audiovisual integration is to match neural signals that not only originate from different sensory modalities but also that typically reach the observer at slightly different times. In humans, complex, unpredictable audiovisual streams lead to higher levels of perceptual coherence than predictable, rhythmic streams. In addition, perceptual coherence for complex signals seems less affected by increased asynchrony between visual and auditory modalities than for simple signals. Here, we used functional magnetic resonance imaging to determine the human neural correlates of audiovisual signals with different levels of temporal complexity and synchrony. Our study demonstrated that greater perceptual asynchrony and lower signal complexity impaired performance in an audiovisual coherence-matching task. Differences in asynchrony and complexity were also underpinned by a partially different set of brain regions. In particular, our results suggest that, while regions in the dorsolateral prefrontal cortex (DLPFC) were modulated by differences in memory load due to stimulus asynchrony, areas traditionally thought to be involved in speech production and recognition, such as the inferior frontal and superior temporal cortex, were modulated by the temporal complexity of the audiovisual signals. Our results, therefore, indicate specific processing roles for different subregions of the fronto-temporal cortex during audiovisual coherence detection. PMID:29354682

The Combined Effect of Periodic Signals and Noise on the Dilution of Precision of GNSS Station Velocity Uncertainties

NASA Astrophysics Data System (ADS)

Klos, Anna; Olivares, German; Teferle, Felix Norman; Bogusz, Janusz

2016-04-01

Station velocity uncertainties determined from a series of Global Navigation Satellite System (GNSS) position estimates depend on both the deterministic and stochastic models applied to the time series. While the deterministic model generally includes parameters for a linear and several periodic terms the stochastic model is a representation of the noise character of the time series in form of a power-law process. For both of these models the optimal model may vary from one time series to another while the models also depend, to some degree, on each other. In the past various power-law processes have been shown to fit the time series and the sources for the apparent temporally-correlated noise were attributed to, for example, mismodelling of satellites orbits, antenna phase centre variations, troposphere, Earth Orientation Parameters, mass loading effects and monument instabilities. Blewitt and Lavallée (2002) demonstrated how improperly modelled seasonal signals affected the estimates of station velocity uncertainties. However, in their study they assumed that the time series followed a white noise process with no consideration of additional temporally-correlated noise. Bos et al. (2010) empirically showed for a small number of stations that the noise character was much more important for the reliable estimation of station velocity uncertainties than the seasonal signals. In this presentation we pick up from Blewitt and Lavallée (2002) and Bos et al. (2010), and have derived formulas for the computation of the General Dilution of Precision (GDP) under presence of periodic signals and temporally-correlated noise in the time series. We show, based on simulated and real time series from globally distributed IGS (International GNSS Service) stations processed by the Jet Propulsion Laboratory (JPL), that periodic signals dominate the effect on the velocity uncertainties at short time scales while for those beyond four years, the type of noise becomes much more important. In other words, for time series long enough, the assumed periodic signals do not affect the velocity uncertainties as much as the assumed noise model. We calculated the GDP to be the ratio between two errors of velocity: without and with inclusion of seasonal terms of periods equal to one year and its overtones till 3rd. To all these cases power-law processes of white, flicker and random-walk noise were added separately. Few oscillations in GDP can be noticed for integer years, which arise from periodic terms added. Their amplitudes in GDP increase along with the increasing spectral index. Strong peaks of oscillations in GDP are indicated for short time scales, especially for random-walk processes. This means that badly monumented stations are affected the most. Local minima and maxima in GDP are also enlarged as the noise approaches random walk. We noticed that the semi-annual signal increased the local GDP minimum for white noise. This suggests that adding power-law noise to a deterministic model with annual term or adding a semi-annual term to white noise causes an increased velocity uncertainty even at the points, where determined velocity is not biased.

Digital Photon Correlation Data Processing Techniques

DTIC Science & Technology

1976-07-01

velocimeter signals. During the conduct of the contract a complementary theoretical effort with the NASA Langley Research Center was in progress ( NASI -13140...6.3.2 Variability Error In an earlier very brief contract with NASA Langley ( NASI -13140) a simplified variability error analysis was performed

The Essence of Nonclassicality: Non-Vanishing Signal Deficit

NASA Astrophysics Data System (ADS)

Aravinda, S.; Srikanth, R.

2015-12-01

Nonclassical properties of correlations- like unpredictability, no-cloning and uncertainty- are known to follow from two assumptions: nonlocality and no-signaling. For two-input-two-output correlations, we derive these properties from a single, unified assumption: namely, the excess of the communication cost over the signaling in the correlation. This is relevant to quantum temporal correlations, resources to simulate quantum correlations and extensions of quantum mechanics. We generalize in the context of such correlations the nonclassicality result for nonlocal-nonsignaling correlations (Masanes et al., Phys. Rev. A 73, 012112 (2006)) and the uncertainty bound on nonlocality (Oppenheim and Wehner, Science 330(6007), 1072 (2010)), when the no-signaling condition is relaxed.

Two-level image authentication by two-step phase-shifting interferometry and compressive sensing

NASA Astrophysics Data System (ADS)

Zhang, Xue; Meng, Xiangfeng; Yin, Yongkai; Yang, Xiulun; Wang, Yurong; Li, Xianye; Peng, Xiang; He, Wenqi; Dong, Guoyan; Chen, Hongyi

2018-01-01

A two-level image authentication method is proposed; the method is based on two-step phase-shifting interferometry, double random phase encoding, and compressive sensing (CS) theory, by which the certification image can be encoded into two interferograms. Through discrete wavelet transform (DWT), sparseness processing, Arnold transform, and data compression, two compressed signals can be generated and delivered to two different participants of the authentication system. Only the participant who possesses the first compressed signal attempts to pass the low-level authentication. The application of Orthogonal Match Pursuit CS algorithm reconstruction, inverse Arnold transform, inverse DWT, two-step phase-shifting wavefront reconstruction, and inverse Fresnel transform can result in the output of a remarkable peak in the central location of the nonlinear correlation coefficient distributions of the recovered image and the standard certification image. Then, the other participant, who possesses the second compressed signal, is authorized to carry out the high-level authentication. Therefore, both compressed signals are collected to reconstruct the original meaningful certification image with a high correlation coefficient. Theoretical analysis and numerical simulations verify the feasibility of the proposed method.

Exploitation of RF-DNA for Device Classification and Verification Using GRLVQI Processing

DTIC Science & Technology

2012-12-01

5 FLD Fisher’s Linear Discriminant . . . . . . . . . . . . . . . . . . . 6 kNN K-Nearest Neighbor...Neighbor ( kNN ), Support Vector Machine (SVM), and simple cross-correlation techniques [40, 57, 82, 88, 94, 95]. The RF-DNA fingerprinting research in...Expansion and the Dis- crete Gabor Transform on a Non-Separable Lattice”. 2000 IEEE Int’l Conf on Acoustics, Speech , and Signal Processing (ICASSP00

ICA-Derived EEG Correlates to Mental Fatigue, Effort, and Workload in a Realistically Simulated Air Traffic Control Task.

PubMed

Dasari, Deepika; Shou, Guofa; Ding, Lei

2017-01-01

Electroencephalograph (EEG) has been increasingly studied to identify distinct mental factors when persons perform cognitively demanding tasks. However, most of these studies examined EEG correlates at channel domain, which suffers the limitation that EEG signals are the mixture of multiple underlying neuronal sources due to the volume conduction effect. Moreover, few studies have been conducted in real-world tasks. To precisely probe EEG correlates with specific neural substrates to mental factors in real-world tasks, the present study examined EEG correlates to three mental factors, i.e., mental fatigue [also known as time-on-task (TOT) effect], workload and effort, in EEG component signals, which were obtained using an independent component analysis (ICA) on high-density EEG data. EEG data were recorded when subjects performed a realistically simulated air traffic control (ATC) task for 2 h. Five EEG independent component (IC) signals that were associated with specific neural substrates (i.e., the frontal, central medial, motor, parietal, occipital areas) were identified. Their spectral powers at their corresponding dominant bands, i.e., the theta power of the frontal IC and the alpha power of the other four ICs, were detected to be correlated to mental workload and effort levels, measured by behavioral metrics. Meanwhile, a linear regression analysis indicated that spectral powers at five ICs significantly increased with TOT. These findings indicated that different levels of mental factors can be sensitively reflected in EEG signals associated with various brain functions, including visual perception, cognitive processing, and motor outputs, in real-world tasks. These results can potentially aid in the development of efficient operational interfaces to ensure productivity and safety in ATC and beyond.

Prefrontal activity during working memory is modulated by the interaction of variation in CB1 and COX2 coding genes and correlates with frequency of cannabis use.

PubMed

Taurisano, Paolo; Antonucci, Linda A; Fazio, Leonardo; Rampino, Antonio; Romano, Raffaella; Porcelli, Annamaria; Masellis, Rita; Colizzi, Marco; Quarto, Tiziana; Torretta, Silvia; Di Giorgio, Annabella; Pergola, Giulio; Bertolino, Alessandro; Blasi, Giuseppe

2016-08-01

The CB1 cannabinoid receptor is targeted in the brain by endocannabinoids under physiological conditions as well as by delta9-tetrahydrocannabinol under cannabis use. Furthermore, its signaling appears to affect brain cognitive processing. Recent findings highlight a crucial role of cyclooxygenase-2 (COX-2) in the mechanism of intraneuronal CB1 signaling transduction, while others indicate that two single nucleotide polymorphisms (SNPs) (rs1406977 and rs20417) modulate expression of CB1 (CNR1) and COX-2 (PTGS2) coding genes, respectively. Here, our aim was to use fMRI to investigate in healthy humans whether these SNPs interact in modulating prefrontal activity during working memory processing and if this modulation is linked with cannabis use. We recruited 242 healthy subjects genotyped for CNR1 rs1406977 and PTGS2 rs20417 that performed the N-back working memory task during fMRI and were interviewed using the Cannabis Experience Questionnaire (CEQ). We found that the interaction between CNR1 rs1406977 and PTGS2 rs20417 is associated with dorsolateral prefrontal cortex (DLPFC) activity such that specific genotype configurations (CNR1 C carriers/PTGS2 C carriers and CNR1 TT/PTGS2 GG) predict lower cortical response versus others in spite of similar behavioral accuracy. Furthermore, DLPFC activity in the cluster associated with the CNR1 by PTGS2 interaction was negatively correlated with behavioral efficiency and positively correlated with frequency of cannabis use in cannabis users. These results suggest that a genetically modulated balancing of signaling within the CB1-COX-2 pathway may reflect on more or less efficient patterns of prefrontal activity during working memory. Frequency of cannabis use may be a factor for further modulation of CNR1/PTGS2-mediated cortical processing associated with this cognitive process. Copyright © 2016 Elsevier Ltd. All rights reserved.

Acoustic interference and recognition space within a complex assemblage of dendrobatid frogs

PubMed Central

Amézquita, Adolfo; Flechas, Sandra Victoria; Lima, Albertina Pimentel; Gasser, Herbert; Hödl, Walter

2011-01-01

In species-rich assemblages of acoustically communicating animals, heterospecific sounds may constrain not only the evolution of signal traits but also the much less-studied signal-processing mechanisms that define the recognition space of a signal. To test the hypothesis that the recognition space is optimally designed, i.e., that it is narrower toward the species that represent the higher potential for acoustic interference, we studied an acoustic assemblage of 10 diurnally active frog species. We characterized their calls, estimated pairwise correlations in calling activity, and, to model the recognition spaces of five species, conducted playback experiments with 577 synthetic signals on 531 males. Acoustic co-occurrence was not related to multivariate distance in call parameters, suggesting a minor role for spectral or temporal segregation among species uttering similar calls. In most cases, the recognition space overlapped but was greater than the signal space, indicating that signal-processing traits do not act as strictly matched filters against sounds other than homospecific calls. Indeed, the range of the recognition space was strongly predicted by the acoustic distance to neighboring species in the signal space. Thus, our data provide compelling evidence of a role of heterospecific calls in evolutionarily shaping the frogs' recognition space within a complex acoustic assemblage without obvious concomitant effects on the signal. PMID:21969562

Signal processing and analysis for copper layer thickness measurement within a large variation range in the CMP process.

PubMed

Li, Hongkai; Zhao, Qian; Lu, Xinchun; Luo, Jianbin

2017-11-01

In the copper (Cu) chemical mechanical planarization (CMP) process, accurate determination of a process reaching the end point is of great importance. Based on the eddy current technology, the in situ thickness measurement of the Cu layer is feasible. Previous research studies focus on the application of the eddy current method to the metal layer thickness measurement or endpoint detection. In this paper, an in situ measurement system, which is independently developed by using the eddy current method, is applied to the actual Cu CMP process. A series of experiments are done for further analyzing the dynamic response characteristic of the output signal within different thickness variation ranges. In this study, the voltage difference of the output signal is used to represent the thickness of the Cu layer, and we can extract the voltage difference variations from the output signal fast by using the proposed data processing algorithm. The results show that the voltage difference decreases as thickness decreases in the conventional measurement range and the sensitivity increases at the same time. However, it is also found that there exists a thickness threshold, and the correlation is negative, when the thickness is more than the threshold. Furthermore, it is possible that the in situ measurement system can be used within a larger Cu layer thickness variation range by creating two calibration tables.

Modeling of low-finesse, extrinsic fiber optic Fabry-Perot white light interferometers

NASA Astrophysics Data System (ADS)

Ma, Cheng; Tian, Zhipeng; Wang, Anbo

2012-06-01

This article introduces an approach for modeling the fiber optic low-finesse extrinsic Fabry-Pérot Interferometers (EFPI), aiming to address signal processing problems in EFPI demodulation algorithms based on white light interferometry. The main goal is to seek physical interpretations to correlate the sensor spectrum with the interferometer geometry (most importantly, the optical path difference). Because the signal demodulation quality and reliability hinge heavily on the understanding of such relationships, the model sheds light on optimizing the sensor performance.

Binary/Analog CCD Correlator Development.

DTIC Science & Technology

1981-07-01

architecture , design and performance of a general purpose, 1,024-stage, programmable transversal filter implemented in CCD/NMOS technology is described. The device features programmability of the reference signal, the filter length and weighting coefficient resolution. Off-ship circuitry is minimized by incorporating both analog and digital support circuitry, on-chip. This results in a monolithic analog signal processing system that has the flexibility to be operated in nine programmable configurations, from 1,024-stages by 1-bit, to 128-stages by 8-bits. The versatility

Correlated components of ongoing EEG point to emotionally laden attention - a possible marker of engagement?

PubMed

Dmochowski, Jacek P; Sajda, Paul; Dias, Joao; Parra, Lucas C

2012-01-01

Recent evidence from functional magnetic resonance imaging suggests that cortical hemodynamic responses coincide in different subjects experiencing a common naturalistic stimulus. Here we utilize neural responses in the electroencephalogram (EEG) evoked by multiple presentations of short film clips to index brain states marked by high levels of correlation within and across subjects. We formulate a novel signal decomposition method which extracts maximally correlated signal components from multiple EEG records. The resulting components capture correlations down to a one-second time resolution, thus revealing that peak correlations of neural activity across viewings can occur in remarkable correspondence with arousing moments of the film. Moreover, a significant reduction in neural correlation occurs upon a second viewing of the film or when the narrative is disrupted by presenting its scenes scrambled in time. We also probe oscillatory brain activity during periods of heightened correlation, and observe during such times a significant increase in the theta band for a frontal component and reductions in the alpha and beta frequency bands for parietal and occipital components. Low-resolution EEG tomography of these components suggests that the correlated neural activity is consistent with sources in the cingulate and orbitofrontal cortices. Put together, these results suggest that the observed synchrony reflects attention- and emotion-modulated cortical processing which may be decoded with high temporal resolution by extracting maximally correlated components of neural activity.

Correlated Components of Ongoing EEG Point to Emotionally Laden Attention – A Possible Marker of Engagement?

PubMed Central

Dmochowski, Jacek P.; Sajda, Paul; Dias, Joao; Parra, Lucas C.

2012-01-01

Recent evidence from functional magnetic resonance imaging suggests that cortical hemodynamic responses coincide in different subjects experiencing a common naturalistic stimulus. Here we utilize neural responses in the electroencephalogram (EEG) evoked by multiple presentations of short film clips to index brain states marked by high levels of correlation within and across subjects. We formulate a novel signal decomposition method which extracts maximally correlated signal components from multiple EEG records. The resulting components capture correlations down to a one-second time resolution, thus revealing that peak correlations of neural activity across viewings can occur in remarkable correspondence with arousing moments of the film. Moreover, a significant reduction in neural correlation occurs upon a second viewing of the film or when the narrative is disrupted by presenting its scenes scrambled in time. We also probe oscillatory brain activity during periods of heightened correlation, and observe during such times a significant increase in the theta band for a frontal component and reductions in the alpha and beta frequency bands for parietal and occipital components. Low-resolution EEG tomography of these components suggests that the correlated neural activity is consistent with sources in the cingulate and orbitofrontal cortices. Put together, these results suggest that the observed synchrony reflects attention- and emotion-modulated cortical processing which may be decoded with high temporal resolution by extracting maximally correlated components of neural activity. PMID:22623915

Image correlation method for DNA sequence alignment.

PubMed

Curilem Saldías, Millaray; Villarroel Sassarini, Felipe; Muñoz Poblete, Carlos; Vargas Vásquez, Asticio; Maureira Butler, Iván

2012-01-01

The complexity of searches and the volume of genomic data make sequence alignment one of bioinformatics most active research areas. New alignment approaches have incorporated digital signal processing techniques. Among these, correlation methods are highly sensitive. This paper proposes a novel sequence alignment method based on 2-dimensional images, where each nucleic acid base is represented as a fixed gray intensity pixel. Query and known database sequences are coded to their pixel representation and sequence alignment is handled as object recognition in a scene problem. Query and database become object and scene, respectively. An image correlation process is carried out in order to search for the best match between them. Given that this procedure can be implemented in an optical correlator, the correlation could eventually be accomplished at light speed. This paper shows an initial research stage where results were "digitally" obtained by simulating an optical correlation of DNA sequences represented as images. A total of 303 queries (variable lengths from 50 to 4500 base pairs) and 100 scenes represented by 100 x 100 images each (in total, one million base pair database) were considered for the image correlation analysis. The results showed that correlations reached very high sensitivity (99.01%), specificity (98.99%) and outperformed BLAST when mutation numbers increased. However, digital correlation processes were hundred times slower than BLAST. We are currently starting an initiative to evaluate the correlation speed process of a real experimental optical correlator. By doing this, we expect to fully exploit optical correlation light properties. As the optical correlator works jointly with the computer, digital algorithms should also be optimized. The results presented in this paper are encouraging and support the study of image correlation methods on sequence alignment.

Pre-Processing and Cross-Correlation Techniques for Time-Distance Helioseismology

NASA Astrophysics Data System (ADS)

Wang, N.; de Ridder, S.; Zhao, J.

2014-12-01

In chaotic wave fields excited by a random distribution of noise sources a cross-correlation of the recordings made at two stations yield the interstation wave-field response. After early successes in helioseismology, laboratory studies and earth-seismology, this technique found broad application in global and regional seismology. This development came with an increasing understanding of pre-processing and cross-correlation workflows to yield an optimal signal-to-noise ratio (SNR). Helioseismologist rely heavily on stacking to increase the SNR. Until now, they have not studied different spectral-whitening and cross-correlation workflows and relies heavily on stacking to increase the SNR. The recordings vary considerably between sunspots and regular portions of the sun. Within the sunspot the periodic effects of the observation satellite orbit are difficult to remove. We remove a running alpha-mean from the data and apply a soft clip to deal with data glitches. The recordings contain energy of both flow and waves. A frequency domain filter selects the wave energy. Then the data is input to several pre-processing and cross-correlation techniques, common to earth seismology. We anticipate that spectral whitening will flatten the energy spectrum of the cross-correlations. We also expect that the cross-correlations converge faster to their expected value when the data is processed over overlapping windows. The result of this study are expected to aid in decreasing the stacking while maintaining good SNR.

A motion-tolerant approach for monitoring SpO2 and heart rate using photoplethysmography signal with dual frame length processing and multi-classifier fusion.

PubMed

Fan, Feiyi; Yan, Yuepeng; Tang, Yongzhong; Zhang, Hao

2017-12-01

Monitoring pulse oxygen saturation (SpO 2 ) and heart rate (HR) using photoplethysmography (PPG) signal contaminated by a motion artifact (MA) remains a difficult problem, especially when the oximeter is not equipped with a 3-axis accelerometer for adaptive noise cancellation. In this paper, we report a pioneering investigation on the impact of altering the frame length of Molgedey and Schuster independent component analysis (ICAMS) on performance, design a multi-classifier fusion strategy for selecting the PPG correlated signal component, and propose a novel approach to extract SpO 2 and HR readings from PPG signal contaminated by strong MA interference. The algorithm comprises multiple stages, including dual frame length ICAMS, a multi-classifier-based PPG correlated component selector, line spectral analysis, tree-based HR monitoring, and post-processing. Our approach is evaluated by multi-subject tests. The root mean square error (RMSE) is calculated for each trial. Three statistical metrics are selected as performance evaluation criteria: mean RMSE, median RMSE and the standard deviation (SD) of RMSE. The experimental results demonstrate that a shorter ICAMS analysis window probably results in better performance in SpO 2 estimation. Notably, the designed multi-classifier signal component selector achieved satisfactory performance. The subject tests indicate that our algorithm outperforms other baseline methods regarding accuracy under most criteria. The proposed work can contribute to improving the performance of current pulse oximetry and personal wearable monitoring devices. Copyright © 2017 Elsevier Ltd. All rights reserved.

Trial-Level Regressor Modulation for Functional Magnetic Resonance Imaging Designs Requiring Strict Periodicity of Stimulus Presentations: Illustrated Using a Go/No-Go Task

PubMed Central

Motes, Michael A; Rao, Neena K; Shokri-Kojori, Ehsan; Chiang, Hsueh-Sheng; Kraut, Michael A; Hart, John

2017-01-01

Computer-based assessment of many cognitive processes (eg, anticipatory and response readiness processes) requires the use of invariant stimulus display times (SDT) and intertrial intervals (ITI). Although designs with invariant SDTs and ITIs have been used in functional magnetic resonance imaging (fMRI) research, such designs are problematic for fMRI studies because of collinearity issues. This study examined regressor modulation with trial-level reaction times (RT) as a method for improving signal detection in a go/no-go task with invariant SDTs and ITIs. The effects of modulating the go regressor were evaluated with respect to the detection of BOLD signal-change for the no-go condition. BOLD signal-change to no-go stimuli was examined when the go regressor was based on a (a) canonical hemodynamic response function (HRF), (b) RT-based amplitude-modulated (AM) HRF, and (c) RT-based amplitude and duration modulated (A&DM) HRF. Reaction time–based modulation reduced the collinearity between the go and no-go regressors, with A&DM producing the greatest reductions in correlations between the regressors, and greater reductions in the correlations between regressors were associated with longer mean RTs and greater RT variability. Reaction time–based modulation increased statistical power for detecting group-level no-go BOLD signal-change across a broad set of brain regions. The findings show the efficacy of using regressor modulation to increase power in detecting BOLD signal-change in fMRI studies in which circumstances dictate the use of temporally invariant stimulus presentations. PMID:29276390

Trial-Level Regressor Modulation for Functional Magnetic Resonance Imaging Designs Requiring Strict Periodicity of Stimulus Presentations: Illustrated Using a Go/No-Go Task.

PubMed

Motes, Michael A; Rao, Neena K; Shokri-Kojori, Ehsan; Chiang, Hsueh-Sheng; Kraut, Michael A; Hart, John

2017-01-01

Computer-based assessment of many cognitive processes (eg, anticipatory and response readiness processes) requires the use of invariant stimulus display times (SDT) and intertrial intervals (ITI). Although designs with invariant SDTs and ITIs have been used in functional magnetic resonance imaging (fMRI) research, such designs are problematic for fMRI studies because of collinearity issues. This study examined regressor modulation with trial-level reaction times (RT) as a method for improving signal detection in a go / no-go task with invariant SDTs and ITIs. The effects of modulating the go regressor were evaluated with respect to the detection of BOLD signal-change for the no-go condition. BOLD signal-change to no-go stimuli was examined when the go regressor was based on a (a) canonical hemodynamic response function (HRF), (b) RT-based amplitude-modulated (AM) HRF, and (c) RT-based amplitude and duration modulated (A&DM) HRF. Reaction time-based modulation reduced the collinearity between the go and no-go regressors, with A&DM producing the greatest reductions in correlations between the regressors, and greater reductions in the correlations between regressors were associated with longer mean RTs and greater RT variability. Reaction time-based modulation increased statistical power for detecting group-level no-go BOLD signal-change across a broad set of brain regions. The findings show the efficacy of using regressor modulation to increase power in detecting BOLD signal-change in fMRI studies in which circumstances dictate the use of temporally invariant stimulus presentations.

A simple iterative independent component analysis algorithm for vibration source signal identification of complex structures

NASA Astrophysics Data System (ADS)

Lee, Dong-Sup; Cho, Dae-Seung; Kim, Kookhyun; Jeon, Jae-Jin; Jung, Woo-Jin; Kang, Myeng-Hwan; Kim, Jae-Ho

2015-01-01

Independent Component Analysis (ICA), one of the blind source separation methods, can be applied for extracting unknown source signals only from received signals. This is accomplished by finding statistical independence of signal mixtures and has been successfully applied to myriad fields such as medical science, image processing, and numerous others. Nevertheless, there are inherent problems that have been reported when using this technique: instability and invalid ordering of separated signals, particularly when using a conventional ICA technique in vibratory source signal identification of complex structures. In this study, a simple iterative algorithm of the conventional ICA has been proposed to mitigate these problems. The proposed method to extract more stable source signals having valid order includes an iterative and reordering process of extracted mixing matrix to reconstruct finally converged source signals, referring to the magnitudes of correlation coefficients between the intermediately separated signals and the signals measured on or nearby sources. In order to review the problems of the conventional ICA technique and to validate the proposed method, numerical analyses have been carried out for a virtual response model and a 30 m class submarine model. Moreover, in order to investigate applicability of the proposed method to real problem of complex structure, an experiment has been carried out for a scaled submarine mockup. The results show that the proposed method could resolve the inherent problems of a conventional ICA technique.

Identifying and quantifying main components of physiological noise in functional near infrared spectroscopy on the prefrontal cortex.

PubMed

Kirilina, Evgeniya; Yu, Na; Jelzow, Alexander; Wabnitz, Heidrun; Jacobs, Arthur M; Tachtsidis, Ilias

2013-01-01

Functional Near-Infrared Spectroscopy (fNIRS) is a promising method to study functional organization of the prefrontal cortex. However, in order to realize the high potential of fNIRS, effective discrimination between physiological noise originating from forehead skin haemodynamic and cerebral signals is required. Main sources of physiological noise are global and local blood flow regulation processes on multiple time scales. The goal of the present study was to identify the main physiological noise contributions in fNIRS forehead signals and to develop a method for physiological de-noising of fNIRS data. To achieve this goal we combined concurrent time-domain fNIRS and peripheral physiology recordings with wavelet coherence analysis (WCA). Depth selectivity was achieved by analyzing moments of photon time-of-flight distributions provided by time-domain fNIRS. Simultaneously, mean arterial blood pressure (MAP), heart rate (HR), and skin blood flow (SBF) on the forehead were recorded. WCA was employed to quantify the impact of physiological processes on fNIRS signals separately for different time scales. We identified three main processes contributing to physiological noise in fNIRS signals on the forehead. The first process with the period of about 3 s is induced by respiration. The second process is highly correlated with time lagged MAP and HR fluctuations with a period of about 10 s often referred as Mayer waves. The third process is local regulation of the facial SBF time locked to the task-evoked fNIRS signals. All processes affect oxygenated haemoglobin concentration more strongly than that of deoxygenated haemoglobin. Based on these results we developed a set of physiological regressors, which were used for physiological de-noising of fNIRS signals. Our results demonstrate that proposed de-noising method can significantly improve the sensitivity of fNIRS to cerebral signals.

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

PubMed

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

2012-06-20

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.

Improving the signal-to-noise ratio in ultrasound-modulated optical tomography by a lock-in amplifier

NASA Astrophysics Data System (ADS)

Zhu, Lili; Wu, Jingping; Lin, Guimin; Hu, Liangjun; Li, Hui

2016-10-01

With high spatial resolution of ultrasonic location and high sensitivity of optical detection, ultrasound-modulated optical tomography (UOT) is a promising noninvasive biological tissue imaging technology. In biological tissue, the ultrasound-modulated light signals are very weak and are overwhelmed by the strong unmodulated light signals. It is a difficulty and key to efficiently pick out the weak modulated light from strong unmodulated light in UOT. Under the effect of an ultrasonic field, the scattering light intensity presents a periodic variation as the ultrasonic frequency changes. So the modulated light signals would be escape from the high unmodulated light signals, when the modulated light signals and the ultrasonic signal are processed cross correlation operation by a lock-in amplifier and without a chopper. Experimental results indicated that the signal-to-noise ratio of UOT is significantly improved by a lock-in amplifier, and the higher the repetition frequency of pulsed ultrasonic wave, the better the signal-to-noise ratio of UOT.

A novel multireceiver communications system configuration based on optimal estimation theory

NASA Technical Reports Server (NTRS)

Kumar, R.

1990-01-01

A multireceiver configuration for the purpose of carrier arraying and/or signal arraying is presented. Such a problem arises for example, in the NASA Deep Space Network where the same data-modulated signal from a spacecraft is received by a number of geographically separated antennas and the data detection must be efficiently performed on the basis of the various received signals. The proposed configuration is arrived at by formulating the carrier and/or signal arraying problem as an optimal estimation problem. Two specific solutions are proposed. The first solution is to simultaneously and optimally estimate the various phase processes received at different receivers with coupled phase locked loops (PLLs) wherein the individual PLLs acquire and track their respective receivers' phase processes, but are aided by each other in an optimal manner. However, when the phase processes are relatively weakly correlated, and for the case of relatively high values of symbol energy-to-noise spectral density ratio, a novel configuration for combining the data modulated, loop-output signals is proposed. The scheme can be extended to the case of low symbol energy-to-noise case by performing the combining/detection process over a multisymbol period. Such a configuration results in the minimization of the effective radio loss at the combiner output, and thus a maximization of energy per bit to noise-power spectral density ration is achieved.

VLBA Archive &Distribution Architecture

NASA Astrophysics Data System (ADS)

Wells, D. C.

1994-01-01

Signals from the 10 antennas of NRAO's VLBA [Very Long Baseline Array] are processed by a Correlator. The complex fringe visibilities produced by the Correlator are archived on magnetic cartridges using a low-cost architecture which is capable of scaling and evolving. Archive files are copied to magnetic media to be distributed to users in FITS format, using the BINTABLE extension. Archive files are labelled using SQL INSERT statements, in order to bind the DBMS-based archive catalog to the archive media.

Posterior Beta and Anterior Gamma Oscillations Predict Cognitive Insight

ERIC Educational Resources Information Center

Sheth, Bhavin R.; Sandkuhler, Simone; Bhattacharya, Joydeep

2009-01-01

Pioneering neuroimaging studies on insight have revealed neural correlates of the emotional "Aha!" component of the insight process, but neural substrates of the cognitive component, such as problem restructuring (a key to transformative reasoning), remain a mystery. Here, multivariate electroencephalogram signals were recorded from human…

Visual Processing of Object Velocity and Acceleration

DTIC Science & Technology

1994-02-04

A failure of motion deblurring in the human visual system. Investigative Opthalmology and Visual Sciences (Suppl),34, 1230 Watamaniuk, S.N.J. and...McKee, S.P. Why is a trajectory more detectable in noise than correlated signal dots? Investigative Opthalmology and Visual Sciences (Suppl),34, 1364

Speech Restoration: An Interactive Process

ERIC Educational Resources Information Center

Grataloup, Claire; Hoen, Michael; Veuillet, Evelyne; Collet, Lionel; Pellegrino, Francois; Meunier, Fanny

2009-01-01

Purpose: This study investigates the ability to understand degraded speech signals and explores the correlation between this capacity and the functional characteristics of the peripheral auditory system. Method: The authors evaluated the capability of 50 normal-hearing native French speakers to restore time-reversed speech. The task required them…

A fast combination calibration of foreground and background for pipelined ADCs

NASA Astrophysics Data System (ADS)

Kexu, Sun; Lenian, He

2012-06-01

This paper describes a fast digital calibration scheme for pipelined analog-to-digital converters (ADCs). The proposed method corrects the nonlinearity caused by finite opamp gain and capacitor mismatch in multiplying digital-to-analog converters (MDACs). The considered calibration technique takes the advantages of both foreground and background calibration schemes. In this combination calibration algorithm, a novel parallel background calibration with signal-shifted correlation is proposed, and its calibration cycle is very short. The details of this technique are described in the example of a 14-bit 100 Msample/s pipelined ADC. The high convergence speed of this background calibration is achieved by three means. First, a modified 1.5-bit stage is proposed in order to allow the injection of a large pseudo-random dithering without missing code. Second, before correlating the signal, it is shifted according to the input signal so that the correlation error converges quickly. Finally, the front pipeline stages are calibrated simultaneously rather than stage by stage to reduce the calibration tracking constants. Simulation results confirm that the combination calibration has a fast startup process and a short background calibration cycle of 2 × 221 conversions.

Multigigahertz range-Doppler correlative processing in crystals

NASA Astrophysics Data System (ADS)

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

2004-06-01

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.

An efficient ASIC implementation of 16-channel on-line recursive ICA processor for real-time EEG system.

PubMed

Fang, Wai-Chi; Huang, Kuan-Ju; Chou, Chia-Ching; Chang, Jui-Chung; Cauwenberghs, Gert; Jung, Tzyy-Ping

2014-01-01

This is a proposal for an efficient very-large-scale integration (VLSI) design, 16-channel on-line recursive independent component analysis (ORICA) processor ASIC for real-time EEG system, implemented with TSMC 40 nm CMOS technology. ORICA is appropriate to be used in real-time EEG system to separate artifacts because of its highly efficient and real-time process features. The proposed ORICA processor is composed of an ORICA processing unit and a singular value decomposition (SVD) processing unit. Compared with previous work [1], this proposed ORICA processor has enhanced effectiveness and reduced hardware complexity by utilizing a deeper pipeline architecture, shared arithmetic processing unit, and shared registers. The 16-channel random signals which contain 8-channel super-Gaussian and 8-channel sub-Gaussian components are used to analyze the dependence of the source components, and the average correlation coefficient is 0.95452 between the original source signals and extracted ORICA signals. Finally, the proposed ORICA processor ASIC is implemented with TSMC 40 nm CMOS technology, and it consumes 15.72 mW at 100 MHz operating frequency.

Developments of FPGA-based digital back-ends for low frequency antenna arrays at Medicina radio telescopes

NASA Astrophysics Data System (ADS)

Naldi, G.; Bartolini, M.; Mattana, A.; Pupillo, G.; Hickish, J.; Foster, G.; Bianchi, G.; Lingua, A.; Monari, J.; Montebugnoli, S.; Perini, F.; Rusticelli, S.; Schiaffino, M.; Virone, G.; Zarb Adami, K.

In radio astronomy Field Programmable Gate Array (FPGA) technology is largely used for the implementation of digital signal processing techniques applied to antenna arrays. This is mainly due to the good trade-off among computing resources, power consumption and cost offered by FPGA chip compared to other technologies like ASIC, GPU and CPU. In the last years several digital backend systems based on such devices have been developed at the Medicina radio astronomical station (INAF-IRA, Bologna, Italy). Instruments like FX correlator, direct imager, beamformer, multi-beam system have been successfully designed and realized on CASPER (Collaboration for Astronomy Signal Processing and Electronics Research, https://casper.berkeley.edu) processing boards. In this paper we present the gained experience in this kind of applications.

The correlates of subjective perception of identity and expression in the face network: an fMRI adaptation study

PubMed Central

Fox, Christopher J.; Moon, So Young; Iaria, Giuseppe; Barton, Jason J.S.

2009-01-01

The recognition of facial identity and expression are distinct tasks, with current models hypothesizing anatomic segregation of processing within a face-processing network. Using fMRI adaptation and a region-of-interest approach, we assessed how the perception of identity and expression changes in morphed stimuli affected the signal within this network, by contrasting (a) changes that crossed categorical boundaries of identity or expression with those that did not, and (b) changes that subjects perceived as causing identity or expression to change, versus changes that they perceived as not affecting the category of identity or expression. The occipital face area (OFA) was sensitive to any structural change in a face, whether it was identity or expression, but its signal did not correlate with whether subjects perceived a change or not. Both the fusiform face area (FFA) and the posterior superior temporal sulcus (pSTS) showed release from adaptation when subjects perceived a change in either identity or expression, although in the pSTS this effect only occurred when subjects were explicitly attending to expression. The middle superior temporal sulcus (mSTS) showed release from adaptation for expression only, and the precuneus for identity only. The data support models where the OFA is involved in the early perception of facial structure. However, evidence for a functional overlap in the FFA and pSTS, with both identity and expression signals in both areas, argues against a complete independence of identity and expression processing in these regions of the core face-processing network. PMID:18852053

The correlates of subjective perception of identity and expression in the face network: an fMRI adaptation study.

PubMed

Fox, Christopher J; Moon, So Young; Iaria, Giuseppe; Barton, Jason J S

2009-01-15

The recognition of facial identity and expression are distinct tasks, with current models hypothesizing anatomic segregation of processing within a face-processing network. Using fMRI adaptation and a region-of-interest approach, we assessed how the perception of identity and expression changes in morphed stimuli affected the signal within this network, by contrasting (a) changes that crossed categorical boundaries of identity or expression with those that did not, and (b) changes that subjects perceived as causing identity or expression to change, versus changes that they perceived as not affecting the category of identity or expression. The occipital face area (OFA) was sensitive to any structural change in a face, whether it was identity or expression, but its signal did not correlate with whether subjects perceived a change or not. Both the fusiform face area (FFA) and the posterior superior temporal sulcus (pSTS) showed release from adaptation when subjects perceived a change in either identity or expression, although in the pSTS this effect only occurred when subjects were explicitly attending to expression. The middle superior temporal sulcus (mSTS) showed release from adaptation for expression only, and the precuneus for identity only. The data support models where the OFA is involved in the early perception of facial structure. However, evidence for a functional overlap in the FFA and pSTS, with both identity and expression signals in both areas, argues against a complete independence of identity and expression processing in these regions of the core face-processing network.

Immunohistochemical evalulation of activated Ras and Rac1 as potential downstream effectors of aquaporin-5 in breast cancer in vivo.

PubMed

Jensen, Helene H; Login, Frédéric H; Park, Ji-Young; Kwon, Tae-Hwan; Nejsum, Lene N

2017-11-25

Aberrant levels of aquaporin-5 (AQP5) expression have been observed in several types of cancer, including breast cancer, where AQP5 overexpression is associated with metastasis and poor prognosis. In cultured cancer cells, AQP5 facilitates cell migration and activates Ras signaling. Both increased cell migration and Ras activation are associated with cancer metastasis, but so far it is unknown if AQP5 also affects these processes in vivo. Therefore, we investigated if high AQP5 expression in breast cancer tissue correlated with increased activation of Ras and of Rac1, which is a GTPase also involved in cell migration. This was accomplished by immunohistochemical analysis of invasive ductal carcinoma of breast tissue sections from human patients, followed by qualitative and quantitative correlation analysis between AQP5 and activated Ras and Rac1. Immunohistochemistry revealed that activation of Ras and Rac1 was positively correlated. There was, however, no correlation between high AQP5 expression and activation of Ras, whereas a nonsignificant, but positive, tendency between the levels of AQP5 and activated Rac1 levels was observed. In summary, this is the first report that correlates AQP5 expression levels to downstream signaling partners in breast cancer tissue sections. The results suggest Rac1 as a potential downstream signaling partner of AQP5 in vivo. Copyright © 2017 Elsevier Inc. All rights reserved.

Multi-step EMG Classification Algorithm for Human-Computer Interaction

NASA Astrophysics Data System (ADS)

Ren, Peng; Barreto, Armando; Adjouadi, Malek

A three-electrode human-computer interaction system, based on digital processing of the Electromyogram (EMG) signal, is presented. This system can effectively help disabled individuals paralyzed from the neck down to interact with computers or communicate with people through computers using point-and-click graphic interfaces. The three electrodes are placed on the right frontalis, the left temporalis and the right temporalis muscles in the head, respectively. The signal processing algorithm used translates the EMG signals during five kinds of facial movements (left jaw clenching, right jaw clenching, eyebrows up, eyebrows down, simultaneous left & right jaw clenching) into five corresponding types of cursor movements (left, right, up, down and left-click), to provide basic mouse control. The classification strategy is based on three principles: the EMG energy of one channel is typically larger than the others during one specific muscle contraction; the spectral characteristics of the EMG signals produced by the frontalis and temporalis muscles during different movements are different; the EMG signals from adjacent channels typically have correlated energy profiles. The algorithm is evaluated on 20 pre-recorded EMG signal sets, using Matlab simulations. The results show that this method provides improvements and is more robust than other previous approaches.

Parallel algorithm of VLBI software correlator under multiprocessor environment

NASA Astrophysics Data System (ADS)

Zheng, Weimin; Zhang, Dong

2007-11-01

The correlator is the key signal processing equipment of a Very Lone Baseline Interferometry (VLBI) synthetic aperture telescope. It receives the mass data collected by the VLBI observatories and produces the visibility function of the target, which can be used to spacecraft position, baseline length measurement, synthesis imaging, and other scientific applications. VLBI data correlation is a task of data intensive and computation intensive. This paper presents the algorithms of two parallel software correlators under multiprocessor environments. A near real-time correlator for spacecraft tracking adopts the pipelining and thread-parallel technology, and runs on the SMP (Symmetric Multiple Processor) servers. Another high speed prototype correlator using the mixed Pthreads and MPI (Massage Passing Interface) parallel algorithm is realized on a small Beowulf cluster platform. Both correlators have the characteristic of flexible structure, scalability, and with 10-station data correlating abilities.

Vestibular blueprint in early vertebrates.

PubMed

Straka, Hans; Baker, Robert

2013-11-19

Central vestibular neurons form identifiable subgroups within the boundaries of classically outlined octavolateral nuclei in primitive vertebrates that are distinct from those processing lateral line, electrosensory, and auditory signals. Each vestibular subgroup exhibits a particular morpho-physiological property that receives origin-specific sensory inputs from semicircular canal and otolith organs. Behaviorally characterized phenotypes send discrete axonal projections to extraocular, spinal, and cerebellar targets including other ipsi- and contralateral vestibular nuclei. The anatomical locations of vestibuloocular and vestibulospinal neurons correlate with genetically defined hindbrain compartments that are well conserved throughout vertebrate evolution though some variability exists in fossil and extant vertebrate species. The different vestibular subgroups exhibit a robust sensorimotor signal processing complemented with a high degree of vestibular and visual adaptive plasticity.

Correlation Filtering of Modal Dynamics using the Laplace Wavelet

NASA Technical Reports Server (NTRS)

Freudinger, Lawrence C.; Lind, Rick; Brenner, Martin J.

1997-01-01

Wavelet analysis allows processing of transient response data commonly encountered in vibration health monitoring tasks such as aircraft flutter testing. The Laplace wavelet is formulated as an impulse response of a single mode system to be similar to data features commonly encountered in these health monitoring tasks. A correlation filtering approach is introduced using the Laplace wavelet to decompose a signal into impulse responses of single mode subsystems. Applications using responses from flutter testing of aeroelastic systems demonstrate modal parameters and stability estimates can be estimated by correlation filtering free decay data with a set of Laplace wavelets.

Optical correlation techniques in fluid dynamics

NASA Astrophysics Data System (ADS)

Schätzel, K.; Schulz-Dubois, E. O.; Vehrenkamp, R.

1981-04-01

Three flow measurement techniques make use of fast digital correlators. The most widely spread is photon correlation velocimetry using crossed laser beams, and detecting Doppler shifted light scattered by small particles in the flow. Depending on the processing of the photon correlation output, this technique yields mean velocity, turbulence level, and even the detailed probability distribution of one velocity component. An improved data processing scheme is demonstrated on laminar vortex flow in a curved channel. In the second method, rate correlation based upon threshold crossings of a high pass filtered laser Doppler signal can be used to obtain velocity correlation functions. The most powerful set-up developed in our laboratory uses a phase locked loop type tracker and a multibit correlator to analyze time-dependent Taylor vortex flow. With two optical systems and trackers, cross-correlation functions reveal phase relations between different vortices. The last method makes use of refractive index fluctuations (eg in two phase flows) instead of scattering particles. Interferometry with bidirectional counting, and digital correlation and probability analysis, constitutes a new quantitative technique related to classical Schlieren methods. Measurements on a mixing flow of heated and cold air contribute new ideas to the theory of turbulent random phase screens.

Two-beam pumped cascaded four-wave-mixing process for producing multiple-beam quantum correlation

NASA Astrophysics Data System (ADS)

Liu, Shengshuai; Wang, Hailong; Jing, Jietai

2018-04-01

We propose a two-beam pumped cascaded four-wave-mixing (CFWM) scheme with a double-Λ energy-level configuration in 85Rb vapor cell and experimentally observe the emission of up to 10 quantum correlated beams from such CFWM scheme. During this process, the seed beam is amplified; four new signal beams and five idler beams are generated. The 10 beams show strong quantum correlation which is characterized by the intensity-difference squeezing of about -6.7 ±0.3 dB. Then, by altering the angle between the two pump beams, we observe the notable transition of the number of the output beams from 10 to eight, and even to six. We find that both the number of the output quantum correlated beams and their degree of quantum correlation from such two-beam pumped CFWM scheme increase with the decrease of the angle between the two pump beams. Such system may find potential applications in quantum information and quantum metrology.

PSGMiner: A modular software for polysomnographic analysis.

PubMed

Umut, İlhan

2016-06-01

Sleep disorders affect a great percentage of the population. The diagnosis of these disorders is usually made by polysomnography. This paper details the development of new software to carry out feature extraction in order to perform robust analysis and classification of sleep events using polysomnographic data. The software, called PSGMiner, is a tool, which visualizes, processes and classifies bioelectrical data. The purpose of this program is to provide researchers with a platform with which to test new hypotheses by creating tests to check for correlations that are not available in commercially available software. The software is freely available under the GPL3 License. PSGMiner is composed of a number of diverse modules such as feature extraction, annotation, and machine learning modules, all of which are accessible from the main module. Using the software, it is possible to extract features of polysomnography using digital signal processing and statistical methods and to perform different analyses. The features can be classified through the use of five classification algorithms. PSGMiner offers an architecture designed for integrating new methods. Automatic scoring, which is available in almost all commercial PSG software, is not inherently available in this program, though it can be implemented by two different methodologies (machine learning and algorithms). While similar software focuses on a certain signal or event composed of a small number of modules with no expansion possibility, the software introduced here can handle all polysomnographic signals and events. The software simplifies the processing of polysomnographic signals for researchers and physicians that are not experts in computer programming. It can find correlations between different events which could help predict an oncoming event such as sleep apnea. The software could also be used for educational purposes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Neural Correlates of Facial Mimicry: Simultaneous Measurements of EMG and BOLD Responses during Perception of Dynamic Compared to Static Facial Expressions

PubMed Central

Rymarczyk, Krystyna; Żurawski, Łukasz; Jankowiak-Siuda, Kamila; Szatkowska, Iwona

2018-01-01

Facial mimicry (FM) is an automatic response to imitate the facial expressions of others. However, neural correlates of the phenomenon are as yet not well established. We investigated this issue using simultaneously recorded EMG and BOLD signals during perception of dynamic and static emotional facial expressions of happiness and anger. During display presentations, BOLD signals and zygomaticus major (ZM), corrugator supercilii (CS) and orbicularis oculi (OO) EMG responses were recorded simultaneously from 46 healthy individuals. Subjects reacted spontaneously to happy facial expressions with increased EMG activity in ZM and OO muscles and decreased CS activity, which was interpreted as FM. Facial muscle responses correlated with BOLD activity in regions associated with motor simulation of facial expressions [i.e., inferior frontal gyrus, a classical Mirror Neuron System (MNS)]. Further, we also found correlations for regions associated with emotional processing (i.e., insula, part of the extended MNS). It is concluded that FM involves both motor and emotional brain structures, especially during perception of natural emotional expressions. PMID:29467691

Fluorescence background removal method for biological Raman spectroscopy based on empirical mode decomposition.

PubMed

Leon-Bejarano, Maritza; Dorantes-Mendez, Guadalupe; Ramirez-Elias, Miguel; Mendez, Martin O; Alba, Alfonso; Rodriguez-Leyva, Ildefonso; Jimenez, M

2016-08-01

Raman spectroscopy of biological tissue presents fluorescence background, an undesirable effect that generates false Raman intensities. This paper proposes the application of the Empirical Mode Decomposition (EMD) method to baseline correction. EMD is a suitable approach since it is an adaptive signal processing method for nonlinear and non-stationary signal analysis that does not require parameters selection such as polynomial methods. EMD performance was assessed through synthetic Raman spectra with different signal to noise ratio (SNR). The correlation coefficient between synthetic Raman spectra and the recovered one after EMD denoising was higher than 0.92. Additionally, twenty Raman spectra from skin were used to evaluate EMD performance and the results were compared with Vancouver Raman algorithm (VRA). The comparison resulted in a mean square error (MSE) of 0.001554. High correlation coefficient using synthetic spectra and low MSE in the comparison between EMD and VRA suggest that EMD could be an effective method to remove fluorescence background in biological Raman spectra.

Match graph generation for symbolic indirect correlation

NASA Astrophysics Data System (ADS)

Lopresti, Daniel; Nagy, George; Joshi, Ashutosh

2006-01-01

Symbolic indirect correlation (SIC) is a new approach for bringing lexical context into the recognition of unsegmented signals that represent words or phrases in printed or spoken form. One way of viewing the SIC problem is to find the correspondence, if one exists, between two bipartite graphs, one representing the matching of the two lexical strings and the other representing the matching of the two signal strings. While perfect matching cannot be expected with real-world signals and while some degree of mismatch is allowed for in the second stage of SIC, such errors, if they are too numerous, can present a serious impediment to a successful implementation of the concept. In this paper, we describe a framework for evaluating the effectiveness of SIC match graph generation and examine the relatively simple, controlled cases of synthetic images of text strings typeset, both normally and in highly condensed fashion. We quantify and categorize the errors that arise, as well as present a variety of techniques we have developed to visualize the intermediate results of the SIC process.

A experiment on radio location of objects in the near-Earth space with VLBI in 2012

NASA Astrophysics Data System (ADS)

Nechaeva, M.; Antipenko, A.; Bezrukovs, V.; Bezrukov, D.; Dementjev, A.; Dugin, N.; Konovalenko, A.; Kulishenko, V.; Liu, X.; Nabatov, A.; Nesteruk, V.; Pupillo, G.; Reznichenko, A.; Salerno, E.; Shmeld, I.; Shulga, O.; Sybiryakova, Y.; Tikhomirov, Yu.; Tkachenko, A.; Volvach, A.; Yang, W.-J.

An experiment on radar location of space debris objects using of the method of VLBI was carried out in April, 2012. The radar VLBI experiment consisted in irradiation of some space debris objects (4 rocket stages and 5 inactive satellites) with a signal of the transmitter with RT-70 in Evpatoria, Ukraine. Reflected signals were received by a complex of radio telescopes in the VLBI mode. The following VLBI stations took part in the observations: Ventspils (RT-32), Urumqi (RT-25), Medicina (RT-32) and Simeiz (RT-22). The experiment included measurements of the Doppler frequency shift and the delay for orbit refining, and measurements of the rotation period and sizes of objects by the amplitudes of output interferometer signals. The cross-correlation of VLBI-data is performed at a correlator NIRFI-4 of Radiophysical Research Institute (Nizhny Novgorod). Preliminary data processing resulted in the series of Doppler frequency shifts, which comprised the information on radial velocities of the objects. Some results of the experiment are presented.

Principal and independent component analysis of concomitant functional near infrared spectroscopy and magnetic resonance imaging data

NASA Astrophysics Data System (ADS)

Schelkanova, Irina; Toronov, Vladislav

2011-07-01

Although near infrared spectroscopy (NIRS) is now widely used both in emerging clinical techniques and in cognitive neuroscience, the development of the apparatuses and signal processing methods for these applications is still a hot research topic. The main unresolved problem in functional NIRS is the separation of functional signals from the contaminations by systemic and local physiological fluctuations. This problem was approached by using various signal processing methods, including blind signal separation techniques. In particular, principal component analysis (PCA) and independent component analysis (ICA) were applied to the data acquired at the same wavelength and at multiple sites on the human or animal heads during functional activation. These signal processing procedures resulted in a number of principal or independent components that could be attributed to functional activity but their physiological meaning remained unknown. On the other hand, the best physiological specificity is provided by broadband NIRS. Also, a comparison with functional magnetic resonance imaging (fMRI) allows determining the spatial origin of fNIRS signals. In this study we applied PCA and ICA to broadband NIRS data to distill the components correlating with the breath hold activation paradigm and compared them with the simultaneously acquired fMRI signals. Breath holding was used because it generates blood carbon dioxide (CO2) which increases the blood-oxygen-level-dependent (BOLD) signal as CO2 acts as a cerebral vasodilator. Vasodilation causes increased cerebral blood flow which washes deoxyhaemoglobin out of the cerebral capillary bed thus increasing both the cerebral blood volume and oxygenation. Although the original signals were quite diverse, we found very few different components which corresponded to fMRI signals at different locations in the brain and to different physiological chromophores.

Correlation between external and internal respiratory motion: a validation study.

PubMed

Ernst, Floris; Bruder, Ralf; Schlaefer, Alexander; Schweikard, Achim

2012-05-01

In motion-compensated image-guided radiotherapy, accurate tracking of the target region is required. This tracking process includes building a correlation model between external surrogate motion and the motion of the target region. A novel correlation method is presented and compared with the commonly used polynomial model. The CyberKnife system (Accuray, Inc., Sunnyvale/CA) uses a polynomial correlation model to relate externally measured surrogate data (optical fibres on the patient's chest emitting red light) to infrequently acquired internal measurements (X-ray data). A new correlation algorithm based on ɛ -Support Vector Regression (SVR) was developed. Validation and comparison testing were done with human volunteers using live 3D ultrasound and externally measured infrared light-emitting diodes (IR LEDs). Seven data sets (5:03-6:27 min long) were recorded from six volunteers. Polynomial correlation algorithms were compared to the SVR-based algorithm demonstrating an average increase in root mean square (RMS) accuracy of 21.3% (0.4 mm). For three signals, the increase was more than 29% and for one signal as much as 45.6% (corresponding to more than 1.5 mm RMS). Further analysis showed the improvement to be statistically significant. The new SVR-based correlation method outperforms traditional polynomial correlation methods for motion tracking. This method is suitable for clinical implementation and may improve the overall accuracy of targeted radiotherapy.

When Is It My Turn To Speak?

ERIC Educational Resources Information Center

Orestrom, Bengt

A study analyzed four dyadic conversations for evidence of the signals operating in the turn-taking process and facilitating the smooth exchange of turns. It found over 20 syntactic, prosodic, and semantic features occurring frequently with turn-taking. The five most significant factors correlating with turn-taking were a prosodically completed…

EMD self-adaptive selecting relevant modes algorithm for FBG spectrum signal

NASA Astrophysics Data System (ADS)

Chen, Yong; Wu, Chun-ting; Liu, Huan-lin

2017-07-01

Noise may reduce the demodulation accuracy of fiber Bragg grating (FBG) sensing signal so as to affect the quality of sensing detection. Thus, the recovery of a signal from observed noisy data is necessary. In this paper, a precise self-adaptive algorithm of selecting relevant modes is proposed to remove the noise of signal. Empirical mode decomposition (EMD) is first used to decompose a signal into a set of modes. The pseudo modes cancellation is introduced to identify and eliminate false modes, and then the Mutual Information (MI) of partial modes is calculated. MI is used to estimate the critical point of high and low frequency components. Simulation results show that the proposed algorithm estimates the critical point more accurately than the traditional algorithms for FBG spectral signal. While, compared to the similar algorithms, the signal noise ratio of the signal can be improved more than 10 dB after processing by the proposed algorithm, and correlation coefficient can be increased by 0.5, so it demonstrates better de-noising effect.

Controller and interface module for the High-Speed Data Acquisition System correlator/accumulator

NASA Technical Reports Server (NTRS)

Brokl, S. S.

1985-01-01

One complex channel of the High-Speed Data Acquisition System (a subsystem used in the Goldstone solar system radar), consisting of two correlator modules and one accumulator module, is operated by the controller and interface module interfaces are provided to the VAX UNIBUS for computer control, monitor, and test of the controller and correlator/accumulator. The correlator and accumulator modules controlled by this module are the key digital signal processing elements of the Goldstone High-Speed Data Acquisition System. This fully programmable unit provides for a wide variety of correlation and filtering functions operating on a three megaword/second data flow. Data flow is to the VAX by way of the I/O port of a FPS 5210 array processor.

Gaussian Process Kalman Filter for Focal Plane Wavefront Correction and Exoplanet Signal Extraction

NASA Astrophysics Data System (ADS)

Sun, He; Kasdin, N. Jeremy

2018-01-01

Currently, the ultimate limitation of space-based coronagraphy is the ability to subtract the residual PSF after wavefront correction to reveal the planet. Called reference difference imaging (RDI), the technique consists of conducting wavefront control to collect the reference point spread function (PSF) by observing a bright star, and then extracting target planet signals by subtracting a weighted sum of reference PSFs. Unfortunately, this technique is inherently inefficient because it spends a significant fraction of the observing time on the reference star rather than the target star with the planet. Recent progress in model based wavefront estimation suggests an alternative approach. A Kalman filter can be used to estimate the stellar PSF for correction by the wavefront control system while simultaneously estimating the planet signal. Without observing the reference star, the (extended) Kalman filter directly utilizes the wavefront correction data and combines the time series observations and model predictions to estimate the stellar PSF and planet signals. Because wavefront correction is used during the entire observation with no slewing, the system has inherently better stability. In this poster we show our results aimed at further improving our Kalman filter estimation accuracy by including not only temporal correlations but also spatial correlations among neighboring pixels in the images. This technique is known as a Gaussian process Kalman filter (GPKF). We also demonstrate the advantages of using a Kalman filter rather than RDI by simulating a real space exoplanet detection mission.

The Development and Application of Random Matrix Theory in Adaptive Signal Processing in the Sample Deficient Regime

DTIC Science & Technology

2014-09-01

optimal diagonal loading which minimizes the MSE. The be- havior of optimal diagonal loading when the arrival process is composed of plane waves embedded...observation vectors. The examples of the ensemble correlation matrix corresponding to the input process consisting of a single or multiple plane waves...Y ∗ij is a complex-conjugate of Yij. This result is used in order to evaluate the expectations of different quadratic forms. The Poincare -Nash

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

NASA Technical Reports Server (NTRS)

Downie, John D.

1995-01-01

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

Nonlinear analysis of pupillary dynamics.

PubMed

Onorati, Francesco; Mainardi, Luca Tommaso; Sirca, Fabiola; Russo, Vincenzo; Barbieri, Riccardo

2016-02-01

Pupil size reflects autonomic response to different environmental and behavioral stimuli, and its dynamics have been linked to other autonomic correlates such as cardiac and respiratory rhythms. The aim of this study is to assess the nonlinear characteristics of pupil size of 25 normal subjects who participated in a psychophysiological experimental protocol with four experimental conditions, namely “baseline”, “anger”, “joy”, and “sadness”. Nonlinear measures, such as sample entropy, correlation dimension, and largest Lyapunov exponent, were computed on reconstructed signals of spontaneous fluctuations of pupil dilation. Nonparametric statistical tests were performed on surrogate data to verify that the nonlinear measures are an intrinsic characteristic of the signals. We then developed and applied a piecewise linear regression model to detrended fluctuation analysis (DFA). Two joinpoints and three scaling intervals were identified: slope α0, at slow time scales, represents a persistent nonstationary long-range correlation, whereas α1 and α2, at middle and fast time scales, respectively, represent long-range power-law correlations, similarly to DFA applied to heart rate variability signals. Of the computed complexity measures, α0 showed statistically significant differences among experimental conditions (p<0.001). Our results suggest that (a) pupil size at constant light condition is characterized by nonlinear dynamics, (b) three well-defined and distinct long-memory processes exist at different time scales, and (c) autonomic stimulation is partially reflected in nonlinear dynamics. (c) autonomic stimulation is partially reflected in nonlinear dynamics.

Aeroelastic Flight Data Analysis with the Hilbert-Huang Algorithm

NASA Technical Reports Server (NTRS)

Brenner, Martin J.; Prazenica, Chad

2006-01-01

This report investigates the utility of the Hilbert Huang transform for the analysis of aeroelastic flight data. It is well known that the classical Hilbert transform can be used for time-frequency analysis of functions or signals. Unfortunately, the Hilbert transform can only be effectively applied to an extremely small class of signals, namely those that are characterized by a single frequency component at any instant in time. The recently-developed Hilbert Huang algorithm addresses the limitations of the classical Hilbert transform through a process known as empirical mode decomposition. Using this approach, the data is filtered into a series of intrinsic mode functions, each of which admits a well-behaved Hilbert transform. In this manner, the Hilbert Huang algorithm affords time-frequency analysis of a large class of signals. This powerful tool has been applied in the analysis of scientific data, structural system identification, mechanical system fault detection, and even image processing. The purpose of this report is to demonstrate the potential applications of the Hilbert Huang algorithm for the analysis of aeroelastic systems, with improvements such as localized online processing. Applications for correlations between system input and output, and amongst output sensors, are discussed to characterize the time-varying amplitude and frequency correlations present in the various components of multiple data channels. Online stability analyses and modal identification are also presented. Examples are given using aeroelastic test data from the F-18 Active Aeroelastic Wing airplane, an Aerostructures Test Wing, and pitch plunge simulation.

Aeroelastic Flight Data Analysis with the Hilbert-Huang Algorithm

NASA Technical Reports Server (NTRS)

Brenner, Marty; Prazenica, Chad

2005-01-01

This paper investigates the utility of the Hilbert-Huang transform for the analysis of aeroelastic flight data. It is well known that the classical Hilbert transform can be used for time-frequency analysis of functions or signals. Unfortunately, the Hilbert transform can only be effectively applied to an extremely small class of signals, namely those that are characterized by a single frequency component at any instant in time. The recently-developed Hilbert-Huang algorithm addresses the limitations of the classical Hilbert transform through a process known as empirical mode decomposition. Using this approach, the data is filtered into a series of intrinsic mode functions, each of which admits a well-behaved Hilbert transform. In this manner, the Hilbert-Huang algorithm affords time-frequency analysis of a large class of signals. This powerful tool has been applied in the analysis of scientific data, structural system identification, mechanical system fault detection, and even image processing. The purpose of this paper is to demonstrate the potential applications of the Hilbert-Huang algorithm for the analysis of aeroelastic systems, with improvements such as localized/online processing. Applications for correlations between system input and output, and amongst output sensors, are discussed to characterize the time-varying amplitude and frequency correlations present in the various components of multiple data channels. Online stability analyses and modal identification are also presented. Examples are given using aeroelastic test data from the F/A-18 Active Aeroelastic Wing aircraft, an Aerostructures Test Wing, and pitch-plunge simulation.

Adaptive Arrays for Weak Interfering Signals: An Experimental System. M.S. Thesis

NASA Technical Reports Server (NTRS)

Ward, James

1987-01-01

An experimental adaptive antenna system was implemented to study the performance of adaptive arrays in the presence of weak interfering signals. It is a sidelobe canceler with two auxiliary elements. Modified feedback loops, which decorrelate the noise components of the two inputs to the loop correlators, control the array weights. Digital processing is used for algorithm implementation and performance evaluation. The results show that the system can suppress interfering signals which are 0 to 10 dB below the thermal noise level in the main channel by 20 to 30 dB. When the desired signal is strong in the auxiliary elements the amount of interference suppression decreases. The amount of degradation depends on the number of interfering signals incident on the communication system. A modified steering vector which overcomes this problem is proposed.

Optical fibres in pre-detector signal processing

NASA Astrophysics Data System (ADS)

Flinn, A. R.

The basic form of conventional electro-optic sensors is described. The main drawback of these sensors is their inability to deal with the background radiation which usually accompanies the signal. This 'clutter' limits the sensors performance long before other noise such as 'shot' noise. Pre-detector signal processing using the complex amplitude of the light is introduced as a means to discriminate between the signal and 'clutter'. Further improvements to predetector signal processors can be made by the inclusion of optical fibres allowing radiation to be used with greater efficiency and enabling certain signal processing tasks to be carried out with an ease unequalled by any other method. The theory of optical waveguides and their application in sensors, interferometers, and signal processors is reviewed. Geometrical aspects of the formation of linear and circular interference fringes are described along with temporal and spatial coherence theory and their relationship to Michelson's visibility function. The requirements for efficient coupling of a source into singlemode and multimode fibres are given. We describe interference experiments between beams of light emitted from a few metres of two or more, singlemode or multimode, optical fibres. Fresnel's equation is used to obtain expressions for Fresnel and Fraunhofer diffraction patterns which enable electro-optic (E-0) sensors to be analysed by Fourier optics. Image formation is considered when the aperture plane of an E-0 sensor is illuminated with partially coherent light. This allows sensors to be designed using optical transfer functions which are sensitive to the spatial coherence of the illuminating light. Spatial coherence sensors which use gratings as aperture plane reticles are discussed. By using fibre arrays, spatial coherence processing enables E-0 sensors to discriminate between a spatially coherent source and an incoherent background. The sensors enable the position and wavelength of the source to be determined. Experiments are described which use optical fibre arrays as masks for correlation with spatial distributions of light in image planes of E-0 sensors. Correlations between laser light from different points in a scene is investigated by interfering the light emitted from an array of fibres, placed in the image plane of a sensor, with each other. Temporal signal processing experiments show that the visibility of interference fringes gives information about path differences in a scene or through an optical system. Most E-0 sensors employ wavelength filtering of the detected radiation to improve their discrimination and this is shown to be less selective than temporal coherence filtering which is sensitive to spectral bandwidth. Experiments using fibre interferometers to discriminate between red and blue laser light by their bandwidths are described. In most cases the path difference need only be a few tens of centimetres. We consider spatial and temporal coherence in fibres. We show that high visibility interference fringes can be produced by red and blue laser light transmitted through over 100 metres of singlemode or multimode fibre. The effect of detector size, relative to speckle size, is considered for fringes produced by multimode fibres. The effect of dispersion on the coherence of the light emitted from fibres is considered in terms of correlation and interference between modes. We describe experiments using a spatial light modulator called SIGHT-MOD. The device is used in various systems as a fibre optic switch and as a programmable aperture plane reticle. The contrast of the device is measured using red and green, HeNe, sources. Fourier transform images of patterns on the SIGHT-MOD are obtained and used to demonstrate the geometrical manipulation of images using 2D fibre arrays. Correlation of Fourier transform images of the SIGHT-MOD with 2D fibre arrays is demonstrated.

Robust real-time extraction of respiratory signals from PET list-mode data

NASA Astrophysics Data System (ADS)

Salomon, André; Zhang, Bin; Olivier, Patrick; Goedicke, Andreas

2018-06-01

Respiratory motion, which typically cannot simply be suspended during PET image acquisition, affects lesions’ detection and quantitative accuracy inside or in close vicinity to the lungs. Some motion compensation techniques address this issue via pre-sorting (‘binning’) of the acquired PET data into a set of temporal gates, where each gate is assumed to be minimally affected by respiratory motion. Tracking respiratory motion is typically realized using dedicated hardware (e.g. using respiratory belts and digital cameras). Extracting respiratory signals directly from the acquired PET data simplifies the clinical workflow as it avoids handling additional signal measurement equipment. We introduce a new data-driven method ‘combined local motion detection’ (CLMD). It uses the time-of-flight (TOF) information provided by state-of-the-art PET scanners in order to enable real-time respiratory signal extraction without additional hardware resources. CLMD applies center-of-mass detection in overlapping regions based on simple back-positioned TOF event sets acquired in short time frames. Following a signal filtering and quality-based pre-selection step, the remaining extracted individual position information over time is then combined to generate a global respiratory signal. The method is evaluated using seven measured FDG studies from single and multiple scan positions of the thorax region, and it is compared to other software-based methods regarding quantitative accuracy and statistical noise stability. Correlation coefficients around 90% between the reference and the extracted signal have been found for those PET scans where motion affected features such as tumors or hot regions were present in the PET field-of-view. For PET scans with a quarter of typically applied radiotracer doses, the CLMD method still provides similar high correlation coefficients which indicates its robustness to noise. Each CLMD processing needed less than 0.4 s in total on a standard multi-core CPU and thus provides a robust and accurate approach enabling real-time processing capabilities using standard PC hardware.

Symmetric Phase-Only Filtering in Particle-Image Velocimetry

NASA Technical Reports Server (NTRS)

Wemet, Mark P.

2008-01-01

Symmetrical phase-only filtering (SPOF) can be exploited to obtain substantial improvements in the results of data processing in particle-image velocimetry (PIV). In comparison with traditional PIV data processing, SPOF PIV data processing yields narrower and larger amplitude correlation peaks, thereby providing more-accurate velocity estimates. The higher signal-to-noise ratios associated with the higher amplitude correlation peaks afford greater robustness and reliability of processing. SPOF also affords superior performance in the presence of surface flare light and/or background light. SPOF algorithms can readily be incorporated into pre-existing algorithms used to process digitized image data in PIV, without significantly increasing processing times. A summary of PIV and traditional PIV data processing is prerequisite to a meaningful description of SPOF PIV processing. In PIV, a pulsed laser is used to illuminate a substantially planar region of a flowing fluid in which particles are entrained. An electronic camera records digital images of the particles at two instants of time. The components of velocity of the fluid in the illuminated plane can be obtained by determining the displacements of particles between the two illumination pulses. The objective in PIV data processing is to compute the particle displacements from the digital image data. In traditional PIV data processing, to which the present innovation applies, the two images are divided into a grid of subregions and the displacements determined from cross-correlations between the corresponding sub-regions in the first and second images. The cross-correlation process begins with the calculation of the Fourier transforms (or fast Fourier transforms) of the subregion portions of the images. The Fourier transforms from the corresponding subregions are multiplied, and this product is inverse Fourier transformed, yielding the cross-correlation intensity distribution. The average displacement of the particles across a subregion results in a displacement of the correlation peak from the center of the correlation plane. The velocity is then computed from the displacement of the correlation peak and the time between the recording of the two images. The process as described thus far is performed for all the subregions. The resulting set of velocities in grid cells amounts to a velocity vector map of the flow field recorded on the image plane. In traditional PIV processing, surface flare light and bright background light give rise to a large, broad correlation peak, at the center of the correlation plane, that can overwhelm the true particle- displacement correlation peak. This has made it necessary to resort to tedious image-masking and background-subtraction procedures to recover the relatively small amplitude particle-displacement correlation peak. SPOF is a variant of phase-only filtering (POF), which, in turn, is a variant of matched spatial filtering (MSF). In MSF, one projects a first image (denoted the input image) onto a second image (denoted the filter) as part of a computation to determine how much and what part of the filter is present in the input image. MSF is equivalent to cross-correlation. In POF, the frequency-domain content of the MSF filter is modified to produce a unitamplitude (phase-only) object. POF is implemented by normalizing the Fourier transform of the filter by its magnitude. The advantage of POFs is that they yield correlation peaks that are sharper and have higher signal-to-noise ratios than those obtained through traditional MSF. In the SPOF, these benefits of POF can be extended to PIV data processing. The SPOF yields even better performance than the POF approach, which is uniquely applicable to PIV type image data. In SPOF as now applied to PIV data processing, a subregion of the first image is treated as the input image and the corresponding subregion of the second image is treated as the filter. The Fourier transforms from both the firs and second- image subregions are normalized by the square roots of their respective magnitudes. This scheme yields optimal performance because the amounts of normalization applied to the spatial-frequency contents of the input and filter scenes are just enough to enhance their high-spatial-frequency contents while reducing their spurious low-spatial-frequency content. As a result, in SPOF PIV processing, particle-displacement correlation peaks can readily be detected above spurious background peaks, without need for masking or background subtraction.

Early anti-correlated BOLD signal changes of physiologic origin.

PubMed

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

2014-02-15

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

Early anti-correlated BOLD signal changes of physiologic origin

PubMed Central

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

2014-01-01

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

The Seismic Tool-Kit (STK): an open source software for seismology and signal processing.

NASA Astrophysics Data System (ADS)

Reymond, Dominique

2016-04-01

We present an open source software project (GNU public license), named STK: Seismic ToolKit, that is dedicated mainly for seismology and signal processing. The STK project that started in 2007, is hosted by SourceForge.net, and count more than 19 500 downloads at the date of writing. The STK project is composed of two main branches: First, a graphical interface dedicated to signal processing (in the SAC format (SAC_ASCII and SAC_BIN): where the signal can be plotted, zoomed, filtered, integrated, derivated, ... etc. (a large variety of IFR and FIR filter is proposed). The estimation of spectral density of the signal are performed via the Fourier transform, with visualization of the Power Spectral Density (PSD) in linear or log scale, and also the evolutive time-frequency representation (or sonagram). The 3-components signals can be also processed for estimating their polarization properties, either for a given window, or either for evolutive windows along the time. This polarization analysis is useful for extracting the polarized noises, differentiating P waves, Rayleigh waves, Love waves, ... etc. Secondly, a panel of Utilities-Program are proposed for working in a terminal mode, with basic programs for computing azimuth and distance in spherical geometry, inter/auto-correlation, spectral density, time-frequency for an entire directory of signals, focal planes, and main components axis, radiation pattern of P waves, Polarization analysis of different waves (including noize), under/over-sampling the signals, cubic-spline smoothing, and linear/non linear regression analysis of data set. A MINimum library of Linear AlGebra (MIN-LINAG) is also provided for computing the main matrix process like: QR/QL decomposition, Cholesky solve of linear system, finding eigen value/eigen vectors, QR-solve/Eigen-solve of linear equations systems ... etc. STK is developed in C/C++, mainly under Linux OS, and it has been also partially implemented under MS-Windows. Usefull links: http://sourceforge.net/projects/seismic-toolkit/ http://sourceforge.net/p/seismic-toolkit/wiki/browse_pages/

Freeze-drying process monitoring using a cold plasma ionization device.

PubMed

Mayeresse, Y; Veillon, R; Sibille, P H; Nomine, C

2007-01-01

A cold plasma ionization device has been designed to monitor freeze-drying processes in situ by monitoring lyophilization chamber moisture content. This plasma device, which consists of a probe that can be mounted directly on the lyophilization chamber, depends upon the ionization of nitrogen and water molecules using a radiofrequency generator and spectrometric signal collection. The study performed on this probe shows that it is steam sterilizable, simple to integrate, reproducible, and sensitive. The limitations include suitable positioning in the lyophilization chamber, calibration, and signal integration. Sensitivity was evaluated in relation to the quantity of vials and the probe positioning, and correlation with existing methods, such as microbalance, was established. These tests verified signal reproducibility through three freeze-drying cycles. Scaling-up studies demonstrated a similar product signature for the same product using pilot-scale and larger-scale equipment. On an industrial scale, the method efficiently monitored the freeze-drying cycle, but in a larger industrial freeze-dryer the signal was slightly modified. This was mainly due to the positioning of the plasma device, in relation to the vapor flow pathway, which is not necessarily homogeneous within the freeze-drying chamber. The plasma tool is a relevant method for monitoring freeze-drying processes and may in the future allow the verification of current thermodynamic freeze-drying models. This plasma technique may ultimately represent a process analytical technology (PAT) approach for the freeze-drying process.

Crosslinking EEG time-frequency decomposition and fMRI in error monitoring.

PubMed

Hoffmann, Sven; Labrenz, Franziska; Themann, Maria; Wascher, Edmund; Beste, Christian

2014-03-01

Recent studies implicate a common response monitoring system, being active during erroneous and correct responses. Converging evidence from time-frequency decompositions of the response-related ERP revealed that evoked theta activity at fronto-central electrode positions differentiates correct from erroneous responses in simple tasks, but also in more complex tasks. However, up to now it is unclear how different electrophysiological parameters of error processing, especially at the level of neural oscillations are related, or predictive for BOLD signal changes reflecting error processing at a functional-neuroanatomical level. The present study aims to provide crosslinks between time domain information, time-frequency information, MRI BOLD signal and behavioral parameters in a task examining error monitoring due to mistakes in a mental rotation task. The results show that BOLD signal changes reflecting error processing on a functional-neuroanatomical level are best predicted by evoked oscillations in the theta frequency band. Although the fMRI results in this study account for an involvement of the anterior cingulate cortex, middle frontal gyrus, and the Insula in error processing, the correlation of evoked oscillations and BOLD signal was restricted to a coupling of evoked theta and anterior cingulate cortex BOLD activity. The current results indicate that although there is a distributed functional-neuroanatomical network mediating error processing, only distinct parts of this network seem to modulate electrophysiological properties of error monitoring.

SPECIAL ISSUE ON OPTICAL PROCESSING OF INFORMATION: Optical information processing with transformation of the spatial coherence of light

NASA Astrophysics Data System (ADS)

Bykovskii, Yurii A.; Markilov, A. A.; Rodin, V. G.; Starikov, S. N.

1995-10-01

A description is given of systems with spatially incoherent illumination, intended for spectral and correlation analysis, and for the recording of Fourier holograms. These systems make use of transformation of the degree of the spatial coherence of light. The results are given of the processing of images and signals, including those transmitted by a bundle of fibre-optic waveguides both as monochromatic light and as quasimonochromatic radiation from a cathode-ray tube. The feasibility of spatial frequency filtering and of correlation analysis of images with a bipolar impulse response is considered for systems with spatially incoherent illumination where these tasks are performed by double transformation of the spatial coherence of light. A description is given of experimental systems and the results of image processing are reported.

Mapping the Information Trace in Local Field Potentials by a Computational Method of Two-Dimensional Time-Shifting Synchronization Likelihood Based on Graphic Processing Unit Acceleration.

PubMed

Zhao, Zi-Fang; Li, Xue-Zhu; Wan, You

2017-12-01

The local field potential (LFP) is a signal reflecting the electrical activity of neurons surrounding the electrode tip. Synchronization between LFP signals provides important details about how neural networks are organized. Synchronization between two distant brain regions is hard to detect using linear synchronization algorithms like correlation and coherence. Synchronization likelihood (SL) is a non-linear synchronization-detecting algorithm widely used in studies of neural signals from two distant brain areas. One drawback of non-linear algorithms is the heavy computational burden. In the present study, we proposed a graphic processing unit (GPU)-accelerated implementation of an SL algorithm with optional 2-dimensional time-shifting. We tested the algorithm with both artificial data and raw LFP data. The results showed that this method revealed detailed information from original data with the synchronization values of two temporal axes, delay time and onset time, and thus can be used to reconstruct the temporal structure of a neural network. Our results suggest that this GPU-accelerated method can be extended to other algorithms for processing time-series signals (like EEG and fMRI) using similar recording techniques.

Being watched: the effect of social self-focus on interoceptive and exteroceptive somatosensory perception.

PubMed

Durlik, Caroline; Cardini, Flavia; Tsakiris, Manos

2014-04-01

We become aware of our bodies interoceptively, by processing signals arising from within the body, and exteroceptively, by processing signals arising on or outside the body. Recent research highlights the importance of the interaction of exteroceptive and interoceptive signals in modulating bodily self-consciousness. The current study investigated the effect of social self-focus, manipulated via a video camera that was facing the participants and that was either switched on or off, on interoceptive sensitivity (using a heartbeat perception task) and on tactile perception (using the Somatic Signal Detection Task (SSDT)). The results indicated a significant effect of self-focus on SSDT performance, but not on interoception. SSDT performance was not moderated by interoceptive sensitivity, although interoceptive sensitivity scores were positively correlated with false alarms, independently of self-focus. Together with previous research, our results suggest that self-focus may exert different effects on body perception depending on its mode (private versus social). While interoception has been previously shown to be enhanced by private self-focus, the current study failed to find an effect of social self-focus on interoceptive sensitivity, instead demonstrating that social self-focus improves exteroceptive somatosensory processing. Copyright © 2014 Elsevier Inc. All rights reserved.

Simple Sample Processing Enhances Malaria Rapid Diagnostic Test Performance

PubMed Central

Davis, K. M.; Gibson, L. E.; Haselton, F. R.; Wright, D. W.

2016-01-01

Lateral flow immunochromatographic rapid diagnostic tests (RDTs) are the primary form of medical diagnostic used for malaria in underdeveloped nations. Unfortunately, many of these tests do not detect asymptomatic malaria carriers. In order for eradication of the disease to be achieved, this problem must be solved. In this study, we demonstrate enhancement in the performance of six RDT brands when a simple sample-processing step is added to the front of the diagnostic process. Greater than a 4-fold RDT signal enhancement was observed as a result of the sample processing step. This lowered the limit of detection for RDT brands to submicroscopic parasitemias. For the best performing RDTs the limits of detection were found to be as low as 3 parasites/μL. Finally, through individual donor samples, the correlations between donor source, WHO panel detection scores and RDT signal intensities were explored. PMID:24787948

Vibration Sensor Monitoring of Nickel-Titanium Alloy Turning for Machinability Evaluation.

PubMed

Segreto, Tiziana; Caggiano, Alessandra; Karam, Sara; Teti, Roberto

2017-12-12

Nickel-Titanium (Ni-Ti) alloys are very difficult-to-machine materials causing notable manufacturing problems due to their unique mechanical properties, including superelasticity, high ductility, and severe strain-hardening. In this framework, the aim of this paper is to assess the machinability of Ni-Ti alloys with reference to turning processes in order to realize a reliable and robust in-process identification of machinability conditions. An on-line sensor monitoring procedure based on the acquisition of vibration signals was implemented during the experimental turning tests. The detected vibration sensorial data were processed through an advanced signal processing method in time-frequency domain based on wavelet packet transform (WPT). The extracted sensorial features were used to construct WPT pattern feature vectors to send as input to suitably configured neural networks (NNs) for cognitive pattern recognition in order to evaluate the correlation between input sensorial information and output machinability conditions.

Vibration Sensor Monitoring of Nickel-Titanium Alloy Turning for Machinability Evaluation

PubMed Central

Segreto, Tiziana; Karam, Sara; Teti, Roberto

2017-01-01

Nickel-Titanium (Ni-Ti) alloys are very difficult-to-machine materials causing notable manufacturing problems due to their unique mechanical properties, including superelasticity, high ductility, and severe strain-hardening. In this framework, the aim of this paper is to assess the machinability of Ni-Ti alloys with reference to turning processes in order to realize a reliable and robust in-process identification of machinability conditions. An on-line sensor monitoring procedure based on the acquisition of vibration signals was implemented during the experimental turning tests. The detected vibration sensorial data were processed through an advanced signal processing method in time-frequency domain based on wavelet packet transform (WPT). The extracted sensorial features were used to construct WPT pattern feature vectors to send as input to suitably configured neural networks (NNs) for cognitive pattern recognition in order to evaluate the correlation between input sensorial information and output machinability conditions. PMID:29231864

Simple sample processing enhances malaria rapid diagnostic test performance.

PubMed

Davis, K M; Gibson, L E; Haselton, F R; Wright, D W

2014-06-21

Lateral flow immunochromatographic rapid diagnostic tests (RDTs) are the primary form of medical diagnostic used for malaria in underdeveloped nations. Unfortunately, many of these tests do not detect asymptomatic malaria carriers. In order for eradication of the disease to be achieved, this problem must be solved. In this study, we demonstrate enhancement in the performance of six RDT brands when a simple sample-processing step is added to the front of the diagnostic process. Greater than a 4-fold RDT signal enhancement was observed as a result of the sample processing step. This lowered the limit of detection for RDT brands to submicroscopic parasitemias. For the best performing RDTs the limits of detection were found to be as low as 3 parasites per μL. Finally, through individual donor samples, the correlations between donor source, WHO panel detection scores and RDT signal intensities were explored.

Navigation Using Orthogonal Frequency Division Multiplexed Signals of Opportunity

DTIC Science & Technology

2007-09-01

transmits a 32,767 bit pseudo -random “short” code that repeats 37.5 times per second. Since the pseudo -random bit pattern and modulation scheme are... correlation process takes two “ sample windows,” both of which are ν = 16 samples wide and are spaced N = 64 samples apart, and compares them. When the...technique in (3.4) is a necessary step in order to get a more accurate estimate of the sample shift from the symbol boundary correlator in (3.1). Figure

Detection of sub-threshold periodic signal by multiplicative and additive cross-correlated sine-Wiener noises in the FitzHugh-Nagumo neuron

NASA Astrophysics Data System (ADS)

Yao, Yuangen; Ma, Chengzhang; Wang, Canjun; Yi, Ming; Gui, Rong

2018-02-01

We study the effects of multiplicative and additive cross-correlated sine-Wiener (CCSW) noises on the performance of sub-threshold periodic signal detection in the FitzHugh-Nagumo (FHN) neuron by calculating Fourier coefficients Q for measuring synchronization between sub-threshold input signal and the response of system. CCSW noises-induced transitions of electrical activity in the FHN neuron model can be observed. Moreover, the performance of sub-threshold periodic signal detection is achieved at moderate noise strength, cross-correlation time and cross-correlation strength of CCSW noises, which indicate the occurrence of CCSW noises-induced stochastic resonance. Furthermore, the performance of sub-threshold signal detection is strongly sensitive to cross-correlation time of CCSW noises. Therefore, the performance can be effectively controlled by regulating cross-correlation time of CCSW noises. These results provide a possible mechanism for amplifying or detecting the sub-threshold signal in the nervous system.

An ultrasonic pseudorandom signal-correlation system

NASA Astrophysics Data System (ADS)

Elias, C. M.

1980-01-01

A working ultrasonic pseudorandom signal-correlation system is described which, unlike ultrasonic random signal-correlation systems, does not require an acoustic delay line. Elimination of the delay line allows faster data acquisition and better range resolution. The system uses two identical shift-register type generators to produce pseudonoise bursts which are subsequences of a 65 535-bit complementary m-sequence. One generator produces the transmitted bursts while the other generates identical reference bursts which start at a variable correlation delay time after the transmitted bursts. The reference bursts are cross-correlated with the received echoes to obtain the approximate impulse response of the transducer/specimen system under test. Range sidelobes are reduced by transmitting and correlating many bursts at a given correlation delay before incrementing the delay. Signal-to-sidelobe ratios of greater than 47 dB have been obtained using this method. Limitations of the system due to sampling constraints and the pseudonoise power spectrum are discussed, and the system design and implementation are outlined. Results of experimental characterization of the system show that the pseudorandom signal-correlation system has approximately the same range resolution as a conventional pulse-echo system but can yield a significant increase in signal-to-noise ratio (SNR).

Humour processing in frontotemporal lobar degeneration: A behavioural and neuroanatomical analysis

PubMed Central

Clark, Camilla N.; Nicholas, Jennifer M.; Henley, Susie M.D.; Downey, Laura E.; Woollacott, Ione O.; Golden, Hannah L.; Fletcher, Phillip D.; Mummery, Catherine J.; Schott, Jonathan M.; Rohrer, Jonathan D.; Crutch, Sebastian J.; Warren, Jason D.

2015-01-01

Humour is a complex cognitive and emotional construct that is vulnerable in neurodegenerative diseases, notably the frontotemporal lobar degenerations. However, humour processing in these diseases has been little studied. Here we assessed humour processing in patients with behavioural variant frontotemporal dementia (n = 22, mean age 67 years, four female) and semantic dementia (n = 11, mean age 67 years, five female) relative to healthy individuals (n = 21, mean age 66 years, 11 female), using a joint cognitive and neuroanatomical approach. We created a novel neuropsychological test requiring a decision about the humorous intent of nonverbal cartoons, in which we manipulated orthogonally humour content and familiarity of depicted scenarios. Structural neuroanatomical correlates of humour detection were assessed using voxel-based morphometry. Assessing performance in a signal detection framework and after adjusting for standard measures of cognitive function, both patient groups showed impaired accuracy of humour detection in familiar and novel scenarios relative to healthy older controls (p < .001). Patient groups showed similar overall performance profiles; however the behavioural variant frontotemporal dementia group alone showed a significant advantage for detection of humour in familiar relative to novel scenarios (p = .045), suggesting that the behavioural variant syndrome may lead to particular difficulty decoding novel situations for humour, while semantic dementia produces a more general deficit of humour detection that extends to stock comedic situations. Humour detection accuracy was associated with grey matter volume in a distributed network including temporo-parietal junctional and anterior superior temporal cortices, with predominantly left-sided correlates of processing humour in familiar scenarios and right-sided correlates of processing novel humour. The findings quantify deficits of core cognitive operations underpinning humour processing in frontotemporal lobar degenerations and suggest a candidate brain substrate in cortical hub regions processing incongruity and semantic associations. Humour is a promising candidate tool with which to assess complex social signal processing in neurodegenerative disease. PMID:25973788

Evaluation of barely visible indentation damage (BVID) in CF/EP sandwich composites using guided wave signals

NASA Astrophysics Data System (ADS)

Mustapha, Samir; Ye, Lin; Dong, Xingjian; Alamdari, Mehrisadat Makki

2016-08-01

Barely visible indentation damage after quasi-static indentation in sandwich CF/EP composites was assessed using ultrasonic guided wave signals. Finite element analyses were conducted to investigate the interaction between guided waves and damage, further to assist in the selection process of the Lamb wave sensitive modes for debonding identification. Composite sandwich beams and panels structures were investigated. Using the beam structure, a damage index was defined based on the change in the peak magnitude of the captured wave signals before and after the indentation, and the damage index was correlated with the residual deformation (defined as the depth of the dent), that was further correlated with the amount of crushing within the core. Both A0 and S0 Lamb wave modes showed high sensitivity to the presence of barely visible indentation damage with residual deformation of 0.2 mm. Furthermore, barely visible indentation damage was assessed in composite sandwich panels after indenting to 3 and 5 mm, and the damage index was defined, based on (a) the peak magnitude of the wave signals before and after indentation or (b) the mismatch between the original and reconstructed wave signals based on a time-reversal algorithm, and was subsequently applied to locate the position of indentation.

Epileptic seizure detection in EEG signal using machine learning techniques.

PubMed

Jaiswal, Abeg Kumar; Banka, Haider

2018-03-01

Epilepsy is a well-known nervous system disorder characterized by seizures. Electroencephalograms (EEGs), which capture brain neural activity, can detect epilepsy. Traditional methods for analyzing an EEG signal for epileptic seizure detection are time-consuming. Recently, several automated seizure detection frameworks using machine learning technique have been proposed to replace these traditional methods. The two basic steps involved in machine learning are feature extraction and classification. Feature extraction reduces the input pattern space by keeping informative features and the classifier assigns the appropriate class label. In this paper, we propose two effective approaches involving subpattern based PCA (SpPCA) and cross-subpattern correlation-based PCA (SubXPCA) with Support Vector Machine (SVM) for automated seizure detection in EEG signals. Feature extraction was performed using SpPCA and SubXPCA. Both techniques explore the subpattern correlation of EEG signals, which helps in decision-making process. SVM is used for classification of seizure and non-seizure EEG signals. The SVM was trained with radial basis kernel. All the experiments have been carried out on the benchmark epilepsy EEG dataset. The entire dataset consists of 500 EEG signals recorded under different scenarios. Seven different experimental cases for classification have been conducted. The classification accuracy was evaluated using tenfold cross validation. The classification results of the proposed approaches have been compared with the results of some of existing techniques proposed in the literature to establish the claim.

Automatic Processing and Interpretation of Long Records of Endogenous Micro-Seismicity: the Case of the Super-Sauze Soft-Rock Landslide.

NASA Astrophysics Data System (ADS)

Provost, F.; Malet, J. P.; Hibert, C.; Doubre, C.

2017-12-01

The Super-Sauze landslide is a clay-rich landslide located the Southern French Alps. The landslide exhibits a complex pattern of deformation: a large number of rockfalls are observed in the 100 m height main scarp while the deformation of the upper part of the accumulated material is mainly affected by material shearing along stable in-situ crests. Several fissures are locally observed. The shallowest layer of the accumulated material tends to behave in a brittle manner but may undergo fluidization and/or rapid acceleration. Previous studies have demonstrated the presence of a rich endogenous micro-seismicity associated to the deformation of the landslide. However, the lack of long-term seismic records and suitable processing chains prevented a full interpretation of the links between the external forcings, the deformation and the recorded seismic signals. Since 2013, two permanent seismic arrays are installed in the upper part of the landslide. We here present the methodology adopted to process this dataset. The processing chain consists of a set of automated methods for automatic and robust detection, classification and location of the recorded seismicity. Thousands of events are detected and further automatically classified. The classification method is based on the description of the signal through attributes (e.g. waveform, spectral content properties). These attributes are used as inputs to classify the signal using a Random Forest machine-learning algorithm in four classes: endogenous micro-quakes, rockfalls, regional earthquakes and natural/anthropogenic noises. The endogenous landslide sources (i.e. micro-quake and rockfall) are further located. The location method is adapted to the type of event. The micro-quakes are located with a 3D velocity model derived from a seismic tomography campaign and an optimization of the first arrival picking with the inter-trace correlation of the P-wave arrivals. The rockfalls are located by optimizing the inter-trace correlation of the whole signal. We analyze the temporal relationships of the endogenous seismic events with rainfall and landslide displacements. Sub-families of landslide micro-quakes are also identified and an interpretation of their source mechanism is proposed from their signal properties and spatial location.

Technical Note: Kinect V2 surface filtering during gantry motion for radiotherapy applications.

PubMed

Nazir, Souha; Rihana, Sandy; Visvikis, Dimitris; Fayad, Hadi

2018-04-01

In radiotherapy, the Kinect V2 camera, has recently received a lot of attention concerning many clinical applications including patient positioning, respiratory motion tracking, and collision detection during the radiotherapy delivery phase. However, issues associated with such applications are related to some materials and surfaces reflections generating an offset in depth measurements especially during gantry motion. This phenomenon appears in particular when the collimator surface is observed by the camera; resulting in erroneous depth measurements, not only in Kinect surfaces itself, but also as a large peak when extracting a 1D respiratory signal from these data. In this paper, we proposed filtering techniques to reduce the noise effect in the Kinect-based 1D respiratory signal, using a trend removal filter, and in associated 2D surfaces, using a temporal median filter. Filtering process was validated using a phantom, in order to simulate a patient undergoing radiotherapy treatment while having the ground truth. Our results indicate a better correlation between the reference respiratory signal and its corresponding filtered signal (Correlation coefficient of 0.76) than that of the nonfiltered signal (Correlation coefficient of 0.13). Furthermore, surface filtering results show a decrease in the mean square distance error (85%) between the reference and the measured point clouds. This work shows a significant noise compensation and surface restitution after surface filtering and therefore a potential use of the Kinect V2 camera for different radiotherapy-based applications, such as respiratory tracking and collision detection. © 2018 American Association of Physicists in Medicine.

Inter-subject Functional Correlation Reveal a Hierarchical Organization of Extrinsic and Intrinsic Systems in the Brain.

PubMed

Ren, Yudan; Nguyen, Vinh Thai; Guo, Lei; Guo, Christine Cong

2017-09-07

The brain is constantly monitoring and integrating both cues from the external world and signals generated intrinsically. These extrinsically and intrinsically-driven neural processes are thought to engage anatomically distinct regions, which are thought to constitute the extrinsic and intrinsic systems of the brain. While the specialization of extrinsic and intrinsic system is evident in primary and secondary sensory cortices, a systematic mapping of the whole brain remains elusive. Here, we characterized the extrinsic and intrinsic functional activities in the brain during naturalistic movie-viewing. Using a novel inter-subject functional correlation (ISFC) analysis, we found that the strength of ISFC shifts along the hierarchical organization of the brain. Primary sensory cortices appear to have strong inter-subject functional correlation, consistent with their role in processing exogenous information, while heteromodal regions that attend to endogenous processes have low inter-subject functional correlation. Those brain systems with higher intrinsic tendency show greater inter-individual variability, likely reflecting the aspects of brain connectivity architecture unique to individuals. Our study presents a novel framework for dissecting extrinsically- and intrinsically-driven processes, as well as examining individual differences in brain function during naturalistic stimulation.

Multivariate analysis of correlation between electrophysiological and hemodynamic responses during cognitive processing

PubMed Central

Kujala, Jan; Sudre, Gustavo; Vartiainen, Johanna; Liljeström, Mia; Mitchell, Tom; Salmelin, Riitta

2014-01-01

Animal and human studies have frequently shown that in primary sensory and motor regions the BOLD signal correlates positively with high-frequency and negatively with low-frequency neuronal activity. However, recent evidence suggests that this relationship may also vary across cortical areas. Detailed knowledge of the possible spectral diversity between electrophysiological and hemodynamic responses across the human cortex would be essential for neural-level interpretation of fMRI data and for informative multimodal combination of electromagnetic and hemodynamic imaging data, especially in cognitive tasks. We applied multivariate partial least squares correlation analysis to MEG–fMRI data recorded in a reading paradigm to determine the correlation patterns between the data types, at once, across the cortex. Our results revealed heterogeneous patterns of high-frequency correlation between MEG and fMRI responses, with marked dissociation between lower and higher order cortical regions. The low-frequency range showed substantial variance, with negative and positive correlations manifesting at different frequencies across cortical regions. These findings demonstrate the complexity of the neurophysiological counterparts of hemodynamic fluctuations in cognitive processing. PMID:24518260

A study of phase defect measurement on EUV mask by multiple detectors CD-SEM

NASA Astrophysics Data System (ADS)

Yonekura, Isao; Hakii, Hidemitsu; Morisaki, Shinya; Murakawa, Tsutomu; Shida, Soichi; Kuribara, Masayuki; Iwai, Toshimichi; Matsumoto, Jun; Nakamura, Takayuki

2013-06-01

We have studied MVM (Multi Vision Metrology) -SEM® E3630 to measure 3D shape of defects. The four detectors (Detector A, B, C and D) are independently set up in symmetry for the primary electron beam axis. Signal processing of four direction images enables not only 2D (width) measurement but also 3D (height) measurement. At last PMJ, we have investigated the relation between the E3630's signal of programmed defect on MoSi-HT and defect height measured by AFM (Atomic Force Microscope). It was confirmed that height of integral profile by this tool is correlated with AFM. It was tested that E3630 has capability of observing multilayer defect on EUV. We have investigated correlation with AFM of width and depth or height of multilayer defect. As the result of observing programmed defects, it was confirmed that measurement result by E3630 is well correlated with AFM. And the function of 3D view image enables to show nm order defect.

A comprehensive statistical investigation of schlieren image velocimetry (SIV) using high-velocity helium jet

NASA Astrophysics Data System (ADS)

Biswas, Sayan; Qiao, Li

2017-03-01

A detailed statistical assessment of seedless velocity measurement using Schlieren Image Velocimetry (SIV) was explored using open source Robust Phase Correlation (RPC) algorithm. A well-known flow field, an axisymmetric turbulent helium jet, was analyzed near and intermediate region (0≤ x/d≤ 20) for two different Reynolds numbers, Re d = 11,000 and Re d = 22,000 using schlieren with horizontal knife-edge, schlieren with vertical knife-edge and shadowgraph technique, and the resulted velocity fields from SIV techniques were compared to traditional Particle Image Velocimetry (PIV) measurements. A novel, inexpensive, easy to setup two-camera SIV technique had been demonstrated to measure high-velocity turbulent jet, with jet exit velocities 304 m/s (Mach = 0.3) and 611 m/s (Mach = 0.6), respectively. Several image restoration and enhancement techniques were tested to improve signal to noise ratio (SNR) in schlieren and shadowgraph images. Processing and post-processing parameters for SIV techniques were examined in detail. A quantitative comparison between self-seeded SIV techniques and traditional PIV had been made using correlation statistics. While the resulted flow field from schlieren with horizontal knife-edge and shadowgraph showed excellent agreement with PIV measurements, schlieren with vertical knife-edge performed poorly. The performance of spatial cross-correlations at different jet locations using SIV techniques and PIV was evaluated. Turbulence quantities like turbulence intensity, mean velocity fields, Reynolds shear stress influenced spatial correlations and correlation plane SNR heavily. Several performance metrics such as primary peak ratio (PPR), peak to correlation energy (PCE), the probability distribution of signal and noise were used to compare capability and potential of different SIV techniques.

Temporal Precision of Neuronal Information in a Rapid Perceptual Judgment

PubMed Central

Ghose, Geoffrey M.; Harrison, Ian T.

2009-01-01

In many situations, such as pedestrians crossing a busy street or prey evading predators, rapid decisions based on limited perceptual information are critical for survival. The brevity of these perceptual judgments constrains how neuronal signals are integrated or pooled over time because the underlying sequence of processes, from sensation to perceptual evaluation to motor planning and execution, all occur within several hundred milliseconds. Because most previous physiological studies of these processes have relied on tasks requiring considerably longer temporal integration, the neuronal basis of such rapid decisions remains largely unexplored. In this study, we examine the temporal precision of neuronal activity associated with a rapid perceptual judgment. We find that the activity of individual neurons over tens of milliseconds can reliably convey information about sensory events and was well correlated with the animals' judgments. There was a strong correlation between sensory reliability and the correlation with behavioral choice, suggesting that rapid decisions were preferentially based on the most reliable sensory signals. We also find that a simple model in which the responses of a small number of individual neurons (<5) are summed can completely explain behavioral performance. These results suggest that neuronal circuits are sufficiently precise to allow for cognitive decisions to be based on small numbers of action potentials from highly reliable neurons. PMID:19109454

Temporal precision of neuronal information in a rapid perceptual judgment.

PubMed

Ghose, Geoffrey M; Harrison, Ian T

2009-03-01

In many situations, such as pedestrians crossing a busy street or prey evading predators, rapid decisions based on limited perceptual information are critical for survival. The brevity of these perceptual judgments constrains how neuronal signals are integrated or pooled over time because the underlying sequence of processes, from sensation to perceptual evaluation to motor planning and execution, all occur within several hundred milliseconds. Because most previous physiological studies of these processes have relied on tasks requiring considerably longer temporal integration, the neuronal basis of such rapid decisions remains largely unexplored. In this study, we examine the temporal precision of neuronal activity associated with a rapid perceptual judgment. We find that the activity of individual neurons over tens of milliseconds can reliably convey information about sensory events and was well correlated with the animals' judgments. There was a strong correlation between sensory reliability and the correlation with behavioral choice, suggesting that rapid decisions were preferentially based on the most reliable sensory signals. We also find that a simple model in which the responses of a small number of individual neurons (<5) are summed can completely explain behavioral performance. These results suggest that neuronal circuits are sufficiently precise to allow for cognitive decisions to be based on small numbers of action potentials from highly reliable neurons.

Top-down regulation of default mode activity in spatial visual attention

PubMed Central

Wen, Xiaotong; Liu, Yijun; Yao, Li; Ding, Mingzhou

2013-01-01

Dorsal anterior cingulate and bilateral anterior insula form a task control network (TCN) whose primary function includes initiating and maintaining task-level cognitive set and exerting top-down regulation of sensorimotor processing. The default mode network (DMN), comprising an anatomically distinct set of cortical areas, mediates introspection and self-referential processes. Resting-state data show that TCN and DMN interact. The functional ramifications of their interaction remain elusive. Recording fMRI data from human subjects performing a visual spatial attention task and correlating Granger causal influences with behavioral performance and blood-oxygen-level-dependent (BOLD) activity we report three main findings. First, causal influences from TCN to DMN, i.e., TCN→DMN, are positively correlated with behavioral performance. Second, causal influences from DMN to TCN, i.e., DMN→TCN, are negatively correlated with behavioral performance. Third, stronger DMN→TCN are associated with less elevated BOLD activity in TCN, whereas the relationship between TCN→DMN and DMN BOLD activity is unsystematic. These results suggest that during visual spatial attention, top-down signals from TCN to DMN regulate the activity in DMN to enhance behavioral performance, whereas signals from DMN to TCN, acting possibly as internal noise, interfere with task control, leading to degraded behavioral performance. PMID:23575842

Spaced antenna diversity in temperate latitude meteor burst systems operating near 40 MHz - Variation of signal cross-correlation coefficients with antenna separation

NASA Astrophysics Data System (ADS)

Cannon, Paul S.; Shukla, Anil K.; Lester, Mark

1993-04-01

We have studied 37-MHz signals received over an 800-km temperate latitude path using 400-W continuous wave transmissions. Signals collected during a 9-day period in February 1990 on two antennas at separations of 5, 10, and 20 lambda were analyzed. Three signal categories were identified (overdense, underdense, and not known (NK)) and cross-correlation coefficients between the signals received by the two antennas were calculated for each signal category. No spatial variation, and in particular no decrease, in average cross-correlation coefficient was observed for underdense or NK signals as the antenna spacing was increased from 5 to 20 lambda. At each antenna separation the cross-correlation coefficients of these two categories were strongly dependent on time. Overdense signals, however, showed no cross-correlation time dependency at 5 and 10 lambda, but there was a strong time dependency at 20 lambda. Recommendations are made in regard to the optimum antenna spacing for a meteor burst communication system using spaced antenna diversity.

Serotonergic antidepressants decrease hedonic signals but leave learning signals in the nucleus accumbens unaffected.

PubMed

Graf, Heiko; Metzger, Coraline D; Walter, Martin; Abler, Birgit

2016-01-06

Investigating the effects of serotonergic antidepressants on neural correlates of visual erotic stimulation revealed decreased reactivity within the dopaminergic reward network along with decreased subjective sexual functioning compared with placebo. However, a global dampening of the reward system under serotonergic drugs is not intuitive considering clinical observations of their beneficial effects in the treatment of depression. Particularly, learning signals as coded in prediction error processing within the dopaminergic reward system can be assumed to be rather enhanced as antidepressant drugs have been demonstrated to facilitate the efficacy of psychotherapeutic interventions relying on learning processes. Within the same study sample, we now explored the effects of serotonergic and dopaminergic/noradrenergic antidepressants on prediction error signals compared with placebo by functional MRI. A total of 17 healthy male participants (mean age: 25.4 years) were investigated under the administration of paroxetine, bupropion and placebo for 7 days each within a randomized, double-blind, within-subject cross-over design. During functional MRI, we used an established monetary incentive task to explore neural prediction error signals within the bilateral nucleus accumbens as region of interest within the dopaminergic reward system. In contrast to diminished neural activations and subjective sexual functioning under the serotonergic agent paroxetine under visual erotic stimulation, we revealed unaffected or even enhanced neural prediction error processing within the nucleus accumbens under this antidepressant along with unaffected behavioural processing. Our study provides evidence that serotonergic antidepressants facilitate prediction error signalling and may support suggestions of beneficial effects of these agents on reinforced learning as an essential element in behavioural psychotherapy.

Application of an improved maximum correlated kurtosis deconvolution method for fault diagnosis of rolling element bearings

NASA Astrophysics Data System (ADS)

Miao, Yonghao; Zhao, Ming; Lin, Jing; Lei, Yaguo

2017-08-01

The extraction of periodic impulses, which are the important indicators of rolling bearing faults, from vibration signals is considerably significance for fault diagnosis. Maximum correlated kurtosis deconvolution (MCKD) developed from minimum entropy deconvolution (MED) has been proven as an efficient tool for enhancing the periodic impulses in the diagnosis of rolling element bearings and gearboxes. However, challenges still exist when MCKD is applied to the bearings operating under harsh working conditions. The difficulties mainly come from the rigorous requires for the multi-input parameters and the complicated resampling process. To overcome these limitations, an improved MCKD (IMCKD) is presented in this paper. The new method estimates the iterative period by calculating the autocorrelation of the envelope signal rather than relies on the provided prior period. Moreover, the iterative period will gradually approach to the true fault period through updating the iterative period after every iterative step. Since IMCKD is unaffected by the impulse signals with the high kurtosis value, the new method selects the maximum kurtosis filtered signal as the final choice from all candidates in the assigned iterative counts. Compared with MCKD, IMCKD has three advantages. First, without considering prior period and the choice of the order of shift, IMCKD is more efficient and has higher robustness. Second, the resampling process is not necessary for IMCKD, which is greatly convenient for the subsequent frequency spectrum analysis and envelope spectrum analysis without resetting the sampling rate. Third, IMCKD has a significant performance advantage in diagnosing the bearing compound-fault which expands the application range. Finally, the effectiveness and superiority of IMCKD are validated by a number of simulated bearing fault signals and applying to compound faults and single fault diagnosis of a locomotive bearing.

Dissociating speech perception and comprehension at reduced levels of awareness

PubMed Central

Davis, Matthew H.; Coleman, Martin R.; Absalom, Anthony R.; Rodd, Jennifer M.; Johnsrude, Ingrid S.; Matta, Basil F.; Owen, Adrian M.; Menon, David K.

2007-01-01

We used functional MRI and the anesthetic agent propofol to assess the relationship among neural responses to speech, successful comprehension, and conscious awareness. Volunteers were scanned while listening to sentences containing ambiguous words, matched sentences without ambiguous words, and signal-correlated noise (SCN). During three scanning sessions, participants were nonsedated (awake), lightly sedated (a slowed response to conversation), and deeply sedated (no conversational response, rousable by loud command). Bilateral temporal-lobe responses for sentences compared with signal-correlated noise were observed at all three levels of sedation, although prefrontal and premotor responses to speech were absent at the deepest level of sedation. Additional inferior frontal and posterior temporal responses to ambiguous sentences provide a neural correlate of semantic processes critical for comprehending sentences containing ambiguous words. However, this additional response was absent during light sedation, suggesting a marked impairment of sentence comprehension. A significant decline in postscan recognition memory for sentences also suggests that sedation impaired encoding of sentences into memory, with left inferior frontal and temporal lobe responses during light sedation predicting subsequent recognition memory. These findings suggest a graded degradation of cognitive function in response to sedation such that “higher-level” semantic and mnemonic processes can be impaired at relatively low levels of sedation, whereas perceptual processing of speech remains resilient even during deep sedation. These results have important implications for understanding the relationship between speech comprehension and awareness in the healthy brain in patients receiving sedation and in patients with disorders of consciousness. PMID:17938125

Power Aware Signal Processing Environment (PASPE) for PAC/C

DTIC Science & Technology

2003-02-01

vs. FFT Size For our implementation , the Annapolis FFT core was radix-256, and therefore the smallest PN code length that could be processed was the...PN-64. A C- code version of correlate was compared to the FPGA 61 implementation . The results in Figure 68 show that for a PN-1024, the...12a. DISTRIBUTION / AVAILABILITY STATEMENT APPROVED FOR PUBLIC RELEASE; DISTRIBUTION UNLIMITED. 12b. DISTRIBUTION CODE 13. ABSTRACT (Maximum

Disentangling neural representations of value and salience in the human brain

PubMed Central

Kahnt, Thorsten; Park, Soyoung Q; Haynes, John-Dylan; Tobler, Philippe N.

2014-01-01

A large body of evidence has implicated the posterior parietal and orbitofrontal cortex in the processing of value. However, value correlates perfectly with salience when appetitive stimuli are investigated in isolation. Accordingly, considerable uncertainty has remained about the precise nature of the previously identified signals. In particular, recent evidence suggests that neurons in the primate parietal cortex signal salience instead of value. To investigate neural signatures of value and salience, here we apply multivariate (pattern-based) analyses to human functional MRI data acquired during a noninstrumental outcome-prediction task involving appetitive and aversive outcomes. Reaction time data indicated additive and independent effects of value and salience. Critically, we show that multivoxel ensemble activity in the posterior parietal cortex encodes predicted value and salience in superior and inferior compartments, respectively. These findings reinforce the earlier reports of parietal value signals and reconcile them with the recent salience report. Moreover, we find that multivoxel patterns in the orbitofrontal cortex correlate with value. Importantly, the patterns coding for the predicted value of appetitive and aversive outcomes are similar, indicating a common neural scale for appetite and aversive values in the orbitofrontal cortex. Thus orbitofrontal activity patterns satisfy a basic requirement for a neural value signal. PMID:24639493

Fast Face-Recognition Optical Parallel Correlator Using High Accuracy Correlation Filter

NASA Astrophysics Data System (ADS)

Watanabe, Eriko; Kodate, Kashiko

2005-11-01

We designed and fabricated a fully automatic fast face recognition optical parallel correlator [E. Watanabe and K. Kodate: Appl. Opt. 44 (2005) 5666] based on the VanderLugt principle. The implementation of an as-yet unattained ultra high-speed system was aided by reconfiguring the system to make it suitable for easier parallel processing, as well as by composing a higher accuracy correlation filter and high-speed ferroelectric liquid crystal-spatial light modulator (FLC-SLM). In running trial experiments using this system (dubbed FARCO), we succeeded in acquiring remarkably low error rates of 1.3% for false match rate (FMR) and 2.6% for false non-match rate (FNMR). Given the results of our experiments, the aim of this paper is to examine methods of designing correlation filters and arranging database image arrays for even faster parallel correlation, underlining the issues of calculation technique, quantization bit rate, pixel size and shift from optical axis. The correlation filter has proved its excellent performance and higher precision than classical correlation and joint transform correlator (JTC). Moreover, arrangement of multi-object reference images leads to 10-channel correlation signals, as sharply marked as those of a single channel. This experiment result demonstrates great potential for achieving the process speed of 10000 face/s.

Imaging Subsurface Structure of Central Zagros Zone/Iran Using Ambient Noise Tomography

NASA Astrophysics Data System (ADS)

Vahidravesh, Shaghayegh; Pakzad, Mehrdad, ,, Dr.; Hatami, Mohammad Reza, ,, Dr.

2017-04-01

The Central Zagros zone, of west Iran & east Iraq, is surrounded by many active faults (including Main Zagros Reversed Fault, Main Recent Fault, High Zagros Fault, Zagros Fold, & Thrust Belt). Recent studies show that cross-correlation of a long-term ambient seismic noise data recorded in station-pair, includes important information regarding empirical Green's functions (EGFs) between stations. Hence, ambient seismic noise carries valuable information of the wave propagation path (which can be extracted). The 2D model of surface waves (Rayleigh & Love) velocities for the studied area is obtained by seismic ambient noise tomography (ANT) method. Throughout this research, we use continuous records of all three vertical, radial, and tangential components (obtained by rotation) recorded by IRSC (Iranian Seismological Center) and IIEES (International Institute of Earthquake Engineering) networks for this area of interest. The IRSC & IIEES networks are equipped by SS-1 kinematics and Guralp CMG-3T sensors respectively. Data of 20 stations were used for 12 months from 2014/Nov. to 2015/Nov. The performed data processing is similar to the one, put into words in detail by Bensen et al. (2007) including the processed daily base data. Mean, trend, and instrument response were removed and the data were decimated to 5 sps (sample per second) to reduce the amount of storage space and computational time required. We then applied merge to handle data gaps. One-bit time-domain normalization was also applied to suppress the influence of instrument irregularities and earthquake signals followed by spectral (frequency-domain) normalization between 0.05-0.2 Hz (period 5-20 sec). After cross-correlation (processing step), we perform rms stacking (new approach of stacking) to stack many cross-correlation functions based on the highest energy in a time interval which we accordingly anticipate to receive Rayleigh & Love waves fundamental modes. To evaluate quality of the stacking process stability quantitatively, we calculate signal-to-noise ratio (SNR), defined as a ratio of the peak amplitude within a time window to the root-mean-square of noise trailing the signal arrival window (Bensen et al., 2007), for each cross-correlation. The cross-correlated time-series is equivalent to the Green's functions between pairs of receivers. We then apply multiple phase-matched filter method of Herrmann (2005) to measure the correct group velocity dispersion of the interferometric surface waves. Eventually, we apply fast marching surface wave tomography (FMST), the iterative nonlinear inversion package developed by Rawlinson, 2005, to extract the velocity model of shallow structure in Central Zagros zone /Iran.

Quantitative measurement of intervertebral disc signal using MRI.

PubMed

Niemeläinen, R; Videman, T; Dhillon, S S; Battié, M C

2008-03-01

To investigate the spinal cord as an alternative intra-body reference to cerebrospinal fluid (CSF) in evaluating thoracic disc signal intensity. T2-weighted magnetic resonance imaging (MRI) images of T6-T12 were obtained using 1.5 T machines for a population-based sample of 523 men aged 35-70 years. Quantitative data on the signal intensities were acquired using an image analysis program (SpEx). A random sample of 30 subjects and intraclass correlation coefficients (ICC) were used to examine the repeatability of the spinal cord measurements. The validity of using the spinal cord as a reference was examined by correlating cord and CSF samples. Finally, thoracic disc signal was validated by correlating it with age without adjustment and adjusting for either cord or CSF. Pearson's r was used for correlational analyses. The repeatability of the spinal cord signal measurements was extremely high (>or=0.99). The correlations between the signals of spinal cord and CSF by level were all above 0.9. The spinal cord-adjusted disc signal and age correlated similarly with CSF-adjusted disc signal and age (r=-0.30 to -0.40 versus r=-0.26 to -0.36). Adjacent spinal cord is a good alternative reference to the current reference standard, CSF, for quantitative measurements of disc signal intensity. Clearly fewer levels were excluded when using spinal cord as compared to CSF due to missing reference samples.

Challenges in Extracting Information From Large Hydrogeophysical-monitoring Datasets

NASA Astrophysics Data System (ADS)

Day-Lewis, F. D.; Slater, L. D.; Johnson, T.

2012-12-01

Over the last decade, new automated geophysical data-acquisition systems have enabled collection of increasingly large and information-rich geophysical datasets. Concurrent advances in field instrumentation, web services, and high-performance computing have made real-time processing, inversion, and visualization of large three-dimensional tomographic datasets practical. Geophysical-monitoring datasets have provided high-resolution insights into diverse hydrologic processes including groundwater/surface-water exchange, infiltration, solute transport, and bioremediation. Despite the high information content of such datasets, extraction of quantitative or diagnostic hydrologic information is challenging. Visual inspection and interpretation for specific hydrologic processes is difficult for datasets that are large, complex, and (or) affected by forcings (e.g., seasonal variations) unrelated to the target hydrologic process. New strategies are needed to identify salient features in spatially distributed time-series data and to relate temporal changes in geophysical properties to hydrologic processes of interest while effectively filtering unrelated changes. Here, we review recent work using time-series and digital-signal-processing approaches in hydrogeophysics. Examples include applications of cross-correlation, spectral, and time-frequency (e.g., wavelet and Stockwell transforms) approaches to (1) identify salient features in large geophysical time series; (2) examine correlation or coherence between geophysical and hydrologic signals, even in the presence of non-stationarity; and (3) condense large datasets while preserving information of interest. Examples demonstrate analysis of large time-lapse electrical tomography and fiber-optic temperature datasets to extract information about groundwater/surface-water exchange and contaminant transport.

An improved method based on wavelet coefficient correlation to filter noise in Doppler ultrasound blood flow signals

NASA Astrophysics Data System (ADS)

Wan, Renzhi; Zu, Yunxiao; Shao, Lin

2018-04-01

The blood echo signal maintained through Medical ultrasound Doppler devices would always include vascular wall pulsation signal .The traditional method to de-noise wall signal is using high-pass filter, which will also remove the lowfrequency part of the blood flow signal. Some scholars put forward a method based on region selective reduction, which at first estimates of the wall pulsation signals and then removes the wall signal from the mixed signal. Apparently, this method uses the correlation between wavelet coefficients to distinguish blood signal from wall signal, but in fact it is a kind of wavelet threshold de-noising method, whose effect is not so much ideal. In order to maintain a better effect, this paper proposes an improved method based on wavelet coefficient correlation to separate blood signal and wall signal, and simulates the algorithm by computer to verify its validity.

Feedforward and recurrent processing in scene segmentation: electroencephalography and functional magnetic resonance imaging.

PubMed

Scholte, H Steven; Jolij, Jacob; Fahrenfort, Johannes J; Lamme, Victor A F

2008-11-01

In texture segregation, an example of scene segmentation, we can discern two different processes: texture boundary detection and subsequent surface segregation [Lamme, V. A. F., Rodriguez-Rodriguez, V., & Spekreijse, H. Separate processing dynamics for texture elements, boundaries and surfaces in primary visual cortex of the macaque monkey. Cerebral Cortex, 9, 406-413, 1999]. Neural correlates of texture boundary detection have been found in monkey V1 [Sillito, A. M., Grieve, K. L., Jones, H. E., Cudeiro, J., & Davis, J. Visual cortical mechanisms detecting focal orientation discontinuities. Nature, 378, 492-496, 1995; Grosof, D. H., Shapley, R. M., & Hawken, M. J. Macaque-V1 neurons can signal illusory contours. Nature, 365, 550-552, 1993], but whether surface segregation occurs in monkey V1 [Rossi, A. F., Desimone, R., & Ungerleider, L. G. Contextual modulation in primary visual cortex of macaques. Journal of Neuroscience, 21, 1698-1709, 2001; Lamme, V. A. F. The neurophysiology of figure ground segregation in primary visual-cortex. Journal of Neuroscience, 15, 1605-1615, 1995], and whether boundary detection or surface segregation signals can also be measured in human V1, is more controversial [Kastner, S., De Weerd, P., & Ungerleider, L. G. Texture segregation in the human visual cortex: A functional MRI study. Journal of Neurophysiology, 83, 2453-2457, 2000]. Here we present electroencephalography (EEG) and functional magnetic resonance imaging data that have been recorded with a paradigm that makes it possible to differentiate between boundary detection and scene segmentation in humans. In this way, we were able to show with EEG that neural correlates of texture boundary detection are first present in the early visual cortex around 92 msec and then spread toward the parietal and temporal lobes. Correlates of surface segregation first appear in temporal areas (around 112 msec) and from there appear to spread to parietal, and back to occipital areas. After 208 msec, correlates of surface segregation and boundary detection also appear in more frontal areas. Blood oxygenation level-dependent magnetic resonance imaging results show correlates of boundary detection and surface segregation in all early visual areas including V1. We conclude that texture boundaries are detected in a feedforward fashion and are represented at increasing latencies in higher visual areas. Surface segregation, on the other hand, is represented in "reverse hierarchical" fashion and seems to arise from feedback signals toward early visual areas such as V1.

Neural Correlates of Perceptual Narrowing in Cross-Species Face-Voice Matching

ERIC Educational Resources Information Center

Grossmann, Tobias; Missana, Manuela; Friederici, Angela D.; Ghazanfar, Asif A.

2012-01-01

Integrating the multisensory features of talking faces is critical to learning and extracting coherent meaning from social signals. While we know much about the development of these capacities at the behavioral level, we know very little about the underlying neural processes. One prominent behavioral milestone of these capacities is the perceptual…

Dynamic Singularity Spectrum Distribution of Sea Clutter

NASA Astrophysics Data System (ADS)

Xiong, Gang; Yu, Wenxian; Zhang, Shuning

2015-12-01

The fractal and multifractal theory have provided new approaches for radar signal processing and target-detecting under the background of ocean. However, the related research mainly focuses on fractal dimension or multifractal spectrum (MFS) of sea clutter. In this paper, a new dynamic singularity analysis method of sea clutter using MFS distribution is developed, based on moving detrending analysis (DMA-MFSD). Theoretically, we introduce the time information by using cyclic auto-correlation of sea clutter. For transient correlation series, the instantaneous singularity spectrum based on multifractal detrending moving analysis (MF-DMA) algorithm is calculated, and the dynamic singularity spectrum distribution of sea clutter is acquired. In addition, we analyze the time-varying singularity exponent ranges and maximum position function in DMA-MFSD of sea clutter. For the real sea clutter data, we analyze the dynamic singularity spectrum distribution of real sea clutter in level III sea state, and conclude that the radar sea clutter has the non-stationary and time-varying scale characteristic and represents the time-varying singularity spectrum distribution based on the proposed DMA-MFSD method. The DMA-MFSD will also provide reference for nonlinear dynamics and multifractal signal processing.

Monitoring temperatures in coal conversion and combustion processes via ultrasound

NASA Astrophysics Data System (ADS)

Gopalsami, N.; Raptis, A. C.; Mulcahey, T. P.

1980-02-01

The state of the art of instrumentation for monitoring temperatures in coal conversion and combustion systems is examined. The instrumentation types studied include thermocouples, radiation pyrometers, and acoustical thermometers. The capabilities and limitations of each type are reviewed. A feasibility study of the ultrasonic thermometry is described. A mathematical model of a pulse-echo ultrasonic temperature measurement system is developed using linear system theory. The mathematical model lends itself to the adaptation of generalized correlation techniques for the estimation of propagation delays. Computer simulations are made to test the efficacy of the signal processing techniques for noise-free as well as noisy signals. Based on the theoretical study, acoustic techniques to measure temperature in reactors and combustors are feasible.

Relationship between central auditory processing and reading skills: preliminary observations in Hebrew speaking children.

PubMed

Cohen-Mimran, Ravit; Sapir, Shimon

2008-01-01

To assess the relationships between central auditory processing (CAP) of sinusoidally modulated speech-like and non-speech acoustic signals and reading skills in shallow (pointed) and deep (unpointed) Hebrew orthographies. Twenty unselected fifth-grade Hebrew speakers performed a rate change detection (RCD) task using the aforementioned acoustic signals. They also performed reading and general ability (IQ) tests. After controlling for general ability, RCD tasks contributed a significant unique variance to the decoding skills. In addition, there was a fairly strong correlation between the score on the RCD with the speech-like stimuli and the unpointed text reading score. CAP abilities may affect reading skills, depending on the nature of orthography (deep vs shallow), at least in the Hebrew language.

Image stitching and image reconstruction of intestines captured using radial imaging capsule endoscope

NASA Astrophysics Data System (ADS)

Ou-Yang, Mang; Jeng, Wei-De; Wu, Yin-Yi; Dung, Lan-Rong; Wu, Hsien-Ming; Weng, Ping-Kuo; Huang, Ker-Jer; Chiu, Luan-Jiau

2012-05-01

This study investigates image processing using the radial imaging capsule endoscope (RICE) system. First, an experimental environment is established in which a simulated object has a shape that is similar to a cylinder, such that a triaxial platform can be used to push the RICE into the sample and capture radial images. Then four algorithms (mean absolute error, mean square error, Pearson correlation coefficient, and deformation processing) are used to stitch the images together. The Pearson correlation coefficient method is the most effective algorithm because it yields the highest peak signal-to-noise ratio, higher than 80.69 compared to the original image. Furthermore, a living animal experiment is carried out. Finally, the Pearson correlation coefficient method and vector deformation processing are used to stitch the images that were captured in the living animal experiment. This method is very attractive because unlike the other methods, in which two lenses are required to reconstruct the geometrical image, RICE uses only one lens and one mirror.

Initial Validation for the Estimation of Resting-State fMRI Effective Connectivity by a Generalization of the Correlation Approach.

PubMed

Xu, Nan; Spreng, R Nathan; Doerschuk, Peter C

2017-01-01

Resting-state functional MRI (rs-fMRI) is widely used to noninvasively study human brain networks. Network functional connectivity is often estimated by calculating the timeseries correlation between blood-oxygen-level dependent (BOLD) signal from different regions of interest (ROIs). However, standard correlation cannot characterize the direction of information flow between regions. In this paper, we introduce and test a new concept, prediction correlation, to estimate effective connectivity in functional brain networks from rs-fMRI. In this approach, the correlation between two BOLD signals is replaced by a correlation between one BOLD signal and a prediction of this signal via a causal system driven by another BOLD signal. Three validations are described: (1) Prediction correlation performed well on simulated data where the ground truth was known, and outperformed four other methods. (2) On simulated data designed to display the "common driver" problem, prediction correlation did not introduce false connections between non-interacting driven ROIs. (3) On experimental data, prediction correlation recovered the previously identified network organization of human brain. Prediction correlation scales well to work with hundreds of ROIs, enabling it to assess whole brain interregional connectivity at the single subject level. These results provide an initial validation that prediction correlation can capture the direction of information flow and estimate the duration of extended temporal delays in information flow between regions of interest ROIs based on BOLD signal. This approach not only maintains the high sensitivity to network connectivity provided by the correlation analysis, but also performs well in the estimation of causal information flow in the brain.

A hybrid method based on Band Pass Filter and Correlation Algorithm to improve debris sensor capacity

NASA Astrophysics Data System (ADS)

Hong, Wei; Wang, Shaoping; Liu, Haokuo; Tomovic, Mileta M.; Chao, Zhang

2017-01-01

The inductive debris detection is an effective method for monitoring mechanical wear, and could be used to prevent serious accidents. However, debris detection during early phase of mechanical wear, when small debris (<100 um) is generated, requires that the sensor has high sensitivity with respect to background noise. In order to detect smaller debris by existing sensors, this paper presents a hybrid method which combines Band Pass Filter and Correlation Algorithm to improve sensor signal-to-noise ratio (SNR). The simulation results indicate that the SNR will be improved at least 2.67 times after signal processing. In other words, this method ensures debris identification when the sensor's SNR is bigger than -3 dB. Thus, smaller debris will be detected in the same SNR. Finally, effectiveness of the proposed method is experimentally validated.

Non-stationarity and cross-correlation effects in the MHD solar activity

NASA Astrophysics Data System (ADS)

Demin, S. A.; Nefedyev, Y. A.; Andreev, A. O.; Demina, N. Y.; Timashev, S. F.

2018-01-01

The analysis of turbulent processes in sunspots and pores which are self-organizing long-lived magnetic structures is a complicated and not yet solved problem. The present work focuses on studying such magneto-hydrodynamic (MHD) formations on the basis of flicker-noise spectroscopy using a new method of multi-parametric analysis. The non-stationarity and cross-correlation effects taking place in solar activity dynamics are considered. The calculated maximum values of non-stationarity factor may become precursors of significant restructuring in solar magnetic activity. The introduced cross-correlation functions enable us to judge synchronization effects between the signals of various solar activity indicators registered simultaneously.

Continuous quantum measurement with independent detector cross correlations.

PubMed

Jordan, Andrew N; Büttiker, Markus

2005-11-25

We investigate the advantages of using two independent, linear detectors for continuous quantum measurement. For single-shot measurement, the detection process may be quantum limited if the detectors are twins. For weak continuous measurement, cross correlations allow a violation of the Korotkov-Averin bound for the detector's signal-to-noise ratio. The joint weak measurement of noncommuting observables is also investigated, and we find the cross correlation changes sign as a function of frequency, reflecting a crossover from incoherent relaxation to coherent, out of phase oscillations. Our results are applied to a double quantum-dot charge qubit, simultaneously measured by two quantum point contacts.

Assessing co-regulation of directly linked genes in biological networks using microarray time series analysis.

PubMed

Del Sorbo, Maria Rosaria; Balzano, Walter; Donato, Michele; Draghici, Sorin

2013-11-01

Differential expression of genes detected with the analysis of high throughput genomic experiments is a commonly used intermediate step for the identification of signaling pathways involved in the response to different biological conditions. The impact analysis was the first approach for the analysis of signaling pathways involved in a certain biological process that was able to take into account not only the magnitude of the expression change of the genes but also the topology of signaling pathways including the type of each interactions between the genes. In the impact analysis, signaling pathways are represented as weighted directed graphs with genes as nodes and the interactions between genes as edges. Edges weights are represented by a β factor, the regulatory efficiency, which is assumed to be equal to 1 in inductive interactions between genes and equal to -1 in repressive interactions. This study presents a similarity analysis between gene expression time series aimed to find correspondences with the regulatory efficiency, i.e. the β factor as found in a widely used pathway database. Here, we focused on correlations among genes directly connected in signaling pathways, assuming that the expression variations of upstream genes impact immediately downstream genes in a short time interval and without significant influences by the interactions with other genes. Time series were processed using three different similarity metrics. The first metric is based on the bit string matching; the second one is a specific application of the Dynamic Time Warping to detect similarities even in presence of stretching and delays; the third one is a quantitative comparative analysis resulting by an evaluation of frequency domain representation of time series: the similarity metric is the correlation between dominant spectral components. These three approaches are tested on real data and pathways, and a comparison is performed using Information Retrieval benchmark tools, indicating the frequency approach as the best similarity metric among the three, for its ability to detect the correlation based on the correspondence of the most significant frequency components. Copyright © 2013. Published by Elsevier Ireland Ltd.

Artificial Neural Network-Based Early-Age Concrete Strength Monitoring Using Dynamic Response Signals.

PubMed

Kim, Junkyeong; Lee, Chaggil; Park, Seunghee

2017-06-07

Concrete is one of the most common materials used to construct a variety of civil infrastructures. However, since concrete might be susceptible to brittle fracture, it is essential to confirm the strength of concrete at the early-age stage of the curing process to prevent unexpected collapse. To address this issue, this study proposes a novel method to estimate the early-age strength of concrete, by integrating an artificial neural network algorithm with a dynamic response measurement of the concrete material. The dynamic response signals of the concrete, including both electromechanical impedances and guided ultrasonic waves, are obtained from an embedded piezoelectric sensor module. The cross-correlation coefficient of the electromechanical impedance signals and the amplitude of the guided ultrasonic wave signals are selected to quantify the variation in dynamic responses according to the strength of the concrete. Furthermore, an artificial neural network algorithm is used to verify a relationship between the variation in dynamic response signals and concrete strength. The results of an experimental study confirm that the proposed approach can be effectively applied to estimate the strength of concrete material from the early-age stage of the curing process.

Artificial Neural Network-Based Early-Age Concrete Strength Monitoring Using Dynamic Response Signals

PubMed Central

Kim, Junkyeong; Lee, Chaggil; Park, Seunghee

2017-01-01

Concrete is one of the most common materials used to construct a variety of civil infrastructures. However, since concrete might be susceptible to brittle fracture, it is essential to confirm the strength of concrete at the early-age stage of the curing process to prevent unexpected collapse. To address this issue, this study proposes a novel method to estimate the early-age strength of concrete, by integrating an artificial neural network algorithm with a dynamic response measurement of the concrete material. The dynamic response signals of the concrete, including both electromechanical impedances and guided ultrasonic waves, are obtained from an embedded piezoelectric sensor module. The cross-correlation coefficient of the electromechanical impedance signals and the amplitude of the guided ultrasonic wave signals are selected to quantify the variation in dynamic responses according to the strength of the concrete. Furthermore, an artificial neural network algorithm is used to verify a relationship between the variation in dynamic response signals and concrete strength. The results of an experimental study confirm that the proposed approach can be effectively applied to estimate the strength of concrete material from the early-age stage of the curing process. PMID:28590456

Tool Condition Monitoring in Micro-End Milling using wavelets

NASA Astrophysics Data System (ADS)

Dubey, N. K.; Roushan, A.; Rao, U. S.; Sandeep, K.; Patra, K.

2018-04-01

In this work, Tool Condition Monitoring (TCM) strategy is developed for micro-end milling of titanium alloy and mild steel work-pieces. Full immersion slot milling experiments are conducted using a solid tungsten carbide end mill for more than 1900 s to have reasonable amount of tool wear. During the micro-end milling process, cutting force and vibration signals are acquired using Kistler piezo-electric 3-component force dynamometer (9256C2) and accelerometer (NI cDAQ-9188) respectively. The force components and the vibration signals are processed using Discrete Wavelet Transformation (DWT) in both time and frequency window. 5-level wavelet packet decomposition using Db-8 wavelet is carried out and the detailed coefficients D1 to D5 for each of the signals are obtained. The results of the wavelet transformation are correlated with the tool wear. In case of vibration signals, de-noising is done for higher frequency components (D1) and force signals were de-noised for lower frequency components (D5). Increasing value of MAD (Mean Absolute Deviation) of the detail coefficients for successive channels depicted tool wear. The predictions of the tool wear are confirmed from the actual wear observed in the SEM of the worn tool.

Optical Correlation Techniques In Fluid Dynamics

NASA Astrophysics Data System (ADS)

Schatzel, K.; Schulz-DuBois, E. O.; Vehrenkamp, R.

1981-05-01

Three flow measurement techniques make use of fast digital correlators. (1) Most widely spread is photon correlation velocimetry using crossed laser beams and detecting Doppler shifted light scattered by small particles in the flow. Depending on the processing of the photon correlogram, this technique yields mean velocity, turbulence level, or even the detailed probability distribution of one velocity component. An improved data processing scheme is demonstrated on laminar vortex flow in a curved channel. (2) Rate correlation based upon threshold crossings of a high pass filtered laser Doppler signal can he used to obtain velocity correlation functions. The most powerful setup developed in our laboratory uses a phase locked loop type tracker and a multibit correlator to analyse time-dependent Taylor vortex flow. With two optical systems and trackers, crosscorrelation functions reveal phase relations between different vortices. (3) Making use of refractive index fluctuations (e. g. in two phase flows) instead of scattering particles, interferometry with bidirectional fringe counting and digital correlation and probability analysis constitute a new quantitative technique related to classical Schlieren methods. Measurements on a mixing flow of heated and cold air contribute new ideas to the theory of turbulent random phase screens.

Evaluation of interaction dynamics of concurrent processes

NASA Astrophysics Data System (ADS)

Sobecki, Piotr; Białasiewicz, Jan T.; Gross, Nicholas

2017-03-01

The purpose of this paper is to present the wavelet tools that enable the detection of temporal interactions of concurrent processes. In particular, the determination of interaction coherence of time-varying signals is achieved using a complex continuous wavelet transform. This paper has used electrocardiogram (ECG) and seismocardiogram (SCG) data set to show multiple continuous wavelet analysis techniques based on Morlet wavelet transform. MATLAB Graphical User Interface (GUI), developed in the reported research to assist in quick and simple data analysis, is presented. These software tools can discover the interaction dynamics of time-varying signals, hence they can reveal their correlation in phase and amplitude, as well as their non-linear interconnections. The user-friendly MATLAB GUI enables effective use of the developed software what enables to load two processes under investigation, make choice of the required processing parameters, and then perform the analysis. The software developed is a useful tool for researchers who have a need for investigation of interaction dynamics of concurrent processes.

Characterizing the EEG correlates of exploratory behavior.

PubMed

Bourdaud, Nicolas; Chavarriaga, Ricardo; Galan, Ferran; Millan, José Del R

2008-12-01

This study aims to characterize the electroencephalography (EEG) correlates of exploratory behavior. Decision making in an uncertain environment raises a conflict between two opposing needs: gathering information about the environment and exploiting this knowledge in order to optimize the decision. Exploratory behavior has already been studied using functional magnetic resonance imaging (fMRI). Based on a usual paradigm in reinforcement learning, this study has shown bilateral activation in the frontal and parietal cortex. To our knowledge, no previous study has been done on it using EEG. The study of the exploratory behavior using EEG signals raises two difficulties. First, the labels of trial as exploitation or exploration cannot be directly derived from the subject action. In order to access this information, a model of how the subject makes his decision must be built. The exploration related information can be then derived from it. Second, because of the complexity of the task, its EEG correlates are not necessarily time locked with the action. So the EEG processing methods used should be designed in order to handle signals that shift in time across trials. Using the same experimental protocol as the fMRI study, results show that the bilateral frontal and parietal areas are also the most discriminant. This strongly suggests that the EEG signal also conveys information about the exploratory behavior.

Statistical properties of a filtered Poisson process with additive random noise: distributions, correlations and moment estimation

NASA Astrophysics Data System (ADS)

Theodorsen, A.; E Garcia, O.; Rypdal, M.

2017-05-01

Filtered Poisson processes are often used as reference models for intermittent fluctuations in physical systems. Such a process is here extended by adding a noise term, either as a purely additive term to the process or as a dynamical term in a stochastic differential equation. The lowest order moments, probability density function, auto-correlation function and power spectral density are derived and used to identify and compare the effects of the two different noise terms. Monte-Carlo studies of synthetic time series are used to investigate the accuracy of model parameter estimation and to identify methods for distinguishing the noise types. It is shown that the probability density function and the three lowest order moments provide accurate estimations of the model parameters, but are unable to separate the noise types. The auto-correlation function and the power spectral density also provide methods for estimating the model parameters, as well as being capable of identifying the noise type. The number of times the signal crosses a prescribed threshold level in the positive direction also promises to be able to differentiate the noise type.

Functional MRI of facial emotion processing in left temporal lobe epilepsy.

PubMed

Szaflarski, Jerzy P; Allendorfer, Jane B; Heyse, Heidi; Mendoza, Lucy; Szaflarski, Basia A; Cohen, Nancy

2014-03-01

Temporal lobe epilepsy (TLE) may negatively affect the ability to recognize emotions. This study aimed to determine the cortical correlates of facial emotion processing (happy, sad, fearful, and neutral) in patients with well-characterized left TLE (LTLE) and to examine the effect of seizure control on emotion processing. We enrolled 34 consecutive patients with LTLE and 30 matched healthy control (HC) subjects. Participants underwent functional MRI (fMRI) with an event-related facial emotion recognition task. The seizures of seventeen patients were controlled (no seizure in at least 3months; LTLE-sz), and 17 continued to experience frequent seizures (LTLE+sz). Mood was assessed with the Beck Depression Inventory (BDI) and the Profile of Mood States (POMS). There were no differences in demographic characteristics and measures of mood between HC subjects and patients with LTLE. In patients with LTLE, fMRI showed decreased blood oxygenation level dependent (BOLD) signal in the hippocampus/parahippocampus and cerebellum in processing of happy faces and increased BOLD signal in occipital regions in response to fearful faces. Comparison of groups with LTLE+sz and LTLE-sz showed worse BDI and POMS scores in LTLE+sz (all p<0.05) except for POMS tension/anxiety (p=0.067). Functional MRI revealed increased BOLD signal in patients with LTLE+sz in the left precuneus and left parahippocampus for "fearful" faces and in the left periarcheocortex for "neutral" faces. There was a correlation between the fMRI and Total Mood Disturbance in the left precuneus in LTLE-sz (p=0.019) and in LTLE+sz (p=0.018). Overall, LTLE appears to have a relatively minor effect on the cortical underpinnings of facial emotion processing, while the effect of seizure state (controlled vs. not controlled) is more pronounced, indicating a significant relationship between seizure control and emotion processing. Copyright © 2014 Elsevier Inc. All rights reserved.

Quantitative Analysis of Signaling Networks across Differentially Embedded Tumors Highlights Interpatient Heterogeneity in Human Glioblastoma

PubMed Central

2015-01-01

Glioblastoma multiforme (GBM) is the most aggressive malignant primary brain tumor, with a dismal mean survival even with the current standard of care. Although in vitro cell systems can provide mechanistic insight into the regulatory networks governing GBM cell proliferation and migration, clinical samples provide a more physiologically relevant view of oncogenic signaling networks. However, clinical samples are not widely available and may be embedded for histopathologic analysis. With the goal of accurately identifying activated signaling networks in GBM tumor samples, we investigated the impact of embedding in optimal cutting temperature (OCT) compound followed by flash freezing in LN2 vs immediate flash freezing (iFF) in LN2 on protein expression and phosphorylation-mediated signaling networks. Quantitative proteomic and phosphoproteomic analysis of 8 pairs of tumor specimens revealed minimal impact of the different sample processing strategies and highlighted the large interpatient heterogeneity present in these tumors. Correlation analyses of the differentially processed tumor sections identified activated signaling networks present in selected tumors and revealed the differential expression of transcription, translation, and degradation associated proteins. This study demonstrates the capability of quantitative mass spectrometry for identification of in vivo oncogenic signaling networks from human tumor specimens that were either OCT-embedded or immediately flash-frozen. PMID:24927040

Few-Flakes Reduced Graphene Oxide Sensors for Organic Vapors with a High Signal-to-Noise Ratio

PubMed Central

Hasan, Nowzesh; Zhang, Wenli

2017-01-01

This paper reports our findings on how to prepare a graphene oxide-based gas sensor for sensing fast pulses of volatile organic compounds with a better signal-to-noise ratio. We use rapid acetone pulses of varying concentrations to test the sensors. First, we compare the effect of graphene oxide deposition method (dielectrophoresis versus solvent evaporation) on the sensor’s response. We find that dielectrophoresis yields films with uniform coverage and better sensor response. Second, we examine the effect of chemical reduction. Contrary to prior reports, we find that graphene oxide reduction leads to a reduction in sensor response and current noise, thus keeping the signal-to-noise ratio the same. We found that if we sonicated the sensor in acetone, we created a sensor with a few flakes of reduced graphene oxide. Such sensors provided a higher signal-to-noise ratio that could be correlated to the vapor concentration of acetone with better repeatability. Modeling shows that the sensor’s response is due to one-site Langmuir adsorption or an overall single exponent process. Further, the desorption of acetone as deduced from the sensor recovery signal follows a single exponent process. Thus, we show a simple way to improve the signal-to-noise ratio in reduced graphene oxide sensors. PMID:29065488

Identification and classification of failure modes in laminated composites by using a multivariate statistical analysis of wavelet coefficients

NASA Astrophysics Data System (ADS)

Baccar, D.; Söffker, D.

2017-11-01

Acoustic Emission (AE) is a suitable method to monitor the health of composite structures in real-time. However, AE-based failure mode identification and classification are still complex to apply due to the fact that AE waves are generally released simultaneously from all AE-emitting damage sources. Hence, the use of advanced signal processing techniques in combination with pattern recognition approaches is required. In this paper, AE signals generated from laminated carbon fiber reinforced polymer (CFRP) subjected to indentation test are examined and analyzed. A new pattern recognition approach involving a number of processing steps able to be implemented in real-time is developed. Unlike common classification approaches, here only CWT coefficients are extracted as relevant features. Firstly, Continuous Wavelet Transform (CWT) is applied to the AE signals. Furthermore, dimensionality reduction process using Principal Component Analysis (PCA) is carried out on the coefficient matrices. The PCA-based feature distribution is analyzed using Kernel Density Estimation (KDE) allowing the determination of a specific pattern for each fault-specific AE signal. Moreover, waveform and frequency content of AE signals are in depth examined and compared with fundamental assumptions reported in this field. A correlation between the identified patterns and failure modes is achieved. The introduced method improves the damage classification and can be used as a non-destructive evaluation tool.

The Seismic Tool-Kit (STK): An Open Source Software For Learning the Basis of Signal Processing and Seismology.

NASA Astrophysics Data System (ADS)

Reymond, D.

2016-12-01

We present an open source software project (GNU public license), named STK: Seismic Tool-Kit, that is dedicated mainly for learning signal processing and seismology. The STK project that started in 2007, is hosted by SourceForge.net, and count more than 20000 downloads at the date of writing.The STK project is composed of two main branches:First, a graphical interface dedicated to signal processing (in the SAC format (SAC_ASCII and SAC_BIN): where the signal can be plotted, zoomed, filtered, integrated, derivated, ... etc. (a large variety of IFR and FIR filter is proposed). The passage in the frequency domain via the Fourier transform is used to introduce the estimation of spectral density of the signal , with visualization of the Power Spectral Density (PSD) in linear or log scale, and also the evolutive time-frequency representation (or sonagram). The 3-components signals can be also processed for estimating their polarization properties, either for a given window, or either for evolutive windows along the time. This polarization analysis is useful for extracting the polarized noises, differentiating P waves, Rayleigh waves, Love waves, ... etc. Secondly, a panel of Utilities-Program are proposed for working in a terminal mode, with basic programs for computing azimuth and distance in spherical geometry, inter/auto-correlation, spectral density, time-frequency for an entire directory of signals, focal planes, and main components axis, radiation pattern of P waves, Polarization analysis of different waves (including noise), under/over-sampling the signals, cubic-spline smoothing, and linear/non linear regression analysis of data set. STK is developed in C/C++, mainly under Linux OS, and it has been also partially implemented under MS-Windows. STK has been used in some schools for viewing and plotting seismic records provided by IRIS, and it has been used as a practical support for teaching the basis of signal processing. Useful links:http://sourceforge.net/projects/seismic-toolkit/http://sourceforge.net/p/seismic-toolkit/wiki/browse_pages/

Effects of coarse-graining on the scaling behavior of long-range correlated and anti-correlated signals.

PubMed

Xu, Yinlin; Ma, Qianli D Y; Schmitt, Daniel T; Bernaola-Galván, Pedro; Ivanov, Plamen Ch

2011-11-01

We investigate how various coarse-graining (signal quantization) methods affect the scaling properties of long-range power-law correlated and anti-correlated signals, quantified by the detrended fluctuation analysis. Specifically, for coarse-graining in the magnitude of a signal, we consider (i) the Floor, (ii) the Symmetry and (iii) the Centro-Symmetry coarse-graining methods. We find that for anti-correlated signals coarse-graining in the magnitude leads to a crossover to random behavior at large scales, and that with increasing the width of the coarse-graining partition interval Δ, this crossover moves to intermediate and small scales. In contrast, the scaling of positively correlated signals is less affected by the coarse-graining, with no observable changes when Δ < 1, while for Δ > 1 a crossover appears at small scales and moves to intermediate and large scales with increasing Δ. For very rough coarse-graining (Δ > 3) based on the Floor and Symmetry methods, the position of the crossover stabilizes, in contrast to the Centro-Symmetry method where the crossover continuously moves across scales and leads to a random behavior at all scales; thus indicating a much stronger effect of the Centro-Symmetry compared to the Floor and the Symmetry method. For coarse-graining in time, where data points are averaged in non-overlapping time windows, we find that the scaling for both anti-correlated and positively correlated signals is practically preserved. The results of our simulations are useful for the correct interpretation of the correlation and scaling properties of symbolic sequences.

Effects of coarse-graining on the scaling behavior of long-range correlated and anti-correlated signals

PubMed Central

Xu, Yinlin; Ma, Qianli D.Y.; Schmitt, Daniel T.; Bernaola-Galván, Pedro; Ivanov, Plamen Ch.

2014-01-01

We investigate how various coarse-graining (signal quantization) methods affect the scaling properties of long-range power-law correlated and anti-correlated signals, quantified by the detrended fluctuation analysis. Specifically, for coarse-graining in the magnitude of a signal, we consider (i) the Floor, (ii) the Symmetry and (iii) the Centro-Symmetry coarse-graining methods. We find that for anti-correlated signals coarse-graining in the magnitude leads to a crossover to random behavior at large scales, and that with increasing the width of the coarse-graining partition interval Δ, this crossover moves to intermediate and small scales. In contrast, the scaling of positively correlated signals is less affected by the coarse-graining, with no observable changes when Δ < 1, while for Δ > 1 a crossover appears at small scales and moves to intermediate and large scales with increasing Δ. For very rough coarse-graining (Δ > 3) based on the Floor and Symmetry methods, the position of the crossover stabilizes, in contrast to the Centro-Symmetry method where the crossover continuously moves across scales and leads to a random behavior at all scales; thus indicating a much stronger effect of the Centro-Symmetry compared to the Floor and the Symmetry method. For coarse-graining in time, where data points are averaged in non-overlapping time windows, we find that the scaling for both anti-correlated and positively correlated signals is practically preserved. The results of our simulations are useful for the correct interpretation of the correlation and scaling properties of symbolic sequences. PMID:25392599

A high performance cost-effective digital complex correlator for an X-band polarimetry survey.

PubMed

Bergano, Miguel; Rocha, Armando; Cupido, Luís; Barbosa, Domingos; Villela, Thyrso; Boas, José Vilas; Rocha, Graça; Smoot, George F

2016-01-01

The detailed knowledge of the Milky Way radio emission is important to characterize galactic foregrounds masking extragalactic and cosmological signals. The update of the global sky models describing radio emissions over a very large spectral band requires high sensitivity experiments capable of observing large sky areas with long integration times. Here, we present the design of a new 10 GHz (X-band) polarimeter digital back-end to map the polarization components of the galactic synchrotron radiation field of the Northern Hemisphere sky. The design follows the digital processing trends in radio astronomy and implements a large bandwidth (1 GHz) digital complex cross-correlator to extract the Stokes parameters of the incoming synchrotron radiation field. The hardware constraints cover the implemented VLSI hardware description language code and the preliminary results. The implementation is based on the simultaneous digitized acquisition of the Cartesian components of the two linear receiver polarization channels. The design strategy involves a double data rate acquisition of the ADC interleaved parallel bus, and field programmable gate array device programming at the register transfer mode. The digital core of the back-end is capable of processing 32 Gbps and is built around an Altera field programmable gate array clocked at 250 MHz, 1 GSps analog to digital converters and a clock generator. The control of the field programmable gate array internal signal delays and a convenient use of its phase locked loops provide the timing requirements to achieve the target bandwidths and sensitivity. This solution is convenient for radio astronomy experiments requiring large bandwidth, high functionality, high volume availability and low cost. Of particular interest, this correlator was developed for the Galactic Emission Mapping project and is suitable for large sky area polarization continuum surveys. The solutions may also be adapted to be used at signal processing subsystem levels for large projects like the square kilometer array testbeds.

Breast Cancer Malignant Processes are Regulated by Pax-5 Through the Disruption of FAK Signaling Pathways

PubMed Central

Benzina, Sami; Harquail, Jason; Guerrette, Roxann; O'Brien, Pierre; Jean, Stéphanie; Crapoulet, Nicolas; Robichaud, Gilles A.

2016-01-01

The study of genetic factors regulating breast cancer malignancy is a top priority to mitigate the morbidity and mortality associated with this disease. One of these factors, Pax-5, modulates cancer aggressiveness through the regulation of various components of the epithelial to mesenchymal transitioning (EMT) process. We have previously reported that Pax-5 expression profiles in cancer tissues inversely correlate with those of the Focal Adhesion Kinase (FAK), a potent activator of breast cancer malignancy. In this study, we set out to elucidate the molecular and regulatory relationship between Pax-5 and FAK in breast cancer processes. Interestingly, we found that Pax-5 mediated suppression of breast cancer cell migration is dependent of FAK activity. Our mechanistic examination revealed that Pax-5 inhibits FAK expression and activation. We also demonstrate that Pax-5 is a potent modulator of FAK repressors (p53 and miR-135b) and activator (NFκB) which results in the overall suppression of FAK-mediated signaling cascades. Altogether, our findings bring more insight to the molecular triggers regulating phenotypic transitioning process and signaling cascades leading to breast cancer progression. PMID:28070224

DOA Estimation for Underwater Wideband Weak Targets Based on Coherent Signal Subspace and Compressed Sensing.

PubMed

Li, Jun; Lin, Qiu-Hua; Kang, Chun-Yu; Wang, Kai; Yang, Xiu-Ting

2018-03-18

Direction of arrival (DOA) estimation is the basis for underwater target localization and tracking using towed line array sonar devices. A method of DOA estimation for underwater wideband weak targets based on coherent signal subspace (CSS) processing and compressed sensing (CS) theory is proposed. Under the CSS processing framework, wideband frequency focusing is accompanied by a two-sided correlation transformation, allowing the DOA of underwater wideband targets to be estimated based on the spatial sparsity of the targets and the compressed sensing reconstruction algorithm. Through analysis and processing of simulation data and marine trial data, it is shown that this method can accomplish the DOA estimation of underwater wideband weak targets. Results also show that this method can considerably improve the spatial spectrum of weak target signals, enhancing the ability to detect them. It can solve the problems of low directional resolution and unreliable weak-target detection in traditional beamforming technology. Compared with the conventional minimum variance distortionless response beamformers (MVDR), this method has many advantages, such as higher directional resolution, wider detection range, fewer required snapshots and more accurate detection for weak targets.

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

NASA Technical Reports Server (NTRS)

Kishoni, Doron; Pietsch, Benjamin E.

1989-01-01

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

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

NASA Technical Reports Server (NTRS)

Kishoni, Doron; Pietsch, Benjamin E.

1990-01-01

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

A modified cross-correlation method for white-light optical fiber extrinsic Fabry-Perot interferometric hydrogen sensors

NASA Astrophysics Data System (ADS)

Yang, Zhen; Zhang, Min; Liao, Yanbiao; Lai, Shurong; Tian, Qian; Li, Qisheng; Zhang, Yi; Zhuang, Zhi

2009-11-01

An extrinsic Fabry-Perot interferometric (EFPI) optical fiber hydrogen sensor based on palladium silver (Pd-Ag) film is designed for hydrogen leakage detection. A modified cross correlation signal processing method for an optical fiber EFPI hydrogen sensor is presented. As the applying of a special correlating factor which advises the effect on the fringe visibility of the gap length and wavelength, the cross correlation method has a high accuracy which is insensitive to light source power drift or changes in attenuation in the fiber, and the segment search method is employed to reduce computation and demodulating speed is fast. The Fabry-Perot gap length resolution of better than 0.2nm is achieved in a certain concentration of hydrogen.

Robust real-time extraction of respiratory signals from PET list-mode data.

PubMed

Salomon, Andre; Zhang, Bin; Olivier, Patrick; Goedicke, Andreas

2018-05-01

Respiratory motion, which typically cannot simply be suspended during PET image acquisition, affects lesions' detection and quantitative accuracy inside or in close vicinity to the lungs. Some motion compensation techniques address this issue via pre-sorting ("binning") of the acquired PET data into a set of temporal gates, where each gate is assumed to be minimally affected by respiratory motion. Tracking respiratory motion is typically realized using dedicated hardware (e.g. using respiratory belts and digital cameras). Extracting respiratory signalsdirectly from the acquired PET data simplifies the clinical workflow as it avoids to handle additional signal measurement equipment. We introduce a new data-driven method "Combined Local Motion Detection" (CLMD). It uses the Time-of-Flight (TOF) information provided by state-of-the-art PET scanners in order to enable real-time respiratory signal extraction without additional hardware resources. CLMD applies center-of-mass detection in overlapping regions based on simple back-positioned TOF event sets acquired in short time frames. Following a signal filtering and quality-based pre-selection step, the remaining extracted individual position information over time is then combined to generate a global respiratory signal. The method is evaluated using 7 measured FDG studies from single and multiple scan positions of the thorax region, and it is compared to other software-based methods regarding quantitative accuracy and statistical noise stability. Correlation coefficients around 90% between the reference and the extracted signal have been found for those PET scans where motion affected features such as tumors or hot regions were present in the PET field-of-view. For PET scans with a quarter of typically applied radiotracer doses, the CLMD method still provides similar high correlation coefficients which indicates its robustness to noise. Each CLMD processing needed less than 0.4s in total on a standard multi-core CPU and thus provides a robust and accurate approach enabling real-time processing capabilities using standard PC hardware. © 2018 Institute of Physics and Engineering in Medicine.

Frequency domain analysis of errors in cross-correlations of ambient seismic noise

NASA Astrophysics Data System (ADS)

Liu, Xin; Ben-Zion, Yehuda; Zigone, Dimitri

2016-12-01

We analyse random errors (variances) in cross-correlations of ambient seismic noise in the frequency domain, which differ from previous time domain methods. Extending previous theoretical results on ensemble averaged cross-spectrum, we estimate confidence interval of stacked cross-spectrum of finite amount of data at each frequency using non-overlapping windows with fixed length. The extended theory also connects amplitude and phase variances with the variance of each complex spectrum value. Analysis of synthetic stationary ambient noise is used to estimate the confidence interval of stacked cross-spectrum obtained with different length of noise data corresponding to different number of evenly spaced windows of the same duration. This method allows estimating Signal/Noise Ratio (SNR) of noise cross-correlation in the frequency domain, without specifying filter bandwidth or signal/noise windows that are needed for time domain SNR estimations. Based on synthetic ambient noise data, we also compare the probability distributions, causal part amplitude and SNR of stacked cross-spectrum function using one-bit normalization or pre-whitening with those obtained without these pre-processing steps. Natural continuous noise records contain both ambient noise and small earthquakes that are inseparable from the noise with the existing pre-processing steps. Using probability distributions of random cross-spectrum values based on the theoretical results provides an effective way to exclude such small earthquakes, and additional data segments (outliers) contaminated by signals of different statistics (e.g. rain, cultural noise), from continuous noise waveforms. This technique is applied to constrain values and uncertainties of amplitude and phase velocity of stacked noise cross-spectrum at different frequencies, using data from southern California at both regional scale (˜35 km) and dense linear array (˜20 m) across the plate-boundary faults. A block bootstrap resampling method is used to account for temporal correlation of noise cross-spectrum at low frequencies (0.05-0.2 Hz) near the ocean microseismic peaks.

Notch3 signaling is associated with MUC5AC expression and favorable prognosis in patients with small intestinal adenocarcinomas.

PubMed

Eom, Dae-Woon; Hong, Seung-Mo; Kim, Jihun; Kim, Gwangil; Bae, Young Kyung; Jang, Kee-Taek; Yu, Eunsil

2014-08-01

Notch signaling plays diverse roles not only in physiologic processes, including development and differentiation but also in tumorigenesis, either as a tumor promoter or suppressor depending on the cellular context, level of expression and cross-talk with other signaling pathways. In this study we investigated the expression of Notch3 and MUC proteins and their clinicopathological significance in small intestinal adenocarcinoma (SIAC). Surgically resected 191 SIACs and their clinical data were collected. Immunohistochemistry for Notch3, MUC2, MUC5AC, and MUC6 using tissue microarrays from formalin-fixed paraffin-embedded normal and matched tumor tissues was performed. Notch3 expression was found in 52 (29.9%) cases of the tumors. MUC2, MUC5AC, and MUC6 were expressed in 52 (27.5%), 51 (31.9%), and 42 (22.0%) cases of the tumor, respectively. Notch3 expression was correlated with the absence of lymphovascular invasion (p=0.009), lower T stage (p=0.038), and histological subtype of tubular adenocarcinoma (p=0.01), respectively. MUC2 was correlated with large tumor size (p=0.013) and mucinous and signet ring cell adenocarcinomas (p=0.01). MUC5A was correlated with proximal tumor location (p<0.0001) and tumor differentiation (p=0.027). MUC6 was correlated with proximal tumor location (p<0.0001) and lower pT stage (p=0.009), and absence of lymphovascular invasion, respectively. A significant correlation was noted between Notch3 and MUC5AC expression (p=0.019). Notch3 expression was a relatively favorable prognostic factor in SIACs by univariate (p=0.05) and multivariate analysis (p=0.08, Cox Hazard ratio 0.841). Our findings indicate that Notch3 signaling, associated with MUC5AC expression, could be a more favorable prognostic factor in SIACs. Copyright © 2014 Elsevier GmbH. All rights reserved.

Striatal and Hippocampal Entropy and Recognition Signals in Category Learning: Simultaneous Processes Revealed by Model-Based fMRI

PubMed Central

Davis, Tyler; Love, Bradley C.; Preston, Alison R.

2012-01-01

Category learning is a complex phenomenon that engages multiple cognitive processes, many of which occur simultaneously and unfold dynamically over time. For example, as people encounter objects in the world, they simultaneously engage processes to determine their fit with current knowledge structures, gather new information about the objects, and adjust their representations to support behavior in future encounters. Many techniques that are available to understand the neural basis of category learning assume that the multiple processes that subserve it can be neatly separated between different trials of an experiment. Model-based functional magnetic resonance imaging offers a promising tool to separate multiple, simultaneously occurring processes and bring the analysis of neuroimaging data more in line with category learning’s dynamic and multifaceted nature. We use model-based imaging to explore the neural basis of recognition and entropy signals in the medial temporal lobe and striatum that are engaged while participants learn to categorize novel stimuli. Consistent with theories suggesting a role for the anterior hippocampus and ventral striatum in motivated learning in response to uncertainty, we find that activation in both regions correlates with a model-based measure of entropy. Simultaneously, separate subregions of the hippocampus and striatum exhibit activation correlated with a model-based recognition strength measure. Our results suggest that model-based analyses are exceptionally useful for extracting information about cognitive processes from neuroimaging data. Models provide a basis for identifying the multiple neural processes that contribute to behavior, and neuroimaging data can provide a powerful test bed for constraining and testing model predictions. PMID:22746951

Sex-related differences in behavioral and amygdalar responses to compound facial threat cues.

PubMed

Im, Hee Yeon; Adams, Reginald B; Cushing, Cody A; Boshyan, Jasmine; Ward, Noreen; Kveraga, Kestutis

2018-03-08

During face perception, we integrate facial expression and eye gaze to take advantage of their shared signals. For example, fear with averted gaze provides a congruent avoidance cue, signaling both threat presence and its location, whereas fear with direct gaze sends an incongruent cue, leaving threat location ambiguous. It has been proposed that the processing of different combinations of threat cues is mediated by dual processing routes: reflexive processing via magnocellular (M) pathway and reflective processing via parvocellular (P) pathway. Because growing evidence has identified a variety of sex differences in emotional perception, here we also investigated how M and P processing of fear and eye gaze might be modulated by observer's sex, focusing on the amygdala, a structure important to threat perception and affective appraisal. We adjusted luminance and color of face stimuli to selectively engage M or P processing and asked observers to identify emotion of the face. Female observers showed more accurate behavioral responses to faces with averted gaze and greater left amygdala reactivity both to fearful and neutral faces. Conversely, males showed greater right amygdala activation only for M-biased averted-gaze fear faces. In addition to functional reactivity differences, females had proportionately greater bilateral amygdala volumes, which positively correlated with behavioral accuracy for M-biased fear. Conversely, in males only the right amygdala volume was positively correlated with accuracy for M-biased fear faces. Our findings suggest that M and P processing of facial threat cues is modulated by functional and structural differences in the amygdalae associated with observer's sex. © 2018 Wiley Periodicals, Inc.

Signal processing in urodynamics: towards high definition urethral pressure profilometry.

PubMed

Klünder, Mario; Sawodny, Oliver; Amend, Bastian; Ederer, Michael; Kelp, Alexandra; Sievert, Karl-Dietrich; Stenzl, Arnulf; Feuer, Ronny

2016-03-22

Urethral pressure profilometry (UPP) is used in the diagnosis of stress urinary incontinence (SUI) which is a significant medical, social, and economic problem. Low spatial pressure resolution, common occurrence of artifacts, and uncertainties in data location limit the diagnostic value of UPP. To overcome these limitations, high definition urethral pressure profilometry (HD-UPP) combining enhanced UPP hardware and signal processing algorithms has been developed. In this work, we present the different signal processing steps in HD-UPP and show experimental results from female minipigs. We use a special microtip catheter with high angular pressure resolution and an integrated inclination sensor. Signals from the catheter are filtered and time-correlated artifacts removed. A signal reconstruction algorithm processes pressure data into a detailed pressure image on the urethra's inside. Finally, the pressure distribution on the urethra's outside is calculated through deconvolution. A mathematical model of the urethra is contained in a point-spread-function (PSF) which is identified depending on geometric and material properties of the urethra. We additionally investigate the PSF's frequency response to determine the relevant frequency band for pressure information on the urinary sphincter. Experimental pressure data are spatially located and processed into high resolution pressure images. Artifacts are successfully removed from data without blurring other details. The pressure distribution on the urethra's outside is reconstructed and compared to the one on the inside. Finally, the pressure images are mapped onto the urethral geometry calculated from inclination and position data to provide an integrated image of pressure distribution, anatomical shape, and location. With its advanced sensing capabilities, the novel microtip catheter collects an unprecedented amount of urethral pressure data. Through sequential signal processing steps, physicians are provided with detailed information on the pressure distribution in and around the urethra. Therefore, HD-UPP overcomes many current limitations of conventional UPP and offers the opportunity to evaluate urethral structures, especially the sphincter, in context of the correct anatomical location. This could enable the development of focal therapy approaches in the treatment of SUI.

Automatic Classification of Extensive Aftershock Sequences Using Empirical Matched Field Processing

NASA Astrophysics Data System (ADS)

Gibbons, Steven J.; Harris, David B.; Kværna, Tormod; Dodge, Douglas A.

2013-04-01

The aftershock sequences that follow large earthquakes create considerable problems for data centers attempting to produce comprehensive event bulletins in near real-time. The greatly increased number of events which require processing can overwhelm analyst resources and reduce the capacity for analyzing events of monitoring interest. This exacerbates a potentially reduced detection capability at key stations, due the noise generated by the sequence, and a deterioration in the quality of the fully automatic preliminary event bulletins caused by the difficulty in associating the vast numbers of closely spaced arrivals over the network. Considerable success has been enjoyed by waveform correlation methods for the automatic identification of groups of events belonging to the same geographical source region, facilitating the more time-efficient analysis of event ensembles as opposed to individual events. There are, however, formidable challenges associated with the automation of correlation procedures. The signal generated by a very large earthquake seldom correlates well enough with the signals generated by far smaller aftershocks for a correlation detector to produce statistically significant triggers at the correct times. Correlation between events within clusters of aftershocks is significantly better, although the issues of when and how to initiate new pattern detectors are still being investigated. Empirical Matched Field Processing (EMFP) is a highly promising method for detecting event waveforms suitable as templates for correlation detectors. EMFP is a quasi-frequency-domain technique that calibrates the spatial structure of a wavefront crossing a seismic array in a collection of narrow frequency bands. The amplitude and phase weights that result are applied in a frequency-domain beamforming operation that compensates for scattering and refraction effects not properly modeled by plane-wave beams. It has been demonstrated to outperform waveform correlation as a classifier of ripple-fired mining blasts since the narrowband procedure is insensitive to differences in the source-time functions. For sequences in which the spectral content and time-histories of the signals from the main shock and aftershocks vary greatly, the spatial structure calibrated by EMFP is an invariant that permits reliable detection of events in the specific source region. Examples from the 2005 Kashmir and 2011 Van earthquakes demonstrate how EMFP templates from the main events detect arrivals from the aftershock sequences with high sensitivity and exceptionally low false alarm rates. Classical waveform correlation detectors are demonstrated to fail for these examples. Even arrivals with SNR below unity can produce significant EMFP triggers as the spatial pattern of the incoming wavefront is identified, leading to robust detections at a greater number of stations and potentially more reliable automatic bulletins. False EMFP triggers are readily screened by scanning a space of phase shifts relative to the imposed template. EMFP has the potential to produce a rapid and robust overview of the evolving aftershock sequence such that correlation and subspace detectors can be applied semi-autonomously, with well-chosen parameter specifications, to identify and classify clusters of very closely spaced aftershocks.

Neural correlates of word production stages delineated by parametric modulation of psycholinguistic variables.

PubMed

Wilson, Stephen M; Isenberg, Anna Lisette; Hickok, Gregory

2009-11-01

Word production is a complex multistage process linking conceptual representations, lexical entries, phonological forms and articulation. Previous studies have revealed a network of predominantly left-lateralized brain regions supporting this process, but many details regarding the precise functions of different nodes in this network remain unclear. To better delineate the functions of regions involved in word production, we used event-related functional magnetic resonance imaging (fMRI) to identify brain areas where blood oxygen level-dependent (BOLD) responses to overt picture naming were modulated by three psycholinguistic variables: concept familiarity, word frequency, and word length, and one behavioral variable: reaction time. Each of these variables has been suggested by prior studies to be associated with different aspects of word production. Processing of less familiar concepts was associated with greater BOLD responses in bilateral occipitotemporal regions, reflecting visual processing and conceptual preparation. Lower frequency words produced greater BOLD signal in left inferior temporal cortex and the left temporoparietal junction, suggesting involvement of these regions in lexical selection and retrieval and encoding of phonological codes. Word length was positively correlated with signal intensity in Heschl's gyrus bilaterally, extending into the mid-superior temporal gyrus (STG) and sulcus (STS) in the left hemisphere. The left mid-STS site was also modulated by reaction time, suggesting a role in the storage of lexical phonological codes.

Application of wavelet filtering and Barker-coded pulse compression hybrid method to air-coupled ultrasonic testing

NASA Astrophysics Data System (ADS)

Zhou, Zhenggan; Ma, Baoquan; Jiang, Jingtao; Yu, Guang; Liu, Kui; Zhang, Dongmei; Liu, Weiping

2014-10-01

Air-coupled ultrasonic testing (ACUT) technique has been viewed as a viable solution in defect detection of advanced composites used in aerospace and aviation industries. However, the giant mismatch of acoustic impedance in air-solid interface makes the transmission efficiency of ultrasound low, and leads to poor signal-to-noise (SNR) ratio of received signal. The utilisation of signal-processing techniques in non-destructive testing is highly appreciated. This paper presents a wavelet filtering and phase-coded pulse compression hybrid method to improve the SNR and output power of received signal. The wavelet transform is utilised to filter insignificant components from noisy ultrasonic signal, and pulse compression process is used to improve the power of correlated signal based on cross-correction algorithm. For the purpose of reasonable parameter selection, different families of wavelets (Daubechies, Symlet and Coiflet) and decomposition level in discrete wavelet transform are analysed, different Barker codes (5-13 bits) are also analysed to acquire higher main-to-side lobe ratio. The performance of the hybrid method was verified in a honeycomb composite sample. Experimental results demonstrated that the proposed method is very efficient in improving the SNR and signal strength. The applicability of the proposed method seems to be a very promising tool to evaluate the integrity of high ultrasound attenuation composite materials using the ACUT.

Reward processing in the value-driven attention network: reward signals tracking cue identity and location.

PubMed

Anderson, Brian A

2017-03-01

Through associative reward learning, arbitrary cues acquire the ability to automatically capture visual attention. Previous studies have examined the neural correlates of value-driven attentional orienting, revealing elevated activity within a network of brain regions encompassing the visual corticostriatal loop [caudate tail, lateral occipital complex (LOC) and early visual cortex] and intraparietal sulcus (IPS). Such attentional priority signals raise a broader question concerning how visual signals are combined with reward signals during learning to create a representation that is sensitive to the confluence of the two. This study examines reward signals during the cued reward training phase commonly used to generate value-driven attentional biases. High, compared with low, reward feedback preferentially activated the value-driven attention network, in addition to regions typically implicated in reward processing. Further examination of these reward signals within the visual system revealed information about the identity of the preceding cue in the caudate tail and LOC, and information about the location of the preceding cue in IPS, while early visual cortex represented both location and identity. The results reveal teaching signals within the value-driven attention network during associative reward learning, and further suggest functional specialization within different regions of this network during the acquisition of an integrated representation of stimulus value. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Amphetamine sensitization alters reward processing in the human striatum and amygdala.

PubMed

O'Daly, Owen G; Joyce, Daniel; Tracy, Derek K; Azim, Adnan; Stephan, Klaas E; Murray, Robin M; Shergill, Sukhwinder S

2014-01-01

Dysregulation of mesolimbic dopamine transmission is implicated in a number of psychiatric illnesses characterised by disruption of reward processing and goal-directed behaviour, including schizophrenia, drug addiction and impulse control disorders associated with chronic use of dopamine agonists. Amphetamine sensitization (AS) has been proposed to model the development of this aberrant dopamine signalling and the subsequent dysregulation of incentive motivational processes. However, in humans the effects of AS on the dopamine-sensitive neural circuitry associated with reward processing remains unclear. Here we describe the effects of acute amphetamine administration, following a sensitising dosage regime, on blood oxygen level dependent (BOLD) signal in dopaminoceptive brain regions during a rewarded gambling task performed by healthy volunteers. Using a randomised, double-blind, parallel-groups design, we found clear evidence for sensitization to the subjective effects of the drug, while rewarded reaction times were unchanged. Repeated amphetamine exposure was associated with reduced dorsal striatal BOLD signal during decision making, but enhanced ventromedial caudate activity during reward anticipation. The amygdala BOLD response to reward outcomes was blunted following repeated amphetamine exposure. Positive correlations between subjective sensitization and changes in anticipation- and outcome-related BOLD signal were seen for the caudate nucleus and amygdala, respectively. These data show for the first time in humans that AS changes the functional impact of acute stimulant exposure on the processing of reward-related information within dopaminoceptive regions. Our findings accord with pathophysiological models which implicate aberrant dopaminergic modulation of striatal and amygdala activity in psychosis and drug-related compulsive disorders.

Removal of correlated noise online for in situ measurements by using multichannel magnetic resonance sounding system

NASA Astrophysics Data System (ADS)

Lin, Tingting; Zhang, Siyuan; Zhang, Yang; Wan, Ling; Lin, Jun

2017-01-01

Compared with the other geophysical approaches, magnetic resonance sounding (MRS) technique is direct and nondestructive in subsurface water exploration. It provides water content distribution and estimates hydrogeological properties. The biggest challenge is that MRS measurement always suffers bad signal-to-noise ratio, and it can be carried out only far from sources of noise. To solve this problem, a series of de-noising methods are developed. However, most of them are post-processing, leading the data quality uncontrolled for in situ measurements. In the present study, a new approach that removal of correlated noise online is found to overcome the restriction. Based on LabVIEW, a method is provided to enable online data quality control by the way of realizing signal acquisition and noise filtering simultaneously. Using one or more reference coils, adaptive noise cancellation based on LabVIEW to eliminate the correlated noise is available for in situ measurements. The approach was examined through numerical simulation and field measurements. The correlated noise is mitigated effectively and the application of MRS measurements is feasible in high-level noise environment. The method shortens the measurement time and improves the measurement efficiency.

Initial Validation for the Estimation of Resting-State fMRI Effective Connectivity by a Generalization of the Correlation Approach

PubMed Central

Xu, Nan; Spreng, R. Nathan; Doerschuk, Peter C.

2017-01-01

Resting-state functional MRI (rs-fMRI) is widely used to noninvasively study human brain networks. Network functional connectivity is often estimated by calculating the timeseries correlation between blood-oxygen-level dependent (BOLD) signal from different regions of interest (ROIs). However, standard correlation cannot characterize the direction of information flow between regions. In this paper, we introduce and test a new concept, prediction correlation, to estimate effective connectivity in functional brain networks from rs-fMRI. In this approach, the correlation between two BOLD signals is replaced by a correlation between one BOLD signal and a prediction of this signal via a causal system driven by another BOLD signal. Three validations are described: (1) Prediction correlation performed well on simulated data where the ground truth was known, and outperformed four other methods. (2) On simulated data designed to display the “common driver” problem, prediction correlation did not introduce false connections between non-interacting driven ROIs. (3) On experimental data, prediction correlation recovered the previously identified network organization of human brain. Prediction correlation scales well to work with hundreds of ROIs, enabling it to assess whole brain interregional connectivity at the single subject level. These results provide an initial validation that prediction correlation can capture the direction of information flow and estimate the duration of extended temporal delays in information flow between regions of interest ROIs based on BOLD signal. This approach not only maintains the high sensitivity to network connectivity provided by the correlation analysis, but also performs well in the estimation of causal information flow in the brain. PMID:28559793

Short-time windowed covariance: A metric for identifying non-stationary, event-related covariant cortical sites

PubMed Central

Blakely, Timothy; Ojemann, Jeffrey G.; Rao, Rajesh P.N.

2014-01-01

Background Electrocorticography (ECoG) signals can provide high spatio-temporal resolution and high signal to noise ratio recordings of local neural activity from the surface of the brain. Previous studies have shown that broad-band, spatially focal, high-frequency increases in ECoG signals are highly correlated with movement and other cognitive tasks and can be volitionally modulated. However, significant additional information may be present in inter-electrode interactions, but adding additional higher order inter-electrode interactions can be impractical from a computational aspect, if not impossible. New method In this paper we present a new method of calculating high frequency interactions between electrodes called Short-Time Windowed Covariance (STWC) that builds on mathematical techniques currently used in neural signal analysis, along with an implementation that accelerates the algorithm by orders of magnitude by leveraging commodity, off-the-shelf graphics processing unit (GPU) hardware. Results Using the hardware-accelerated implementation of STWC, we identify many types of event-related inter-electrode interactions from human ECoG recordings on global and local scales that have not been identified by previous methods. Unique temporal patterns are observed for digit flexion in both low- (10 mm spacing) and high-resolution (3 mm spacing) electrode arrays. Comparison with existing methods Covariance is a commonly used metric for identifying correlated signals, but the standard covariance calculations do not allow for temporally varying covariance. In contrast STWC allows and identifies event-driven changes in covariance without identifying spurious noise correlations. Conclusions: STWC can be used to identify event-related neural interactions whose high computational load is well suited to GPU capabilities. PMID:24211499

Enhanced correlation of received power-signal fluctuations in bidirectional optical links

NASA Astrophysics Data System (ADS)

Minet, Jean; Vorontsov, Mikhail A.; Polnau, Ernst; Dolfi, Daniel

2013-02-01

A study of the correlation between the power signals received at both ends of bidirectional free-space optical links is presented. By use of the quasi-optical approximation, we show that an ideal (theoretically 100%) power-signal correlation can be achieved in optical links with specially designed monostatic transceivers based on single-mode fiber collimators. The theoretical prediction of enhanced correlation is supported both by experiments conducted over a 7 km atmospheric path and wave optics numerical analysis of the corresponding bidirectional optical link. In the numerical simulations, we also compare correlation properties of received power signals for different atmospheric conditions and for optical links with monostatic and bistatic geometries based on single-mode fiber collimator and on power-in-the-bucket transceiver types. Applications of the observed phenomena for signal fading mitigation and turbulence-enhanced communication link security in free-space laser communication links are discussed.

Process-specific analysis in episodic memory retrieval using fast optical signals and hemodynamic signals in the right prefrontal cortex

NASA Astrophysics Data System (ADS)

Dong, Sunghee; Jeong, Jichai

2018-02-01

Objective. Memory is formed by the interaction of various brain functions at the item and task level. Revealing individual and combined effects of item- and task-related processes on retrieving episodic memory is an unsolved problem because of limitations in existing neuroimaging techniques. To investigate these issues, we analyze fast and slow optical signals measured from a custom-built continuous wave functional near-infrared spectroscopy (CW-fNIRS) system. Approach. In our work, we visually encode the words to the subjects and let them recall the words after a short rest. The hemodynamic responses evoked by the episodic memory are compared with those evoked by the semantic memory in retrieval blocks. In the fast optical signal, we compare the effects of old and new items (previously seen and not seen) to investigate the item-related process in episodic memory. The Kalman filter is simultaneously applied to slow and fast optical signals in different time windows. Main results. A significant task-related HbR decrease was observed in the episodic memory retrieval blocks. Mean amplitude and peak latency of a fast optical signal are dependent upon item types and reaction time, respectively. Moreover, task-related hemodynamic and item-related fast optical responses are correlated in the right prefrontal cortex. Significance. We demonstrate that episodic memory is retrieved from the right frontal area by a functional connectivity between the maintained mental state through retrieval and item-related transient activity. To the best of our knowledge, this demonstration of functional NIRS research is the first to examine the relationship between item- and task-related memory processes in the prefrontal area using single modality.

Process-specific analysis in episodic memory retrieval using fast optical signals and hemodynamic signals in the right prefrontal cortex.

PubMed

Dong, Sunghee; Jeong, Jichai

2018-02-01

Memory is formed by the interaction of various brain functions at the item and task level. Revealing individual and combined effects of item- and task-related processes on retrieving episodic memory is an unsolved problem because of limitations in existing neuroimaging techniques. To investigate these issues, we analyze fast and slow optical signals measured from a custom-built continuous wave functional near-infrared spectroscopy (CW-fNIRS) system. In our work, we visually encode the words to the subjects and let them recall the words after a short rest. The hemodynamic responses evoked by the episodic memory are compared with those evoked by the semantic memory in retrieval blocks. In the fast optical signal, we compare the effects of old and new items (previously seen and not seen) to investigate the item-related process in episodic memory. The Kalman filter is simultaneously applied to slow and fast optical signals in different time windows. A significant task-related HbR decrease was observed in the episodic memory retrieval blocks. Mean amplitude and peak latency of a fast optical signal are dependent upon item types and reaction time, respectively. Moreover, task-related hemodynamic and item-related fast optical responses are correlated in the right prefrontal cortex. We demonstrate that episodic memory is retrieved from the right frontal area by a functional connectivity between the maintained mental state through retrieval and item-related transient activity. To the best of our knowledge, this demonstration of functional NIRS research is the first to examine the relationship between item- and task-related memory processes in the prefrontal area using single modality.

Modeling perceptual grouping and figure-ground segregation by means of active reentrant connections.

PubMed

Sporns, O; Tononi, G; Edelman, G M

1991-01-01

The segmentation of visual scenes is a fundamental process of early vision, but the underlying neural mechanisms are still largely unknown. Theoretical considerations as well as neurophysiological findings point to the importance in such processes of temporal correlations in neuronal activity. In a previous model, we showed that reentrant signaling among rhythmically active neuronal groups can correlate responses along spatially extended contours. We now have modified and extended this model to address the problems of perceptual grouping and figure-ground segregation in vision. A novel feature is that the efficacy of the connections is allowed to change on a fast time scale. This results in active reentrant connections that amplify the correlations among neuronal groups. The responses of the model are able to link the elements corresponding to a coherent figure and to segregate them from the background or from another figure in a way that is consistent with the so-called Gestalt laws.

Modeling Perceptual Grouping and Figure-Ground Segregation by Means of Active Reentrant Connections

NASA Astrophysics Data System (ADS)

Sporns, Olaf; Tononi, Giulio; Edelman, Gerald M.

1991-01-01

The segmentation of visual scenes is a fundamental process of early vision, but the underlying neural mechanisms are still largely unknown. Theoretical considerations as well as neurophysiological findings point to the importance in such processes of temporal correlations in neuronal activity. In a previous model, we showed that reentrant signaling among rhythmically active neuronal groups can correlate responses along spatially extended contours. We now have modified and extended this model to address the problems of perceptual grouping and figure-ground segregation in vision. A novel feature is that the efficacy of the connections is allowed to change on a fast time scale. This results in active reentrant connections that amplify the correlations among neuronal groups. The responses of the model are able to link the elements corresponding to a coherent figure and to segregate them from the background or from another figure in a way that is consistent with the so-called Gestalt laws.

Phasic dopamine release in the rat nucleus accumbens predicts approach and avoidance performance

PubMed Central

Gentry, Ronny N.; Lee, Brian; Roesch, Matthew R.

2016-01-01

Dopamine (DA) is critical for reward processing, but significantly less is known about its role in punishment avoidance. Using a combined approach-avoidance task, we measured phasic DA release in the nucleus accumbens (NAc) of rats during presentation of cues that predicted reward, punishment or neutral outcomes and investigated individual differences based on avoidance performance. Here we show that DA release within a single microenvironment is higher for reward and avoidance cues compared with neutral cues and positively correlated with poor avoidance behaviour. We found that DA release delineates trial-type during sessions with good avoidance but is non-selective during poor avoidance, with high release correlating with poor performance. These data demonstrate that phasic DA is released during cued approach and avoidance within the same microenvironment and abnormal processing of value signals is correlated with poor performance. PMID:27786172

Individual variation in the neural processes of motor decisions in the stop signal task: the influence of novelty seeking and harm avoidance personality traits.

PubMed

Hu, Jianping; Lee, Dianne; Hu, Sien; Zhang, Sheng; Chao, Herta; Li, Chiang-Shan R

2016-06-01

Personality traits contribute to variation in human behavior, including the propensity to take risk. Extant work targeted risk-taking processes with an explicit manipulation of reward, but it remains unclear whether personality traits influence simple decisions such as speeded versus delayed responses during cognitive control. We explored this issue in an fMRI study of the stop signal task, in which participants varied in response time trial by trial, speeding up and risking a stop error or slowing down to avoid errors. Regional brain activations to speeded versus delayed motor responses (risk-taking) were correlated to novelty seeking (NS), harm avoidance (HA) and reward dependence (RD), with age and gender as covariates, in a whole brain regression. At a corrected threshold, the results showed a positive correlation between NS and risk-taking responses in the dorsomedial prefrontal, bilateral orbitofrontal, and frontopolar cortex, and between HA and risk-taking responses in the parahippocampal gyrus and putamen. No regional activations varied with RD. These findings demonstrate that personality traits influence the neural processes of executive control beyond behavioral tasks that involve explicit monetary reward. The results also speak broadly to the importance of characterizing inter-subject variation in studies of cognition and brain functions.

A Rhizobium radiobacter Histidine Kinase Can Employ Both Boolean AND and OR Logic Gates to Initiate Pathogenesis.

PubMed

Fang, Fang; Lin, Yi-Han; Pierce, B Daniel; Lynn, David G

2015-10-12

The molecular logic gates that regulate gene circuits are necessarily intricate and highly regulated, particularly in the critical commitments necessary for pathogenesis. We now report simple AND and OR logic gates to be accessible within a single protein receptor. Pathogenesis by the bacterium Rhizobium radiobacter is mediated by a single histidine kinase, VirA, which processes multiple small molecule host signals (phenol and sugar). Mutagenesis analyses converged on a single signal integration node, and finer functional analyses revealed that a single residue could switch VirA from a functional AND logic gate to an OR gate where each of two signals activate independently. Host range preferences among natural strains of R. radiobacter correlate with these gate logic strategies. Although the precise mechanism for the signal integration node requires further analyses, long-range signal transmission through this histidine kinase can now be exploited for synthetic signaling circuits. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A lateral signalling pathway coordinates shape volatility during cell migration

PubMed Central

Zhang, Liang; Luga, Valbona; Armitage, Sarah K.; Musiol, Martin; Won, Amy; Yip, Christopher M.; Plotnikov, Sergey V.; Wrana, Jeffrey L.

2016-01-01

Cell migration is fundamental for both physiological and pathological processes. Migrating cells usually display high dynamics in morphology, which is orchestrated by an integrative array of signalling pathways. Here we identify a novel pathway, we term lateral signalling, comprised of the planar cell polarity (PCP) protein Pk1 and the RhoGAPs, Arhgap21/23. We show that the Pk1–Arhgap21/23 complex inhibits RhoA, is localized on the non-protrusive lateral membrane cortex and its disruption leads to the disorganization of the actomyosin network and altered focal adhesion dynamics. Pk1-mediated lateral signalling confines protrusive activity and is regulated by Smurf2, an E3 ubiquitin ligase in the PCP pathway. Furthermore, we demonstrate that dynamic interplay between lateral and protrusive signalling generates cyclical fluctuations in cell shape that we quantify here as shape volatility, which strongly correlates with migration speed. These studies uncover a previously unrecognized lateral signalling pathway that coordinates shape volatility during productive cell migration. PMID:27226243

On-line Tool Wear Detection on DCMT070204 Carbide Tool Tip Based on Noise Cutting Audio Signal using Artificial Neural Network

NASA Astrophysics Data System (ADS)

Prasetyo, T.; Amar, S.; Arendra, A.; Zam Zami, M. K.

2018-01-01

This study develops an on-line detection system to predict the wear of DCMT070204 tool tip during the cutting process of the workpiece. The machine used in this research is CNC ProTurn 9000 to cut ST42 steel cylinder. The audio signal has been captured using the microphone placed in the tool post and recorded in Matlab. The signal is recorded at the sampling rate of 44.1 kHz, and the sampling size of 1024. The recorded signal is 110 data derived from the audio signal while cutting using a normal chisel and a worn chisel. And then perform signal feature extraction in the frequency domain using Fast Fourier Transform. Feature selection is done based on correlation analysis. And tool wear classification was performed using artificial neural networks with 33 input features selected. This artificial neural network is trained with back propagation method. Classification performance testing yields an accuracy of 74%.

Frequency-domain preprocessing and directional correlation-based feature extraction for classification of the buried objects using GPR B-scan data

NASA Astrophysics Data System (ADS)

Bahadirlar, Yildirim; Kaplan, Gulay B.

2004-09-01

A new preprocessing and feature extracting approach for classification of non-metallic buried objects are aimed using GPR B-scan data. A frequency-domain adaptive filter without a reference channel effectively removes the background signal resulting mostly from the discontinuity on the air-to-ground path of the electromagnetic waves. The filter only needs average of the first five A-scans as the reference signal for this elimination, and also serves for masking of the B-scan in the frequency-domain. A preprocessed GPR data with significantly suppressed clutter is then obtained by precisely positioning the Hanning window in the frequency-domain. A directional correlation function defined over a B-scan frame gives distinctive curves of buried objects. The main axis of directional correlation, on which the pivotal correlating pixels and short lines of pixels being correlated are considered, makes an angle to the scanning direction of the B-scan. This form of correlation is applied to the frame from the left-hand and the right-hand side and two over-plotted curves are obtained. Nine measures as features emphasizing directional signatures are extracted from these curves. Nine-element feature vectors are applied to the two-layer Artificial Neural Network and preliminary results over test set are promising to continue to comprehensive training and testing processes.

Automated electrohysterographic detection of uterine contractions for monitoring of pregnancy: feasibility and prospects.

PubMed

Muszynski, C; Happillon, T; Azudin, K; Tylcz, J-B; Istrate, D; Marque, C

2018-05-08

Preterm birth is a major public health problem in developed countries. In this context, we have conducted research into outpatient monitoring of uterine electrical activity in women at risk of preterm delivery. The objective of this preliminary study was to perform automated detection of uterine contractions (without human intervention or tocographic signal, TOCO) by processing the EHG recorded on the abdomen of pregnant women. The feasibility and accuracy of uterine contraction detection based on EHG processing were tested and compared to expert decision using external tocodynamometry (TOCO) . The study protocol was approved by local Ethics Committees under numbers ID-RCB 2016-A00663-48 for France and VSN 02-0006-V2 for Iceland. Two populations of women were included (threatened preterm birth and labour) in order to test our system of recognition of the various types of uterine contractions. EHG signal acquisition was performed according to a standardized protocol to ensure optimal reproducibility of EHG recordings. A system of 18 Ag/AgCl surface electrodes was used by placing 16 recording electrodes between the woman's pubis and umbilicus according to a 4 × 4 matrix. TOCO was recorded simultaneously with EHG recording. EHG signals were analysed in real-time by calculation of the nonlinear correlation coefficient H 2 . A curve representing the number of correlated pairs of signals according to the value of H 2 calculated between bipolar signals was then plotted. High values of H 2 indicated the presence of an event that may correspond to a contraction. Two tests were performed after detection of an event (fusion and elimination of certain events) in order to increase the contraction detection rate. The EHG database contained 51 recordings from pregnant women, with a total of 501 contractions previously labelled by analysis of the corresponding tocographic recording. The percentage recognitions obtained by application of the method based on coefficient H 2 was 100% with 782% of false alarms. Addition of fusion and elimination tests to the previously obtained detections allowed the false alarm rate to be divided by 8.5, while maintaining an excellent detection rate (96%). These preliminary results appear to be encouraging for monitoring of uterine contractions by algorithm-based automated detection to process the electrohysterographic signal (EHG). This compact recording system, based on the use of surface electrodes attached to the skin, appears to be particularly suitable for outpatient monitoring of uterine contractions, possibly at home, allowing telemonitoring of pregnancies. One of the advantages of EHG processing is that useful information concerning contraction efficiency can be extracted from this signal, which is not possible with the TOCO signal.

Coil-to-coil physiological noise correlations and their impact on functional MRI time-series signal-to-noise ratio.

PubMed

Triantafyllou, Christina; Polimeni, Jonathan R; Keil, Boris; Wald, Lawrence L

2016-12-01

Physiological nuisance fluctuations ("physiological noise") are a major contribution to the time-series signal-to-noise ratio (tSNR) of functional imaging. While thermal noise correlations between array coil elements have a well-characterized effect on the image Signal to Noise Ratio (SNR 0 ), the element-to-element covariance matrix of the time-series fluctuations has not yet been analyzed. We examine this effect with a goal of ultimately improving the combination of multichannel array data. We extend the theoretical relationship between tSNR and SNR 0 to include a time-series noise covariance matrix Ψ t , distinct from the thermal noise covariance matrix Ψ 0 , and compare its structure to Ψ 0 and the signal coupling matrix SS H formed from the signal intensity vectors S. Inclusion of the measured time-series noise covariance matrix into the model relating tSNR and SNR 0 improves the fit of experimental multichannel data and is shown to be distinct from Ψ 0 or SS H . Time-series noise covariances in array coils are found to differ from Ψ 0 and more surprisingly, from the signal coupling matrix SS H . Correct characterization of the time-series noise has implications for the analysis of time-series data and for improving the coil element combination process. Magn Reson Med 76:1708-1719, 2016. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Left prefrontal cortex control of novel occurrences during recollection: a psychopharmacological study using scopolamine and event-related fMRI.

PubMed

Bozzali, M; MacPherson, S E; Dolan, R J; Shallice, T

2006-10-15

Recollection and familiarity represent two processes involved in episodic memory retrieval. We investigated how scopolamine (an antagonist of acetylcholine muscarinic receptors) influenced brain activity during memory retrieval, using a paradigm that separated recollection and familiarity. Eighteen healthy volunteers were recruited in a randomized, placebo-controlled, double-blind design using event-related fMRI. Participants were required to perform a verbal recognition memory task within the scanner, either under placebo or scopolamine conditions. Depending on the subcondition, participants were required to make a simple recognition decision (old/new items) or base their decision on more specific information related to prior experience (target/non-target/new items). We show a drug modulation in left prefrontal and perirhinal cortex during recollection. Such an effect was specifically driven by novelty and showed an inverse correlation with accuracy performance. Additionally, we show a direct correlation between drug-related signal change in left prefrontal and perirhinal cortices. We discuss the findings in terms of acetylcholine mediation of the familiarity/novelty signal through perirhinal cortex and the control of the relative signal strength through prefrontal cortex.

Modeling Array Stations in SIG-VISA

NASA Astrophysics Data System (ADS)

Ding, N.; Moore, D.; Russell, S.

2013-12-01

We add support for array stations to SIG-VISA, a system for nuclear monitoring using probabilistic inference on seismic signals. Array stations comprise a large portion of the IMS network; they can provide increased sensitivity and more accurate directional information compared to single-component stations. Our existing model assumed that signals were independent at each station, which is false when lots of stations are close together, as in an array. The new model removes that assumption by jointly modeling signals across array elements. This is done by extending our existing Gaussian process (GP) regression models, also known as kriging, from a 3-dimensional single-component space of events to a 6-dimensional space of station-event pairs. For each array and each event attribute (including coda decay, coda height, amplitude transfer and travel time), we model the joint distribution across array elements using a Gaussian process that learns the correlation lengthscale across the array, thereby incorporating information of array stations into the probabilistic inference framework. To evaluate the effectiveness of our model, we perform ';probabilistic beamforming' on new events using our GP model, i.e., we compute the event azimuth having highest posterior probability under the model, conditioned on the signals at array elements. We compare the results from our probabilistic inference model to the beamforming currently performed by IMS station processing.