Search results for "Pattern"

showing 10 items of 4203 documents

Nonparametric statistics for DOA estimation in the presence of multipath

2002

This paper is concerned with array signal processing in nonGaussian noise and in the presence of multipath. Robust and fully nonparametric high resolution algorithms for direction of arrival (DOA) estimation are presented. The algorithms are based on multivariate spatial sign and rank concepts. Spatial smoothing of the multivariate rank and sign based covariance matrices is employed as a preprocessing step in order to deal with coherent sources. The performance of the algorithms is studied using simulations. The results show that almost optimal performance is obtained in wide variety of different noise conditions.

Signal processingRank (linear algebra)business.industryNoise (signal processing)Nonparametric statisticsDirection of arrivalPattern recognitionArtificial intelligenceCovariancebusinessSmoothingMultipath propagationMathematicsProceedings of the 2000 IEEE Sensor Array and Multichannel Signal Processing Workshop. SAM 2000 (Cat. No.00EX410)
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Signal reconstruction, modeling and simulation of a vehicle full-scale crash test based on Morlet wavelets

2012

Creating a mathematical model of a vehicle crash is a task which involves considerations and analysis of different areas which need to be addressed because of the mathematical complexity of a crash event representation. Therefore, to simplify the analysis and enhance the modeling process, in this paper a novel wavelet-based approach is introduced to reproduce acceleration pulse of a vehicle involved in a crash event. The acceleration of a colliding vehicle is measured in its center of gravity-this crash pulse contains detailed information about vehicle behavior throughout a collision. Three types of signal analysis are elaborated here: time domain analysis (i.e. description of kinematics of…

Signal processingSignal reconstructionComputer scienceMultiresolution analysisCognitive NeuroscienceCrashComputer Science Applications1707 Computer Vision and Pattern RecognitionCrash testComputer Science ApplicationsMorlet wavelet; Multiresolution analysis; Signal reproduction; Vehicle crash modeling; Computer Science Applications1707 Computer Vision and Pattern Recognition; Cognitive Neuroscience; Artificial IntelligenceWaveletMorlet waveletArtificial IntelligenceFrequency domainTime domainSignal reproductionMorlet waveletMultiresolution analysisVehicle crash modelingSimulation
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Anamorphic fractional Fourier transform: optical implementation and applications

1995

An additional degree of freedom is introduced to fractional-Fourier-transform systems by use of anamorphic optics. A different fractional Fourier order along the orthogonal principal directions is performed. A laboratory experimental system shows preliminary results that demonstrate the proposed theory. Applications such as anamorphic fractional correlation and multiplexing in fractional domains are briefly suggested.

Signal processingSpatial filterComputer sciencebusiness.industryMaterials Science (miscellaneous)Optical signal processingFractional fourier transformMultiplexingIndustrial and Manufacturing EngineeringFractional Fourier transformsymbols.namesakeOpticsFourier transformExperimental systemPattern recognition (psychology)symbolsBusiness and International ManagementbusinessAnamorphic systems
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Support Vector Machines Framework for Linear Signal Processing

2005

This paper presents a support vector machines (SVM) framework to deal with linear signal processing (LSP) problems. The approach relies on three basic steps for model building: (1) identifying the suitable base of the Hilbert signal space in the model, (2) using a robust cost function, and (3) minimizing a constrained, regularized functional by means of the method of Lagrange multipliers. Recently, autoregressive moving average (ARMA) system identification and non-parametric spectral analysis have been formulated under this framework. The generalized, yet simple, formulation of SVM LSP problems is particularized here for three different issues: parametric spectral estimation, stability of I…

Signal processingTelecomunicacionesSupport vector machinesSystem identificationLinear signal processingSpectral density estimationSpectral estimationSupport vector machineGamma filterControl and Systems EngineeringControl theoryComplex ARMASignal ProcessingAutoregressive–moving-average model3325 Tecnología de las TelecomunicacionesComputer Vision and Pattern RecognitionElectrical and Electronic EngineeringInfinite impulse responseDigital filterAlgorithmSoftwareParametric statisticsMathematics
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Event signal characterization for disturbance interpretation in power grid

2018

This paper presents the signal processing approach to detect and characterize the physical events that occur in power system using PMUs signals. A small window is applied so that the extracted spectral features belong to a stationary signal. This is based on applying empirical mode decomposition, followed by square root of spectral kurtosis (SRSK) for computation of statistical indices to indicate the event occurrence. Subsequently, features from these events are extracted using mel frequency cepstral coefficients on SRSK. © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/re…

Signal processingWaveletStationary processComputer sciencebusiness.industryKurtosisPattern recognitionMel-frequency cepstrumArtificial intelligencebusinessSignalHilbert–Huang transformEvent (probability theory)
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Pattern dynamics in a nonlinear electrical lattice

2003

International audience; In this paper, we present experiments using a nonlinear electrical line, modeling the FitzHugh-Nagumo equation, without recovery term. Different patterns are studied according to the para meters of this medium and initial conditions. We then propose to apply these results to the domain of signal processing. We show that erosion and dilation of a binary signal, two kinds,of binarization-one depending on an amplitude threshold, the other on an energetical threshold-and nonlinear filtering allowing noise removal can be obtained in the same medium.

Signal processing[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingNonlinear filteringApplied MathematicsMathematical analysis[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing01 natural sciencesBinary signal010305 fluids & plasmasNonlinear systemAmplitude[NLIN.NLIN-PS]Nonlinear Sciences [physics]/Pattern Formation and Solitons [nlin.PS][INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingControl theoryModeling and SimulationLattice (order)0103 physical sciences[ NLIN.NLIN-PS ] Nonlinear Sciences [physics]/Pattern Formation and Solitons [nlin.PS]010306 general physicsNoise removalEngineering (miscellaneous)[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingMathematics
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Space–bandwidth product of optical signals and systems

1996

The space–bandwidth product (SW) is fundamental for judging the performance of an optical system. Often the SW of a system is defined only as a pure number that counts the degrees of freedom of the system. We claim that a quasi-geometrical representation of the SW in the Wigner domain is more useful. We also represent the input signal as a SW in the Wigner domain. For perfect signal processing it is necessary that the system SW fully embrace the signal SW.

Signal processingbusiness.industryComputer scienceBandwidth (signal processing)TopologyAtomic and Molecular Physics and OpticsElectronic Optical and Magnetic Materialssymbols.namesakeFourier transformOpticssymbolsComputer Vision and Pattern RecognitionSpatial frequencybusinessJournal of the Optical Society of America A
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Nonlinear morphological correlation: optoelectronic implementation

2008

An optoelectronic implementation of the nonlinear morphological correlation by use of a threshold-decomposition technique and a joint transform correlator architecture is presented. This nonlinear morphological correlation provides improved image detection compared with standard linear optical pattern-recognition correlation methods. It also offers a more robust detection of low-intensity images in the presence of high-intensity patterns to be rejected.

Signal processingbusiness.industryComputer scienceMachine visionMaterials Science (miscellaneous)Morphological correlationIndustrial and Manufacturing EngineeringNonlinear systemOpticsPattern recognition (psychology)OptoelectronicsBusiness and International ManagementbusinessLinear filterApplied Optics
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P300-based brain computer interface experimental setup

2009

A Brain-Computer interface (BCI) is a communication system that enables the generation of a control signal from brain signals such as sensorymotor rhythms and evoked potentials; therefore, it constitutes a novel communication option for people with severe motor disabilities (such as Amyotrophic Lateral Sclerosis patients). This paper presents the development of a P300-based BCI. This prototype uses a homemade six-channel electroencephalograph for the acquisition of the signals, and a visual stimulation matrix; since this matrix contains letters of the alphabet as well as images associated to them, it permits word-writing and the elaboration of messages with the images. To process the signal…

Signal processingmedicine.diagnostic_testComputer scienceSpeech recognitionInterface (computing)BrainReproducibility of ResultsElectroencephalographyElectroencephalographyLinear discriminant analysisEvent-Related Potentials P300Sensitivity and SpecificityLeast squaresUser-Computer InterfacePattern Recognition VisualmedicineAlgorithmsVisual CortexBrain–computer interface2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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Mutual Information Analysis of Brain-Heart Interactions in Epileptic Children

2021

In this work we apply the network physiology paradigm to retrieve information from central and autonomic nervous systems before focal epileptic seizure, represented respectively by electroencephalogram (EEG) signals and R-R intervals (RRI), and investigate on the presence and strength of brain-heart interactions by computing mutual information (MI) measures. Statistical significance of MI values was tested through surrogate time series generated with the random shuffle approach. Our results suggest that the proposed method for aligning signals representing brain and heart activity measured with different sampling rates, is capable of revealing coupling between RRI representing heart system,…

Signal processingmedicine.diagnostic_testbusiness.industryTotal frequencySpectral densityPattern recognitionMutual informationHeart activityElectroencephalographyEpilepsy seizure EEG R-R intervals mutual information brain-heart interactionsSettore ING-INF/06 - Bioingegneria Elettronica E InformaticamedicineArtificial intelligenceEpileptic seizuremedicine.symptombusinessMathematics
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