Search results for "Pattern Recognition"

showing 10 items of 2301 documents

Electrocardiogram Signal Analysing - Delineation and Localization of ECG Component

2016

In this paper, we develop a new approach based on nonlinear filtering scheme (NLFS) on cardiac signal to evaluate a robust single-lead electrocardiogram (ECG) delineation system and waves localization method based on nonlinear filtering approach. This system is built in two phases, in the first phase, we proposed a mathematical model for detecting ECG features like QRS complex peak, P and T-waves onsets and ends from noise free of synthetic ECG signal. Later, we develop a theoretical model to obtain real approach for detecting these features from real noisy ECG signals. Our method has been evaluated on electrocardiogram signals of QT-MIT standard database, the QRS peak achieve sensitivity (…

Signal processingNoise (signal processing)Computer sciencebusiness.industryPhase (waves)Pattern recognitionSignalStandard deviationQRS complexComputer visionSensitivity (control systems)Artificial intelligenceEcg signalbusinessProceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies
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Observer-based finite-time fuzzy H∞ control for discrete-time systems with stochastic jumps and time-delays

2014

This paper is concerned with the problem of observer-based finite-time H ∞ control for a family of discrete-time Markovian jump nonlinear systems with time-delays represented by Takagi-Sugeno (T-S) model. The main contribution of this paper is to design an observer-based finite-time H ∞ controller such that the resulting closed-loop system is stochastic finite-time bounded and satisfies a prescribed H ∞ disturbance attenuation level over the given finite-time interval. Sufficient criteria on stochastic finite-time H ∞ stabilization via observer-based fuzzy state feedback are presented for the solvability of the problem, which can be tackled by a feasibility problem in terms of linear matrix…

Signal processingObserver (quantum physics)Finite-time H∞ controlTakagi-Sugeno (T-S) modelMarkovian jump systemsFuzzy control systemFuzzy logicFinite-time H∞ control; Markovian jump systems; Observer-based control; Takagi-Sugeno (T-S) model; Electrical and Electronic Engineering; Control and Systems Engineering; Software; Signal Processing; 1707Nonlinear systemobserver-based controlTakagi–Sugeno (T–S) modelDiscrete time and continuous timeControl and Systems EngineeringControl theoryBounded functionSignal ProcessingComputer Vision and Pattern RecognitionState observerElectrical and Electronic Engineeringfinite-time H∞ controlfinite-time H infinity controlObserver-based controlSoftware1707Mathematics
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Information – theoretic characterization of concurrent activity of neural spike trains

2021

The analysis of massively parallel spike train recordings facilitates investigation of communications and synchronization in neural networks. In this work we develop and evaluate a measure of concurrent neural activity, which is based on intrinsic firing properties of the recorded neural units. An overall single neuron activity is unfolded in time and decomposed into working and non-firing state, providing a coarse, binary representation of the neurons functional state. We propose a modified measure of mutual information to reflect the degree of simultaneous activation and concurrency in neural firing patterns. The measure is shown to be sensitive to both correlations and anti-correlations,…

Signal processingQuantitative Biology::Neurons and CognitionArtificial neural networkComputer sciencebusiness.industrySpike trainFiring patterns020206 networking & telecommunicationsPattern recognition02 engineering and technologyMeasure (mathematics)Concurrent activityMutual informationNeural activitymedicine.anatomical_structure0202 electrical engineering electronic engineering information engineeringmedicineSpike trains020201 artificial intelligence & image processingSpike (software development)NeuronArtificial intelligencebusinessNeural synchrony2020 28th European Signal Processing Conference (EUSIPCO)
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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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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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