Search results for "fast fourier transform."

showing 7 items of 67 documents

Object Classification Technique for mmWave FMCW Radars using Range-FFT Features

2021

In this article, we present a novel target classification technique by mmWave frequency modulated continuous wave (FMCW) Radars using the Machine Learning on raw data features obtained from range fast Fourier transform (FFT) plot. FFT plots are extracted from the measured raw data obtained with a Radar operating in the frequency range of 77- 81 GHz. The features such as peak, width, area, standard deviation, and range on range FFT plot peaks are extracted and fed to a machine learning model. Two light weight classification models such as Logistic Regression, Naive Bayes are explored to assess the performance. Based on the results, we demonstrate and achieve an accuracy of 86.9% using Logist…

business.industryComputer scienceFeature extractionFast Fourier transformCognitive neuroscience of visual object recognitionPattern recognitionPlot (graphics)law.inventionNaive Bayes classifierlawRange (statistics)Artificial intelligenceRadarbusinessFrequency modulation2021 International Conference on COMmunication Systems & NETworkS (COMSNETS)
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Simplified model of mean double step (MDS) in human body movement

2012

In this paper we present a simplified and useful model of the human body movement based on the full gait cycle description, called the Mean Double Step (MDS). It enables the parameterization and simplification of the human movement. Furthermore it allows a description of the gait cycle by providing standardized estimators to transform the gait cycle into a periodical movement process. Moreover the method of simplifying the MDS model and its compression are demonstrated. The simplification is achieved by reducing the number of bars of the spectrum and I or by reducing the number of samples describing the MDS both in terms of reducing their computational burden and their resources for the dat…

business.industryComputer scienceMovement (music)Compression (functional analysis)Computer data storageFast Fourier transformProcess (computing)EstimatorBody movementbusinessGait cycleAlgorithmSimulationSPIE Proceedings
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Classification of Chitinozoa (Llandoverian, Canada) Using Image Analysis

1996

Chitinozoa (Llandoverian, Canada) were studied using image analysis. After digitalization of the objects, shape parameters were calculated. The boundary of each fossil was then traced by a vector centred at the centroid for Fast Fourier Transform (FFT). Results of the two methods were used as variables in a hierarchical cluster analysis in order to group the samples. These results show that Chitinozoa can be significantly classified in terms of taxa using independent shape parameters obtained by image analysis.

business.industryFast Fourier transformCentroidBoundary (topology)Pattern recognitionImage (mathematics)Hierarchical clusteringsymbols.namesakeFourier transformsymbolsArtificial intelligencebusinessInstrumentationMathematicsMicroscopy Microanalysis Microstructures
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Fractional-Fourier-transform calculation through the fast-Fourier-transform algorithm.

1996

A method for the calculation of the fractional Fourier transform (FRT) by means of the fast Fourier transform (FFT) algorithm is presented. The process involves mainly two FFT’s in cascade; thus the process has the same complexity as this algorithm. The method is valid for fractional orders varying from −1 to 1. Scaling factors for the FRT and Fresnel diffraction when calculated through the FFT are discussed.

business.industryNon-uniform discrete Fourier transformMaterials Science (miscellaneous)Fast Fourier transformPrime-factor FFT algorithmShort-time Fourier transformIndustrial and Manufacturing EngineeringFractional Fourier transformDiscrete Fourier transformOpticsSplit-radix FFT algorithmRader's FFT algorithmBusiness and International ManagementbusinessAlgorithmMathematicsApplied optics
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A fast Fourier transform based direct solver for the Helmholtz problem

2018

This article is devoted to the efficient numerical solution of the Helmholtz equation in a two‐ or three‐dimensional (2D or 3D) rectangular domain with an absorbing boundary condition (ABC). The Helmholtz problem is discretized by standard bilinear and trilinear finite elements on an orthogonal mesh yielding a separable system of linear equations. The main key to high performance is to employ the fast Fourier transform (FFT) within a fast direct solver to solve the large separable systems. The computational complexity of the proposed FFT‐based direct solver is O(N log N) operations. Numerical results for both 2D and 3D problems are presented confirming the efficiency of the method discussed…

finite‐element discretizationHelmholtz equationDiscretizationFast Fourier transform010103 numerical & computational mathematicsSystem of linear equationsabsorbing boundary conditions01 natural sciencessymbols.namesake35J05 42A38 65F05 65N22FOS: MathematicsFourier'n sarjatApplied mathematicsBoundary value problemMathematics - Numerical AnalysisHelmholtz equation0101 mathematicsMathematicsosittaisdifferentiaaliyhtälötAlgebra and Number Theorynumeeriset menetelmätApplied MathematicsNumerical Analysis (math.NA)SolverFinite element method010101 applied mathematicsFourier transformsymbolsFourier transformnumeerinen analyysifast direct solver
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Classification of Targets Using Statistical Features from Range FFT of mmWave FMCW Radars

2021

Radars with mmWave frequency modulated continuous wave (FMCW) technology accurately estimate the range and velocity of targets in their field of view (FoV). The targeted angle of arrival (AoA) estimation can be improved by increasing receiving antennas or by using multiple-input multiple-output (MIMO). However, obtaining target features such as target type remains challenging. In this paper, we present a novel target classification method based on machine learning and features extracted from a range fast Fourier transform (FFT) profile by using mmWave FMCW radars operating in the frequency range of 77–81 GHz. The measurements are carried out in a variety of realistic situations, including p…

mmWave radarrange FFT featuresTK7800-8360Computer Networks and CommunicationsComputer scienceVDP::Technology: 500Fast Fourier transformReal-time computingtargets classificationFMCW radarSupport vector machineContinuous-wave radarStatistical classificationNaive Bayes classifiermachine learningautonomous systemsHardware and ArchitectureControl and Systems EngineeringFeature (computer vision)Angle of arrivalSignal Processingground station radarGradient boostingElectrical and Electronic EngineeringElectronics
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Detecting clusters in spatially correlated waveforms

2017

Seismic networks often record signals characterized by similar shapes that provide important information according to their geographic positions. We propose an approach to identify homogeneous clusters of seismic waves, combining analysis of waveforms with metadata and spectrogram information. In waveforms clustering, cross-correlation measures between signals may presents some limitations, so we refer to more recent contributes relating data-depth based clustering analysis. The mechanism for alignment is also an important topic of the analysis: warping (or aligning) procedures identify nuisance effects in phase variation, that, if ignored, may result in a possible loss of information and t…

spatial clusteringfast fourier transform.Seismic waveformfunctional data analysiSettore SECS-S/01 - StatisticaSeismic waveforms; spatial clustering; functional data analysis; fast fourier transform.
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