Search results for "Numerical Analysis"

showing 10 items of 883 documents

Description of x-ray beams using the fluorescence yields of a set of thick targets

1995

Quantitative methods in x-ray fluorescence analysis require a knowledge of the spectral distribution of the fluorescence-exciting beam. The use of XRF yield measurements of a set of thick pure element targets is proposed for the description of a fluorescence-exciting x-ray beam, without the need to obtain its spectral distribution. This new approach is derived theoretically and verified by comparing thin-target yields calculated from XRF yield measurements of thick pure element specimens with those obtained from a calculated spectral distribution. The difference between the two methods of obtaining the thin-target yields is within 9% relative error.

Spectral power distributionChemistrybusiness.industryAstrophysics::High Energy Astrophysical PhenomenaNumerical analysisX ray beamFluorescenceSet (abstract data type)OpticsApproximation errorYield (chemistry)businessSpectroscopyBeam (structure)X-Ray Spectrometry
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Performance potential for simulating spin models on GPU

2012

Graphics processing units (GPUs) are recently being used to an increasing degree for general computational purposes. This development is motivated by their theoretical peak performance, which significantly exceeds that of broadly available CPUs. For practical purposes, however, it is far from clear how much of this theoretical performance can be realized in actual scientific applications. As is discussed here for the case of studying classical spin models of statistical mechanics by Monte Carlo simulations, only an explicit tailoring of the involved algorithms to the specific architecture under consideration allows to harvest the computational power of GPU systems. A number of examples, ran…

Spin glassPhysics and Astronomy (miscellaneous)Computer scienceMonte Carlo methodFOS: Physical sciencesComputational scienceCUDAHigh Energy Physics - LatticeStatistical physicsGraphicsCondensed Matter - Statistical MechanicsNumerical AnalysisStatistical Mechanics (cond-mat.stat-mech)Applied MathematicsHigh Energy Physics - Lattice (hep-lat)RangingStatistical mechanicsDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksComputational Physics (physics.comp-ph)Computer Science ApplicationsComputational MathematicsModeling and SimulationIsing modelParallel temperingPhysics - Computational Physics
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Periodic Discrete and Discrete-Time Splines

2018

Periodic discrete splines with different periods and spans are introduced in Sect. 3.4 of Volume I (Averbuch, Neittaanmaki and Zheludev, Spline and Spline Wavelet Methods with Applications to Signal and Image Processing, Springer, Berlin, 2014) [2]. In this chapter, we regard periodic discrete splines as a base for the design of periodic discrete-time wavelets, wavelet packets and wavelet frames. Therefore, only the discrete splines whose spans are 2 are outlined. These discrete splines are linear combinations of the discrete B-splines. So also, the so-called discrete-time splines are discussed in the chapter that are linear combinations of the discrete-time B-splines. The discrete-time B-s…

Spline (mathematics)Computer Science::GraphicsWaveletDiscrete time and continuous timeComputer scienceSpline waveletFast Fourier transformApplied mathematicsImage processingLinear combinationMathematics::Numerical AnalysisWavelet packet decomposition
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Quasi-interpolating and Smoothing Local Splines

2015

In this chapter, local quasi-interpolating and smoothing splines are described. Although approximation properties of local spline are similar to properties of the global interpolating and smoothing splines, their design does not require the IIR filtering of the whole data array. The computation of a local spline value at some point utilizes only a few adjacent grid samples. Therefore, local splines can be used for real-time processing of signals and for the design of FIR filter banks generating wavelets and wavelet frames (Chaps. 12 and 14). In the chapter, local splines of different orders are designed and their approximation properties are established which are compared with the propertie…

Spline (mathematics)Smoothing splineComputer Science::GraphicsWaveletFinite impulse responseComputer scienceApproximation propertyComputationApplied mathematicsArray data typeSmoothingMathematics::Numerical Analysis
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Non-linear systems under impulsive parametric input

1999

In this paper the problem of the response of non-linear systems excited by an impulsive parametric input is treated. For such systems the response exhibits a jump depending on the amplitude of the impulse as well as on the value of the state variables immediately before the impulse occurrence. Recently, the jump prediction has been obtained in a series form. Here the incremental rule for any scalar real valued function is obtained in an analytical form involving the jump of the state variables. It is also shown that the formulation for the jump evaluation is also able to give a new step-by-step integration technique.

State variableApplied MathematicsMechanical EngineeringNumerical analysisDuffing equationImpulse (physics)Nonlinear systemReal-valued functionMechanics of MaterialsControl theoryJumpApplied mathematicsMathematicsParametric statistics
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Statistical correlation of fractional oscillator response by complex spectral moments and state variable expansion

2016

Abstract The statistical characterization of the oscillator response with non-integer order damping under Gaussian noise represents an important challenge in the modern stochastic mechanics. In fact, this kind of problem appears in several issues of different type (wave propagation in viscoelastic media, Brownian motion, fluid dynamics, RLC circuit, etc.). The aim of this paper is to provide a stochastic characterization of the stationary response of linear fractional oscillator forced by normal white noise. In particular, this paper shows a new method to obtain the correlation function by exact complex spectral moments. These complex quantities contain all the information to describe the r…

State variableNon-Newtonian damping Fractional-order state variables Analytical stationary variance Exact complex spectral moments02 engineering and technologyFractional-order state variable01 natural sciencesAnalytical stationary variance010305 fluids & plasmassymbols.namesake0203 mechanical engineering0103 physical sciencesExact complex spectral momentNumerical AnalysiBrownian motionMathematicsNumerical AnalysisMellin transformStochastic processApplied MathematicsMathematical analysisWhite noiseNon-Newtonian dampingMoment (mathematics)Correlation function (statistical mechanics)020303 mechanical engineering & transportsGaussian noiseModeling and Simulationsymbols
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On-line Construction of Two-Dimensional Suffix Trees

1999

AbstractWe say that a data structure is builton-lineif, at any instant, we have the data structure corresponding to the input we have seen up to that instant. For instance, consider the suffix tree of a stringx[1,n]. An algorithm building iton-lineis such that, when we have read the firstisymbols ofx[1,n], we have the suffix tree forx[1,i]. We present a new technique, which we refer to asimplicit updates, based on which we obtain: (a) an algorithm for theon-lineconstruction of the Lsuffix tree of ann×nmatrixA—this data structure is the two-dimensional analog of the suffix tree of a string; (b) simple algorithms implementing primitive operations forLZ1-typeon-line losslessimage compression m…

Statistics and ProbabilityCompressed suffix arrayNumerical AnalysisControl and OptimizationAlgebra and Number TheoryTheoretical computer scienceApplied MathematicsGeneral MathematicsSuffix treeString (computer science)Generalized suffix treelaw.inventionLongest common substring problemTree (data structure)lawSuffixAlgorithmFM-indexMathematicsJournal of Complexity
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Binary distributions of concentric rings

2014

We introduce families of jointly symmetric, binary distributions that are generated over directed star graphs whose nodes represent variables and whose edges indicate positive dependences. The families are parametrized in terms of a single parameter. It is an outstanding feature of these distributions that joint probabilities relate to evenly spaced concentric rings. Kronecker product characterizations make them computationally attractive for a large number of variables. We study the behavior of different measures of dependence and derive maximum likelihood estimates when all nodes are observed and when the inner node is hidden.

Statistics and ProbabilityContingency tableKronecker productDiscrete mathematicsNumerical AnalysisBinary numberStar (graph theory)Combinatoricssymbols.namesakeConditional independenceJoint probability distributionsymbolsFeature (machine learning)Node (circuits)Statistics Probability and UncertaintyMathematicsJournal of Multivariate Analysis
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The rank of random regular digraphs of constant degree

2018

Abstract Let d be a (large) integer. Given n ≥ 2 d , let A n be the adjacency matrix of a random directed d -regular graph on n vertices, with the uniform distribution. We show that the rank of A n is at least n − 1 with probability going to one as n grows to infinity. The proof combines the well known method of simple switchings and a recent result of the authors on delocalization of eigenvectors of A n .

Statistics and ProbabilityControl and OptimizationUniform distribution (continuous)General Mathematics0102 computer and information sciencesrandom matrices01 natural sciencesCombinatoricsIntegerFOS: Mathematics60B20 15B52 46B06 05C80Rank (graph theory)Adjacency matrix0101 mathematicsEigenvalues and eigenvectorsMathematicsNumerical AnalysisAlgebra and Number TheoryDegree (graph theory)Applied MathematicsProbability (math.PR)010102 general mathematicsrandom regular graphssingularity probabilityrank010201 computation theory & mathematicsRegular graphRandom matrixMathematics - ProbabilityJournal of Complexity
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The affine equivariant sign covariance matrix: asymptotic behavior and efficiencies

2003

We consider the affine equivariant sign covariance matrix (SCM) introduced by Visuri et al. (J. Statist. Plann. Inference 91 (2000) 557). The population SCM is shown to be proportional to the inverse of the regular covariance matrix. The eigenvectors and standardized eigenvalues of the covariance, matrix can thus be derived from the SCM. We also construct an estimate of the covariance and correlation matrix based on the SCM. The influence functions and limiting distributions of the SCM and its eigenvectors and eigenvalues are found. Limiting efficiencies are given in multivariate normal and t-distribution cases. The estimates are highly efficient in the multivariate normal case and perform …

Statistics and ProbabilityCovariance functionaffine equivarianceinfluence functionMultivariate normal distributionrobustnessComputer Science::Human-Computer InteractionEfficiencyestimatorsEstimation of covariance matricesScatter matrixStatisticsAffine equivarianceApplied mathematicsCMA-ESMultivariate signCovariance and correlation matricesRobustnessmultivariate medianMathematicsprincipal componentsInfluence functionNumerical AnalysisMultivariate medianCovariance matrixcovariance and correlation matricesdiscriminant-analysisCovarianceComputer Science::Otherdispersion matricesefficiencyLaw of total covariancemultivariate locationtestsStatistics Probability and Uncertaintyeigenvectors and eigenvaluesEigenvectors and eigenvaluesmultivariate signJournal of Multivariate Analysis
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