Search results for "Characteristic function"

showing 10 items of 26 documents

Stochastic dynamics of nonlinear systems with a fractional power-law nonlinear term: The fractional calculus approach

2011

Fractional power-law nonlinear drift arises in many applications of engineering interest, as in structures with nonlinear fluid viscous–elastic dampers. The probabilistic characterization of such structures under external Gaussian white noise excitation is still an open problem. This paper addresses the solution of such a nonlinear system providing the equation governing the evolution of the characteristic function, which involves the Riesz fractional operator. An efficient numerical procedure to handle the problem is also proposed.

Differential equationOpen problemAerospace EngineeringOcean EngineeringFractional calculuStochastic differential equationsymbols.namesakeFractional programmingNonlinear viscous–elastic damperCivil and Structural EngineeringMathematicsStochastic differential equationMechanical EngineeringCharacteristic functionMathematical analysisPower-law driftStatistical and Nonlinear PhysicsWhite noiseCondensed Matter PhysicsFractional differential equationFractional calculusNonlinear systemNuclear Energy and EngineeringGaussian noisesymbolsSettore ICAR/08 - Scienza Delle CostruzioniProbabilistic Engineering Mechanics
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Sur les problèmes d'optimisation structurelle

2000

We discuss existence theorems for shape optimization and material distribution problems. The conditions that we impose on the unknown sets are continuity of the boundary, respectively a certain measurability hypothesis. peerReviewed

Dirichlet problemCharacteristic function (probability theory)CalculusNeumann boundary conditionApplied mathematicsExistence theoremBoundary (topology)Shape optimizationGeneral MedicineBoundary value problemOptimal controlMathematics
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Radon transform as a set of probability distributions

2009

It is proved that the Radon transform of the Wigner function gives the probability distributions related to measuring the observable operators obtained as linear combinations of position and momentum of the relevant particle. The generalization to an arbitrary number of degrees of freedom is given.

Integral transformsOptical tomographySettore FIS/02 - Fisica Teorica Modelli E Metodi MatematiciRadon transformCharacteristic function (probability theory)Mathematical analysisWigner semicircle distributionCondensed Matter PhysicsConvolution of probability distributionsAtomic and Molecular Physics and OpticsSettore FIS/03 - Fisica Della MateriaRegular conditional probabilityProbability distributionWigner distribution functionQuantum tomographyMathematical PhysicsMathematicsK-distribution
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Stochastic analysis of external and parametric dynamical systems under sub-Gaussian Levy white-noise

2008

In this study stochastic analysis of non-linear dynamical systems under α-stable, multiplicative white noise has been conducted. The analysis has dealt with a special class of α-stable stochastic processes namely sub-Gaussian white noises. In this setting the governing equation either of the probability density function or of the characteristic function of the dynamical response may be obtained considering the dynamical system forced by a Gaussian white noise with an uncertain factor with α/2- stable distribution. This consideration yields the probability density function or the characteristic function of the response by means of a simple integral involving the probability density function …

Mathematical optimizationDynamical systems theoryCharacteristic function (probability theory)Stochastic processMechanical EngineeringFokker-Planck equationProbability density functionLévy white noiseBuilding and ConstructionWhite noiseStable processstochastic differential calculusymbols.namesakeAdditive white Gaussian noiseMechanics of MaterialssymbolsStatistical physicssub-Gaussian white noise.Settore ICAR/08 - Scienza Delle CostruzioniRandom dynamical systemCivil and Structural EngineeringMathematicsStructural Engineering and Mechanics
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Riesz fractional integrals and complex fractional moments for the probabilistic characterization of random variables

2012

Abstract The aim of this paper is the probabilistic representation of the probability density function (PDF) or the characteristic function (CF) in terms of fractional moments of complex order. It is shown that such complex moments are related to Riesz and complementary Riesz integrals at the origin. By invoking the inverse Mellin transform theorem, the PDF or the CF is exactly evaluated in integral form in terms of complex fractional moments. Discretization leads to the conclusion that with few fractional moments the whole PDF or CF may be restored. Application to the pathological case of an α -stable random variable is discussed in detail, showing the impressive capability to characterize…

Mellin transformFractional spectral momentDiscretizationCharacteristic function (probability theory)Mechanical EngineeringCharacteristic functionMathematical analysisAerospace EngineeringComplex order momentOcean EngineeringStatistical and Nonlinear PhysicsProbability density functionFractional calculuCondensed Matter PhysicsFractional calculusNuclear Energy and EngineeringProbability density functionApplied mathematicsFractional momentRandom variableCumulantMellin transformCivil and Structural EngineeringMathematicsTaylor expansions for the moments of functions of random variablesProbabilistic Engineering Mechanics
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Limits in the characteristic function description of non-Lindblad-type open quantum systems

2005

In this paper I investigate the usability of the characteristic functions for the description of the dynamics of open quantum systems focussing on non-Lindblad-type master equations. I consider, as an example, a non-Markovian generalized master equation containing a memory kernel which may lead to nonphysical time evolutions characterized by negative values of the density matrix diagonal elements [S.M. Barnett and S. Stenholm, Phys. Rev. A {\bf 64}, 033808 (2001)]. The main result of the paper is to demonstrate that there exist situations in which the symmetrically ordered characteristic function is perfectly well defined while the corresponding density matrix loses positivity. Therefore no…

PhysicsDensity matrixQuantum PhysicsQuantum decoherenceCharacteristic function (probability theory)Stochastic processDiagonalFOS: Physical sciencesAtomic and Molecular Physics and OpticsQuantum mechanicsKernel (statistics)Master equationStatistical physicsQuantum Physics (quant-ph)Quantum
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LÉVY FLIGHT SUPERDIFFUSION: AN INTRODUCTION

2008

After a short excursion from discovery of Brownian motion to the Richardson "law of four thirds" in turbulent diffusion, the article introduces the L\'{e}vy flight superdiffusion as a self-similar L\'{e}vy process. The condition of self-similarity converts the infinitely divisible characteristic function of the L\'{e}vy process into a stable characteristic function of the L\'{e}vy motion. The L\'{e}vy motion generalizes the Brownian motion on the base of the $\alpha$-stable distributions theory and fractional order derivatives. The further development of the idea lies on the generalization of the Langevin equation with a non-Gaussian white noise source and the use of functional approach. Th…

PhysicsStationary distributionStatistical Mechanics (cond-mat.stat-mech)Characteristic function (probability theory)Applied MathematicsFOS: Physical sciencesWhite noiseLévy processLangevin equationNonlinear systemLévy flightModeling and SimulationStatistical physicsEngineering (miscellaneous)Condensed Matter - Statistical MechanicsBrownian motionInternational Journal of Bifurcation and Chaos
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Mixed Convolutions and Zak Transforms

2015

In this chapter we introduce the mixed continuous–discrete and discrete–discrete convolutions. Important special cases of such convolutions are the polynomial and discrete splines, respectively. The Zak transforms, which are introduced in the chapter, provide integral representation of signals, which, in the following chapters, serves as a tool for the design of splines and spline-wavelets and operations over them. The exponential splines, which are the Zak transforms of polynomial and discrete B-splines are introduced. Explicit formulas for the characteristic functions of splines’ spaces are derived.

PolynomialPure mathematicsComputer Science::GraphicsIntegral representationCharacteristic function (probability theory)Fourier seriesExponential splineMathematics::Numerical AnalysisMathematics
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The norm of the characteristic function of a set in the John‐Nirenberg space of exponent p

2020

Set (abstract data type)Characteristic function (convex analysis)Pure mathematicsGeneral MathematicsGeneral EngineeringExponentSpace (mathematics)Nirenberg and Matthaei experimentBounded mean oscillationMathematicsMathematical Methods in the Applied Sciences
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Stationary and non-stationary probability density function for non-linear oscillators

1997

A method for the evaluation of the stationary and non-stationary probability density function of non-linear oscillators subjected to random input is presented. The method requires the approximation of the probability density function of the response in terms of C-type Gram-Charlier series expansion. By applying the weighted residual method, the Fokker-Planck equation is reduced to a system of non-linear first order ordinary differential equations, where the unknowns are the coefficients of the series expansion. Furthermore, the relationships between the A-type and C-type Gram-Charlier series coefficient are derived.

Stationary distributionCharacteristic function (probability theory)Applied MathematicsMechanical EngineeringMathematical analysisProbability density functionStationary sequencestochastic non-linear dynamics; Gram-Charlier expansions; approximate probability density functionGram-Charlier expansionsMechanics of Materialsstochastic non-linear dynamicsProbability distributionProbability-generating functionapproximate probability density functionSeries expansionRandom variableMathematics
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