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RESEARCH PRODUCT
Non-linear systems under parametric alpha-stable LÉVY WHITE NOISES
Mario Di PaolaAntonina PirrottaMassimiliano Zingalessubject
symbols.namesakeNonlinear systemFourier transformDynamical systems theoryCharacteristic function (probability theory)Stochastic processControl theoryDifferential equationsymbolsProbability density functionWhite noiseStatistical physicsMathematicsdescription
In this study stochastic analysis of nonlinear dynamical systems under a-stable, multiplicative white noise has been performed. Analysis has been conducted by means of the Ito rule extended to the case of α-stable noises. In this context the order of increments of Levy process has been evaluated and differential equations ruling the evolutions of statistical moments of either parametrically and external dynamical systems have been obtained. The extended Ito rule has also been used to yield the differential equation ruling the evolution of the characteristic function for parametrically excited dynamical systems. The Fourier transform of the characteristic function, namely the probability density function is ruled by the extended Einstein-Smoluchowsky differential equation to case of parametrically excited dynamical systems. Some numerical applications have been reported to assess the reliability of the proposed formulation.Copyright © 2005 by ASME
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2005-01-01 |