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 of the system under Gaussian white noise and the probability density function of the α/2-stable random parameter. Some numerical applications have been reported assessing the reliability of the proposed formulation. Moreover a proper way to perform digital simulation of the sub-Gaussian α-stable random process preventing dynamical systems from numerical overflows has been reported and discussed in detail.
Di Paola, M., Pirrotta, A., Zingales, M. (2008). Stochastic analysis of external and parametric dynamical systems under sub-Gaussian Lévy white-noise. STRUCTURAL ENGINEERING AND MECHANICS, 28(4), 373-386 [10.12989/sem.2008.28.4.373].
Stochastic analysis of external and parametric dynamical systems under sub-Gaussian Lévy white-noise
DI PAOLA, Mario;PIRROTTA, Antonina;ZINGALES, Massimiliano
2008-01-01
Abstract
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 of the system under Gaussian white noise and the probability density function of the α/2-stable random parameter. Some numerical applications have been reported assessing the reliability of the proposed formulation. Moreover a proper way to perform digital simulation of the sub-Gaussian α-stable random process preventing dynamical systems from numerical overflows has been reported and discussed in detail.File | Dimensione | Formato | |
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