TY - JOUR
T1 - Stochastic analysis of external and parametric dynamical systems under sub-Gaussian Lévy white-noise
AU - Di Paola, Mario
AU - Zingales, Massimiliano
AU - Pirrotta, Antonina
AU - Di Paola, Mario
AU - Zingales, Massimiliano
AU - Pirrotta, Antonina
PY - 2008
Y1 - 2008
N2 - 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-stablestochastic processes namely sub-Gaussian white noises. In this setting the governing equation either of theprobability density function or of the characteristic function of the dynamical response may be obtainedconsidering 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 functionof the response by means of a simple integral involving the probability density function of the systemunder Gaussian white noise and the probability density function of the α/2-stable random parameter. Somenumerical applications have been reported assessing the reliability of the proposed formulation. Moreovera proper way to perform digital simulation of the sub-Gaussian α-stable random process preventingdynamical systems from numerical overflows has been reported and discussed in detail.
AB - 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-stablestochastic processes namely sub-Gaussian white noises. In this setting the governing equation either of theprobability density function or of the characteristic function of the dynamical response may be obtainedconsidering 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 functionof the response by means of a simple integral involving the probability density function of the systemunder Gaussian white noise and the probability density function of the α/2-stable random parameter. Somenumerical applications have been reported assessing the reliability of the proposed formulation. Moreovera proper way to perform digital simulation of the sub-Gaussian α-stable random process preventingdynamical systems from numerical overflows has been reported and discussed in detail.
KW - Fokker-Planck equation
KW - Lévy white noise
KW - stochastic differential calculus
KW - sub-Gaussian white noise.
KW - Fokker-Planck equation
KW - Lévy white noise
KW - stochastic differential calculus
KW - sub-Gaussian white noise.
UR - http://hdl.handle.net/10447/43477
M3 - Article
VL - 28
SP - 373
EP - 386
JO - Structural Engineering and Mechanics
JF - Structural Engineering and Mechanics
SN - 1225-4568
ER -