In this paper, the probabilistic response of nonlinear systems driven by alpha-stable Levy white noises is considered. The path integral solution is adopted for determining the evolution of the probability density function of nonlinear oscillators. Specifically, based on the properties of alpha-stable random variables and processes, the path integral solution is extended to deal with Levy white noises input with any value of the stability index alpha. It is shown that at the limit when the time increments tend to zero, the Einstein-Smoluchowsky equation, governing the evolution of the response probability density function, is fully restored. Application to linear and nonlinear systems under different values of alpha is reported. Comparisons...
In this paper the first passage problem is examined for linear and nonlinear systems driven by Poiss...
A new method is presented for approximating the stationary probability density function of the respo...
A new method is presented for approximating the stationary probability density function of the respo...
In this paper the problem of the first-passage probabilities determination of nonlinear systems unde...
In this paper, the first-passage problem for nonlinear systems driven by (Formula presented.)-stable...
In this paper the response of nonlinear systems under stationary Gaussian white noise excitation is ...
In this paper the problem of the response evaluation in terms of probability density function of non...
In this paper the response in terms of probability density function of non-linear systems under Pois...
Aim of this paper is an investigation on the consistency of the Path Integration (PI) method already...
In this paper the extension of the Path Integral to non-linear systems driven by Poissonian White No...
In this paper, the probability density evolution of Markov processes is analyzed for a class of barr...
In this paper the nonstationary response of a class of nonlinear systems subject to broad-band stoch...
The stochastic response of linear and non-linear systems to external \u3b1-stable L\ue9vy white nois...
The response of a dynamical system modelled by differential equations with white noise as the forcin...
A numerical method for approximating the statistics of the solution of nonlinear stochastic systems ...
In this paper the first passage problem is examined for linear and nonlinear systems driven by Poiss...
A new method is presented for approximating the stationary probability density function of the respo...
A new method is presented for approximating the stationary probability density function of the respo...
In this paper the problem of the first-passage probabilities determination of nonlinear systems unde...
In this paper, the first-passage problem for nonlinear systems driven by (Formula presented.)-stable...
In this paper the response of nonlinear systems under stationary Gaussian white noise excitation is ...
In this paper the problem of the response evaluation in terms of probability density function of non...
In this paper the response in terms of probability density function of non-linear systems under Pois...
Aim of this paper is an investigation on the consistency of the Path Integration (PI) method already...
In this paper the extension of the Path Integral to non-linear systems driven by Poissonian White No...
In this paper, the probability density evolution of Markov processes is analyzed for a class of barr...
In this paper the nonstationary response of a class of nonlinear systems subject to broad-band stoch...
The stochastic response of linear and non-linear systems to external \u3b1-stable L\ue9vy white nois...
The response of a dynamical system modelled by differential equations with white noise as the forcin...
A numerical method for approximating the statistics of the solution of nonlinear stochastic systems ...
In this paper the first passage problem is examined for linear and nonlinear systems driven by Poiss...
A new method is presented for approximating the stationary probability density function of the respo...
A new method is presented for approximating the stationary probability density function of the respo...