Article

# An adaptive scheme for the approximation of dissipative systems

Stochastic Processes and their Applications (Impact Factor: 1.05). 03/2005; DOI: 10.1016/j.spa.2007.02.004

Source: arXiv

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**ABSTRACT:**In a previous paper, we studied the ergodic properties of an Euler scheme of a stochastic differential equation with a Gaussian additive noise in order to approximate the stationary regime of such equation. We now consider the case of multiplicative noise when the Gaussian process is a fractional Brownian Motion with Hurst parameter H>1/2 and obtain some (functional) convergences properties of some empirical measures of the Euler scheme to the stationary solutions of such SDEs.Stochastic Processes and their Applications 11/2012; · 1.05 Impact Factor - [Show abstract] [Hide abstract]

**ABSTRACT:**In this paper, we obtain some existence results of stationary solutions to a class of SDEs driven by continuous Gaussian processes with stationary increments. We propose a constructive approach based on the study of some sequences of empirical measures of Euler schemes of these SDEs. In our main result, we obtain the functional convergence of this sequence to a stationary solution to the SDE. We also obtain some specific properties of the stationary solution. In particular, we show that, in contrast to Markovian SDEs, the initial random value of a stationary solution and the driving Gaussian process are always dependent. This emphasizes the fact that the concept of invariant distribution is definitely different to the Markovian case.01/2009; -
##### Article: RECURSIVE COMPUTATION OF THE INVARIANT MEASURE OF A STOCHASTIC DIFFERENTIAL EQUATION DRIVEN BY A L

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**ABSTRACT:**We study some recursive procedures based on exact or approx- imate Euler schemes with decreasing step to compute the invariant measure of Levy driven SDEs. We prove the convergence of these procedures toward the invariant measure under weak conditions on the moment of the Levy process and on the mean-reverting of the dy- namical system. We also show that an a.s. CLT for stable processes can be derived from our main results. Finally, we illustrate our results by several simulations.

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