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STABILITY PROPERTIES OF SYSTEMS OF LINEAR STOCHASTIC DIFFERENTIAL EQUATIONS WITH RANDOM COEFFICIENTS

机译:随机系数线性随机微分方程系统的稳定性特性

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摘要

This work is concerned with the stability properties of linear stochastic differential equations with random (drift and diffusion) coefficient matrices and the stability of a corresponding random transition matrix (or exponential semigroup). We consider a class of random matrix drift coefficients that involves random perturbations of an exponentially stable flow of deterministic (time-varying) drift matrices. In contrast with more conventional studies, our analysis is not based on the existence of Lyapunov functions, and it does not rely on any ergodic properties. These approaches are often difficult to apply in practice when the drift/diffusion coefficients are random. We present rather weak and easily checked perturbation-type conditions for the asymptotic stability of time-varying and random linear stochastic differential equations. We provide new log-Lyapunov estimates and exponential contraction inequalities on any time horizon as soon as the fluctuation parameter is sufficiently small. These seem to be the first results of this type for this class of linear stochastic differential equations with random coefficient matrices.
机译:该工作涉及具有随机(漂移和扩散)系数矩阵的线性随机微分方程的稳定性特性以及相应的随机转换矩阵(或指数半群)的稳定性。我们考虑一类随机矩阵漂移系数,其涉及对指数稳定的确定性(时变)漂移矩阵的指数稳定流动的随机扰动。与更传统的研究相比,我们的分析不是基于Lyapunov功能的存在,并且它不依赖于任何ergodic属性。当漂移/扩散系数随机时,这些方法往往难以在实践中应用。我们为时变和随机线性随机微分方程的渐近稳定性呈现相当弱且易于检查的扰动型条件。一旦波动参数足够小,我们就提供了新的Log-Lyapunov估计和指数收缩不平等。这些似乎是具有随机系数矩阵的这类线性随机微分方程的这种类型的第一个结果。

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