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Exponential ergodicity of some Markov dynamical systems with application to a Poisson-driven stochastic differential equation

机译:某些Markov动力系统的指数遍历性及其在Poisson驱动的随机微分方程中的应用

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摘要

We are concerned with the asymptotics of the Markov chain given by the post-jump locations of a certain piecewise-deterministic Markov process with a state-dependent jump intensity. We provide sufficient conditions for such a model to possess a unique invariant distribution, which is exponentially attracting in the dual-bounded Lipschitz distance. Having established this, we generalize a result of J. Kazak on the jump process defined by a Poisson-driven stochastic differential equation with a solution-dependent intensity of perturbations.
机译:我们关注由某些分段确定性马尔可夫过程的跳跃后位置给出的马尔可夫链的渐近性,该过程具有与状态有关的跳跃强度。我们为这样的模型提供了充分的条件,使其拥有唯一的不变分布,该分布在双边界Lipschitz距离中呈指数吸引。确定了这一点后,我们推广了J. Kazak关于由泊松驱动的随机微分方程定义的跳跃过程的结果,该方程具有与解有关的扰动强度。

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