Optimization-based Lyapunov function construction for continuous-time Markov chains with affine transition rates

A. Milias-Argeitis, M. Khammash
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引用次数: 11

Abstract

We address the problem of Lyapunov function construction for a class of continuous-time Markov chains with affine transition rates, typically encountered in stochastic chemical kinetics. Following an optimization approach, we take advantage of existing bounds from the Foster-Lyapunov stability theory to obtain functions that enable us to estimate the region of high stationary probability, as well as provide upper bounds on moments of the chain. Our method can be used to study the stationary behavior of a given chain without resorting to stochastic simulation, in a fast and efficient manner.
具有仿射跃迁速率的连续马尔可夫链基于优化的Lyapunov函数构造
我们解决了一类具有仿射跃迁速率的连续马尔可夫链的Lyapunov函数构造问题,这类问题通常在随机化学动力学中遇到。根据优化方法,我们利用Foster-Lyapunov稳定性理论的现有边界来获得使我们能够估计高平稳概率区域的函数,并提供链矩的上界。该方法可以在不需要随机模拟的情况下,快速有效地研究给定链的平稳行为。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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