随机环境中马氏链状态的几点注记

Some Notes for State of Markov Chains in Random Environments

利用双链(Xn,Tn→ξ)的马氏性对随机环境中马氏链的状态进行了研究,并指出当集合F是最小闭集时,则该集合中几乎所有的点都可达F的任意一个非零测度子集.

In this paper, we draw on （Xn,T^nξ^→） Markov bichains to study the State of Markov chains in random environments, at the same time point out that if F is minimal closed set, the point in F can arrive to positive measure subset of F.