随机环境中马氏链的强遍历性
STRONG ERGODICITY OF MARKOV CHAIN IN RANDOM ENVIRONMENTS

本文研究了随机环境中单链X的强遍历性,得到了单链强遍历的充分条件以及与强遍历性等价的一些形式.利用鞅收敛定理,给出了单链强遍历下尾的结构,最后证明了在环境平稳的条件下,强遍历、平凡尾、弱遍历三者之间的关系,推广了经典马氏链理论中相应的结果.
This paper investigates the Strong ergodicity of Markov chain in random environments, obtain a su-cient condition of strong ergodicity for single-chain X in random environments and some equivalent condition of strong ergodicity.use martingale convergence theorem we obtain structure of tail under condition of strong ergodic,then proved the relationship between strong ergodic,weak ergodic and trivial tail in stationary environment,which improve the result of Markov chain theory