随机环境中马氏链的强遍历性  

STRONG ERGODICITY OF MARKOV CHAIN IN RANDOM ENVIRONMENTS

作　　者：洪沆[1] 

机构地区：[1]黄山学院数学与统计学院,安徽黄山245041

出　　处：《数学杂志》2015年第5期1259-1268,共10页Journal of Mathematics

基　　金：安徽省高校省级自然科学研究项目(KJ2010B216)

摘　　要：本文研究了随机环境中单链■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 sufficient 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.

关 键 词：随机环境 马氏链 强遍历性 鞅 

分 类 号：O211.62[理学—概率论与数理统计]