随机环境中的马氏链状态分类

给出了随机环境中马氏链的特征数和状态的定义,讨论了状态间的传递性,自反性,对称性,是经典马氏链相应结果的一般化.并运用位势方法研究了状态间的关系,它们在极限理论的研究中非常有用.

Some Notes of the Classification of States for Markov Chains to Markov Chains in Random Environments

The main result of this paper is the classification of states on Markov Chains in random environments,and a series of relations among the states is given,and the transfer characteristic,self-reciprocal criteria and balance criteria of the states are studied by potential theory,these results are the generalization for corresponding results in classical Markov Chains,they are useful in the study on limit theory for Markov Chains in random environments.