2006Journal of Changsha University of Science & TechnologyRequires access

The ergodic properties of Markov chains in random environments

Wang Hesong

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Abstract

For Markov chains in random environments,Li Ying-qiu(2003,2004) introduced the concepts of weak ergodicity,uniformly weak ergodicity,strong ergodicity,uniformly strong ergodicity of Markov chains in double infinitely random environments when the starting time is arbitrarily given point.Based on above results,all kinds of relationships among these ergodicities are discussed,and that θ→-chains is weak ergodicity if P(θ) limited to inevitable exit sets can be proved.

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What this paper is about

For Markov chains in random environments,Li Ying-qiu(2003,2004) introduced the concepts of weak ergodicity,uniformly weak ergodicity,strong ergodicity,uniformly strong ergodicity of Markov chains in double infinitely random environments when the starting time is arbitrarily given point.Based on above results,all kinds of relationships among these ergodicities are discussed,and that θ→-chains is weak ergodicity if P(θ) limited to inevitable exit sets can be proved.

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Available abstract

For Markov chains in random environments,Li Ying-qiu(2003,2004) introduced the concepts of weak ergodicity,uniformly weak ergodicity,strong ergodicity,uniformly strong ergodicity of Markov chains in double infinitely random environments when the starting time is arbitrarily given point.Based on above results,all kinds of relationships among these ergodicities are discussed,and that θ→-chains is weak ergodicity if P(θ) limited to inevitable exit sets can be proved.

Key concepts: Ergodicity, Markov chain, Ergodic theory, Mathematics, Statistical physics, Markov process, Examples of Markov chains, Variable-order Markov model

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