长沙理工大学学报（自然科学版）2004，Vol.1Issue(1)：86-90,5.
随机环境中马氏链的一致强遍历性
Uniformly Strong Ergodicity of Markov Chains in Random Environments
摘要
Abstract
For Markov chains in random environments, Cogburn(1984, 1990) first introduced weak ergodic concept that "starting time" is original point, and gave some conditions ensuring that the chains are weakly ergodic; Li Ying-qiu, Yan Xiao-bing, Wang He-song(2003) and LI Ying-qiu, YAN Xiao-bing and LI Ming-liang (2003) introduced uniformly weak ergodic and strong ergodic concept that "starting time" is any point, and gave some conditions ensuring that the chains are uniformly weakly ergodic or strongly ergodic. In term of above ideas, the definitions of uniformly strong ergodic and XN+-uniformly weak ergodic that "starting time" is any point are introduced. Some conditions ensuring that the chains are uniformly strongly ergodic are given. It is the basis of further research for Markov chains in random environments.关键词
随机环境中马氏链/一致弱遍历/强遍历/一致强遍历/(θ→)-链Key words
Markov chains in random environments/uniformly weak ergodicity/strong ergodicity/uniformly strong ergodicity/(θ→)-chain分类
数理科学引用本文复制引用
李应求,李明亮,汪和松,晏小兵..随机环境中马氏链的一致强遍历性[J].长沙理工大学学报（自然科学版）,2004,1(1):86-90,5.基金项目
NNSF of China(10271020 ) and Hunan Provincial Foundation for Young and Middleaged People(00JJEY2141) （10271020 ）
