随机单调的离散时间马氏链强遍历速度的估计I

研究了离散时间马氏链的强遍历性,对随机单调的离散时间马氏链,给出了最大强遍历收敛速度的下界估计。     

二重非齐次马氏链的遍历性及其应用

给出二重非齐次马氏链的强遍历性,绝对平均强遍历性,Cesaro平均收敛的概念．利用二维马氏链的遍历性和C-K方程,建立了二维马氏链与二重非齐次马氏链遍历性的关系．并讨论了齐次二重马氏链绝对平均强遍历与强遍历的等价性．最后给出Cesaro平均收敛在马氏决策过程和信息论中应用．     

关于可列非齐次马氏链的广义C-强遍历性

马氏链遍历性理论在生物,数值计算,信息理论,自动控制,近代物理和公用事业中的服务系统等众多领域都有着广泛的应用,马氏链的C-强遍历性是马氏链遍历性理论的重要内容.本文给出了马氏链C-强遍历性的一个推广,首先给出了在可列状态空间取值的非齐次马氏链的广义C-强遍历性和广义一致C-强遍历性的概念,然后研究这两种遍历性成立的充分条件.     

抽象空间中的马氏过程的强遍历性及收敛速度

<正> §1.引言Doob 在[2]中对一般状态的时齐的马氏过程的遍历性理论,作了系统的研究,得到了完满的结果.D.G.Kendall 在[8]中,J.F.C.Kingman 在[6]、[7]中,D.Vere-Jones在[5]中,对可数状态的时齐的马氏过程的遍历极限的收敛速度,作了研究,这些文章的一个共同特点是:假定对某一状态其遍历极限的收敛速度为几何速度(指数速度),证明对其它状态,其遍历极限的收敛速度亦然.然而 D.Isaacson 在[1]中,研究了可数状态时齐的马氏过程的强遍历性,而且证明了强遍历性蕴含了收敛速度是几何速度(指数速度).本文研究的是一般状态的马氏过程(时齐的或非时齐的),得到了马氏过程满足强遍历性的各种充要条件;证明了强遍历性蕴含了收敛的指数速度;找出了最佳收敛速度;并证明了在什么条件下达到最佳收敛速度.     

关于连续状态非齐次马氏链的绝对平均强遍历性

引进连续状态非齐次马氏链绝对平均强遍历的概念,研究连续状态非齐次马氏链满足这种强遍历的一个充分条件,并给出绝对平均强遍历性在马氏决策过程中的应用.     

关于非刘次马氏链的绝对平均强遍历性及若干应用

本文引进非齐次马氏链绝对平均强遍历我概念并得到非齐次马氏链满足这种强遍历的一个充分条件，最后给出绝对平均强遍历性在马氏决策过程和信息论听应用。     

随机环境中马氏链的强遍历性

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.     

连续状态马氏链遍历性的初等证明

本文介绍了连续状态马氏链Dobrushin系数、指数强遍历性、强遍历性以及弱遍历性,在此基础上给出指数强遍历、强遍历和弱遍历之间相互等价的一个初等证明.     

用耦合方法研究马氏链f-指数遍历

该文在一般状态空间下研究马氏链指数遍历性,指数遍历马氏链,增加条件π(f~p)<∞, p> 1,利用耦合方法得到了存在满的吸收集,使得马氏链在其上是f-指数遍历的.     

一类非齐次马氏链的绝对平均强遍历性

引用马氏链绝对平均强遍历的概念,首先给出齐次马氏链绝对平均强遍历与强遍历的等价性,其次通过引进另一个强遍历的非齐次马氏链,给出一个非齐次马氏链绝对平均强遍历的充分条件.     

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In this paper, we mainly studied the limit properties for the countable nonhomogeneous Markov chains. We established some limit properties for the functions of the countable nonhomogeneous Markov chains with variables under the convergence in the sense, which extended the similar conclusions for the functions with two variables. At last, as a corollary, we given the similar result in the homogeneous Markov stock market.     

可列齐次马氏链熵率的指数收敛速度

运用Markov不等式和期望、强遍历、δ系数的性质,利用Chang提出的研究指数收敛速度的方法,在给出5个引理的基础上,研究了初始状态给定的一类可列齐次马氏链熵率的收敛速度,推广了Chang的结果.     

The asymptotic equipartition property of Markov chains in single infinite Markovian environment on countable state space

ABSTRACT

The asymptotic equipartition property is a basic theorem in information theory. In this paper, we study the strong law of large numbers of Markov chains in single-infinite Markovian environment on countable state space. As corollary, we obtain the strong laws of large numbers for the frequencies of occurrence of states and ordered couples of states for this process. Finally, we give the asymptotic equipartition property of Markov chains in single-infinite Markovian environment on countable state space.     

关于渐近循环马氏链泛函的强大数定律

研究了一类非齐次马氏链———渐近循环马氏链泛函的强大数定律,首先引出了渐近循环马氏链的概念,然后给出了若干引理.利用了渐近循环马氏链关于状态序偶出现频率的强大数定理给出并证明了关于渐近循环马氏链泛函的强大数定律,所得定理作为推论可得到已有的结果.     

A class of strong limit theorems for countable nonhomogeneous Markov chains on the generalized gambling system

In this paper, we study the limit properties of countable nonhomogeneous Markov chains in the generalized gambling system by means of constructing compatible distributions and martingales. By allowing random selection functions to take values in arbitrary intervals, the concept of random selection is generalized. As corollaries, some strong limit theorems and the asymptotic equipartition property (AEP) theorems for countable nonhomogeneous Markov chains in the generalized gambling system are established. Some results obtained are extended.      

On duality for mathematical programs with vanishing constraints

We make a review of several variants of ergodicity for continuous-time Markov chains on a countable state space. These include strong ergodicity, ergodicity in weighted-norm spaces, exponential and subexponential ergodicity. We also study uniform exponential ergodicity for continuous-time controlled Markov chains, as a tool to deal with average reward and related optimality criteria. A discussion on the corresponding ergodicity properties is made, and an application to a controlled population system is shown.     

Geometric ergodicity for classes of homogeneous Markov chains

The paper deals with non asymptotic computable bounds for the geometric convergence rate of homogeneous ergodic Markov processes. Some sufficient conditions are stated for simultaneous geometric ergodicity of Markov chain classes. This property is applied to nonparametric estimation in ergodic diffusion processes.     

Strong law of large numbers for countable nonhomogeneous Markov chains

The aim of this paper is to establish a strong law of large numbers for the bivariate functions of countable nonhomogeneous Markov chains under the condition of uniform convergence in the Cesàro sense which differs from my previous results. As corollaries, we generalize one of the Liu and Liu’s results for the univariate functions case and obtain another Shannon–McMillan–Breiman theorem for this Markov chains.     

Strong laws of large numbers for asymptotic even–odd Markov chains indexed by a homogeneous tree

In this paper, we are going to study the strong laws of large numbers for asymptotic even–odd Markov chains indexed by a homogeneous tree. First, the definition of the asymptotic even–odd Markov chain is introduced. Then the strong limit theorem for asymptotic even–odd Markov chains indexed by a homogeneous tree is established. Next, the strong laws of large numbers for the frequencies of occurrence of states and ordered couple of states for asymptotic even–odd Markov chains indexed by a homogeneous tree are obtained. Finally, we prove the asymptotic equipartition property (AEP) for these Markov chains.     

一类特殊非齐次树上马氏链的若干强大数定律

首先给出了一类特殊非齐次树上可数状态马氏链的局部收敛定理,作为推论,得到了此类树上可数状态马氏链关于状态与状态序偶出现频率的若干极限性质,最后得到了这类特殊非齐次树上有限状态马氏链关于状态与状态序偶出现频率的强大数定律.