跳过程的强遍历性

研究了一般状态空间跳过程的强遍历性,利用骨架链的方法,给出了强遍历性的几个等价条件,得到的结论类似于离散时间一般状态空间马氏链.     

一般状态空间跳过程的遍历性

该文研究了一般状态空间跳过程的遍历性,得到了与连续时间可数状态空间马氏链类似的结果.     

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.     

绕积马氏链的几个结果

本文利用一般马氏链的理论讨论了随机环境中的马氏链的各种状态的特征及遍历性,并用两种方式将状态空间进行严格的分类.     

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.     

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．     

一般状态空间跳过程的Harris常返

研究了一般状态空间跳过程的Harris常返,利用马氏性,得到了跳过程Harris常返的几个等价条件.     

一类带随机延滞的时间序列模型的遍历性

本利用马氏化方法和一般状态空间马氏链的基本理论研究了一类带随机延滞的时间序列模型的遍历性，得到了该模型伴随几何遍历的一个判别准则．     

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.     

Average stochastic games for continuous-time jump processes

We consider nonzero-sum games for continuous-time jump processes with unbounded transition rates under expected average payoff criterion. The state and action spaces are Borel spaces and reward rates are unbounded. We introduce an approximating sequence of stochastic game models with extended state space, for which the uniform exponential ergodicity is obtained. Moreover, we prove the existence of a stationary almost Markov Nash equilibrium by introducing auxiliary static game models. Finally, a cash flow model is employed to illustrate the results.     

Uniform ergodicities and perturbation bounds of Markov chains on base norm spaces

It is known that Dobrushin's ergodicity coefficient is one of the effective tools in the investigations of limiting behavior of Markov processes. Several interesting properties of the ergodicity coefficient of a positive mapping defined on base norm spaces have been studied. In this paper, we consider uniformly mean ergodic and asymptotically stable Markov operators on such spaces. In terms of the ergodicity coefficient, we establish uniform mean ergodicity criterion. Moreover, we develop the perturbation theory for uniformly asymptotically stable Markov chains on base norm spaces. In particularly, main results open new perspectives in the perturbation theory for quantum Markov processes defined on von Neumann algebras.     

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.     

跳过程ρ最优耦合算子的存在性

本文在适当的条件下，证明了一般状态跳过程ρ最优耦合算子的存在性．     

Recurrence conditions for Markov decision processes with Borel state space: A survey

This paper describes virtually all the recurrence conditions used heretofore for Markov decision processes with Borel state and action spaces, which include some forms of mixing and contraction properties, Doeblin's condition, Harris recurrence, strong ergodicity, and the existence of bounded solutions to the optimality equation for average reward processes. The aim is to establish (when possible) implications and equivalences between these conditions.This research was partially supported by the Third World Academy of Sciences under grant RG MP 898-152.     

Geometric Ergodicity for Piecewise Contracting Processes with Applications for Tropical Stochastic Lattice Models

Stochastic lattice models are increasingly prominent as a way to capture highly intermittent unresolved features of moist tropical convection in climate science and as continuum mesoscopic models in material science. Stochastic lattice models consist of suitably discretized continuum partial differential equations interacting with Markov jump processes at each lattice site with transition rates depending on the local value of the continuum equation; they are a special case of piecewise deterministic Markov processes but often have an infinite state space and unbounded transition rates. Here a general theorem on geometric ergodicity for piecewise deterministic contracting processes is developed with full generality to apply to stochastic lattice models. A highly nontrivial application to the stochastic skeleton model for the Madden‐Julian oscillation (Thual et al., 2013) is developed here where there is an infinite state space with unbounded and also degenerate transition rates. Geometric ergodicity for the stochastic skeleton model guarantees exponential convergence to a unique invariant measure that defines the statistical tropical climate of the model. Another application of the general framework is developed here for stochastic lattice models designed to capture intermittent fluctuation in the simplest tropical climate models. Other straightforward applications to models motivated by material science are mentioned briefly here. © 2016 Wiley Periodicals, Inc.     

Stability of piecewise deterministic Markovian metapopulation processes on networks

The purpose of this paper is to study a Markovian metapopulation model on a directed graph with edge-supported transfers and deterministic intra-nodal population dynamics. We first state tractable stability conditions for two typical frameworks motivated by applications: constant jump rates with multiplicative transfer amplitudes, and coercive jump rates with unitary transfers. More general criteria for boundedness, petiteness and ergodicity are then given.     

Bivariate step processes and random evolutions

A random evolution process constructed from regular step processes with a common state space and indexed on an evolution rule space is shown to be a regular step process on the product space. Conversely, it is shown that under mild conditions, any regular step process on a product space is equivalent to a random evolution process. Conditions are given on the cardinality of the spaces and on the parameters of the process that are sufficient for the process to have various recurrence and ergodicity properties. Applications to birth-death processes are given.     

Metastability of reversible finite state Markov processes

We prove the metastable behavior of reversible Markov processes on finite state spaces under minimal conditions on the jump rates. To illustrate the result we deduce the metastable behavior of the Ising model with a small magnetic field at very low temperature.     

An inequality connecting entropy distance,Fisher Information and large deviations

In this paper we introduce a new generalisation of the relative Fisher Information for Markov jump processes on a finite or countable state space, and prove an inequality which connects this object with the relative entropy and a large deviation rate functional. In addition to possessing various favourable properties, we show that this generalised Fisher Information converges to the classical Fisher Information in an appropriate limit. We then use this generalised Fisher Information and the aforementioned inequality to qualitatively study coarse-graining problems for jump processes on discrete spaces.