可修系统中半马氏过程的稳态分布

众所周知,可修系统是可靠性理论中讨论的一类非常重要的系统,也是可靠性数学主要研究对象之一,研究可修系统的主要数学工具是马氏理论.当构成系统各部件的寿命分布和故障后的修理时间分布,及其出现的有关分布均为指数分布时,只要适当的定义系统的状态,这样的系统总可以用马氏过程来描述.大部分学者为了方便,均是在马氏框架下研究问题的.但是在实践中经常遇到部件的寿命或修理时间分布不是指数分布的情形,这时可修系统所构成的随机过程是半马氏过程,用现有的马氏理论无法解决相关问题.目前,关于半马氏的理论研究的研究又很少,基于此,针对半马氏的随机模型给出了与马氏理论相平行的稳态分布的求解方法.     

生灭型半马氏骨架过程

本文首先引进了生灭型半马氏骨架过程的定义,求出了两骨架时跳跃点τn-1(ω)与τn(ω)之间的嵌入过程X(n)(t,ω)的初始分布及寿命分布.得到了生灭型半马氏骨架过程的一维分布.其次引进了生灭型半马氏骨架过程的数字特征并讨论了它们的概率意义及相互关系.讨论了生灭型半马氏骨架过程的向上和向下的积分型随机泛函.最后讨论了它的遍历性及平稳分布,求出了平均首达时间及平均返回时间.得到了常返和正常返的充分必要条件,求出了在正常返的条件下的平稳分布.     

半马氏生灭过程

本文提出了半马氏生灭过程的概念，引进了其数字特征，并讨论了向下和向上的积分型随机泛函、遍历性及平稳分布．     

半马尔可夫过程的极限分布及其推广

本文运用马尔可夫骨架过程的极限理论研究齐次可列半马尔可夫过程,得到其极限分布.当更新间隔的分布不是格子分布时,本文的结果和邓永录等[1]中的结果一致,但采用的方法不同,本文采用的是马尔可夫骨架过程的理论方法,而[1]中采用的是交替更新过程的方法;而且关于更新间隔服从格子分布的情形,[1]中没有研究,而本文给出了结果.最...     

非负费用折扣半马氏决策过程

本文考虑可数状态非负费用的折扣半马氏决策过程.首先在给定半马氏决策核和策略下构造一个连续时间半马氏决策过程,然后用最小非负解方法证明值函数满足最优方程和存在ε-最优平稳策略,并进一步给出最优策略的存在性条件及其一些性质.最后,给出了值迭代算法和一个数值算例.     

离散型冲击折扣半马氏决策过程

本文讨论离散型冲击折扣半马氏决策过程，在建立模型后，我们将它化成了一个等价的离散时间马氏决策过程．     

半马氏过程的积分型随机泛函

本文讨论了半马氏过程的积分型随机泛函,求出了“首达”时间的积分型随机泛函公式,并讨论了半马氏过程“正则性”条件,得到了飞跃点积分型随机泛函的两个0—1律     

一类半马氏过程的常返性与正常返性

对于逗留时为正整数值的半马氏过程程｛ξ（ｔ）｝,本文研究了｛ξ（ｔ）｝、相应过程｛ξ（ｎ）｝、嵌入链｛ξ_ｎ｝的常返性和正常返性之间的关系．定理 ２．１证明了三过程的状态常返性是等价的．定理 ２．２证明了ξ（ｔ）、ξ（ｎ）的状态正常返性是等价的,ξ（ｔ）的状态正常返是嵌入链状态正常返的充分条件．定理２．３给出了ξ（ｎ）的状态正常返的充分条件．该条件在状态空间有限时也是必要条件．     

一类两参数马氏过程的构造──在马氏过程上生长马氏过程

本文概率地实现了在单参数马氏过程上生长单参数马氏过程的构想，定义了一类重要的两参数过程；ＭＭ类过程．证明了：ＭＭ类过程具有宽过去马氏性和１马氏性；ＭＭ过程不具有马氏性，单点马氏性，２马氏性和宽将来马氏性，除非它退化．     

Doob过程的存活时间分布

对于寿命为σ的（Ｑ,π）Ｄｏｏｂ过程Ｘ＝｛ｘ（ｔ）,ｔ〈σ｝,研究它首次爆发后还能存活多久,求出了它首次爆发后至寿终的存活时间分布、平均存活时间和首次爆发就寿终的概率。     

Entropy Maximization for Markov and Semi-Markov Processes

The literature about maximum of entropy for Markov processes deals mainly with discrete-time Markov chains. Very few papers dealing with continuous-time jump Markov processes exist and none dealing with semi-Markov processes. It is the aim of this paper to contribute to fill this lack. We recall the basics concerning entropy for Markov and semi-Markov processes and we study several problems to give an overview of the possible directions of use of maximum entropy in connection with these processes. Numeric illustrations are presented, in particular in application to reliability.     

Nonparametric Estimation for Semi-Markov Processes Based on its Hazard Rate Functions

The problem of estimating the Markov renewal matrix and the semi-Markov transition matrix based on a history of a finite semi-Markov process censored at time T (fixed) is addressed for the first time. Their asymptotic properties are studied. We begin by the definition of the transition rate of this process and propose a maximum likelihood estimator for the hazard rate functions and then we show that this estimator is uniformly strongly consistent and converges weakly to a normal random variable. We construct a new estimator for an absolute continous semi-Markov kernel and give detailed derivation of uniform strong consistency and weak convergence of this estimator as the censored time tends to infinity. This revised version was published online in June 2006 with corrections to the Cover Date.     

马尔可夫骨架过程的极限分布

本文运用基本更新定理和Smith关键更新定理等理论和方法,对马尔可夫骨架过程的极限分布进行深入研究,得到主要结果如下:去掉了原有结果中要求的绝对连续的条件,给出了马尔可夫骨架过程极限分布存在的充分条件;得到了马尔可夫骨架过程极限分布的具体公式,并证明了该极限分布为概率分布.     

Non-Stationary Semi-Markov Decision Processes on a Finite Horizon

We introduce and study a class of non-stationary semi-Markov decision processes on a finite horizon. By constructing an equivalent Markov decision process, we establish the existence of a piecewise open loop relaxed control which is optimal for the finite horizon problem.     

Parametric and Non Homogeneous Semi-Markov Process for HIV Control

In AIDS control, physicians have a growing need to use pragmatically useful and interpretable tools in their daily medical taking care of patients. Semi-Markov process seems to be well adapted to model the evolution of HIV-1 infected patients. In this study, we introduce and define a non homogeneous semi-Markov (NHSM) model in continuous time. Then the problem of finding the equations that describe the biological evolution of patient is studied and the interval transition probabilities are computed. A parametric approach is used and the maximum likelihood estimators of the process are given. A Monte Carlo algorithm is presented for realizing non homogeneous semi-Markov trajectories. As results, interval transition probabilities are computed for distinct times and follow-up has an impact on the evolution of patients.      

马氏骨架理论在系统可靠性中的应用

本文利用侯振挺等人提出的马尔可夫骨架过程理论讨论了串——并联混合系统的可靠性.该模型有四个不同部件和一个修理工组成,部件的寿命和修理时间均服从一般分布.     

Numerical Solution of non-Homogeneous Semi-Markov Processes in Transient Case*

In this article a numerical solution for the evolution equation of a continuous time non-homogeneous semi-Markov process (NHSMP) is obtained using a quadrature method. The paper, after a short introduction to continuous time NHSMP, presents the numerical solution of the process evolution equation with a general quadrature method. Furthermore, the paper gives results that justify this approach, proving that the numerical solution tends to the evolution equation of the continuous time NHSMP. Moreover, the formulae related to some specific quadrature methods are given and a method for obtaining the discrete time NHSMP by applying a very particular quadrature formula for the discretization is shown. In this way the relation between the continuous and discrete time NHSMP is proved. Then, the problem of obtaining the continuous time NHSMP from the discrete one is considered. This problem is solved showing that the discrete process converges in law to the continuous one if the discretized time interval tends to zero. In addition, the discrete time NHSMP in matrix form is presented, and the fact that the solution to this process always exists is proved. Finally, an algorithm for solving the discrete time NHSMP is given. To illustrate the use of this algorithm for a discrete NHSMP, an example in the area of finance is presented.