markov process

markov process的基本解释

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[计] 马尔可夫过程, 马尔可夫处理

与markov process相关的网络例句 [注：此内容来源于网络，仅供参考]

Thirdly,in virtue of Markov theory,we get the herd coefficient matrix from Markov change probability matrix and construct the CA-Markov composite Model and get some characteristics of the CA-Markov composite Model Finally,we do simulations and sort for Xinjian County by using the Markov Model and the CA-Markov composite Model, respectively and analyze and compare the simulation results abortively.

然后，借鉴马尔科夫理论，采用转移概率矩阵估计从众系数矩阵，构建出CA-Markov复合模型，并研究了相关的性质。

Recently, Professor Liu Wen and his associates study the strong law of large numbers for Markov chain fields on trees. But for the nonhomogeneous Markov chain fields ,they only study the even-odd Markov chain and non-symmetric Markov chain. However, this article goes in the normal nonhono-geneous Markov chain fields and gets a class of limit theorems for the functions of two variables of finite nonhomogeneous Markov chain fields. Some limit theorems on the frequences of states and ordered state couples are obtained by several corollaries.

最近刘文教授及其合作者对树上的马氏链场的极限定理作了研究，对于非齐次马氏链场，仅对其中的奇偶马氏链场和非对称马氏链场作了研究，本文讨论了一般的非齐次马氏链场的极限性质，得到了关于Caylay树上有限非齐次马氏链场二元泛函的一类极限定理，作为推论得到了关于状态与状态序偶出现频率的极限定理。

This paper summarizes the research job of predecessors, full text is divided in four part:The first part introduces the develop history and present conditions of MCRE;In the second part, the concept of average Markov process is introduced. Moreover we investigate the relations for Markov processes, martingales, stationary processes and average Markov process systematically.The third part summarizes the model that constructs the MCRE by p-m chains and skew product Markov chains by p-m chains, also we discuss the relations among the basic gunctions of the probability character for MCREIn the fourth part, we discuss the dimension of GW-tree and the canonical branching chain in random environment, furthermore we summarize the exact formulas of mathematical expectation and variance of branching chain in random environment.

本文主要是综述这方面前人工作，全文分成四个部分：第一部分介绍了MCRE的发展历史和研究现状；第二部分研究了马氏过程、鞅和平稳过程这三类经典的随机过程的相互关系，包括他们之间的包含和排斥关系，引入了&均马氏过程&的概念，研究了它与三类经典过程—马氏过程、鞅及平稳过程的关系；第三部分综述了用p-m链构造的构造的随机环境中的马氏链和绕积马氏链，讨论了与之相关的概率特性函数的性质；第四部分讨论了GW树的维数，并综述了随机环境中的典范的分枝链，讨论了随机环境中的分枝链的数学期望和方差的计算公式。

与markov process相关的网络解释 [注：此内容来源于网络，仅供参考]

markov process：马尔可夫过程

各态历经假设(ergodic hypothesis) 当进行了N次不同时间的观察,马尔可夫过程(Markov process) 又称无后效过程. 其特点是如从当

markov process：马可夫过程

随机过程(Stochastic Processes)是我主要的研究领域.这门课我教过多次.马可夫过程(Markov Process)是课中第一个题材.其中会将状态分成递廻的(recurrent),及暂时的(transient)两类.若从一状态出发,会回到该状态之机率为1,此状态便称为递廻

markov process：马尔科夫过程

马尔科夫过程(MarKov Process)是一个典型的随机过程.设X(t)是一随机过程.当过程在时刻t0所处的状态为已知时.时刻t(t>t0)所处的状态与过程在t0时刻之前的状态无关.这个特性成为无后效性.无后效的随机过程称为马尔科夫过程.马尔科夫过程

markov process：过程

也有很多假设:债券未来市场价值和风险完全由其远期利率分布曲线决定(相同信用等级的远期利率分布曲线是相同的),在模型中,唯一的变量是信用等级;信用等级是离散的,在同一级别的债券具有相同的迁移矩阵和违约率,迁移概率遵循马尔可夫过程(Markov Process),同时迁移概率具有稳定性,

multiple markov process：多重马尔可夫过程

multiple hypergraph 多重超图 | multiple markov process 多重马尔可夫过程 | multiple point 多重点