中文说明：资源描述随机过程的概念 一个随机试验的结果有多种可能性，在数学上用一个随机变量（或随机向量）来描 述。在许多情况下，人们不仅需要对随机现象进行一次观测，而且要进行多次，甚至接 连不断地观测它的变化过程。这就要研究无限多个，即一族随机变量。随机过程理论就 是研究随机现象变化过程的概率规律性的。 定义 1 设{ , t T} t ξ ∈ 是一族随机变量，T 是一个实数集合，若对任意实数 t t∈T,ξ 是一个随机变量，则称{ ,t T} t ξ ∈ 为随机过程。 T 称为参数集合，参数t 可以看作时间。t ξ 的每一个可能取值称为随机过程的一个 状态。其全体可能取值所构成的集合称为状态空间，记作E 。当参数集合T 为非负整 数集时，随机过程又称随机序列。本章要介绍的马尔可夫链就是一类特殊的随机序列。
English Description：
Application backgroundConcept of stochastic processesThe results of a randomized trial have many possibilities, and a random variable (or random vector) is used in mathematics.The. In many cases, people not only need to observe the random phenomena, but also to carry out many times, and even to meetContinuous observation of its changing process. This is to study infinite, that is, a group of random variables. Stochastic process theoryIt is the probability law of the study of the change of random phenomena.Definition 1 let t T} T and zeta {, is a random variable, T is a set of real number, if for any real t t in T,.Is a random variable, called t T} T, zeta {, stochastic process.T is called parameter collection, and the parameter t can be considered as time. T.Each of the possible values is called a random process.State. A collection of all possible values is called the state space, denoted as E. When the parameter set T is non negative integerWhen the number of sets