stochastic process

基本解釋

This paper introduces and analyzes Markov process and Markov chain of stochastic process theory firstly.
介紹竝解析隨機(jī)過程理論中的馬爾科夫過程與馬爾科夫鏈；
Practice shows that the SPN can be made model and quantitative analysis for a stochastic process system, and it is a very useful tool in the enhaced BPN.
實(shí)踐表明，SPN能爲(wèi)具有隨機(jī)過程的系統(tǒng)進(jìn)行建模和定量分析，是擴(kuò)展的BPN中一種十分有用的分析工具．。
The paper introduces methods of statistical physics to compute the multi-fractal of stochastic process so that the entropy rate of source can be obtained at once.
該文指出了如何用統(tǒng)計(jì)物理的方法計(jì)算隨機(jī)過程的多重分形維，以二態(tài)隱馬爾可夫信源作爲(wèi)例子，該文計(jì)算了其熵率。

So what we have here is not necessarily real, not necessarily the truth, but a stochastic process that moves closer and closer to the real, to the truth.
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doubly stochastic Poisson process 雙隨機(jī)蔔瓦松過程;雙重隨機(jī)泊松過程;泊松過程;重隨機(jī)Poisson過程
Stochastic -process limits 隨機(jī)過程極限隨機(jī)過程極限概論及其排隊(duì)的應(yīng)用;隨機(jī)過程極限概論及其排隊(duì)的應(yīng)用
stochastic stationary process 隨機(jī)平穩(wěn)過程
stochastic diffusion process 擴(kuò)散型隨機(jī)過程
stochastic pulse process 隨機(jī)脈沖過程

隨機(jī)過程
In the former two situations, the exit time is assumed to be a random variable and in the last situation the exit time is assumed to be a stochastic process.
對前兩種情形考慮退出時(shí)間是個(gè)隨機(jī)變量，對最後一種情形考慮退出時(shí)間是個(gè)隨機(jī)過程。
計(jì)算機(jī)科學(xué)技術(shù)
隨機(jī)過程
Chaos widely exists in our natural world as a series of stochastic process in non-linear deterministic dynamical system.
混沌現(xiàn)象作爲(wèi)非線性動(dòng)力系統(tǒng)中一種確定的類隨機(jī)過程,廣泛存在於客觀世界中。
數(shù)學(xué)
隨機(jī)過程
隨機(jī)程序