Commingled in an endless Markov chain!

合成一条无穷无尽的马尔可夫链！

A global convergence is proved by analysis of Markov chain.

通过马尔可夫链的分析，证明它是全局收敛的。

A traffic load forecast model by optimally combined Markov chain is presented.

提出了一种基于最优组合马尔柯夫链的业务量预测模型.

In this method, a business process was regarded as a finite stationary Markov chain.

在该方法中, 业务过程被看作是一条有限齐次的马尔可夫链.

This developed the predictable method of Markov chain and widened the practice range.

发展了马尔科夫链预测方法,拓宽了其应用范围.

A residence time distribution mathematic model by continuous-time Markov chain was built up.

将连续时间马尔科夫链与多级全混流串联模型结合建立停留时间分布数学模型。

A residence time distribution mathematic model by continuous - time Markov chain was built up.

将连续时间马尔科夫链与多级全混流串联模型结合建立停留时间分布数学模型.

An abridged algorithm of 2 D hidden Markov chain model and its parameter estimation method are made.

针对现有的二维隐马氏模型算法给出了一种简化算法及参数估计方法.

This paper proves the ordinary nature about information entropy increase of the limited state Markov chain.

本文给出了有限状态markov链的熵转移的一个重要结论,即信息熵增加的平凡性定理.

In this paper, A new markov chain monte carlo algorithm for estimating stochastic volatility model is given.

研究用马尔科夫链蒙特卡罗(MCMC)算法估计随机波动模型的参数问题.