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The book: Hidden Markov Models (Theory & Methods) Markov Chains Particle Filter Monte Carlo
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Hidden Markov Model (HMM) Toolbox written by Kevin Murphy
A problem of fundamental interest is characterizing such real-world signals in terms of signal models. HMM is referred to as Markov sources or probabilistic functions of Markov chains in the
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The General Hidden Markov Model library (GHMM) is a freely available LGPL-ed C library implementing efficient data structures and algorithms for basic and extended HMMs. The development is hosted at Sourceforge http://sourceforge.net/projects/ghmm/,
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马尔科夫链的matlab仿真,马尔可夫模型（Markov Model，MM）是统计模型，它用来描述一个含有隐含未知参数的马尔可夫过程。-Matlab simulation of Markov chains, Markov models (Markov Model, MM) is a statistical model, which is used to describe an unknown parameter containing hidden Markov process.
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股票预测的GUIDE界面，包括读取文件，选择方法，生成所得图像等操作。但还未将如何傅里叶变换、如何用时间序列进行分析、如何用隐式马尔科夫链嵌入其中。-Stock prediction GUIDE interface, including reading the file, choose the method to generate the resulting image and other operations. But how will the Fourier transform yet, h
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物理马尔可夫链通常用来建模排队理论和统计学中的建模，还可作为信号模型用于熵编码技术，如算术编码（著名的LZMA数据压缩算法就使用了马尔可夫链与类似于算术编码的区间编码）。马尔可夫链也有众多的生物学应用，特别是人口过程，可以帮助模拟生物人口过程的建模。隐蔽马尔可夫模型还被用于生物信息学，用以编码区域或基因预测-Physical Markov chains are typically used to model queuing theory and statistics in modeling, b
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Parameter estimation for hidden Markov chains
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隐马尔科夫模型是关于时序的概率模型，描述由一个隐藏的马尔科夫链随机生成不可观测的状态随机序列，再由各个状态生成一个观测而产生观测序列的过程。隐藏的马尔科夫链随机生成的状态的序列，称为状态序列；每个状态生成一个观测，而由此产生的观测的随机序列，称为观测序列。马尔科夫链由初始概率分布、状态转移概率分布以及观测概率分布确定(The hidden Markov model is a probabilistic model for time series. It describes the process
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