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Hidden_Markov_model_for_automatic_speech_recogniti
- Hidden_Markov_model_for_automatic_speech_recognition This code implements in C++ a basic left-right hidden Markov model and corresponding Baum-Welch (ML) training algorithm. It is meant as an example of the HMM algorithms described by L.Rabiner
baum-welch
- 该程序实现了Baum-Welch算法，对于通信里面的调制解调有很大帮助，其次，该程序具有通用性。-The program achieved the Baum-Welch algorithm, for the communication modem inside helps a lot, and secondly, the program has the versatility.
BaumWelchLearner
- this is source code for baum welch imlplementation
cdhmm
- 连续隐马尔可夫识别程序。 包含的模块，可以比较完整地进行语言识别。 主要模块： Test.m Train.m viterbi.m baum.m pdf.m recog.m mixture.m mfcc.m -speech recognize using HMM include 11 matlab fuction: Test.m Train.m viterbi.m baum.m pdf.m recog.m mixture.
baum
- this document is about baum-welch algorithm
viabw
- 用viterbi算法和baum-welch训练找到和更新best path-find best path using Viterbi algorithm and Baum-Welch training
Hidden-Markov-algorithm
- 隐马尔可夫算法的实现，其中包括前向算法，后向算法，Viterbi算法，Baum-Welch算法-Hidden Markov algorithm, including backward algorithm, Viterbi algorithm, Baum-Welch algorithm to the algorithm,
matlab
- 了解隐马尔科夫模型HMM的概念、组成和需要解决的问题；通过matlab分析和三个基本算法分析读研和就业问题：forward算法、Viterbi算法和Baum-Welch算法-Understand the concept of Hidden Markov Model HMM, composition and problems to be solved matlab analysis by three basic algorithms: forward algorithm, Viterbi alg
matlab-experiment
- 了解隐马尔科夫模型HMM的概念、组成和需要解决的问题；掌握三个基本算法：forward算法、Viterbi算法和Baum-Welch算法，并利用matlab进行实验分析一道具体问题-Understand the concept of Hidden Markov Model HMM, composition and problems to be solved mastered three basic algorithms: forward algorithm, Viterbi algorithm
Baum_Welch-algorithm
- 用Baum-Welch算法来迭代估计一个隐马尔科夫模型（HMM）的初始状态概率分布以及其状态转移概率矩阵。其中文件有mainfile_B_W.m为主函数，Baum_Welch.m为Baum-Welch算法迭代函数，Forward_variable.m与Backward_variable.m与Gamma_variable.m与Ksi_variable.m是需要计算的四种因子，B_pdf.m为混淆散射概率密度函数。-It s Baum-Welch algorithm for iteratively
viterbiaEM
- 1.用隐马尔科夫模型（HMM）模拟肿瘤细胞整个染色体的拷贝数（CN）变异。并用viteri算法得到最可能的（CN）状态转移序列； 2.使用baum welch算法根据所给序列数据和初始状态转移矩阵，重新估算状态转移矩阵。-HMM, Hidden Markov, baulm welch, viterbi, SNP-array
HMM
- Hidden markov model with baum welch algo and vertibi algo
HMM
- %函数名称：HMMTrain %参数：V-------训练观察序列（n X 1Cell矩阵），IPI,IA,IB-------模型参数初始值 %返回值：PI,A,B-------模型参数的学习结果 %函数功能：隐含马尔科夫模型的Baum-Welch学习算法(% function name: HMMTrain % parameters: V------- trains the observation sequence (n, X, 1Cell matrix), IPI, IA, and I
HMM
- 离散HMM的matlab程序，包含有前向—后向算法、 Baum-Welch算法以及Vertebi算法(The matlab program of discrete HMM, including forward-backward algorithm, Baum-Welch algorithm and Vertebi algorithm)
HMM-homework
- 隐马尔科夫实现，包含forward-hmm, Viterbi-hmm, Baum-Welch-hmm(Hidden Markov implementation, including forward-hmm, Viterbi-hmm, Baum-Welch-hmm)