文件名称:HMM
介绍说明－－下载内容均来自于网络，请自行研究使用
隐马尔科夫模型工具箱，readme文档介绍了该工具箱的使用方法-Hidden Markov Model (HMM) Toolbox written by Kevin Murphy (1998).
Seehttp://www.ai.mit.edu/~murphyk/Software/hmm.html for details.
Models
dhmm = HMM with discrete output
mhmm = HMM with mixture of Gaussians output Use mhmm with M=1 components to simulate an HMM with a single Gaussian output.
Seehttp://www.ai.mit.edu/~murphyk/Software/hmm.html for details.
Models
dhmm = HMM with discrete output
mhmm = HMM with mixture of Gaussians output Use mhmm with M=1 components to simulate an HMM with a single Gaussian output.
(系统自动生成,下载前可以参看下载内容)
下载文件列表
HMM
...\#README.txt#
...\#fwdback.m#
...\#mhmm_em.m#
...\README.txt
...\dhmm_em.m
...\dhmm_em_demo.m
...\dhmm_em_online.m
...\dhmm_em_online_demo.m
...\dhmm_logprob.m
...\dhmm_logprob_brute_force.m
...\dhmm_logprob_path.m
...\dhmm_sample.m
...\dhmm_sample_endstate.m
...\fixed_lag_smoother.m
...\fixed_lag_smoother_demo.m
...\fwdback.m
...\fwdback_xi.m
...\fwdprop_backsample.m
...\gausshmm_train_observed.m
...\mc_sample.m
...\mc_sample_endstate.m
...\mdp_sample.m
...\mhmmParzen_train_observed.m
...\mhmm_em.m
...\mhmm_em_demo.m
...\mhmm_logprob.m
...\mhmm_sample.m
...\mk_leftright_transmat.m
...\mk_rightleft_transmat.m
...\pomdp_sample.m
...\publishHMM.m
...\testHMM.m
...\transmat_train_observed.m
...\viterbi_path.m