HMMall
所属分类：其他
开发工具：matlab
文件大小：729KB
下载次数：24
上传日期：2010-04-08 15:54:41
上 传 者：
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说明： 隐马尔可夫模型工具箱，包括了与HMM相关的所有程序。
(Hidden Markov Model toolkit, including all the procedures related with the HMM.)
文件列表:
HMMall\HMM\#dhmm_em.m# (3862, 2004-10-22)
HMMall\HMM\#fwdback.m# (6339, 2005-06-08)
HMMall\HMM\#mhmm_em.m# (5589, 2006-02-16)
HMMall\HMM\#testHMM.m# (25, 2005-06-08)
HMMall\HMM\#viterbi_path.m# (1541, 2004-10-22)
HMMall\HMM\dhmm_em.m (4081, 2005-06-08)
HMMall\HMM\dhmm_em_demo.m (687, 2003-05-04)
HMMall\HMM\dhmm_em_online.m (2376, 2003-05-04)
HMMall\HMM\dhmm_em_online_demo.m (2249, 2003-05-04)
HMMall\HMM\dhmm_logprob.m (640, 2003-05-04)
HMMall\HMM\dhmm_logprob_brute_force.m (552, 2002-05-29)
HMMall\HMM\dhmm_logprob_path.m (448, 2002-05-29)
HMMall\HMM\dhmm_sample.m (408, 2004-05-31)
HMMall\HMM\dhmm_sample_endstate.m (622, 2003-05-04)
HMMall\HMM\fixed_lag_smoother.m (2096, 2003-01-22)
HMMall\HMM\fixed_lag_smoother_demo.m (987, 2005-06-08)
HMMall\HMM\fwdback.m (6431, 2005-06-08)
HMMall\HMM\fwdback_xi.m (6642, 2005-12-08)
HMMall\HMM\fwdprop_backsample.m (1899, 2006-02-23)
HMMall\HMM\gausshmm_train_observed.m (1561, 2004-02-12)
HMMall\HMM\mc_sample.m (442, 2004-05-24)
HMMall\HMM\mc_sample_endstate.m (711, 2003-01-22)
HMMall\HMM\mdp_sample.m (490, 2002-05-29)
HMMall\HMM\mhmmParzen_train_observed.m (1203, 2004-02-13)
HMMall\HMM\mhmm_em.m (5562, 2004-02-07)
HMMall\HMM\mhmm_em_demo.m (1013, 2003-05-13)
HMMall\HMM\mhmm_logprob.m (960, 2003-05-04)
HMMall\HMM\mhmm_sample.m (1071, 2004-05-25)
HMMall\HMM\mk_leftright_transmat.m (248, 2002-05-29)
HMMall\HMM\mk_rightleft_transmat.m (249, 2002-11-22)
HMMall\HMM\pomdp_sample.m (612, 2003-05-04)
HMMall\HMM\publishHMM.m (32, 2006-07-10)
HMMall\HMM\testHMM.m (138, 2005-06-08)
HMMall\HMM\transmat_train_observed.m (1245, 2004-08-29)
HMMall\HMM\viterbi_path.m (1541, 2004-10-22)
HMMall\KPMstats\#histCmpChi2.m# (267, 2005-05-03)
HMMall\KPMstats\beta_sample.m (1955, 2005-04-25)
HMMall\KPMstats\chisquared_histo.m (199, 2005-04-25)
... ...
Hidden Markov Model (HMM) Toolbox written by Kevin Murphy (19***).
See http://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.
Demos
-----
mhmm_em_demo
dhmm_em_demo
dhmm_em_online_demo
fixed_lag_smoother_demo
References
-----------
See "A tutorial on Hidden Markov Models and selected applications in speech recognition",
L. Rabiner, 1***9, Proc. IEEE 77(2):257--286.
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