文件列表:

HMM工具箱\#mc_sample.m# (442, 2004-05-24)
HMM工具箱\#mhmm_sample.m# (1071, 2004-05-25)
HMM工具箱\dhmm_em.m (3862, 2003-07-03)
HMM工具箱\dhmm_em_demo.m (687, 2003-05-04)
HMM工具箱\dhmm_em_online.m (2376, 2003-05-04)
HMM工具箱\dhmm_em_online_demo.m (2249, 2003-05-04)
HMM工具箱\dhmm_logprob.m (640, 2003-05-04)
HMM工具箱\dhmm_logprob_brute_force.m (552, 2002-05-29)
HMM工具箱\dhmm_logprob_path.m (448, 2002-05-29)
HMM工具箱\dhmm_sample.m (408, 2004-05-31)
HMM工具箱\dhmm_sample.m~ (408, 2003-05-04)
HMM工具箱\dhmm_sample_endstate.m (622, 2003-05-04)
HMM工具箱\fixed_lag_smoother.m (2096, 2003-01-22)
HMM工具箱\fixed_lag_smoother_demo.m (986, 2003-05-04)
HMM工具箱\fwdback.m (6357, 2004-06-07)
HMM工具箱\fwdback.m~ (6357, 2004-05-24)
HMM工具箱\gausshmm_train_observed.m (1561, 2004-02-12)
HMM工具箱\mc_sample.m (442, 2004-05-24)
HMM工具箱\mc_sample.m~ (442, 2002-05-29)
HMM工具箱\mc_sample_endstate.m (711, 2003-01-22)
HMM工具箱\mdp_sample.m (490, 2002-05-29)
HMM工具箱\mhmmParzen_train_observed.m (1203, 2004-02-13)
HMM工具箱\mhmm_em.m (5562, 2004-02-07)
HMM工具箱\mhmm_em_demo.m (1013, 2003-05-13)
HMM工具箱\mhmm_logprob.m (960, 2003-05-04)
HMM工具箱\mhmm_sample.m (1071, 2004-05-25)
HMM工具箱\mhmm_sample.m~ (1071, 2003-05-04)
HMM工具箱\mk_leftright_transmat.m (248, 2002-05-29)
HMM工具箱\mk_rightleft_transmat.m (249, 2002-11-22)
HMM工具箱\pomdp_sample.m (612, 2003-05-04)
HMM工具箱\transmat_train_observed.m (1245, 2004-02-10)
HMM工具箱\viterbi_path.m (1541, 2003-01-22)
HMM工具箱 (0, 2005-11-02)

Hidden Markov Model (HMM) Toolbox written by Kevin Murphy (19***). See http://www.ai.mit.edu/~murphyk/Software/hmm.html for details. Installation ------------ 1. Install netlab from http://www.ncrg.aston.ac.uk/netlab 2. Install KPMtools and KPMstats from http://www.ai.mit.edu/~murphyk/Software/index.html 3. Assuming you installed all these files in your matlab directory, in Matlab type addpath matlab/netlab addpath matlab/KPMtools addpath matlab/KPMstats addpath matlab/HMM 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. 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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