详细说明：一个HMM的Matlab实现方法，可实现孤立词语音识别

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文件列表(点击判断是否您需要的文件):
  HMMall
  ......\HMM
  ......\...\#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.m~
  ......\...\fwdback_xi.m
  ......\...\fwdprop_backsample.m
  ......\...\fwdprop_backsample.m~
  ......\...\gausshmm_train_observed.m
  ......\...\herbert.txt~
  ......\...\mc_sample.m
  ......\...\mc_sample_endstate.m
  ......\...\mdp_sample.m
  ......\...\mhmmParzen_train_observed.m
  ......\...\mhmm_em.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
  ......\...\README.txt
  ......\...\README.txt~
  ......\...\transmat_train_observed.m
  ......\...\viterbi_path.m
  ......\KPMstats
  ......\........\#histCmpChi2.m#
  ......\........\beta_sample.m
  ......\........\chisquared_prob.m
  ......\........\chisquared_readme.txt
  ......\........\chisquared_table.m
  ......\........\clg_Mstep.m
  ......\........\clg_Mstep_simple.m
  ......\........\clg_prob.m
  ......\........\condGaussToJoint.m
  ......\........\condgaussTrainObserved.m
  ......\........\condgauss_sample.m
  ......\........\cond_indep_fisher_z.m
  ......\........\cwr_demo.m
  ......\........\cwr_em.m
  ......\........\cwr_predict.m
  ......\........\cwr_prob.m
  ......\........\cwr_readme.txt
  ......\........\cwr_test.m
  ......\........\dirichletpdf.m
  ......\........\dirichletrnd.m
  ......\........\dirichlet_sample.m
  ......\........\distchck.m
  ......\........\eigdec.m
  ......\........\est_transmat.m
  ......\........\fit_partitioned_model.m
  ......\........\gamma_sample.m
  ......\........\gaussian_prob.m
  ......\........\gaussian_sample.m
  ......\........\histCmpChi2.m
  ......\........\histCmpChi2.m~
  ......\........\KLgauss.m
  ......\........\linear_regression.m
  ......\........\logist2.m
  ......\........\logist2Apply.m
  ......\........\logist2Fit.m
  ......\........\logist2FitRegularized.m
  ......\........\logistK.m
  ......\........\logistK_eval.m
  ......\........\marginalize_gaussian.m
  ......\........\matrix_normal_pdf.m
  ......\........\matrix_T_pdf.m
  ......\........\mc_stat_distrib.m
  ......\........\mixgauss_classifier_apply.m
  ......\........\mixgauss_classifier_train.m
  ......\........\mixgauss_em.m
  ......\........\mixgauss_init.m
  ......\........\mixgauss_Mstep.m
  ......\........\mixgauss_prob.m
  ......\........\mixgauss_prob_test.m
  ......\........\mixgauss_sample.m
  ......\........\mkPolyFvec.m
  ......\........\mk_unit_norm.m
  ......\........\multinomial_prob.m
  ......\........\multinomial_sample.m
  ......\........\multipdf.m
  ......\........\multirnd.m
  ......\........\normal_coef.m
  ......\........\partial_corr_coef.m
  ......\........\parzen.m
  ......\........\parzenC.c