文件名称:HMMall
- 所属分类：
- 图形图像处理(光照,映射..)
- 资源属性：
- [Matlab] [源码]
- 上传时间：
- 2014-04-06
- 文件大小：
- 814kb
- 下载次数：
- 1次
- 提 供 者：
- 南来北***
- 相关连接：
- 无
- 下载说明：
- 别用迅雷下载，失败请重下，重下不扣分！
介绍说明－－下载内容均来自于网络，请自行研究使用
隐马尔可夫模型matlab代码，可应用于步态识别等-Hidden Markov model matlab code, can be applied to gait recognition
(系统自动生成,下载前可以参看下载内容)
下载文件列表
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
......\...\publishHMM.m
......\...\README.txt
......\...\README.txt~
......\...\testHMM.m
......\...\transmat_train_observed.m
......\...\viterbi_path.m
......\KPMstats
......\........\#histCmpChi2.m#
......\........\beta_sample.m
......\........\chisquared_histo.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
......\........\convertBinaryLabels.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_paritioned_model_testfn.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
......\........\logist2ApplyRegularized.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