文件名称:MIT_code

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  • 语音合成与识别
  • 资源属性:
  • [Matlab] [源码]
  • 上传时间:
  • 2012-11-26
  • 文件大小:
  • 17.79mb
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麻省理工穿戴计算源代码,含HMMall、LifeWear Annotation Tool、LifeWear Matlab Code、LifeWear_C四个文件夹,-MIT wearable computing source code, containing HMMall, LifeWear Annotation Tool, LifeWear Matlab Code, LifeWear_C four folders,
(系统自动生成,下载前可以参看下载内容)

下载文件列表

MIT code

........\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

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