文件名称:KPMstats
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语音识别重要函数汇集，函数书写严格按照相关论文，是研究语音的重要工具。-Speech Recognition brings together the important function, function to write in strict accordance with the relevant papers, is an important tool to study voice.
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下载文件列表
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
........\multipdf.m
........\multirnd.m
........\normal_coef.m
........\partial_corr_coef.m
........\parzen.m
........\parzenC.c
........\parzenC.dll
........\parzenC.mexglx
........\parzenC_test.m
........\parzen_fit_select_unif.m
........\pca.m
........\README.txt
........\rndcheck.m
........\sample.m
........\sample_discrete.m
........\sample_gaussian.m
........\standardize.m
........\standardize.m~
........\student_t_logprob.m
........\student_t_prob.m
........\test_dir.m
........\unidrndKPM.m
........\unidrndKPM.m~
........\unif_discrete_sample.m
........\weightedRegression.m
........\#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
........\multipdf.m
........\multirnd.m
........\normal_coef.m
........\partial_corr_coef.m
........\parzen.m
........\parzenC.c
........\parzenC.dll
........\parzenC.mexglx
........\parzenC_test.m
........\parzen_fit_select_unif.m
........\pca.m
........\README.txt
........\rndcheck.m
........\sample.m
........\sample_discrete.m
........\sample_gaussian.m
........\standardize.m
........\standardize.m~
........\student_t_logprob.m
........\student_t_prob.m
........\test_dir.m
........\unidrndKPM.m
........\unidrndKPM.m~
........\unif_discrete_sample.m
........\weightedRegression.m