代码搜索：MIXTURE
找到约 1,805 项符合「MIXTURE」的源代码
代码结果 1,805
www.eeworm.com/read/319794/13442790
m init_mog.m
function mix1 = init_MoG(x,m,init_method,priors)
% mix1 = init_MoG(x,m,init_method,priors)
%
% Initialises a 1-dimensional Gaussian mixture model
% for learning using the Variational Bayes framework.
www.eeworm.com/read/319794/13442791
m init_mog1.m
function mix1 = init_MoG1(x)
% mix1 = init_MoG1(x)
%
% Initialises a 1-d, 1-component Gaussian mixture model
% for learning using the Variational Bayes framework.
%
% Called from 'init_MoG'.
%
%
% --
www.eeworm.com/read/314474/13566671
gawk compute-best-mix.gawk
#!/usr/local/bin/gawk -f
#
# compute-best-mix --
# Compute the best mixture weight (-lambda) for interpolating N
# LMs.
#
# usage: compute-best-mix [lambda="l1 l2 ..."] [precision=p] pplout1 pplout2 .
www.eeworm.com/read/303048/13823214
m som_probability_gmm.m
function [pd,Pdm,pmd] = som_probability_gmm(D, sM, K, P)
%SOM_PROBABILITY_GMM Probabilities based on a gaussian mixture model.
%
% [pd,Pdm,pmd] = som_probability_gmm(D, sM, K, P)
%
% [K,P] = som_e
www.eeworm.com/read/158037/11648158
m mixgauss_prob.m
function [B, B2] = mixgauss_prob(data, mu, Sigma, mixmat, unit_norm)
% EVAL_PDF_COND_MOG Evaluate the pdf of a conditional mixture of Gaussians
% function [B, B2] = eval_pdf_cond_mog(data, mu, Sigma
www.eeworm.com/read/259241/11812411
m mixgauss_prob.m
function [B, B2] = mixgauss_prob(data, mu, Sigma, mixmat, unit_norm)
% EVAL_PDF_COND_MOG Evaluate the pdf of a conditional mixture of Gaussians
% function [B, B2] = eval_pdf_cond_mog(data, mu, Sigma,
www.eeworm.com/read/13871/284260
m mixgauss_prob.m
function [B, B2] = mixgauss_prob(data, mu, Sigma, mixmat, unit_norm)
% EVAL_PDF_COND_MOG Evaluate the pdf of a conditional mixture of Gaussians
% function [B, B2] = eval_pdf_cond_mog(data, mu, Sigma
www.eeworm.com/read/465297/1521482
c gms_gprune.c
/**
* @file gms_gprune.c
*
*
* @brief Gaussian Mixture Selection のための Gaussian pruning を脱いたモノフォンHMMの纷换
*
*
*
* @brief Calculate the GMS monophone %HMM for Gaussian Mixtur
www.eeworm.com/read/396844/2407770
m som_probability_gmm.m
function [pd,Pdm,pmd] = som_probability_gmm(D, sM, K, P)
%SOM_PROBABILITY_GMM Probabilities based on a gaussian mixture model.
%
% [pd,Pdm,pmd] = som_probability_gmm(D, sM, K, P)
%
% [K,P] = som_e
www.eeworm.com/read/294611/8216614
m som_probability_gmm.m
function [pd,Pdm,pmd] = som_probability_gmm(D, sM, K, P)
%SOM_PROBABILITY_GMM Probabilities based on a gaussian mixture model.
%
% [pd,Pdm,pmd] = som_probability_gmm(D, sM, K, P)
%
% [K,P] = som_e