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/451547/7461963
m dd_aic.m
function e = dd_aic(w,x)
%DD_AIC compute the Akaike Information Criterion for MoG
%
% E = DD_AIC(W,X)
%
% Compute the Akaike Information Criterion of the Mixture of
% Gaussians. We assume we have
www.eeworm.com/read/397111/8067274
m dd_aic.m
function e = dd_aic(w,x)
%DD_AIC compute the Akaike Information Criterion for MoG
%
% E = DD_AIC(W,X)
%
% Compute the Akaike Information Criterion of the Mixture of
% Gaussians. We assume we have
www.eeworm.com/read/314474/13566585
h loglinearmix.h
/*
* LoglinearMix.h --
* Log-linear Mixture language model
*
* Copyright (c) 2005 SRI International. All Rights Reserved.
*
* @(#)$Header: /home/srilm/devel/lm/src/RCS/LoglinearMix.h,v 1.1 2005
www.eeworm.com/read/314474/13566596
h adaptivemix.h
/*
* AdaptiveMix.h --
* Adaptive Mixture language model
*
* Copyright (c) 1998-2003 SRI International. All Rights Reserved.
*
* @(#)$Header: /home/srilm/devel/lm/src/RCS/AdaptiveMix.h,v 1.6 200
www.eeworm.com/read/140847/5779116
m mfa.m
% function [Lh,Ph,Mu,Pi,LL]=mfa(X,M,K,cyc,tol);
%
% Maximum Likelihood Mixture of Factor Analysis using EM
%
% X - data matrix
% M - number of mixtures (default 1)
% K - number of factors in each mix
www.eeworm.com/read/133943/5897302
m mfa.m
% function [Lh,Ph,Mu,Pi,LL]=mfa(X,M,K,cyc,tol);
%
% Maximum Likelihood Mixture of Factor Analysis using EM
%
% X - data matrix
% M - number of mixtures (default 1)
% K - number of factors in each mix
www.eeworm.com/read/493294/6400311
m dd_aic.m
function e = dd_aic(w,x)
%DD_AIC compute the Akaike Information Criterion for MoG
%
% E = DD_AIC(W,X)
%
% Compute the Akaike Information Criterion of the Mixture of
% Gaussians. We assume we have
www.eeworm.com/read/492400/6422282
m dd_aic.m
function e = dd_aic(w,x)
%DD_AIC compute the Akaike Information Criterion for MoG
%
% E = DD_AIC(W,X)
%
% Compute the Akaike Information Criterion of the Mixture of
% Gaussians. We assume we have
www.eeworm.com/read/400576/11573535
m dd_aic.m
function e = dd_aic(w,x)
%DD_AIC compute the Akaike Information Criterion for MoG
%
% E = DD_AIC(W,X)
%
% Compute the Akaike Information Criterion of the Mixture of
% Gaussians. We assume we have
www.eeworm.com/read/343227/11962643
m pm_em.m
function [wght, rate, logl,postprob] = pm_em(count, wght, rate, Nit)
%pm_em Estimates the parameters of a Poisson mixture using the EM algorithm.
% Use: [wght,rate,logl,postprob] = pm_em(co