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/373460/2761830

m pnmix.m

function [hellipse,hcenter]=pnmix(X,MI,SIGMA,I,hellipse,hcenter) % [hellipse,hcenter]=pnmix(X,MI,SIGMA,I,hellipse,hcenter) % % PNMIX vizualizes mixture of normal distributions in 2D space. % Each n
www.eeworm.com/read/160391/5571158

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 ea
www.eeworm.com/read/392854/8322678

m mixgauss_mstep.m

function [mu, Sigma] = mixgauss_Mstep(w, Y, YY, YTY, varargin) % MSTEP_COND_GAUSS Compute MLEs for mixture of Gaussians given expected sufficient statistics % function [mu, Sigma] = Mstep_cond_gauss(w
www.eeworm.com/read/367442/9747807

m pnmix.m

function [hellipse,hcenter]=pnmix(X,MI,SIGMA,I,hellipse,hcenter) % [hellipse,hcenter]=pnmix(X,MI,SIGMA,I,hellipse,hcenter) % % PNMIX vizualizes mixture of normal distributions in 2D space. % Each n
www.eeworm.com/read/334240/12616002

description

Package: mixdist Version: 0.5-2 Date: 2008-05-02 Title: Finite Mixture Distribution Models Author: Peter Macdonald , with contributions from Juan Du
www.eeworm.com/read/237675/13939021

c mvgmmrnd.c

/* mvgmmrnd.c Draw samples from a mixture of multivariate Gaussian PDF usage: [Z , index] = mvgmmrnd(N , mu , sigma , p , [n1] , ... , [nl]) mu : Mean vector (d x 1 x M x
www.eeworm.com/read/465320/1520845

c calc_tied_mix.c

/** * @file calc_tied_mix.c * @author Akinobu LEE * @date Thu Feb 17 14:22:44 2005 * * * @brief 寒圭ガウス尸邵の脚みつき下の纷换¨tied-mixture脱·キャッシュ铜り * * Tied-mixture 脱のガウス寒圭尸邵纷换ではキャッシュが雇胃されますˉ *
www.eeworm.com/read/165316/10068053

html index.html

EM algorithm for Mixture models
www.eeworm.com/read/165316/10068054

html index.html

EM algorithm for Mixture models
www.eeworm.com/read/360995/10070034

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