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/434858/1867993
m mhmm1.m
% Make an HMM with mixture of Gaussian observations
% Q1 ---> Q2
% / | / |
% M1 | M2 |
% \ v \ v
% Y1 Y2
% where Pr(m=j|q=i) is a multinomial and Pr(y|m,q) is a Gaussian
www.eeworm.com/read/393163/2487916
m mhmm1.m
% Make an HMM with mixture of Gaussian observations
% Q1 ---> Q2
% / | / |
% M1 | M2 |
% \ v \ v
% Y1 Y2
% where Pr(m=j|q=i) is a multinomial and Pr(y|m,q) is a Gaussian
www.eeworm.com/read/160391/5571237
m mhmm1.m
% Make an HMM with mixture of Gaussian observations
% Q1 ---> Q2
% / | / |
% M1 | M2 |
% \ v \ v
% Y1 Y2
% where Pr(m=j|q=i) is a multinomial and Pr(y|m,q) is a Gaussian
www.eeworm.com/read/204456/15339251
m mog_update.m
function w = mog_update(w,x,maxiter)
%MOG_UPDATE Train a MoG
%
% W = MOG_UPDATE(W,X,MAXITER)
%
% Fit a Mixture of Gaussians model W to data X, for MAXITER number of EM
% steps.
%
% See also: mog_d
www.eeworm.com/read/384512/8866059
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/428167/8885974
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/427909/8912962
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/373249/9467821
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/164422/10108696
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/277988/10587775
m em_gm.m
function [W,M,V,L] = EM_GM(X,k,ltol,maxiter,pflag,Init)
% [W,M,V,L] = EM_GM(X,k,ltol,maxiter,pflag,Init)
%
% EM algorithm for k multidimensional Gaussian mixture estimation
%
% Inputs:
% X(n,d) -