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/336521/12439492
m gaussmix.m
function [m,v,w,g,f,pp,gg]=gaussmix(x,c,l,m0,v0,w0)
%GAUSSMIX fits a gaussian mixture pdf to a set of data observations [m,v,w,g,f]=(x,c,l,m0,v0,w0)
%
% Inputs: n data values, k mixtures, p paramet
www.eeworm.com/read/228372/14387921
m gaussmix.m
function [m,v,w,g,f,pp,gg]=gaussmix(x,c,l,m0,v0,w0)
%GAUSSMIX fits a gaussian mixture pdf to a set of data observations [m,v,w,g,f]=(x,xv,l,m0,v0,w0)
%
% Inputs: n data values, k mixtures, p parame
www.eeworm.com/read/124825/14536283
tex hinit.tex
%/* ----------------------------------------------------------- */
%/* */
%/* ___ */
www.eeworm.com/read/124825/14536354
tex hhed.tex
%/* ----------------------------------------------------------- */
%/* */
%/* ___ */
www.eeworm.com/read/393518/8281135
m gaussmixp.m
function [m,v,w,g,f,gg,pp,mi,pm]=gaussmix(x,c,l,m0,v0,w0)
%GAUSSMIX fits a gaussian mixture pdf to a set of data observations [m,v,w,g,f]=(x,c,l,m0,v0,w0)
%
% Inputs: n data values, k mixtures, p p
www.eeworm.com/read/429878/8783967
htm mdn.htm
Netlab Reference Manual mdn
mdn
Purpose
Creates a Mixture Density Network with specified architecture.
Synopsis
www.eeworm.com/read/429878/8784251
htm demgmm2.htm
Netlab Reference Manual demgmm1
demgmm1
Purpose
Demonstrate density modelling with a Gaussian mixture model.
Synopsis
www.eeworm.com/read/177674/9442376
m demgmm3.m
%DEMGMM3 Demonstrate density modelling with a Gaussian mixture model.
%
% Description
% The problem consists of modelling data generated by a mixture of
% three Gaussians in 2 dimensions with a mixtu
www.eeworm.com/read/177674/9442643
m demgmm4.m
%DEMGMM4 Demonstrate density modelling with a Gaussian mixture model.
%
% Description
% The problem consists of modelling data generated by a mixture of
% three Gaussians in 2 dimensions with a mixtu
www.eeworm.com/read/176823/9483082
m demgmm3.m
%DEMGMM3 Demonstrate density modelling with a Gaussian mixture model.
%
% Description
% The problem consists of modelling data generated by a mixture of
% three Gaussians in 2 dimensions with a mixtu