代码搜索：MIXTURE
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www.eeworm.com/read/253950/12173570
m demgmm2.m
%DEMGMM1 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. The priors
www.eeworm.com/read/253950/12173859
htm mdnfwd.htm
Netlab Reference Manual mdnfwd
mdnfwd
Purpose
Forward propagation through Mixture Density Network.
Synopsis
mix
www.eeworm.com/read/253950/12174063
htm gmmunpak.htm
Netlab Reference Manual gmmunpak
gmmunpak
Purpose
Separates a vector of Gaussian mixture model parameters into its components.
www.eeworm.com/read/253950/12174218
m mdnerr.m
function e = mdnerr(net, x, t)
%MDNERR Evaluate error function for Mixture Density Network.
%
% Description
% E = MDNERR(NET, X, T) takes a mixture density network data structure
% NET, a matrix X of
www.eeworm.com/read/339665/12211152
m demgmm1.m
%DEMGMM1 Demonstrate EM for Gaussian mixtures.
%
% Description
% This script demonstrates the use of the EM algorithm to fit a mixture
% of Gaussians to a set of data using maximum likelihood. A colou
www.eeworm.com/read/339665/12211306
m demhmc1.m
%DEMHMC1 Demonstrate Hybrid Monte Carlo sampling on mixture of two Gaussians.
%
% Description
% The problem consists of generating data from a mixture of two
% Gaussians in two dimensions using a hybr
www.eeworm.com/read/339665/12211332
m demgmm5.m
%DEMGMM5 Demonstrate density modelling with a PPCA mixture model.
%
% Description
% The problem consists of modelling data generated by a mixture of
% three Gaussians in 2 dimensions with a mixture m
www.eeworm.com/read/339665/12211410
m contents.m
% Netlab Toolbox
% Version 3.3.1 18-Jun-2004
%
% conffig - Display a confusion matrix.
% confmat - Compute a confusion matrix.
% conjgrad - Conjugate gradients optimization.
% consist - Ch
www.eeworm.com/read/339665/12211562
m demgmm2.m
%DEMGMM1 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. The priors
www.eeworm.com/read/339665/12211880
m mdnerr.m
function e = mdnerr(net, x, t)
%MDNERR Evaluate error function for Mixture Density Network.
%
% Description
% E = MDNERR(NET, X, T) takes a mixture density network data structure
% NET, a matrix X of