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/323193/13347627
m mdlreduceorder.m
function mixture1 = MDLReduceOrder(mixture, verbose)
% MDLReduceOrder reduce the order of the mixture by 1 by combining the
% two closest distance clusters
K=mixture.K;
for k1=1:K
www.eeworm.com/read/140704/5783174
cc tr_tr_set_0.cc
// file: tr_tr_set_0.cc
//
// isip include files
//
#include "train_trace.h"
#include "train_trace_constants.h"
// method: set_max_mixture_cc
//
// arguments:
// int_4 max_mix: (input) the mixture
www.eeworm.com/read/422198/10657108
pdf baseball_playfield_segmentation_using_adaptive_gaussian_mixture_models.pdf
www.eeworm.com/read/429878/8783856
htm mdnfwd.htm
Netlab Reference Manual mdnfwd
mdnfwd
Purpose
Forward propagation through Mixture Density Network.
Synopsis
mix
www.eeworm.com/read/429878/8784033
htm gmmunpak.htm
Netlab Reference Manual gmmunpak
gmmunpak
Purpose
Separates a vector of Gaussian mixture model parameters into its components.
www.eeworm.com/read/385824/8787637
m em2.m
function tralala= em2
%%This programm estimates the parameters of a mixture of two univariate
%%normals using the EM algorithm and the convergence is demonstrated " on-line".
%%It can be used for a
www.eeworm.com/read/385824/8787638
m em1.m
function tralala= em1
%%This programm estimates the parameters of a mixture of two univariate
%%normals using the EM algorithm and the convergence is demonstrated " on-line".
%%It can be used for a
www.eeworm.com/read/177674/9442369
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/177674/9442427
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/177674/9442435
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