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/421949/10676621
m unsuni.m
function [MI,SIGMA,Pk,I,solution,t]=unsuni(X,K,tmax,randinit,t,MI,SIGMA,Pk)
% UNSUNI EM algorithm, mixture of Gaussians, diag. cov. matrix.
% [MI,SIGMA,Pk,I,solution,t]=unsuni(X,K,tmax,randinit,t,MI
www.eeworm.com/read/483011/6607246
m em_gm_fast.m
function [W,M,V,L] = EM_GM_fast(X,k,ltol,maxiter,pflag,Init)
% [W,M,V,L] = EM_GM_fast(X,k,ltol,maxiter,pflag,Init)
%
% EM algorithm for k multidimensional Gaussian mixture estimation
% (EM_GM_fa
www.eeworm.com/read/483011/6607247
m plot_gm.m
function Plot_GM(W,M,V,flag,X)
% Plot_GM(W,M,V,X)
%
% Plots a 1D or 2D Gaussian mixture.
%
% Inputs:
% W(1,k) - weights of each GM component, k is the number of component
% M(d,k) - m
www.eeworm.com/read/253950/12173954
htm mdninit.htm
Netlab Reference Manual mdninit
mdninit
Purpose
Initialise the weights in a Mixture Density Network.
Synopsis
n
www.eeworm.com/read/253950/12174115
htm mdnerr.htm
Netlab Reference Manual mdnerr
mdnerr
Purpose
Evaluate error function for Mixture Density Network.
Synopsis
e =
www.eeworm.com/read/150905/12250146
htm mdninit.htm
Netlab Reference Manual mdninit
mdninit
Purpose
Initialise the weights in a Mixture Density Network.
Synopsis
n
www.eeworm.com/read/150905/12250288
htm mdnerr.htm
Netlab Reference Manual mdnerr
mdnerr
Purpose
Evaluate error function for Mixture Density Network.
Synopsis
e =
www.eeworm.com/read/336234/12462471
m sigmix_2ch.m
function [S,A,X,Fs] = Sigmix_2ch
% Sigmix_2ch is used to generate a mixture of 2 sine signals at
% 1kHz and 2kHz with 30800 sample at sampling rate of 16kHz
% Usage: [S,A,X,Fs] = Sigmix_2ch
% Inpu
www.eeworm.com/read/128468/14295419
m unsuni.m
function [MI,SIGMA,Pk,I,solution,t]=unsuni(X,K,tmax,randinit,t,MI,SIGMA,Pk)
% UNSUNI EM algorithm, mixture of Gaussians, diag. cov. matrix.
% [MI,SIGMA,Pk,I,solution,t]=unsuni(X,K,tmax,randinit,t,MI
www.eeworm.com/read/481713/1293572
m unsuni.m
function [MI,SIGMA,Pk,I,solution,t]=unsuni(X,K,tmax,randinit,t,MI,SIGMA,Pk)
% UNSUNI EM algorithm, mixture of Gaussians, diag. cov. matrix.
% [MI,SIGMA,Pk,I,solution,t]=unsuni(X,K,tmax,randinit,t,MI