代码搜索：MIXTURE

找到约 1,805 项符合「MIXTURE」的源代码

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www.eeworm.com/read/469416/6976494

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 c
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www.eeworm.com/read/469416/6976498

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
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www.eeworm.com/read/468647/6986168

m hmtmodel.m

function [ES, PS, MU, SI] = hmtmodel(N) % function [ES, PS, MU, SI] = hmtmodel(N) % % Creates a HMT model for real-world images with 2 mixuture densities. % The model is identically distributed in eac
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www.eeworm.com/read/458010/7314265

m randvec.m

function x=randvec(n,m,c,w,mode) %RANDVEC Generate real or complex random vectors X=(N,M,C,W,MODE) % generates a random matrix of size (|n|,p) where p is the maximum % dimension of M or C % Inpu
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www.eeworm.com/read/448350/7534490

m randvec.m

function x=randvec(n,m,c,w,mode) %RANDVEC Generate real or complex random vectors X=(N,M,C,W,MODE) % generates a random matrix of size (|n|,p) where p is the maximum % dimension of M or C % Inpu
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www.eeworm.com/read/448350/7534514

m gaussmixp.m

function [lp,rp,kh,kp]=gaussmixp(y,m,v,w,a,b) %GAUSSMIXP calculate probability densities from a Gaussian mixture model % % Inputs: n data values, k mixtures, p parameters, q data vector size % %
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www.eeworm.com/read/440750/7682248

m randvec.m

function x=randvec(n,m,c,w,mode) %RANDVEC Generate real or complex random vectors X=(N,M,C,W,MODE) % generates a random matrix of size (|n|,p) where p is the maximum % dimension of M or C % Inpu
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www.eeworm.com/read/143706/12849480

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
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www.eeworm.com/read/143706/12849575

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
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www.eeworm.com/read/143706/12849608

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
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