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annotate toolboxes/FullBNT-1.0.7/netlab3.3/demgpot.m @ 0:e9a9cd732c1e tip

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first hg version after svn
author wolffd
date Tue, 10 Feb 2015 15:05:51 +0000
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wolffd@0 1 function g = demgpot(x, mix)
wolffd@0 2 %DEMGPOT Computes the gradient of the negative log likelihood for a mixture model.
wolffd@0 3 %
wolffd@0 4 % Description
wolffd@0 5 % This function computes the gradient of the negative log of the
wolffd@0 6 % unconditional data density P(X) with respect to the coefficients of
wolffd@0 7 % the data vector X for a Gaussian mixture model. The data structure
wolffd@0 8 % MIX defines the mixture model, while the matrix X contains the data
wolffd@0 9 % vector as a row vector. Note the unusual order of the arguments: this
wolffd@0 10 % is so that the function can be used in DEMHMC1 directly for sampling
wolffd@0 11 % from the distribution P(X).
wolffd@0 12 %
wolffd@0 13 % See also
wolffd@0 14 % DEMHMC1, DEMMET1, DEMPOT
wolffd@0 15 %
wolffd@0 16
wolffd@0 17 % Copyright (c) Ian T Nabney (1996-2001)
wolffd@0 18
wolffd@0 19 % Computes the potential gradient
wolffd@0 20
wolffd@0 21 temp = (ones(mix.ncentres,1)*x)-mix.centres;
wolffd@0 22 temp = temp.*(gmmactiv(mix,x)'*ones(1, mix.nin));
wolffd@0 23 % Assume spherical covariance structure
wolffd@0 24 if ~strcmp(mix.covar_type, 'spherical')
wolffd@0 25 error('Spherical covariance only.')
wolffd@0 26 end
wolffd@0 27 temp = temp./(mix.covars'*ones(1, mix.nin));
wolffd@0 28 temp = temp.*(mix.priors'*ones(1, mix.nin));
wolffd@0 29 g = sum(temp, 1)/gmmprob(mix, x);