function net = rbfsetbf(net, options, x)%RBFSETBF Set basis functions of RBF from data.%%	Description%	NET = RBFSETBF(NET, OPTIONS, X) sets the basis functions of the RBF%	network NET so that they model the unconditional density of the%	dataset X.  This is done by training a GMM with spherical covariances%	using GMMEM.  The OPTIONS vector is passed to GMMEM. The widths of%	the functions are set by a call to RBFSETFW.%%	See also%	RBFTRAIN, RBFSETFW, GMMEM%%	Copyright (c) Ian T Nabney (1996-2001)errstring = consist(net, 'rbf', x);if ~isempty(errstring)  error(errstring);end% Create a spherical Gaussian mixture modelmix = gmm(net.nin, net.nhidden, 'spherical');% Initialise the parameters from the input data% Just use a small number of k means iterationskmoptions = zeros(1, 18);kmoptions(1) = -1;	% Turn off warningskmoptions(14) = 5;  % Just 5 iterations to get centres roughly rightmix = gmminit(mix, x, kmoptions);% Train mixture model using EM algorithm[mix, options] = gmmem(mix, x, options);% Now set the centres of the RBF from the centres of the mixture modelnet.c = mix.centres;% options(7) gives scale of function widthsnet = rbfsetfw(net, options(7));