%RBNC Radial basis neural net classifier% % 	W = rbnc(A,n)% % A feedforward neural network classifier with one hidden layer with % at most n radial basis units is computed for the labeled dataset % A.% % See also datasets, mappings, neurc, bpxnc, lmnc% This routine calls MATHWORK's solverb routine (NN toolbox) as solvb% Copyright: R.P.W. Duin, duin@ph.tn.tudelft.nl% Faculty of Applied Physics, Delft University of Technology% P.O. Box 5046, 2600 GA Delft, The Netherlandsfunction W = rbnc(a,n)[nlab,lablist,m,k,c] = dataset(a);if nargin < 2 | isempty(n), n = 100; end				% set targetsT = 0.1*ones(c,c) + 0.8 * eye(c);T = T(nlab,:)';				% scaleWP = scalem(a,'variance');				% compute rbf networkhold offr = randn(m,k) * 1e-10; % add noise because solvb has sometimes						% problems with identical inputs[W1,B1,W2,B2,n,r] = solvb(+(a*WP)'+r',T,[inf n m*0.05 0.5]);hu = length(B1);				% compute resulting mapWP = WP*proxm(W1,'d',2);WP = WP*cmapm(B1'.^2,'scale');WP = WP*cmapm(hu,'nexp');w = [W2,B2]';W = WP*mapping('affine',w,lablist,hu,c,1);%WT = packd(w(:),[1,hu,c,1],lablist);%W = classc(WP,WT);return