wolffd@0: function net = rbfunpak(net, w)
wolffd@0: %RBFUNPAK Separates a vector of RBF weights into its components.
wolffd@0: %
wolffd@0: %	Description
wolffd@0: %	NET = RBFUNPAK(NET, W) takes an RBF network data structure NET and  a
wolffd@0: %	weight vector W, and returns a network data structure identical to
wolffd@0: %	the input network, except that the centres C, the widths WI, the
wolffd@0: %	second-layer weight matrix W2 and the second-layer bias vector B2
wolffd@0: %	have all been set to the corresponding elements of W.
wolffd@0: %
wolffd@0: %	See also
wolffd@0: %	RBFPAK, RBF
wolffd@0: %
wolffd@0: 
wolffd@0: %	Copyright (c) Ian T Nabney (1996-2001)
wolffd@0: 
wolffd@0: % Check arguments for consistency
wolffd@0: errstring = consist(net, 'rbf');
wolffd@0: if ~errstring
wolffd@0:   error(errstring);
wolffd@0: end
wolffd@0: 
wolffd@0: if net.nwts ~= length(w)
wolffd@0:   error('Invalid length of weight vector')
wolffd@0: end
wolffd@0: 
wolffd@0: nin 	= net.nin;
wolffd@0: nhidden = net.nhidden;
wolffd@0: nout 	= net.nout;
wolffd@0: 
wolffd@0: mark1 = nin*nhidden;
wolffd@0: net.c = reshape(w(1:mark1), nhidden, nin);
wolffd@0: if strcmp(net.actfn, 'gaussian')
wolffd@0:   mark2 = mark1 + nhidden;
wolffd@0:   net.wi = reshape(w(mark1+1:mark2), 1, nhidden);
wolffd@0: else
wolffd@0:   mark2 = mark1;
wolffd@0:   net.wi = [];
wolffd@0: end
wolffd@0: mark3 = mark2 + nhidden*nout;
wolffd@0: net.w2 = reshape(w(mark2+1:mark3), nhidden, nout);
wolffd@0: mark4 = mark3 + nout;
wolffd@0: net.b2 = reshape(w(mark3+1:mark4), 1, nout);