wolffd@0: function g = netgrad_weighted(w, net, x, t, eso_w)
wolffd@0: %NETGRAD Evaluate network error gradient for generic optimizers
wolffd@0: %
wolffd@0: %	Description
wolffd@0: %
wolffd@0: %	G = NETGRAD(W, NET, X, T) takes a weight vector W and a network data
wolffd@0: %	structure NET, together with the matrix X of input vectors and the
wolffd@0: %	matrix T of target vectors, and returns the gradient of the error
wolffd@0: %	function evaluated at W.
wolffd@0: %
wolffd@0: %	See also
wolffd@0: %	MLP, NETERR, NETOPT
wolffd@0: %
wolffd@0: 
wolffd@0: %	Copyright (c) Ian T Nabney (1996-9)
wolffd@0: 
wolffd@0: gradstr = [net.type, 'grad_weighted'];
wolffd@0: 
wolffd@0: net = netunpak(net, w);
wolffd@0: 
wolffd@0: g = feval(gradstr, net, x, t, eso_w);