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function g = mlpderiv(net, x)
%MLPDERIV Evaluate derivatives of network outputs with respect to weights.
%
% Description
% G = MLPDERIV(NET, X) takes a network data structure NET and a matrix
% of input vectors X and returns a three-index matrix G whose I, J, K
% element contains the derivative of network output K with respect to
% weight or bias parameter J for input pattern I. The ordering of the
% weight and bias parameters is defined by MLPUNPAK.
%
% See also
% MLP, MLPPAK, MLPGRAD, MLPBKP
%
% Copyright (c) Ian T Nabney (1996-2001)
% Check arguments for consistency
errstring = consist(net, 'mlp', x);
if ~isempty(errstring);
error(errstring);
end
[y, z] = mlpfwd(net, x);
ndata = size(x, 1);
if isfield(net, 'mask')
nwts = size(find(net.mask), 1);
temp = zeros(1, net.nwts);
else
nwts = net.nwts;
end
g = zeros(ndata, nwts, net.nout);
for k = 1 : net.nout
delta = zeros(1, net.nout);
delta(1, k) = 1;
for n = 1 : ndata
if isfield(net, 'mask')
temp = mlpbkp(net, x(n, :), z(n, :), delta);
g(n, :, k) = temp(logical(net.mask));
else
g(n, :, k) = mlpbkp(net, x(n, :), z(n, :),...
delta);
end
end
end
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