diff toolboxes/FullBNT-1.0.7/netlab3.3/glmderiv.m @ 0:e9a9cd732c1e tip

first hg version after svn

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/toolboxes/FullBNT-1.0.7/netlab3.3/glmderiv.m	Tue Feb 10 15:05:51 2015 +0000
@@ -0,0 +1,40 @@
+function g = glmderiv(net, x)
+%GLMDERIV Evaluate derivatives of GLM outputs with respect to weights.
+%
+%	Description
+%	G = GLMDERIV(NET, X) takes a network data structure NET and a matrix
+%	of input vectors X and returns a three-index matrix mat{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 GLMUNPAK.
+%
+
+%	Copyright (c) Ian T Nabney (1996-2001)
+
+% Check arguments for consistency
+errstring = consist(net, 'glm', x);
+if ~isempty(errstring)
+    error(errstring);
+end
+
+ndata = size(x, 1);
+if isfield(net, 'mask')
+  nwts = size(find(net.mask), 1);
+  mask_array = logical(net.mask)*ones(1, net.nout);
+else
+  nwts = net.nwts;
+end
+g = zeros(ndata, nwts, net.nout);
+
+temp = zeros(net.nwts, net.nout);
+for n = 1:ndata
+    % Weight matrix w1
+    temp(1:(net.nin*net.nout), :) = kron(eye(net.nout), (x(n, :))');
+    % Bias term b1
+    temp(net.nin*net.nout+1:end, :) = eye(net.nout);
+    if isfield(net, 'mask')
+	g(n, :, :) = reshape(temp(find(mask_array)), nwts, net.nout);
+    else
+	g(n, :, :) = temp;
+    end
+end