comparison toolboxes/FullBNT-1.0.7/netlab3.3/rbfderiv.m @ 0:e9a9cd732c1e tip

first hg version after svn

+function g = rbfderiv(net, x)
+%RBFDERIV Evaluate derivatives of RBF network outputs with respect to weights.
+%
+%	Description
+%	G = RBFDERIV(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 RBFUNPAK.  This function
+%	also takes into account any mask in the network data structure.
+%
+%	See also
+%	RBF, RBFPAK, RBFGRAD, RBFBKP
+%
+
+%	Copyright (c) Ian T Nabney (1996-2001)
+
+% Check arguments for consistency
+errstring = consist(net, 'rbf', x);
+if ~isempty(errstring);
+  error(errstring);
+end
+
+if ~strcmp(net.outfn, 'linear')
+  error('Function only implemented for linear outputs')
+end
+
+[y, z, n2] = rbffwd(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 = rbfbkp(net, x(n, :), z(n, :), n2(n, :), delta);
+	  g(n, :, k) = temp(logical(net.mask));
+      else
+	  g(n, :, k) = rbfbkp(net, x(n, :), z(n, :), n2(n, :),...
+	      delta);
+      end
+  end
+end
+
+