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1 function g = rbfderiv(net, x)
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2 %RBFDERIV Evaluate derivatives of RBF network outputs with respect to weights.
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3 %
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4 % Description
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5 % G = RBFDERIV(NET, X) takes a network data structure NET and a matrix
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6 % of input vectors X and returns a three-index matrix G whose I, J, K
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7 % element contains the derivative of network output K with respect to
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8 % weight or bias parameter J for input pattern I. The ordering of the
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9 % weight and bias parameters is defined by RBFUNPAK. This function
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10 % also takes into account any mask in the network data structure.
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11 %
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12 % See also
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13 % RBF, RBFPAK, RBFGRAD, RBFBKP
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14 %
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15
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16 % Copyright (c) Ian T Nabney (1996-2001)
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17
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18 % Check arguments for consistency
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19 errstring = consist(net, 'rbf', x);
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20 if ~isempty(errstring);
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21 error(errstring);
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22 end
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23
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24 if ~strcmp(net.outfn, 'linear')
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25 error('Function only implemented for linear outputs')
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26 end
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27
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28 [y, z, n2] = rbffwd(net, x);
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29 ndata = size(x, 1);
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30
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31 if isfield(net, 'mask')
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32 nwts = size(find(net.mask), 1);
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33 temp = zeros(1, net.nwts);
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34 else
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35 nwts = net.nwts;
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36 end
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37
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38 g = zeros(ndata, nwts, net.nout);
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39 for k = 1 : net.nout
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40 delta = zeros(1, net.nout);
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41 delta(1, k) = 1;
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42 for n = 1 : ndata
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43 if isfield(net, 'mask')
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44 temp = rbfbkp(net, x(n, :), z(n, :), n2(n, :), delta);
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45 g(n, :, k) = temp(logical(net.mask));
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46 else
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47 g(n, :, k) = rbfbkp(net, x(n, :), z(n, :), n2(n, :),...
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48 delta);
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49 end
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50 end
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51 end
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52
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53 |
