Mercurial > hg > camir-aes2014
comparison toolboxes/FullBNT-1.0.7/netlab3.3/rbfjacob.m @ 0:e9a9cd732c1e tip
first hg version after svn
author | wolffd |
---|---|
date | Tue, 10 Feb 2015 15:05:51 +0000 |
parents | |
children |
comparison
equal
deleted
inserted
replaced
-1:000000000000 | 0:e9a9cd732c1e |
---|---|
1 function jac = rbfjacob(net, x) | |
2 %RBFJACOB Evaluate derivatives of RBF network outputs with respect to inputs. | |
3 % | |
4 % Description | |
5 % G = RBFJACOB(NET, X) takes a network data structure NET and a matrix | |
6 % of input vectors X and returns a three-index matrix G whose I, J, K | |
7 % element contains the derivative of network output K with respect to | |
8 % input parameter J for input pattern I. | |
9 % | |
10 % See also | |
11 % RBF, RBFGRAD, RBFBKP | |
12 % | |
13 | |
14 % Copyright (c) Ian T Nabney (1996-2001) | |
15 | |
16 % Check arguments for consistency | |
17 errstring = consist(net, 'rbf', x); | |
18 if ~isempty(errstring); | |
19 error(errstring); | |
20 end | |
21 | |
22 if ~strcmp(net.outfn, 'linear') | |
23 error('Function only implemented for linear outputs') | |
24 end | |
25 | |
26 [y, z, n2] = rbffwd(net, x); | |
27 | |
28 ndata = size(x, 1); | |
29 jac = zeros(ndata, net.nin, net.nout); | |
30 Psi = zeros(net.nin, net.nhidden); | |
31 % Calculate derivative of activations wrt n2 | |
32 switch net.actfn | |
33 case 'gaussian' | |
34 dz = -z./(ones(ndata, 1)*net.wi); | |
35 case 'tps' | |
36 dz = 2*(1 + log(n2+(n2==0))); | |
37 case 'r4logr' | |
38 dz = 2*(n2.*(1+2.*log(n2+(n2==0)))); | |
39 otherwise | |
40 error(['Unknown activation function ', net.actfn]); | |
41 end | |
42 | |
43 % Ignore biases as they cannot affect Jacobian | |
44 for n = 1:ndata | |
45 Psi = (ones(net.nin, 1)*dz(n, :)).* ... | |
46 (x(n, :)'*ones(1, net.nhidden) - net.c'); | |
47 % Now compute the Jacobian | |
48 jac(n, :, :) = Psi * net.w2; | |
49 end |