Mercurial > hg > camir-aes2014
diff toolboxes/FullBNT-1.0.7/netlab3.3/mlpfwd.m @ 0:e9a9cd732c1e tip
first hg version after svn
author | wolffd |
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date | Tue, 10 Feb 2015 15:05:51 +0000 |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/toolboxes/FullBNT-1.0.7/netlab3.3/mlpfwd.m Tue Feb 10 15:05:51 2015 +0000 @@ -0,0 +1,65 @@ +function [y, z, a] = mlpfwd(net, x) +%MLPFWD Forward propagation through 2-layer network. +% +% Description +% Y = MLPFWD(NET, X) takes a network data structure NET together with a +% matrix X of input vectors, and forward propagates the inputs through +% the network to generate a matrix Y of output vectors. Each row of X +% corresponds to one input vector and each row of Y corresponds to one +% output vector. +% +% [Y, Z] = MLPFWD(NET, X) also generates a matrix Z of the hidden unit +% activations where each row corresponds to one pattern. +% +% [Y, Z, A] = MLPFWD(NET, X) also returns a matrix A giving the summed +% inputs to each output unit, where each row corresponds to one +% pattern. +% +% See also +% MLP, MLPPAK, MLPUNPAK, MLPERR, MLPBKP, MLPGRAD +% + +% Copyright (c) Ian T Nabney (1996-2001) + +% Check arguments for consistency +errstring = consist(net, 'mlp', x); +if ~isempty(errstring); + error(errstring); +end + +ndata = size(x, 1); + +z = tanh(x*net.w1 + ones(ndata, 1)*net.b1); +a = z*net.w2 + ones(ndata, 1)*net.b2; + +switch net.outfn + + case 'linear' % Linear outputs + + y = a; + + case 'logistic' % Logistic outputs + % Prevent overflow and underflow: use same bounds as mlperr + % Ensure that log(1-y) is computable: need exp(a) > eps + maxcut = -log(eps); + % Ensure that log(y) is computable + mincut = -log(1/realmin - 1); + a = min(a, maxcut); + a = max(a, mincut); + y = 1./(1 + exp(-a)); + + case 'softmax' % Softmax outputs + + % Prevent overflow and underflow: use same bounds as glmerr + % Ensure that sum(exp(a), 2) does not overflow + maxcut = log(realmax) - log(net.nout); + % Ensure that exp(a) > 0 + mincut = log(realmin); + a = min(a, maxcut); + a = max(a, mincut); + temp = exp(a); + y = temp./(sum(temp, 2)*ones(1, net.nout)); + + otherwise + error(['Unknown activation function ', net.outfn]); +end