Mercurial > hg > camir-ismir2012
diff toolboxes/FullBNT-1.0.7/netlab3.3/mlpgrad.m @ 0:cc4b1211e677 tip
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646 (e263d8a21543) added further path and more save "camirversion.m"
author | Daniel Wolff |
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date | Fri, 19 Aug 2016 13:07:06 +0200 |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/toolboxes/FullBNT-1.0.7/netlab3.3/mlpgrad.m Fri Aug 19 13:07:06 2016 +0200 @@ -0,0 +1,33 @@ +function [g, gdata, gprior] = mlpgrad(net, x, t) +%MLPGRAD Evaluate gradient of error function for 2-layer network. +% +% Description +% G = MLPGRAD(NET, X, T) takes a network data structure NET together +% with a matrix X of input vectors and a matrix T of target vectors, +% and evaluates the gradient G of the error function with respect to +% the network weights. The error funcion corresponds to the choice of +% output unit activation function. Each row of X corresponds to one +% input vector and each row of T corresponds to one target vector. +% +% [G, GDATA, GPRIOR] = MLPGRAD(NET, X, T) also returns separately the +% data and prior contributions to the gradient. In the case of multiple +% groups in the prior, GPRIOR is a matrix with a row for each group and +% a column for each weight parameter. +% +% See also +% MLP, MLPPAK, MLPUNPAK, MLPFWD, MLPERR, MLPBKP +% + +% Copyright (c) Ian T Nabney (1996-2001) + +% Check arguments for consistency +errstring = consist(net, 'mlp', x, t); +if ~isempty(errstring); + error(errstring); +end +[y, z] = mlpfwd(net, x); +delout = y - t; + +gdata = mlpbkp(net, x, z, delout); + +[g, gdata, gprior] = gbayes(net, gdata);