a = rbffwd(net, x) function [a, z, n2] = rbffwd(net, x)
a = rbffwd(net, x)takes a network data structure
netand a matrix
xof input vectors and forward propagates the inputs through the network to generate a matrix
aof output vectors. Each row of
xcorresponds to one input vector and each row of
acontains the corresponding output vector. The activation function that is used is determined by
[a, z, n2] = rbffwd(net, x) also generates a matrix
the hidden unit activations where each row corresponds to one pattern.
These hidden unit activations represent the
design matrix for
the RBF. The matrix
n2 is the squared distances between each
basis function centre and each pattern in which each row corresponds
to a data point.
[a, z] = rbffwd(net, x);Here
temp = pinv([z ones(size(x, 1), 1)]) * t; net.w2 = temp(1: nd(2), :); net.b2 = temp(size(x, nd(2)) + 1, :);
xis the input data,
tare the target values, and we use the pseudo-inverse to find the output weights and biases.
Copyright (c) Ian T Nabney (1996-9)