mixes = mdnfwd(net, x) [mixes, y, z] = mdnfwd(net, x) [mixes, y, z, a] = mdnfwd(net, x)
mixes = mdnfwd(net, x) takes a mixture density network data
structure net and a matrix x of input vectors, and forward
propagates the inputs through the network to generate an array
mixes of output mixture models. Each row of x represents
one input vector and the corresponding row of mixes represents
the data structure vector of the corresponding mixture model for the
conditional probability of target vectors.
[mixes, y, z] = mdnfwd(net, x) also generates a matrix y of
the outputs of the MLP and a matrix z of the hidden
unit activations where each row corresponds to one pattern.
[mixes, 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.
gmm, mdn, mdnerr, mdngrad, mlpfwdCopyright (c) Christopher M Bishop, Ian T Nabney (1996, 1997)