g = mdngrad(net, x, t)
g = mdngrad(net, x, t) takes a mixture density network data
structure net, 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 function
is negative log likelihood of the target data. Each row of x
corresponds to one input vector and each row of t corresponds to
one target vector.
mdn, mdnfwd, mdnerr, mdnprob, mlpbkpCopyright (c) Ian T Nabney (1996-9)
David J Evans (1998)