# mdngrad

## Purpose

Evaluate gradient of error function for Mixture Density Network.

## Synopsis

    g = mdngrad(net, x, t)

## Description

`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.

## See Also

`mdn`, `mdnfwd`, `mdnerr`, `mdnprob`, `mlpbkp`

Pages: Index

Copyright (c) Ian T Nabney (1996-9)

David J Evans (1998)