# mlppak

## Purpose

Combines weights and biases into one weights vector.

## Synopsis

    w = mlppak(net)

## Description

`w = mlppak(net)` takes a network data structure `net` and combines the component weight matrices bias vectors into a single row vector `w`. The facility to switch between these two representations for the network parameters is useful, for example, in training a network by error function minimization, since a single vector of parameters can be handled by general-purpose optimization routines.

The ordering of the paramters in `w` is defined by

      w = [net.w1(:)', net.b1, net.w2(:)', net.b2];

where `w1` is the first-layer weight matrix, `b1` is the first-layer bias vector, `w2` is the second-layer weight matrix, and `b2` is the second-layer bias vector.

## See Also

`mlp`, `mlpunpak`, `mlpfwd`, `mlperr`, `mlpbkp`, `mlpgrad`

Pages: Index

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