# demolgd1

## Purpose

Demonstrate simple MLP optimisation with on-line gradient descent

## Synopsis

    demolgd1

## Description

The problem consists of one input variable `x` and one target variable `t` with data generated by sampling `x` at equal intervals and then generating target data by computing `sin(2*pi*x)` and adding Gaussian noise. A 2-layer network with linear outputs is trained by minimizing a sum-of-squares error function using on-line gradient descent.

## See Also

`demmlp1`, `olgd`

Pages: Index

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