Accession Number:

ADA220767

Title:

A Sum Rule Satisfied by Optimised Feed-Forward Layered Networks

Descriptive Note:

Memorandum rept.

Corporate Author:

ROYAL SIGNALS AND RADAR ESTABLISHMENT MALVERN (UNITED KINGDOM)

Personal Author(s):

Report Date:

1989-01-24

Pagination or Media Count:

10.0

Abstract:

Take a feed-forward layered network such as a multilayer perceptron or a radial basis function network which is to operate as a pattern classifier. The network may have several hidden layers, as many nodes as required and any desired nonlinearities on the hidden units. The transfer functions of the output nodes should be linear. If the network is trained using any appropriate problem to minimise the sum squared error over all outputs and patterns such that the output weights have minimum norm, then the output values of the trained network for any subsequent input pattern will sum to a constant. keywords Radar, Great Britain.

Subject Categories:

  • Active and Passive Radar Detection and Equipment

Distribution Statement:

APPROVED FOR PUBLIC RELEASE