Optical Implementation of a Second-Order Neural Network Discriminator Model

1 July 1990

journal article
Published by IOP Publishing in Japanese Journal of Applied Physics

Vol. 29 (7A) , L1328-1331
https://doi.org/10.1143/jjap.29.l1328

Abstract

Some of the symmetries inherent in a second-order translation invariant classifier model are described. The operational characteristics of this model for pattern recognition tasks such as fault and noise tolerance are explored. A particular optical architecture is detailed which exploits particular features of the model suited to optics and the operation of this system described.

Keywords

MACHINE TRANSLATION
NEURAL NET
PATTERN RECOGNITION
DISCRIMINATIVE MODEL
NEURAL NETWORKS
SECOND ORDER
NEURAL NETWORK
FAULT TOLERANT

This publication has 3 references indexed in Scilit:

Learning, invariance, and generalization in high-order neural networks
Applied Optics, 1987
Parallel Distributed Processing
Published by MIT Press ,1986
Optical matrix–matrix multiplier based on outer product decomposition
Applied Optics, 1982