Share Email Print

Proceedings Paper

High-order neural network employing adaptive architecture
Author(s): Ronald Michaels
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

For the two category classification problem a method of creating an adaptive architecture network (AANET) is presented and discussed. The principal means of adaptation of this network is the modification of its architecture. AANET is constructed using the repeated application of the outer product expansion, the Karhunen-Loeve expansion, and the Ho- Kashyap algorithm. A multilayer AANET may then be transformed into an equivalent single layer network by passing a vector x having symbolic terms through the network.

Paper Details

Date Published: 1 July 1992
PDF: 12 pages
Proc. SPIE 1710, Science of Artificial Neural Networks, (1 July 1992); doi: 10.1117/12.140108
Show Author Affiliations
Ronald Michaels, Univ. of Tennessee/Knoxville (United States)

Published in SPIE Proceedings Vol. 1710:
Science of Artificial Neural Networks
Dennis W. Ruck, Editor(s)

© SPIE. Terms of Use
Back to Top