Share Email Print
cover

Proceedings Paper

Dynamic Autoassociative Neural Memory Performance VS. Capacity
Author(s): Abbas M. Youssef; Mohamad H. Hassoun
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

A new capacity measure is proposed for the class of dynamic autoassociative neural memories (ANMs). The proposed associative memory capacity measure is based on the memory's performance vs. the number of stored memory vectors, where performance is defined in terms of the memory's error-correcting ability and its fundamental memories' attraction volumes. This new method of measuring ANM capacity is very effective when ANMs are used in pattern recognition and error-tolerant content-addressable memories. The proposed capacity/performance measure has been tested for several ANMs having the same dynamic Hopfield memory-like architecture, each employing a different recording technique. Correlation, generalized inverse (orthogonal), and Ho-Kashyap memory recordings have been investigated. Monte Carlo analysis has been performed on ANMs recorded with randomly generated patterns, in order to determine and compare performance characteristics and dynamics.

Paper Details

Date Published: 29 June 1989
PDF: 8 pages
Proc. SPIE 1053, Optical Pattern Recognition, (29 June 1989); doi: 10.1117/12.951515
Show Author Affiliations
Abbas M. Youssef, Wayne State University (United States)
Mohamad H. Hassoun, Wayne State University (United States)


Published in SPIE Proceedings Vol. 1053:
Optical Pattern Recognition
Hua-Kuang Liu, Editor(s)

© SPIE. Terms of Use
Back to Top