Weighted-outer-product associative neural network

Han-Bing Ji

doi:10.1117/12.50404

1 November 1991 Weighted-outer-product associative neural network

Han-Bing Ji

Proceedings Volume 1606, Visual Communications and Image Processing '91: Image Processing; (1991) https://doi.org/10.1117/12.50404
Event: Visual Communications, '91, 1991, Boston, MA, United States

Abstract

A weighted outer product learning (WOPL) scheme for associative memory neural network is presented in which learning orders are incorporated to the Hopfield model. WOPL can be guaranteed to achieve correct recall of some stored datums no matter whether or not they are stable in the Hopfield model, and whether the number of stored datums is small or large. A technically sufficient condition is also discussed for how to suitably choose learning orders to fully utilize WOPL for correct recall of as many stored datums as possible.

Citation Download Citation

Han-Bing Ji "Weighted-outer-product associative neural network", Proc. SPIE 1606, Visual Communications and Image Processing '91: Image Processing, (1 November 1991); https://doi.org/10.1117/12.50404

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