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Proceedings Paper

Associative Learning, Adaptive Pattern Recognition, And Cooperative-Competitive Decision Making By Neural Networks
Author(s): Gail A. Carpenter; Stephen Grossberg
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Paper Abstract

This article describes models of associative pattern learning, adaptive pattern recognition, and parallel decision-making by neural networks. It is shown that a small set of real-time non-linear neural equations within a larger set of specialized neural circuits can be used to study a wide variety of such problems. Models of energy minimization, cooperative-competitive decision making, competitive learning, adaptive resonance, interactive activation, and back propagation are discussed and compared.

Paper Details

Date Published: 13 February 1986
PDF: 30 pages
Proc. SPIE 0634, Optical and Hybrid Computing, (13 February 1986); doi: 10.1117/12.964016
Show Author Affiliations
Gail A. Carpenter, Northeastern University (United States)
Stephen Grossberg, Boston University (United States)


Published in SPIE Proceedings Vol. 0634:
Optical and Hybrid Computing
Harold H. Szu, Editor(s)

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