Generalized associative memory models: Their memory capacities and potential application

College

Gokongwei College of Engineering

Department/Unit

Electronics And Communications Engg

Document Type

Article

Source Title

Journal of Advanced Computational Intelligence and Intelligent Informatics

Volume

8

Issue

1

First Page

56

Last Page

64

Publication Date

2004

Abstract

The Hopfield and bi-directional associative memory (BAM) models are well developed and carefully studied models for associative memory that are patterned after the memory structure of the animal brain. Their basic limitation is that they can only perform associations between at most two sets of patterns. Several different models for generalized associative memory are proposed. These models are all extensions or generalization of the Hopfield and BAM models that can perform multiple associations. Extensive software simulations are conducted to evaluate the different models, using the memory capacity as basis for comparing their performance. Lastly, potential application of these models as data fusion systems is explored.

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Disciplines

Computer Sciences

Keywords

Associative storage; Multisensor data fusion; Learning classifier systems; Brain—Mathematical models; Brain—Models

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