Constructing associative memories using neural networks

X. Xu; W. T. Tsai

doi:10.1016/0893-6080(90)90073-T

Constructing associative memories using neural networks

X. Xu, W. T. Tsai

Computing, Informatics and Decision Systems Engineering, School of (CIDSE)

Research output: Contribution to journal › Article › peer-review

11 Scopus citations

Abstract

This paper proposes using a generalized Hopfield's model, also known as the McCulloch-Pitts model, as associative memories. The system always converges to the nearest stored words. This is not true for Hopfield's model. We also determine the information capacity of this generalized model. Our result is better than those in the literature.

Original language	English (US)
Pages (from-to)	301-309
Number of pages	9
Journal	Neural Networks
Volume	3
Issue number	3
DOIs	https://doi.org/10.1016/0893-6080(90)90073-T
State	Published - 1990

Keywords

Associative memory
Memory capacity
Neural network model

ASJC Scopus subject areas

Cognitive Neuroscience
Artificial Intelligence

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10.1016/0893-6080(90)90073-T

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abstract = "This paper proposes using a generalized Hopfield's model, also known as the McCulloch-Pitts model, as associative memories. The system always converges to the nearest stored words. This is not true for Hopfield's model. We also determine the information capacity of this generalized model. Our result is better than those in the literature.",

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