Convergence time and memory capacity of higher-order Hopfield associative memory with multi-valued neurons

Daniel Y. Chao; David T. Wang; Douglas D.C. Hung

doi:10.1093/comjnl/36.6.554

Convergence time and memory capacity of higher-order Hopfield associative memory with multi-valued neurons

Daniel Y. Chao, David T. Wang, Douglas D.C. Hung

Computer Science

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

1 Scopus citations

Abstract

We investigate the two basic properties, i.e. convergence time and memory capacity, of the higher-order Hopfield associative memory with multi-valued neurons. The second-order Hopfield neural network of multi-valued neurons is presented analytically. The properties of the combined higher-order multi-valued model is then studied. Finally, the memory capacity of the higher-higher order binary-valued model is studied using a statistical approach.

Original language	English (US)
Pages (from-to)	554-561
Number of pages	8
Journal	Computer Journal
Volume	36
Issue number	6
DOIs	https://doi.org/10.1093/comjnl/36.6.554
State	Published - 1993

All Science Journal Classification (ASJC) codes

General Computer Science

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10.1093/comjnl/36.6.554

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title = "Convergence time and memory capacity of higher-order Hopfield associative memory with multi-valued neurons",

abstract = "We investigate the two basic properties, i.e. convergence time and memory capacity, of the higher-order Hopfield associative memory with multi-valued neurons. The second-order Hopfield neural network of multi-valued neurons is presented analytically. The properties of the combined higher-order multi-valued model is then studied. Finally, the memory capacity of the higher-higher order binary-valued model is studied using a statistical approach.",

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N2 - We investigate the two basic properties, i.e. convergence time and memory capacity, of the higher-order Hopfield associative memory with multi-valued neurons. The second-order Hopfield neural network of multi-valued neurons is presented analytically. The properties of the combined higher-order multi-valued model is then studied. Finally, the memory capacity of the higher-higher order binary-valued model is studied using a statistical approach.

AB - We investigate the two basic properties, i.e. convergence time and memory capacity, of the higher-order Hopfield associative memory with multi-valued neurons. The second-order Hopfield neural network of multi-valued neurons is presented analytically. The properties of the combined higher-order multi-valued model is then studied. Finally, the memory capacity of the higher-higher order binary-valued model is studied using a statistical approach.

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DO - 10.1093/comjnl/36.6.554

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AN - SCOPUS:0027883237

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JO - Computer Journal

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Convergence time and memory capacity of higher-order Hopfield associative memory with multi-valued neurons

Abstract

All Science Journal Classification (ASJC) codes

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