ON STABLE POINTS AND CYCLES IN BINARY NEURAL NETWORKS.

Moshe Kam, Allon Guez, Roger Cheng

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The design of content-addressable memories by means of binary neural networks is tied to the synthesis of stable points with a guaranteed region of convergence for pattern storage and retrieval. The authors define a local minimum in the binary field, and suggest the usefulness of the concept in memory design. It is shown that N (nonarbitrary) stable points, left bracket N/2 right bracket local minima, and left bracket N/2 right bracket four-cycles can always be assigned. Simple procedures for selection of these points are outlined. The tradeoff between memory capacity and pattern retrievability through a definition of entropy in the memory is demonstrated.

Original languageEnglish (US)
Title of host publicationUnknown Host Publication Title
PublisherIEEE
Pages321-326
Number of pages6
ISBN (Print)0818607610
StatePublished - Jan 1 1987
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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