A localized learning rule for analog VLSI implementation of neural networks

Hiroyuki Wasaki, Yoshihiko Horio, Shogo Nakamura

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

1 Citation (Scopus)

Abstract

A modified Hebbian type learning rule for self-organization which uses only the local information is proposed. As the result of computer simulations of self-organizing networks, the validity of the rule was confirmed and learning speed was improved. Furthermore, circuit examples for implementing the learning rule are proposed.

Original languageEnglish
Title of host publicationMidwest Symposium on Circuits and Systems
PublisherPubl by IEEE
Pages17-20
Number of pages4
ISBN (Print)0780300815
Publication statusPublished - 1991 Dec 1
Externally publishedYes
Event33rd Midwest Symposium on Circuits and Systems - Calgary, Alberta, Can
Duration: 1990 Aug 121990 Aug 15

Publication series

NameMidwest Symposium on Circuits and Systems
Volume1

Other

Other33rd Midwest Symposium on Circuits and Systems
CityCalgary, Alberta, Can
Period90/8/1290/8/15

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Electrical and Electronic Engineering

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