Design of single electron circuitry for a stochastic logic neural network

Hisanao Akima, Shigeo Sato, Koji Nakajima

研究成果: Chapter

抄録

Single electron devices are ultra low power and extremely small devices, and suitable for implementation of large scale integrated circuits. An artificial neural network (ANN) is one of the possible applications of single electron devices. We apply stochastic logic in which various complex operations can be done with basic logic gates. We design basic subcircuits of a single electron stochastic neural network, and confirm that backgate bias control and a redundant configuration are necessary for a feedback loop configuration by computer simulation based- on Monte Carlo method. The proposed single electron circuit is well-suited for hardware implementation of a stochastic logic neural network.

本文言語English
ホスト出版物のタイトルLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
編集者Mircea Gh. Negoita, Robert J. Howlett, Lakhmi C. Jain
出版社Springer Verlag
ページ1010-1016
ページ数7
ISBN(印刷版)9783540301325
DOI
出版ステータスPublished - 2004 1 1

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
3213
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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