Single electron stochastic neural network

Hisanao Akimia, Saiboku Yamada, Shigeo Sato, Koji Nakajima

Research output: Contribution to journalArticle

Abstract

Single electron devices are ultra low power and extremely small devices, and suitable for implementation of large scale integrated circuits. Artificial neural networks (ANNs), which require a large number of transistors for being to be applied to practical use, is one of the possible applications of single electron devices. In order to simplify a single electron circuit configuration, 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 neural network because we can save circuit area and power consumption by using a single electron random number generator (RNG) instead of a conventional complementary metal oxide semiconductor (CMOS) RNG.

Original languageEnglish
Pages (from-to)2221-2226
Number of pages6
JournalIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
VolumeE87-A
Issue number9
Publication statusPublished - 2004 Sep

Keywords

  • Artificial neural network (ANN)
  • Single electron random number generator
  • Single electron transistor (SET)
  • Stochastic logic

ASJC Scopus subject areas

  • Signal Processing
  • Computer Graphics and Computer-Aided Design
  • Electrical and Electronic Engineering
  • Applied Mathematics

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