Single Electron Stochastic Neural Network

Hisanao AKIMA; Saiboku YAMADA; Shigeo SATO; Koji NAKAJIMA

Single Electron Stochastic Neural Network

Hisanao AKIMA, Saiboku YAMADA, Shigeo SATO, Koji NAKAJIMA

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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.

Publication: IEICE TRANSACTIONS on Fundamentals Vol.E87-A No.9 pp.2221-2226

Publication Date: 2004/09/01

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Type of Manuscript: Special Section PAPER (Special Section on Nonlinear Theory and its Applications)

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Hisanao AKIMA, Saiboku YAMADA, Shigeo SATO, Koji NAKAJIMA, "Single Electron Stochastic Neural Network" in IEICE TRANSACTIONS on Fundamentals, vol. E87-A, no. 9, pp. 2221-2226, September 2004, doi: .
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.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e87-a_9_2221/_p

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@ARTICLE{e87-a_9_2221,
author={Hisanao AKIMA, Saiboku YAMADA, Shigeo SATO, Koji NAKAJIMA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Single Electron Stochastic Neural Network},
year={2004},
volume={E87-A},
number={9},
pages={2221-2226},
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.},
keywords={},
doi={},
ISSN={},
month={September},}

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TY - JOUR
TI - Single Electron Stochastic Neural Network
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2221
EP - 2226
AU - Hisanao AKIMA
AU - Saiboku YAMADA
AU - Shigeo SATO
AU - Koji NAKAJIMA
PY - 2004
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E87-A
IS - 9
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - September 2004
AB - 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.
ER -