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ID 49006
file
creator
Katayama, Haruna
Fujii, Toshiyuki
abstract
The physical basis of an artificial neuron is studied using a model that is based on the stochastic transition between two states in a double well potential. It is shown that the stochastic transition model generates an energy-defined sigmoid function acting as an activation (or transfer) function in neurons. The model is also applied to circuit neurons using superconducting quantum interference devices in artificial neural networks.
description
PACS numbers: 87.19.ll, 85.25.Dq, 07.05.Mh.
This work is supported in part by MEXT (17K05579).
journal title
Journal of Applied Physics
volume
Volume 124
issue
Issue 15
start page
152106
date of issued
2018-09-25
publisher
AIP Publishing
issn
0021-8979
ncid
publisher doi
language
eng
nii type
Journal Article
HU type
Journal Articles
DCMI type
text
format
application/pdf
text version
author
rights
This document is the Accepted Manuscript version of a Published Work that appeared in final form in Journal of Applied Physics, copyright © AIP Publishing after peer review and technical editing by the publisher. To access the final edited and published work see https://doi.org/10.1063/1.5037718.
This is not the published version. Please cite only the published version. この論文は出版社版でありません。引用の際には出版社版をご確認、ご利用ください。
relation url
department
Graduate School of Integrated Arts and Sciences