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Paper Abstract and Keywords
Presentation 2020-01-17 13:15
[Poster Presentation] Investigation of neuron with sigmoid activation function for quantum-flux-parametron-based neural network
Daiki Yamaguchi, Yuki Yamanashi, Nobuyuki Yoshikawa (Yokohama Natl. Univ.) SCE2019-60 Link to ES Tech. Rep. Archives: SCE2019-60
Abstract (in Japanese) (See Japanese page) 
(in English) An ANN is a circuit that imitates the brain of a human, which is effective for pattern recognition and filtering, and so on. A superconducting circuit can operate at the high fre-quency with low power consumption, it is attractive for realization of energy-efficient ANNs. In order to perform ANN learning, it is necessary for the activation function of neurons in the middle layer to have characteristics like sigmoid/hyperbolic tangent function. The rf-superconducting quantum interference device (rf-SQUID) is composed of a supercon-ducting loop including a Josephson junction and an inductance, and when a magnetic flux is applied to the circuit, a circular current is generated as if sine is inclined. Applying the cir-cuit of rf-SQUID, it is known that the input/output relationship of magnetic flux has charac-teristics close to the sigmoid/hyperbolic tangent function. In this study, we designed a neuron with a hyperbolic tangent activation function using the AIST fabrication process. Fur-thermore, we investigated tuning method of the quantum-flux-parametron-based supercon-ducting neural network toward its learning.
Keyword (in Japanese) (See Japanese page) 
(in English) rf-SQUID / ANN / sigmoid / hyperbolic tangent / / / /  
Reference Info. IEICE Tech. Rep., vol. 119, no. 369, SCE2019-60, pp. 125-127, Jan. 2020.
Paper # SCE2019-60 
Date of Issue 2020-01-09 (SCE) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
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All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF SCE2019-60 Link to ES Tech. Rep. Archives: SCE2019-60

Conference Information
Committee SCE  
Conference Date 2020-01-16 - 2020-01-17 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To SCE 
Conference Code 2020-01-SCE 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Investigation of neuron with sigmoid activation function for quantum-flux-parametron-based neural network 
Sub Title (in English)  
Keyword(1) rf-SQUID  
Keyword(2) ANN  
Keyword(3) sigmoid  
Keyword(4) hyperbolic tangent  
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1st Author's Name Daiki Yamaguchi  
1st Author's Affiliation Yokohama National University (Yokohama Natl. Univ.)
2nd Author's Name Yuki Yamanashi  
2nd Author's Affiliation Yokohama National University (Yokohama Natl. Univ.)
3rd Author's Name Nobuyuki Yoshikawa  
3rd Author's Affiliation Yokohama National University (Yokohama Natl. Univ.)
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Speaker Author-1 
Date Time 2020-01-17 13:15:00 
Presentation Time 135 minutes 
Registration for SCE 
Paper # SCE2019-60 
Volume (vol) vol.119 
Number (no) no.369 
Page pp.125-127 
#Pages
Date of Issue 2020-01-09 (SCE) 


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