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Paper Abstract and Keywords
Presentation 2022-09-07 14:10
Efficient Learning of Spiking Neural Networks with Genetic Algorithm and its FPGA Acceleration
Taiki Watanabe, Yukinori Sato (TUT) RECONF2022-26
Abstract (in Japanese) (See Japanese page) 
(in English) Spiking Neural Network (SNN) is one of the promising models of neuromorphic architecture. A learning method using a genetic algorithm is proposed for this SNN. This method enables optimization by adding and removing nodes and edges in the network, in addition to adjusting the weight parameters. In this paper, we propose parallelization, partial C implementation, and hardware acceleration methods for accelerating the training of SNNs with genetic algorithms. We also implement an FPGA using high-level synthesis based on the C language implementation.
Keyword (in Japanese) (See Japanese page) 
(in English) / / / / / / /  
Reference Info. IEICE Tech. Rep., vol. 122, no. 174, RECONF2022-26, pp. 1-6, Sept. 2022.
Paper # RECONF2022-26 
Date of Issue 2022-08-31 (RECONF) 
ISSN Online edition: ISSN 2432-6380
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)
Notes on Review This article is a technical report without peer review, and its polished version will be published elsewhere.
Download PDF RECONF2022-26

Conference Information
Committee RECONF  
Conference Date 2022-09-07 - 2022-09-08 
Place (in Japanese) (See Japanese page) 
Place (in English) emCAMPUS STUDIO 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Reconfigurable system, etc. 
Paper Information
Registration To RECONF 
Conference Code 2022-09-RECONF 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Efficient Learning of Spiking Neural Networks with Genetic Algorithm and its FPGA Acceleration 
Sub Title (in English)  
1st Author's Name Taiki Watanabe  
1st Author's Affiliation Toyohashi University of Technology (TUT)
2nd Author's Name Yukinori Sato  
2nd Author's Affiliation Toyohashi University of Technology (TUT)
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Speaker Author-1 
Date Time 2022-09-07 14:10:00 
Presentation Time 25 minutes 
Registration for RECONF 
Paper # RECONF2022-26 
Volume (vol) vol.122 
Number (no) no.174 
Page pp.1-6 
Date of Issue 2022-08-31 (RECONF) 

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