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Paper Abstract and Keywords
Presentation 2020-03-26 11:25
Reservoir computing using fluid motion
Keita Kohashi, Masanobu Inubushi, Susumu Goto (Osaka Univ.) CCS2019-40
Abstract (in Japanese) (See Japanese page) 
(in English) Reservoir computing (RC) is a machine learning method using nonlinear dynamical systems, which is effective for time-series processing. As a novel method of Natural Computing, various physical phenomena as the nonlinear dynamics have been utilized in the framework of RC so far. However, little is known about information processing performance by RC with spatiotemporal dynamics. In this study, we show that RC using fluid motion as spatiotemporal dynamics is effective for a variety of machine learning tasks including time-series prediction and speech recognition. Moreover, we study a relationship between physical properties of fluid motion and information processing performance, and discuss key issues inherent in the implementation of RC with spatiotemporal dynamics.
Keyword (in Japanese) (See Japanese page) 
(in English) Reservoir computing / Echo state network / Machine learning / Fluid motion / Lyapunov analysis / / /  
Reference Info. IEICE Tech. Rep., vol. 119, no. 485, CCS2019-40, pp. 25-27, March 2020.
Paper # CCS2019-40 
Date of Issue 2020-03-18 (CCS) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
Copyright
and
reproduction
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 CCS2019-40

Conference Information
Committee CCS  
Conference Date 2020-03-25 - 2020-03-26 
Place (in Japanese) (See Japanese page) 
Place (in English) Hosei Univ. Ichigaya Campus 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Natural Computing, etc. 
Paper Information
Registration To CCS 
Conference Code 2020-03-CCS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Reservoir computing using fluid motion 
Sub Title (in English)  
Keyword(1) Reservoir computing  
Keyword(2) Echo state network  
Keyword(3) Machine learning  
Keyword(4) Fluid motion  
Keyword(5) Lyapunov analysis  
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1st Author's Name Keita Kohashi  
1st Author's Affiliation Osaka University (Osaka Univ.)
2nd Author's Name Masanobu Inubushi  
2nd Author's Affiliation Osaka University (Osaka Univ.)
3rd Author's Name Susumu Goto  
3rd Author's Affiliation Osaka University (Osaka Univ.)
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Speaker Author-1 
Date Time 2020-03-26 11:25:00 
Presentation Time 25 minutes 
Registration for CCS 
Paper # CCS2019-40 
Volume (vol) vol.119 
Number (no) no.485 
Page pp.25-27 
#Pages
Date of Issue 2020-03-18 (CCS) 


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