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Paper Abstract and Keywords
Presentation 2015-07-18 15:50
Analysis of a chaotic time series using connection weight vectors of neural networks
Masatake Akutagawa, Takahiro Kinouchi, Takahiro Emoto, Hirofumi Nagashino, Shinsuke Konaka, Yohsuke Kinouchi (Tokushima Univ.) MBE2015-24
Abstract (in Japanese) (See Japanese page) 
(in English) A method to analyze a time series to quantify change of internal state of a non-linear system is introduced. A multi-layered neural network is trained to embed a model of the system from given time series. The state is considered to be embedded as a connection weight vector in the neural network. The change of the state is able to be quantified from the connection weight vectors. Generally, the sensitivity of the measure becomes lower because the dimension of the connection weight is high. To avoid this concentration of the measure phenomenon, dimension of the connection weight vector is compressed by the principal component analysis. As result of them, we confirmed applicability of the proposed method for the Ikeda map, which generates chaotic time series.
Keyword (in Japanese) (See Japanese page) 
(in English) time series / neural network / FNN / PCA / Ikeda map / / /  
Reference Info. IEICE Tech. Rep., vol. 115, no. 147, MBE2015-24, pp. 23-28, July 2015.
Paper # MBE2015-24 
Date of Issue 2015-07-11 (MBE) 
ISSN Print edition: ISSN 0913-5685    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)
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Conference Information
Committee MBE NC  
Conference Date 2015-07-18 - 2015-07-18 
Place (in Japanese) (See Japanese page) 
Place (in English) The University of Tokushima 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Me, general 
Paper Information
Registration To MBE 
Conference Code 2015-07-MBE-NC 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Analysis of a chaotic time series using connection weight vectors of neural networks 
Sub Title (in English)  
Keyword(1) time series  
Keyword(2) neural network  
Keyword(3) FNN  
Keyword(4) PCA  
Keyword(5) Ikeda map  
1st Author's Name Masatake Akutagawa  
1st Author's Affiliation Tokushima University (Tokushima Univ.)
2nd Author's Name Takahiro Kinouchi  
2nd Author's Affiliation Tokushima University (Tokushima Univ.)
3rd Author's Name Takahiro Emoto  
3rd Author's Affiliation Tokushima University (Tokushima Univ.)
4th Author's Name Hirofumi Nagashino  
4th Author's Affiliation Tokushima University (Tokushima Univ.)
5th Author's Name Shinsuke Konaka  
5th Author's Affiliation Tokushima University (Tokushima Univ.)
6th Author's Name Yohsuke Kinouchi  
6th Author's Affiliation Tokushima University (Tokushima Univ.)
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Speaker Author-1 
Date Time 2015-07-18 15:50:00 
Presentation Time 25 minutes 
Registration for MBE 
Paper # MBE2015-24 
Volume (vol) vol.115 
Number (no) no.147 
Page pp.23-28 
Date of Issue 2015-07-11 (MBE) 

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