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Paper Abstract and Keywords
Presentation 2022-11-24 10:45
Quantifying the dynamical instability of complex time series based on information entropy
Kota Shiozawa, Isao Tokuda (Ritsumeikan Univ.) NLP2022-57
Abstract (in Japanese) (See Japanese page) 
(in English) Various methods based on information entropy have been proposed to quantify the complexity of time series. One of the most common methods is the permutation entropy proposed by Bandt and Pompe. Their method has been widely used in many fields such as physiology and mechanical engineering. Although the usefulness of information entropy-based methods, it is not straightforward to interpret the obtained results since the relationship between these complexity measures and the dynamical quantities is unclear. In this paper, we extend the existing methods and propose a complexity measure which has a clear link to the dynamical quantities and can be easily interpreted.
Keyword (in Japanese) (See Japanese page) 
(in English) Time Series Analysis / Chaos / Lyapunov Exponent / Information Entropy / Permutation Entropy / / /  
Reference Info. IEICE Tech. Rep., vol. 122, no. 280, NLP2022-57, pp. 5-8, Nov. 2022.
Paper # NLP2022-57 
Date of Issue 2022-11-17 (NLP) 
ISSN Online edition: ISSN 2432-6380
Copyright
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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)
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Conference Information
Committee NLP  
Conference Date 2022-11-24 - 2022-11-25 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To NLP 
Conference Code 2022-11-NLP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Quantifying the dynamical instability of complex time series based on information entropy 
Sub Title (in English)  
Keyword(1) Time Series Analysis  
Keyword(2) Chaos  
Keyword(3) Lyapunov Exponent  
Keyword(4) Information Entropy  
Keyword(5) Permutation Entropy  
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Keyword(7)  
Keyword(8)  
1st Author's Name Kota Shiozawa  
1st Author's Affiliation Ritsumeikan University (Ritsumeikan Univ.)
2nd Author's Name Isao Tokuda  
2nd Author's Affiliation Ritsumeikan University (Ritsumeikan Univ.)
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Speaker Author-1 
Date Time 2022-11-24 10:45:00 
Presentation Time 25 minutes 
Registration for NLP 
Paper # NLP2022-57 
Volume (vol) vol.122 
Number (no) no.280 
Page pp.5-8 
#Pages
Date of Issue 2022-11-17 (NLP) 


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