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Paper Abstract and Keywords
Presentation 2022-11-25 15:15
Towards Defining Minimal Time Series Length for Normalized Recurrence Quantification Analysis
Nina Sviridova, Tohru Ikeguchi (TUS) NLP2022-78
Abstract (in Japanese) (See Japanese page) 
(in English) Estimating the minimal required time series length is an important problem in many applied studies. In our previous study, recurrence quantification analysis applied to the recurrence plot was used to estimate the minimal required length that preserves specific dynamical properties of the biomedical signal. However, recurrence plot size-dependent measures, the longest diagonal line length and the average diagonal line length, were found to be nonapplicable or of limited applicability. In this technical report, these two measures were normalized by the recurrence plot size in an attempt to improve our previous results. Obtained results demonstrated that the normalization would yield an increase in the relative error of the longest diagonal line length and the average diagonal line length estimation. However, these results were obtained for the time series with the longest diagonal line length and the average diagonal line length significantly shorter compared with the maximal recurrent plot size used in this study; therefore, further investigation for the data with longer diagonal lines was found to be necessary.
Keyword (in Japanese) (See Japanese page) 
(in English) nonlinear dynamics / recurrence plot / recurrence quantification analysis / time series length / / / /  
Reference Info. IEICE Tech. Rep., vol. 122, no. 280, NLP2022-78, pp. 97-102, Nov. 2022.
Paper # NLP2022-78 
Date of Issue 2022-11-17 (NLP) 
ISSN 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)
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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 English (Japanese title is available) 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Towards Defining Minimal Time Series Length for Normalized Recurrence Quantification Analysis 
Sub Title (in English)  
Keyword(1) nonlinear dynamics  
Keyword(2) recurrence plot  
Keyword(3) recurrence quantification analysis  
Keyword(4) time series length  
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Keyword(6)  
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1st Author's Name Nina Sviridova  
1st Author's Affiliation Tokyo University of Science (TUS)
2nd Author's Name Tohru Ikeguchi  
2nd Author's Affiliation Tokyo University of Science (TUS)
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Speaker Author-1 
Date Time 2022-11-25 15:15:00 
Presentation Time 25 minutes 
Registration for NLP 
Paper # NLP2022-78 
Volume (vol) vol.122 
Number (no) no.280 
Page pp.97-102 
#Pages 6 
Date of Issue 2022-11-17 (NLP) 

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