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| Presentation | 2020-09-10 10:30 On Investigation of Invariant Characteristics of Deterministic Nonlinear Dynamical Systems and Marked Point Processes Kazuya Sawada (TUS), Yutaka Shimada (Saitama Univ.), Tohru Ikeguchi (TUS)  NLP2020-22 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | In recent years, various kinds of time series data have been observed. One of the kinds is a marked point process. For example, stock trading and seismic data are typical examples of marked point process. Although various stochastic methods for generating marked point processes have been proposed, a method for generating marked point processes that follows deterministic dynamics has not been sufficiently discussed. One of the methods for generating marked point processes according to deterministic dynamics is to extract maxima of observed time series produced from a nonlinear dynamical system. In this article, we investigate whether the marked point processes generated from the nonlinear deterministic dynamical system by the maximum extraction preserve the characteristics of the original dynamical system. To evaluate the characteristics of the dynamical system, we used KL and JS divergence of the distribution of distance between two points on attractors of the original dynamical system and the marked point process. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | point process / marked point process / KL divergence / JS divergence / Lorenz equation / Izhikevich neuron model / / | |
| Reference Info. | IEICE Tech. Rep., vol. 120, no. 165, NLP2020-22, pp. 1-6, Sept. 2020. | |
| Paper # | NLP2020-22 | |
| Date of Issue | 2020-09-03 (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) | |
| Download PDF | NLP2020-22 |
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| Conference Information | |
| Committee | NLP |
| Conference Date | 2020-09-10 - 2020-09-10 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | etc. |
| Paper Information | |
| Registration To | NLP |
| Conference Code | 2020-09-NLP |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | On Investigation of Invariant Characteristics of Deterministic Nonlinear Dynamical Systems and Marked Point Processes |
| Sub Title (in English) | |
| Keyword(1) | point process |
| Keyword(2) | marked point process |
| Keyword(3) | KL divergence |
| Keyword(4) | JS divergence |
| Keyword(5) | Lorenz equation |
| Keyword(6) | Izhikevich neuron model |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Kazuya Sawada |
| 1st Author's Affiliation | Tokyo University of Science (TUS) |
| 2nd Author's Name | Yutaka Shimada |
| 2nd Author's Affiliation | Saitama University (Saitama Univ.) |
| 3rd Author's Name | Tohru Ikeguchi |
| 3rd Author's Affiliation | Tokyo University of Science (TUS) |
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| Speaker | Author-1 |
| Date Time | 2020-09-10 10:30:00 |
| Presentation Time | 25 minutes |
| Registration for | NLP |
| Paper # | NLP2020-22 |
| Volume (vol) | vol.120 |
| Number (no) | no.165 |
| Page | pp.1-6 |
| #Pages | 6 |
| Date of Issue | 2020-09-03 (NLP) |
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