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| Presentation | 2022-08-25 14:15 Multiresolution Convolutional-Sparse-Coded Dynamic Mode Decomposition and Its Application to Riverbed State Estimation Eisuke Kobayashi, Shogo Muramatsu, Hiroyasu Yasuda, Kiyoshi Hayasaka (Niigata Univ.)  SIP2022-54 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | In this report, we propose a method that incorporates multi-resolution representation into Convolutional-Sparse-Coded Dynamic Mode Decomposition (CSC-DMD). CSC-DMD is a time series analysis method that introduces a learnable convolutional dictionary into extended dynamic mode decomposition (EDMD), and its effectiveness has been confirmed in a previous study by applying it to riverbed condition estimation. However, the simultaneous representation of spatial global and local changes remained an issue. In this study, we propose a multi-resolution extension of the convolutional dictionary of CSC-DMD. We confirm the effectiveness of the proposed method using time series data obtained from an experimental river model. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Multiresolution analysis / Convolutional dictionary learning / Extended dynamic mode decomposition / Time-series data analysis / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 122, no. 165, SIP2022-54, pp. 25-30, Aug. 2022. | |
| Paper # | SIP2022-54 | |
| Date of Issue | 2022-08-18 (SIP) | |
| 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 | SIP2022-54 |
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| Conference Information | |
| Committee | SIP |
| Conference Date | 2022-08-25 - 2022-08-26 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Nobumoto Ohama Memorial Hall (Ishigaki Island) |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Signal processing, etc. |
| Paper Information | |
| Registration To | SIP |
| Conference Code | 2022-08-SIP |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Multiresolution Convolutional-Sparse-Coded Dynamic Mode Decomposition and Its Application to Riverbed State Estimation |
| Sub Title (in English) | |
| Keyword(1) | Multiresolution analysis |
| Keyword(2) | Convolutional dictionary learning |
| Keyword(3) | Extended dynamic mode decomposition |
| Keyword(4) | Time-series data analysis |
| Keyword(5) | |
| Keyword(6) | |
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| Keyword(8) | |
| 1st Author's Name | Eisuke Kobayashi |
| 1st Author's Affiliation | Niigata University (Niigata Univ.) |
| 2nd Author's Name | Shogo Muramatsu |
| 2nd Author's Affiliation | Niigata University (Niigata Univ.) |
| 3rd Author's Name | Hiroyasu Yasuda |
| 3rd Author's Affiliation | Niigata University (Niigata Univ.) |
| 4th Author's Name | Kiyoshi Hayasaka |
| 4th Author's Affiliation | Niigata University (Niigata Univ.) |
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| Speaker | Author-1 |
| Date Time | 2022-08-25 14:15:00 |
| Presentation Time | 18 minutes |
| Registration for | SIP |
| Paper # | SIP2022-54 |
| Volume (vol) | vol.122 |
| Number (no) | no.165 |
| Page | pp.25-30 |
| #Pages | 6 |
| Date of Issue | 2022-08-18 (SIP) |
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