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| Presentation | 2013-02-01 10:50 Sampling and Recovery of Continuous Sparse Signals by Maximum Likelihood Estimation Yosuke Hironaga, Akira Hirabayashi (Yamaguchi Univ.), Laurent Condat (Grenoble INP)  SIP2012-102 RCS2012-259 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | We propose a maximum likelihood estimation approach for the recovery of continuously-defined sparse signals from noisy measurements, in particular periodic sequences of derivatives of Diracs and piecewise polynomials. The conventional approach for this problem is based on total-least-squares (a.k.a. annihilating filter method) and Cadzow denoising. It requires more measurements than the number of unknown parameters and mistakenly splits the derivatives of Diracs into several Diracs at different positions. Further on, Cadzow denoising does not guarantee any optimality. The proposed parametric approach solves all of these problems by defining an appropriate likelihood function. Since the likelihood function is non-convex, we exploit the stochastic method of particle swarm optimization (PSO) to find the global solution. Simulation results confirm the effectiveness of the proposed approach, for a reasonable cost. |
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| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Signals with finite rate of innovation / derivative of Diracs / piecewise polynomials / maximum likelihood estimation / Cadzow denoising / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 112, no. 423, SIP2012-102, pp. 127-132, Jan. 2013. | |
| Paper # | SIP2012-102 | |
| Date of Issue | 2013-01-24 (SIP, RCS) | |
| ISSN | Print edition: ISSN 0913-5685 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 | SIP2012-102 RCS2012-259 |
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| Conference Information | |
| Committee | SIP RCS |
| Conference Date | 2013-01-31 - 2013-02-01 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Viewport-Kure-Hotel (Kure) |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | SIP |
| Conference Code | 2013-01-SIP-RCS |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Sampling and Recovery of Continuous Sparse Signals by Maximum Likelihood Estimation |
| Sub Title (in English) | |
| Keyword(1) | Signals with finite rate of innovation |
| Keyword(2) | derivative of Diracs |
| Keyword(3) | piecewise polynomials |
| Keyword(4) | maximum likelihood estimation |
| Keyword(5) | Cadzow denoising |
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| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Yosuke Hironaga |
| 1st Author's Affiliation | Yamaguchi University (Yamaguchi Univ.) |
| 2nd Author's Name | Akira Hirabayashi |
| 2nd Author's Affiliation | Yamaguchi University (Yamaguchi Univ.) |
| 3rd Author's Name | Laurent Condat |
| 3rd Author's Affiliation | Grenoble Institute of Technology (Grenoble INP) |
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| Speaker | Author-2 |
| Date Time | 2013-02-01 10:50:00 |
| Presentation Time | 25 minutes |
| Registration for | SIP |
| Paper # | SIP2012-102, RCS2012-259 |
| Volume (vol) | vol.112 |
| Number (no) | no.423(SIP), no.424(RCS) |
| Page | pp.127-132 |
| #Pages | 6 |
| Date of Issue | 2013-01-24 (SIP, RCS) |
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