Paper Abstract and Keywords |
Presentation |
2021-06-04 11:45
Frequency-domain Robust Principal Component Analysis Manabu Sueyasu, Seisuke Kyochi (The Univ. of Kitakyushu), Shunsuke Ono (Tokyo Tech) SIP2021-10 BioX2021-10 IE2021-10 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Low-rank modeling is one of the most effective approaches that can analyze and extract isomorphic components from an observation matrix. Robust PCA (RPCA) can extract isomorphic components lying a low-dimensional subspace from an observed matrix in the presence of outliers by using regularization functions of nuclear/l1 norms. One of the drawback of RPCA is the sensitivity against the shift or the misalignment of target components. When target components are not aligned exactly due the shift, they are not lying low-dimensional subspace any more. Consequently, RPCA cannot extract the isomorphic components precisely. To resolve this drawback, we propose a novel regularizer called “amplitude spectrum nuclear norm” (ASNN). Thanks to the fundamental signal processing theory, the amplitude spectra of an original and its (circularly) shifted signals are the same. Thus, we can extract misaligned isomorphic components by minimizing nuclear norm of the amplitude spectra. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
amplitude spectrogram / epigraph constraint / low rank / nuclear norm / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 121, no. 54, SIP2021-10, pp. 46-50, June 2021. |
Paper # |
SIP2021-10 |
Date of Issue |
2021-05-27 (SIP, BioX, IE) |
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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SIP2021-10 BioX2021-10 IE2021-10 |
Conference Information |
Committee |
IE SIP BioX ITE-IST ITE-ME |
Conference Date |
2021-06-03 - 2021-06-04 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Online |
Topics (in Japanese) |
(See Japanese page) |
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Paper Information |
Registration To |
SIP |
Conference Code |
2021-06-IE-SIP-BioX-IST-ME |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Frequency-domain Robust Principal Component Analysis |
Sub Title (in English) |
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Keyword(1) |
amplitude spectrogram |
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epigraph constraint |
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low rank |
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nuclear norm |
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1st Author's Name |
Manabu Sueyasu |
1st Author's Affiliation |
The University of Kitakyushu (The Univ. of Kitakyushu) |
2nd Author's Name |
Seisuke Kyochi |
2nd Author's Affiliation |
The University of Kitakyushu (The Univ. of Kitakyushu) |
3rd Author's Name |
Shunsuke Ono |
3rd Author's Affiliation |
Tokyo Institute of Technology (Tokyo Tech) |
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Speaker |
Author-1 |
Date Time |
2021-06-04 11:45:00 |
Presentation Time |
30 minutes |
Registration for |
SIP |
Paper # |
SIP2021-10, BioX2021-10, IE2021-10 |
Volume (vol) |
vol.121 |
Number (no) |
no.54(SIP), no.55(BioX), no.56(IE) |
Page |
pp.46-50 |
#Pages |
5 |
Date of Issue |
2021-05-27 (SIP, BioX, IE) |
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