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Paper Abstract and Keywords
Presentation 2017-10-22 09:00
[Invited Talk] Blind source separation based on independent low-rank matrix analysis
Daichi Kitamura (UT), Nobutaka Ono (NII), Hiroshi Sawada, Hirokazu Kameoka (NTT), Hiroshi Saruwatari (UT) EA2017-56
Abstract (in Japanese) (See Japanese page) 
(in English) In this paper, we propose a new effective algorithm for blind source separation problem (BSS) called independent low-rank matrix analysis (ILRMA). ILRMA is a unified method of independent vector analysis (IVA) and nonnegative matrix factorization (NMF) and can be interpreted as a natural extension of the source separation theory based on statistical independence. Also, ILRMA is identical to a special case of multichannel NMF (MNMF), and this fact reveals the relationship between the state-of-the-art BSS techniques including IVA and MNMF.
Keyword (in Japanese) (See Japanese page) 
(in English) blind source separation / independent component analysis / nonnegative matrix factorization / / / / /  
Reference Info. IEICE Tech. Rep., vol. 117, no. 255, EA2017-56, pp. 73-80, Oct. 2017.
Paper # EA2017-56 
Date of Issue 2017-10-14 (EA) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
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. (No. 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF EA2017-56

Conference Information
Committee EA ASJ-H  
Conference Date 2017-10-21 - 2017-10-22 
Place (in Japanese) (See Japanese page) 
Place (in English) Ushidake-Onsen 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Beginners Session(Engineering/Electro Acoustics, Psychological and Physiological Acoustics, and Related Topics) 
Paper Information
Registration To EA 
Conference Code 2017-10-EA-H 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Blind source separation based on independent low-rank matrix analysis 
Sub Title (in English)  
Keyword(1) blind source separation  
Keyword(2) independent component analysis  
Keyword(3) nonnegative matrix factorization  
1st Author's Name Daichi Kitamura  
1st Author's Affiliation The University of Tokyo (UT)
2nd Author's Name Nobutaka Ono  
2nd Author's Affiliation National Institute of Informatics (NII)
3rd Author's Name Hiroshi Sawada  
3rd Author's Affiliation Nippon Telegraph and Telephone Corporation (NTT)
4th Author's Name Hirokazu Kameoka  
4th Author's Affiliation Nippon Telegraph and Telephone Corporation (NTT)
5th Author's Name Hiroshi Saruwatari  
5th Author's Affiliation The University of Tokyo (UT)
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Date Time 2017-10-22 09:00:00 
Presentation Time 60 
Registration for EA 
Paper # IEICE-EA2017-56 
Volume (vol) IEICE-117 
Number (no) no.255 
Page pp.73-80 
#Pages IEICE-8 
Date of Issue IEICE-EA-2017-10-14 

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