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Paper Abstract and Keywords
Presentation 2016-01-18 10:10
Effectiveness of L1 Regularization for Sparse Impulse Response Estimation Using colored Noise
Keito Kito, Ryo Tanaka, Takahiro Murakami (Meiji Univ.) IT2015-58 SIP2015-72 RCS2015-290
Abstract (in Japanese) (See Japanese page) 
(in English) In this paper, we show an effectiveness of L1 regularization for a sparse impulse response estimation using a colored noise.
When an impulse response is estimated, a model to be estimated is modeled using a white noise as an input signal.
However, in practice, the noise is not an exact white noise due to an influence of frequency characteristics of measurement instruments.
Therefore, a technique that estimates an accurate impulse response using a colored noise is required.
When the colored noise is used as the input signal, the performance of the impulse response estimation using the second order statistics such as the MSE (Mean Square Error) algorithm is degraded.
Then, we apply the negentropy and the L1-norm to the impulse response estimation. By maximizing the negentropy, the performance of estimation is improved in terms of the probability distribution.
By minimising the L1-norm, the performance of estimation is improved in terms of sparsity of the impulse response.
In the proposed method, we use the FOBOS (Forward Backward Splitting) algorithm to optimize the negentropy and the L1-norm.
Keyword (in Japanese) (See Japanese page) 
(in English) impulse response / independent component analysis / negentropy / sparsity / L1 regularization / FOBOS / /  
Reference Info. IEICE Tech. Rep., vol. 115, no. 395, SIP2015-72, pp. 61-66, Jan. 2016.
Paper # SIP2015-72 
Date of Issue 2016-01-11 (IT, 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 IT2015-58 SIP2015-72 RCS2015-290

Conference Information
Committee RCS IT SIP  
Conference Date 2016-01-18 - 2016-01-19 
Place (in Japanese) (See Japanese page) 
Place (in English) Kwansei Gakuin Univ. Osaka Umeda Campus 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Signal Processing for Wireless Communications, Learning, Mathematical Science, Communication Theory, etc. 
Paper Information
Registration To SIP 
Conference Code 2016-01-RCS-IT-SIP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Effectiveness of L1 Regularization for Sparse Impulse Response Estimation Using colored Noise 
Sub Title (in English)  
Keyword(1) impulse response  
Keyword(2) independent component analysis  
Keyword(3) negentropy  
Keyword(4) sparsity  
Keyword(5) L1 regularization  
Keyword(6) FOBOS  
Keyword(7)  
Keyword(8)  
1st Author's Name Keito Kito  
1st Author's Affiliation Meiji University (Meiji Univ.)
2nd Author's Name Ryo Tanaka  
2nd Author's Affiliation Meiji University (Meiji Univ.)
3rd Author's Name Takahiro Murakami  
3rd Author's Affiliation Meiji University (Meiji Univ.)
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Speaker Author-1 
Date Time 2016-01-18 10:10:00 
Presentation Time 25 minutes 
Registration for SIP 
Paper # IT2015-58, SIP2015-72, RCS2015-290 
Volume (vol) vol.115 
Number (no) no.394(IT), no.395(SIP), no.396(RCS) 
Page pp.61-66 
#Pages 6 
Date of Issue 2016-01-11 (IT, SIP, RCS) 

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