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Paper Abstract and Keywords
Presentation 2019-03-06 10:55
Performance Analysis for Nonlinear Separation Model with a Flexible Approximation
Lu Wang, Tomoaki Ohtsuki (Keio Univ.) RCS2018-292
Abstract (in Japanese) (See Japanese page) 
(in English) The process deals with blind source separation in the nonlinear domain is to estimate the original signals or mixture functions from the degraded signals, without any prior information about the mixing functions. The fundamental problem is to recover the original sources by estimating an approximation function under such assumptions so as to estimate the inverse of mixing functions. However, in practice, the approximation function is derived from some estimation algorithm with a finite sample size that even larger estimation error appears with improper model construction. In this paper, we work on the convergence and asymptotic analysis of the separation approach, where the nonlinearity of the mixture function is extracted by the flexible approximation and the nonlinear problem is solved linearly in the feature space. The analysis stems from the performance of a mismatched estimator that accesses the finite sample size. By providing a closed-form expression of the mean squared error (MSE), we can present a novel algebraic formalization as well as derive an upper bound on the estimation error. The simulation results show that if the nonlinearity of mixing functions can be extracted by the flexible approximation, the consistency of numerical MSE and analytical MSE can be achieved as the sample size tends to be infinity. This implies that the algorithm is feasible to separate the distortion of the nonlinear mixture.
Keyword (in Japanese) (See Japanese page) 
(in English) Nonlinear blind source separation / performance analysis / vanishing component analysis / temporal structure / independent component analysis / / /  
Reference Info. IEICE Tech. Rep., vol. 118, no. 474, RCS2018-292, pp. 61-66, March 2019.
Paper # RCS2018-292 
Date of Issue 2019-02-27 (RCS) 
ISSN Online edition: ISSN 2432-6380
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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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Conference Information
Committee RCS SR SRW  
Conference Date 2019-03-06 - 2019-03-08 
Place (in Japanese) (See Japanese page) 
Place (in English) YRP 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Mobile Communication Workshop 
Paper Information
Registration To RCS 
Conference Code 2019-03-RCS-SR-SRW 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Performance Analysis for Nonlinear Separation Model with a Flexible Approximation 
Sub Title (in English)  
Keyword(1) Nonlinear blind source separation  
Keyword(2) performance analysis  
Keyword(3) vanishing component analysis  
Keyword(4) temporal structure  
Keyword(5) independent component analysis  
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1st Author's Name Lu Wang  
1st Author's Affiliation Keio University (Keio Univ.)
2nd Author's Name Tomoaki Ohtsuki  
2nd Author's Affiliation Keio University (Keio Univ.)
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Speaker Author-1 
Date Time 2019-03-06 10:55:00 
Presentation Time 25 minutes 
Registration for RCS 
Paper # RCS2018-292 
Volume (vol) vol.118 
Number (no) no.474 
Page pp.61-66 
#Pages
Date of Issue 2019-02-27 (RCS) 


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