NDLI: A new method for kurtosis maximization and source separation

Content Provider	IEEE Xplore Digital Library
Author	Castella, M. Moreau, E.
Copyright Year	2010
Description	Author affiliation: University of Sud Toulon Var, ISITV, LSEET UMR-CNRS 6017, av. G. Pompidou, BP56, 83162 La Valette du Var Cedex, France (Moreau, E.) \|\| Institut TELECOM; TELECOM SudParis, Département CITI; UMR-CNRS 5157, 9 rue Charles Fourier, 91011 Evry Cedex, France (Castella, M.)
Abstract	This paper introduces a new method to maximize kurtosis-based contrast functions. Such contrast functions appear in the problem of blind source separation of convolutivelymixed sources: the corresponding methods recover the sources one by one using a deflation approach. The proposed maximization algorithm is based on the particular nature of the criterion. The method is similar in spirit to a gradient ascent method, but differs in the fact that a “reference” contrast function is considered at each line search. The convergence of the method to a stationary point of the criterion can be proved. The theoretical result is illustrated by simulation.
Starting Page	2670
Ending Page	2673
File Size	212618
Page Count	4
File Format	PDF
ISBN	9781424442959
ISSN	15206149
DOI	10.1109/ICASSP.2010.5496250
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-03-14
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Source separation Blind source separation Telecommunications Reactive power Convergence Optimization methods Filters Higher order statistics Iterative methods Particle separators Blind Source Separation Contrast Function Deflation Higher-Order Statistics Reference System Optimization
Content Type	Text
Resource Type	Article

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