Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/92566
Type: Artigo de evento
Title: An Ica-based Method For Blind Source Separation In Sparse Domains
Author: Nadalin E.Z.
Suyama R.
Attux R.
Abstract: In this work, we propose and analyze a method to solve the problem of underdetermined blind source separation (and identification) that employs the ideas of sparse component analysis (SCA) and independent component analysis (ICA). The main rationale of the approach is to allow the possibility of reaching a method that is more robust with respect to the degree of sparseness of the involved signals and more effective in the use of information brought by multiple sensors. The ICA-based solution is tested with the aid of three representative scenarios and its performance is compared with that of one of the soundest SCA techniques available, the DEMIXN algorithm. © Springer-Verlag Berlin Heidelberg 2009.
Editor: 
Rights: fechado
Identifier DOI: 10.1007/978-3-642-00599-2_75
Address: http://www.scopus.com/inward/record.url?eid=2-s2.0-67149103690&partnerID=40&md5=eb0f59ca9c6bc9abd15f11880dc9c6de
Date Issue: 2009
Appears in Collections:Unicamp - Artigos e Outros Documentos

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