Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/92559
Type: Artigo de evento
Title: Blind Source Separation Of Post-nonlinear Mixtures Using Evolutionary Computation And Gaussianization
Author: Dias T.M.
Attux R.
Romano J.M.T.
Suyama R.
Abstract: In this work, we propose a new method for source separation of post- nonlinear mixtures that combines evolutionary-based global search, gaussianization and a local search step based on FastICA algorithm. The rationale of the proposal is to attempt to obtain efficient and precise solutions using with parsimony the available computational resources, and, as shown by the simulation results, this aim was satisfactorily fulfilled. © Springer-Verlag Berlin Heidelberg 2009.
Editor: 
Rights: fechado
Identifier DOI: 10.1007/978-3-642-00599-2_30
Address: http://www.scopus.com/inward/record.url?eid=2-s2.0-67149123465&partnerID=40&md5=994b81852833757bbaf7f574f313a544
Date Issue: 2009
Appears in Collections:Unicamp - Artigos e Outros Documentos

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