Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/349580
Type: Artigo
Title: Blind source separation: fundamentals and perspectives on galois fields and sparse signals
Author: Silva, Daniel
Duarte, Leonardo
Attux, Romis
Abstract: The problem of blind source separation (BSS) has been intensively studied by the signal processing community. The first solutions to deal with BSS were proposed in the 1980's and are founded on the concept of independent component analysis (ICA). More recently, aiming at tackling some limitations of ICA-based methods, much attention has been paid to alternative BSS approaches. In this tutorial, in addition to providing a brief review of the classical BSS framework, we present two research trends in this area, namely source separation over Galois fields and sparse component analysis. For both subjects, we provide an overview of the main criteria, highlighting scenarios that can benefit from these more recent BSS paradigms
Subject: Separação cega de fontes
Country: Brasil
Editor: Sociedade Brasileira de Telecomunicações
Rights: Aberto
Identifier DOI: 10.14209/jcis.2016.16
Address: https://jcis.sbrt.org.br/jcis/article/view/385
Date Issue: 2016
Appears in Collections:FEEC - Artigos e Outros Documentos
FCA - Artigos e Outros Documentos

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