Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/76062
Type: Artigo
Title: A Michigan-like immune-inspired framework for performing independent component analysis over Galois fields of prime order
Author: Silva, Daniel G.
Nadalin, Everton Z.
Coelho, Guilherme P.
Duarte, Leonardo T.
Suyama, Ricardo
Attux, Romis
Von Zuben, Fernando J.
Montalvão, Jugurta
Abstract: In this work, we present a novel bioinspired framework for performing ICA over finite (Galois) fields of prime order P. The proposal is based on a state-of-the-art immune-inspired algorithm, the cob-aiNet[C], which is employed to solve a combinatorial optimization problem associated with a minimal entropy configuration adopting a Michigan-like population structure. The simulation results reveal that the strategy is capable of reaching a performance similar to that of standard methods for lower-dimensional instances with the advantage of also handling scenarios with an elevated number of sources. (C) 2013 Elsevier B.V. All rights reserved.
In this work, we present a novel bioinspired framework for performing ICA over finite (Galois) fields of prime order P. The proposal is based on a state-of-the-art immune-inspired algorithm, the cob-aiNet[C], which is employed to solve a combinatorial opt
Subject: Sistema imunológico
Country: Países Baixos
Editor: Elsevier
Citation: Signal Processing. Elsevier Science Bv, v. 96, n. 153, n. 163, 2014.
Rights: fechado
fechado
Identifier DOI: 10.1016/j.sigpro.2013.09.004
Address: https://www.sciencedirect.com/science/article/pii/S0165168413003472
Date Issue: 2014
Appears in Collections:FEEC - Artigos e Outros Documentos
FCA - Artigos e Outros Documentos
FT - Artigos e Outros Documentos

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