Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/76062
Type: Artigo de periódico
Title: A Michigan-like immune-inspired framework for performing independent component analysis over Galois fields of prime order
Author: Silva, DG
Nadalin, EZ
Coelho, GP
Duarte, LT
Suyama, R
Attux, R
Von Zuben, FJ
Montalvao, J
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.
Subject: ICA
Galois field
Artificial Immune Systems
Cob-aiNet[C]
Country: Holanda
Editor: Elsevier Science Bv
Rights: fechado
Identifier DOI: 10.1016/j.sigpro.2013.09.004
Date Issue: 2014
Appears in Collections:Unicamp - Artigos e Outros Documentos

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