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|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.
Von Zuben, Fernando 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.|
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
|Citation:||Signal Processing. Elsevier Science Bv, v. 96, n. 153, n. 163, 2014.|
|Appears in Collections:||FEEC - Artigos e Outros Documentos|
FCA - Artigos e Outros Documentos
FT - Artigos e Outros Documentos
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