Artículos de revistas
A Michigan-like immune-inspired framework for performing independent component analysis over Galois fields of prime order
Registro en:
Signal Processing. Elsevier Science Bv, v. 96, n. 153, n. 163, 2014.
0165-1684
1879-2677
WOS:000330203500003
10.1016/j.sigpro.2013.09.004
Autor
Silva, DG
Nadalin, EZ
Coelho, GP
Duarte, LT
Suyama, R
Attux, R
Von Zuben, FJ
Montalvao, J
Institución
Resumen
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) 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. 96 B 153 163 Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)