Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/87846
Type: Artigo de periódico
Title: A Michigan-like Immune-inspired Framework For Performing Independent Component Analysis Over Galois Fields Of Prime Order
Author: Silva D.G.
Nadalin E.Z.
Coelho G.P.
Duarte L.T.
Suyama R.
Attux R.
Von Zuben F.J.
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. © 2013 Elsevier B.V.
Editor: 
Rights: fechado
Identifier DOI: 10.1016/j.sigpro.2013.09.004
Address: http://www.scopus.com/inward/record.url?eid=2-s2.0-84887297276&partnerID=40&md5=5066f6b0eb0869e559bf2432d930ec90
Date Issue: 2014
Appears in Collections:Unicamp - Artigos e Outros Documentos

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