Titre:	Immune-inspired optimization with autocorrentropy function for blind inversion of wiener systems
Auteur(s):	Fernandez, Stephanie A. Fantinato, Denis G. Montalvão, Jugurta Attux, Romis Silva, Daniel Guerreiro e
Assunto::	Sistemas não-lineares Framework
Date de publication:	2018
Référence bibliographique:	FERNANDEZ, Stephanie A. et al. Immune-inspired optimization with autocorrentropy function for blind inversion of wiener systems. In: IEEE WORLD CONGRESS ON COMPUTATIONAL INTELLIGENCE - WCCI 2018, 2018, Rio Janeiro.
Abstract:	Blind inversion of nonlinear systems is a complex task that requires some sort of prior information about the source e.g. whether it is composed of independent samples or, particularly in this work, a dependence “signature” which is assumed to be known via the autocorrentropy function. Furthermore, it involves the solution of a nonlinear, multimodal optimization problem to determine the parameters of the inverse model. Thus, we propose a blind method for Wiener systems inversion, which is composed of a correntropy-based criterion in association to the well-known CLONALG immune-inspired optimization metaheuristic. The empirical results validate the methodology for continuous and discrete signals.
metadata.dc.description.unidade:	Faculdade de Tecnologia (FT) Departamento de Engenharia Elétrica (FT ENE)
Licença::	Autorização concedida ao Repositório Institucional da Universidade de Brasília (RIUnB) pelo Prof. Daniel Guerreiro e Silva, em 29 de janeiro de 2019, para disponibilizar o trabalho, gratuitamente, para fins de leitura, impressão e/ou download, a título de divulgação da obra.
Collection(s) :	Trabalhos apresentados em evento

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