| DC Field | Value | Language |
|---|
| dc.contributor.author | Fernandez, Stephanie A. | - |
| dc.contributor.author | Fantinato, Denis G. | - |
| dc.contributor.author | Montalvão, Jugurta | - |
| dc.contributor.author | Attux, Romis | - |
| dc.contributor.author | Silva, Daniel Guerreiro e | - |
| dc.date.accessioned | 2019-01-30T15:10:40Z | - |
| dc.date.available | 2019-01-30T15:10:40Z | - |
| dc.date.issued | 2018 | - |
| dc.identifier.citation | 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. | pt_BR |
| dc.identifier.uri | http://repositorio.unb.br/handle/10482/33879 | - |
| dc.language.iso | Inglês | pt_BR |
| dc.rights | Acesso Aberto | pt_BR |
| dc.title | Immune-inspired optimization with autocorrentropy function for blind inversion of wiener systems | pt_BR |
| dc.type | Trabalho | pt_BR |
| dc.subject.keyword | Sistemas não-lineares | pt_BR |
| dc.subject.keyword | Framework | pt_BR |
| dc.rights.license | 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. | pt_BR |
| dc.description.abstract1 | 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. | pt_BR |
| Appears in Collections: | ENE - Trabalhos apresentados em eventos
|
