Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/95421
Type: Artigo de periódico
Title: Aplicacao Da Rede De Hopfield Na Estimacao Robusta De Regioes De Pertinencia Parametrica Para Modelos Lineares
Author: da Silva Ivan Nunes
de Arruda Lucia Valeria Ramos
do Amaral Wagner Caradori
Abstract: This paper is concerned with the robust identification of linear model when the modeling error is assumed bounded. A modified Hopfield's Neural Network is developed to calculate a membership set for the model parameters. The valid-subspace technique is applied to obtain the internal parameters of the Hopfield's Neural Network. These parameters are explicitly computed to assure the network convergence. In this case, the equilibrium point represents a solution to robust estimation problem with unknown-but-bounded error. A comparative analysis with other robust estimation approaches is carried out by simulation examples.
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Rights: aberto
Identifier DOI: 
Address: http://www.scopus.com/inward/record.url?eid=2-s2.0-0030233929&partnerID=40&md5=0d9559db424ad68be7c62753dfbed25b
Date Issue: 1996
Appears in Collections:Unicamp - Artigos e Outros Documentos

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