Métodos de análise da robustez de redes neurais artificiais sujeitas a retardo no tempo

• Ano de defesa: 2005
• Autor(a) principal: Fernando de Oliveira Souza
• Outros Autores: Reinaldo Martinez Palhares
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Minas Gerais; UFMG
• Palavras-chave em Português: Retardo no tempo; Redes neurais; Estabilidade robusta; Engenharia elétrica
• Link de acesso: http://hdl.handle.net/1843/RMPS-6JTHS8

This work presents sufficient conditions for analysis of asymptotic and exponential stability of a class of artificial neural network (ANN) subject to constant or timevarying delays and polytope-bounded uncertainties.The approaches proposed is the type of delay-dependent and the methodology is based on four points: the selection of slack matrices that express the influence of the Newton-Leibniz condition; the appropriate definition of Lyapunov-Krasovskii functionals; the use of linear matrix inequalities (LMIs) and the use of tools of convex optimization to solve problems described in LMI terms. Several examples are presented that corroborate with the theory presented of analysis of the stability of ANN with time-varying delay.