Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/13164
Título: | Global asymptotic stability for neural network models with distributed delays |
Autor(es): | Oliveira, José J. |
Palavras-chave: | Delayed neural network models Distributed delays Time-varing delays Global asymptotic stability M-matrix Time-varying delays |
Data: | Jul-2009 |
Editora: | Elsevier |
Revista: | Mathematical and Computer Modelling |
Resumo(s): | In this paper, we obtain the global asymptotic stability of the zero solution of a general n-dimensional delayed differential system, by imposing a condition of dominance of the nondelayed terms which cancels the delayed effect. We consider several delayed differential systems in general settings, which allow us to study, as subclasses, the well known neural network models of Hopfield, Cohn-Grossberg, bidirectional associative memory, and static with S-type distributed delays. For these systems, we establish sufficient conditions for the existence of a unique equilibrium and its global asymptotic stability, without using the Lyapunov functional technique. Our results improve and generalize some existing ones. |
Tipo: | Artigo |
URI: | https://hdl.handle.net/1822/13164 |
DOI: | 10.1016/j.mcm.2009.02.002 |
ISSN: | 0895-7177 |
Versão da editora: | http://www.sciencedirect.com |
Arbitragem científica: | yes |
Acesso: | Acesso aberto |
Aparece nas coleções: | CMAT - Artigos em revistas com arbitragem / Papers in peer review journals |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
---|---|---|---|---|
neural_jo.pdf | Documento principal | 201,08 kB | Adobe PDF | Ver/Abrir |