Global stability of a Cohen-Grossberg neural network with both time-varying and continuous distributed delays

In this paper, a generalized neural network of Cohen-Grossberg type with both discrete time-varying and distributed unbounded delays is considered. Based on M-matrix theory, sufficient conditions are established to ensure the existence and global attractivity of an equilibrium point. The global expo...

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Detalhes bibliográficos
Autor principal: Oliveira, José J. (author)
Formato: article
Idioma:eng
Publicado em: 2011
Assuntos:
Texto completo:http://hdl.handle.net/1822/13163
País:Portugal
Oai:oai:repositorium.sdum.uminho.pt:1822/13163
Descrição
Resumo:In this paper, a generalized neural network of Cohen-Grossberg type with both discrete time-varying and distributed unbounded delays is considered. Based on M-matrix theory, sufficient conditions are established to ensure the existence and global attractivity of an equilibrium point. The global exponential stability of the equilibrium is also addressed, but for the model with bounded discrete time-varying delays. A comparison of results shows that these results generalize and improve some earlier publications.