Global asymptotic stability for neural network models with distributed delays

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, w...

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Bibliographic Details
Main Author: Oliveira, José J. (author)
Format: article
Language:eng
Published: 2009
Subjects:
Online Access:http://hdl.handle.net/1822/13164
Country:Portugal
Oai:oai:repositorium.sdum.uminho.pt:1822/13164
Description
Summary: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.