General criteria for asymptotic and exponential stabilities of neural network models with unbounded delays

General criteria for asymptotic and exponential stabilities of neural network models with unbounded delays

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Article ID: iaor20116401
Volume: 217
Issue: 23
Start Page Number: 9646
End Page Number: 9658
Publication Date: Aug 2011
Journal: Applied Mathematics and Computation
Authors: ,
Keywords: simulation, differential equations, optimization
Abstract:

For a family of differential equations with infinite delay, we give sufficient conditions for the global asymptotic, and global exponential stability of an equilibrium point. This family includes most of the delayed models of neural networks of Cohen–Grossberg type, with both bounded and unbounded distributed delay, for which general asymptotic and exponential stability criteria are derived. As illustrations, the results are applied to several concrete models studied in the literature, and a comparison of results is given.

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