Global exponential stability of nonautonomous neural network models with continuous distributed delays

• Author(s): Esteves, Salete ; Gokmen, Elçin ; Oliveira, José J.
• Date: 2013
• Persistent ID: http://hdl.handle.net/1822/23929
• Origin: RepositóriUM - Universidade do Minho
• Subject(s): Hopfield neural network; BAM neural network; Time-varying coefficient; Distributed time delay; Periodic solution; Global exponential stability; Science & Technology
• Document Type: Journal article
• Language: English
• Contributor(s): Universidade do Minho

Description

For a family of non-autonomous differential equations with distributed delays, we give sufficient conditions for the global exponential stability of an equilibrium point. This family includes most of the delayed models of neural networks of Hopfield type, with time-varying coefficients and distributed delays. For these models, we establish sufficient conditions for their global exponential stability. The existence and global exponential stability of a periodic solution is also addressed. A comparison of results shows that these results are general, news, and add something new to some earlier publications.

Fundação para a Ciência e a Tecnologia (FCT)