Stability of Delayed Reaction-Diffusion High-Order Cohen-Grossberg Neural Networks with Variable Coefficient

Author

Yan, Ping ; Lv, Teng

Author_Institution

Coll. of Math. & Syst. Sci., Xinjiang Univ., Urumqi

Volume

1

fYear

2008

fDate

20-22 Dec. 2008

Firstpage

741

Lastpage

745

Abstract

In this paper, we study reaction-diffusion high-order Cohen-Grossberg neural networks with delays and variable coefficient. Under the Dirichlet boundary condition, by using topology degree theory and constructing Lyapunov functional method, some sufficient conditions are given to ensure the existence, uniqueness and globally exponential stability of the equilibrium point. Finally, a numerical example is given to verify the theoretical analysis.

Keywords

Lyapunov methods; asymptotic stability; boundary-value problems; delays; neural nets; reaction-diffusion systems; topology; Dirichlet boundary condition; Lyapunov functional method; delayed reaction-diffusion high-order Cohen-Grossberg neural network; global exponential stability; topology degree theory; variable coefficient; Computer networks; Convergence; Delay effects; Information technology; Intelligent networks; Network topology; Neural networks; Neurons; Stability; Sufficient conditions; Cohen-Grossberg neural networks; Dirichlet boundary condition; Lyapunov functional; reaction-diffusion;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Information Technology Application, 2008. IITA '08. Second International Symposium on

Conference_Location

Shanghai

Print_ISBN

978-0-7695-3497-8

Type

conf

DOI

10.1109/IITA.2008.19

Filename

4739670