New sufficient conditions for global asymptotic stability of delayed Cohen-Grossberg neural networks

Author

Fang, Qiu ; Baotong, Cui

Author_Institution

Coll. of Commun. & Control Eng., Jiangnan Univ., Wuxi

fYear

2008

fDate

16-18 July 2008

Firstpage

48

Lastpage

52

Abstract

In this paper, global asymptotic stability of the delayed Cohen-Grossberg neural networks is investigated. By constructing suitable Lyapunov functional and employing nonsmooth analysis, some sufficient conditions are obtained without demanding the boundedness and differentiability of the activation function. Moreover, two examples are demonstrated to illustrate the effectiveness of the proposed criteria in comparison with some existing results.

Keywords

Lyapunov matrix equations; asymptotic stability; delay systems; neurocontrollers; Lyapunov function; delayed Cohen-Grossberg neural network; global asymptotic stability; nonsmooth analysis; Asymptotic stability; Cellular neural networks; Communication system control; Educational institutions; Eigenvalues and eigenfunctions; Hopfield neural networks; Neural networks; Neurons; Sufficient conditions; Symmetric matrices; Cohen-Grossberg; Global asymptotic stability; Nonsmooth analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Conference, 2008. CCC 2008. 27th Chinese

Conference_Location

Kunming

Print_ISBN

978-7-900719-70-6

Electronic_ISBN

978-7-900719-70-6

Type

conf

DOI

10.1109/CHICC.2008.4605193

Filename

4605193