Delay-dependent exponential stability analysis of delayed cellular neural networks

Author

Liao, Xiaofeng ; Yu, Juebang ; Chen, Guanrong

Author_Institution

Dept. of Comput. Sci. & Eng., Chongqing Univ., China

Volume

2

fYear

2002

fDate

29 June-1 July 2002

Firstpage

1657

Abstract

For the delayed cellular neural networks, the estimate of exponential convergence rate and exponential stability is considered in this paper. The Lyapunov-Krasovskii functionals combined with linear matrix inequality (LMI) approach are employed to investigate the bound on the cell template and delay-type cell template matrices so that the systems are exponentially stable. Some criteria for the exponential stability which can give information on the delay-dependence are derived.

Keywords

Lyapunov matrix equations; cellular neural nets; linear matrix inequalities; stability; Lyapunov-Krasovskii functionals; cell template; delay-dependent exponential stability analysis; delay-type cell template matrices; delayed cellular neural networks; exponential convergence rate; linear matrix inequality; Cellular neural networks; Computer science; Convergence; Delay effects; Delay estimation; Delay systems; Differential equations; Linear matrix inequalities; Stability analysis; Stability criteria;

fLanguage

English

Publisher

ieee

Conference_Titel

Communications, Circuits and Systems and West Sino Expositions, IEEE 2002 International Conference on

Print_ISBN

0-7803-7547-5

Type

conf

DOI

10.1109/ICCCAS.2002.1179095

Filename

1179095