Exponential Stability of Cellular Neural Networks with Uncertain and Time-Varying Delay

Author

Wu, Xue-li ; Lv, Xuan ; Meng, Hua ; Li, Yang

Author_Institution

Hebei Univ. of Sci. & Technol., Shijiazhuang, China

Volume

3

fYear

2009

fDate

14-16 Aug. 2009

Firstpage

500

Lastpage

504

Abstract

A novel method is proposed in this note for exponential stability of cellular neural networks with uncertain and time-varying delay. New delay-dependent exponential stability conditions of cellular neural network with time-varying delay is presented by constructing Lyapunov function and using linear matrix inequality (LMI). The sufficient conditions on exponential stability established in this paper, which are easily verifiable, have a wider adaptive range. Finally, a numerical example is given to demonstrate the effect of the proposed method.

Keywords

Lyapunov methods; asymptotic stability; cellular neural nets; delays; linear matrix inequalities; time-varying systems; uncertain systems; Lyapunov function; cellular neural networks; delay-dependent exponential stability conditions; linear matrix inequality; sufficient conditions; time-varying delay; uncertain delay; Cellular neural networks; Computer networks; Electronic mail; Linear matrix inequalities; Lyapunov method; Neurofeedback; Stability criteria; State feedback; Sufficient conditions; Uncertainty; Exponential stability; LMI; Lyapunov functional; delayed cellular neural networks (DCNNs);

fLanguage

English

Publisher

ieee

Conference_Titel

Natural Computation, 2009. ICNC '09. Fifth International Conference on

Conference_Location

Tianjin

Print_ISBN

978-0-7695-3736-8

Type

conf

DOI

10.1109/ICNC.2009.384

Filename

5365696