An Improved Result on Stability of Cellular Neural Networks with Time-Varying Delay

Author

Hu, Yanxia ; Ma, Na

Author_Institution

Sch. of Math. & Phys., North China Electr. Power Univ., Beijing, China

Volume

3

fYear

2009

fDate

14-16 Aug. 2009

Firstpage

486

Lastpage

489

Abstract

In a recent paper written by Yu et al., a sufficient condition on the existence of unique equilibrium point and its global asymptotic stability for delayed cellular neural networks (DCNNs) is proposed. In this note, we point out some errors in the paper and an improved result on global asymptotic stability of DCNNs is established in terms of linear matrix inequality. Furthermore, the new result concerning global asymptotic delay-dependent stability of DCNNs can guarantee exponential asymptotic stability of the system.

Keywords

asymptotic stability; cellular neural nets; delays; linear matrix inequalities; time-varying systems; cellular neural networks stability; delayed cellular neural networks; global asymptotic stability; linear matrix inequality; time-varying delay; Asymptotic stability; Cellular neural networks; Computer networks; Delay effects; Delay lines; Linear matrix inequalities; Mathematics; Physics computing; Sufficient conditions; Cellular neural networks; Delay; Linear matrix inequality;

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.2009.74

Filename

5365561