Global exponential stability for uncertain dynamic neural networks with discrete and distributed time-varying delays

Author

Wu, Liang ; Ma, Baolin ; Cheng, Jianfeng ; Yin, Jingben

Author_Institution

Dept. of Math., Henan Inst. of Sci. & Technol., Xinxiang, China

fYear

2010

fDate

26-28 May 2010

Firstpage

1273

Lastpage

1276

Abstract

In this paper, the global exponential stability was discussed for the uncertain dynamic neural networks with discrete and distributed time-varying delays. The parameter uncertainties are assumed to be norm bounded. Then based on Lyapunov-Krasovskii functional stability analysis and linear matrix inequality (LMI) approach, a new sufficient condition is derived to assure the global exponential stability of the equilibrium, which generalizes the previous results in literature less conservatively.

Keywords

asymptotic stability; delays; linear matrix inequalities; neural nets; time-varying systems; LMI approach; Lyapunov-Krasovskii functional stability analysis; discrete time-varying delays; distributed time-varying delays; dynamic neural networks; global exponential stability; linear matrix inequality; parameter uncertainties; Cellular neural networks; Delay effects; Linear matrix inequalities; Mathematics; Neural networks; Stability analysis; Stability criteria; Time varying systems; Uncertain systems; Uncertainty; Discrete; Distributed; Global Exponential Stability; LMI; Lyapunov Functional; Uncertain;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Decision Conference (CCDC), 2010 Chinese

Conference_Location

Xuzhou

Print_ISBN

978-1-4244-5181-4

Electronic_ISBN

978-1-4244-5182-1

Type

conf

DOI

10.1109/CCDC.2010.5498172

Filename

5498172