Robust Exponential Stability Analysis for Unertain Neural Networks with Time Delay

Author

Tang, Xinhuai ; Xie, Li

Author_Institution

Sch. of Software, Shanghai Jiaotong Univ., Shanghai, China

Volume

3

fYear

2009

fDate

21-22 Nov. 2009

Firstpage

473

Lastpage

476

Abstract

The robust exponential stability of uncertain neural networks with time delay is analyzed based on Lyapunov stability theory. The nonlinear uncertain perturbation in the neural networks satisfies the cone bounded condition. By choosing suitable Lyapunov functional, several sufficient conditions on robust stability and robust exponential stability of uncertain neural networks with time delays are given. All the stable criteria in this paper are presented in terms of linear matrix inequality.

Keywords

Lyapunov methods; asymptotic stability; delays; linear matrix inequalities; neural nets; Lyapunov functional; Lyapunov stability theory; linear matrix inequality; nonlinear uncertain perturbation; robust exponential stability analysis; time delay; uncertain neural networks; Computational intelligence; Delay effects; Intelligent networks; Linear matrix inequalities; Lyapunov method; Neural networks; Neurons; Robust stability; Stability analysis; Sufficient conditions; linear matrix inequality; nonlinear perturbation; robust exponential stability; time delay; uncertain neural networks;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Information Technology Application, 2009. IITA 2009. Third International Symposium on

Conference_Location

Nanchang

Print_ISBN

978-0-7695-3859-4

Type

conf

DOI

10.1109/IITA.2009.483

Filename

5370404