Novel criterions for global asymptotic stability of static neural networks with time-varying delays

Author

Wang, Li ; Yu, Xiaopeng

Author_Institution

Jilin Normal Univ., Siping, China

fYear

2011

fDate

23-25 May 2011

Firstpage

1115

Lastpage

1119

Abstract

In this paper, we investigate the global asymptotic stability of the static neural networks with time-varying delays. Based on the Lyapunov functional method and some free-weighting matrix, two innovative criterions are obtained, which are the significant improvement in the performance. Compared with the former references, our results are less conservative, and the conditions are expressed by linear matrix inequalities, which can be easily computed in MATLAB toolbox. Two numerical examples are provided to illustrate the effectiveness of the proposed result.

Keywords

Lyapunov methods; asymptotic stability; delays; linear matrix inequalities; neural nets; time-varying systems; Lyapunov functional method; MATLAB toolbox; free-weighting matrix; global asymptotic stability; linear matrix inequalities; static neural networks; time-varying delays; Artificial neural networks; Asymptotic stability; Circuit stability; Delay; Linear matrix inequalities; Stability criteria; Free-weighting matrix; Global asymptotic stability; Linear matrix inequalities(LMI); Lyapunov function; Neural networks; Time-varying delays;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Decision Conference (CCDC), 2011 Chinese

Conference_Location

Mianyang

Print_ISBN

978-1-4244-8737-0

Type

conf

DOI

10.1109/CCDC.2011.5968352

Filename

5968352