Global exponential stability of complex-valued neural networks with time-varying delays on time scales

Author

Zhao Zhenjiang ; Song Qiankun

Author_Institution

Dept. of Math., Huzhou Teachers Coll., Huzhou, China

fYear

2014

fDate

28-30 July 2014

Firstpage

5080

Lastpage

5085

Abstract

In this paper, the global exponential stability of complex-valued neural networks (CVNN) with time-varying delays is investigated. By constructing appropriate Lyapunov-Krasovskii functionals and using matrix inequality technique, a new delay-dependent criterion for checking the global exponential stability of the addressed CVNN is established in terms of linear matrix inequalities (LMIs), which can be checked numerically using the effective LMI toolbox in MATLAB. An example with simulations is given to show the effectiveness of the proposed criterion.

Keywords

Lyapunov methods; asymptotic stability; delay systems; linear matrix inequalities; neurocontrollers; time-varying systems; CVNN; LMI toolbox; LMIs; Lyapunov-Krasovskii functionals; Matlab; complex-valued neural networks; delay-dependent criterion; global exponential stability; linear matrix inequalities; matrix inequality technique; time scales; time-varying delays; Biological neural networks; Control theory; Delays; Stability criteria; Complex-Valued Neural Networks; Global Exponential Stability; Linear Matrix Inequality; Time Scales; Time-Varying Delay;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Conference (CCC), 2014 33rd Chinese

Conference_Location

Nanjing

Type

conf

DOI

10.1109/ChiCC.2014.6895804

Filename

6895804