New Delay-Dependent Stability Criteria for Neural Networks With Two Additive Time-Varying Delay Components

Author

Shao, Hanyong ; Han, Qing-Long

Author_Institution

Sch. of Electr. & Inf. Autom., Qufu Normal Univ., Rizhao, China

Volume

22

Issue

5

fYear

2011

fDate

5/1/2011 12:00:00 AM

Firstpage

812

Lastpage

818

Abstract

This brief is concerned with delay-dependent stability for neural networks with two additive time-varying delay components. By constructing a new Lyapunov functional and using a convex polyhedron method to estimate the derivative of the Lyapunov functional, some new delay-dependent stability criteria are derived. These stability criteria are less conservative than some existing ones. An example is given to demonstrate the less conservatism of the stability results.

Keywords

Lyapunov methods; delay systems; neurocontrollers; stability; time-varying systems; Lyapunov functional; additive time-varying delay component; convex polyhedron method; delay-dependent stability criteria; derivative estimation; neural network; Additives; Artificial neural networks; Asymptotic stability; Australia; Delay; Stability criteria; Lyapunov functional; neural networks; stability; time-varying delays; Artificial Intelligence; Computer Simulation; Mathematical Concepts; Models, Theoretical; Neural Networks (Computer); Reaction Time; Time Factors;

fLanguage

English

Journal_Title

Neural Networks, IEEE Transactions on

Publisher

ieee

ISSN

1045-9227

Type

jour

DOI

10.1109/TNN.2011.2114366

Filename

5735229