Impulsive Stabilization of High-Order Hopfield-Type Neural Networks With Time-Varying Delays

Author

Liu, Xinzhi ; Wang, Qing

Author_Institution

Univ. of Waterloo, Waterloo

Volume

19

Issue

1

fYear

2008

Firstpage

71

Lastpage

79

Abstract

This paper studies the problems of global exponential stability for impulsive high-order Hopfield-type neural networks (NNs) with time-varying delays. By employing the Lyapunov-Razumikhin technique, some criteria ensuring global exponential stability are derived. Our results are then used to obtain some sufficient conditions under which some NNs can be forced to converge by impulsive control. Numerical examples are also discussed to illustrate our results.

Keywords

Hopfield neural nets; Lyapunov methods; asymptotic stability; delays; neurocontrollers; time-varying systems; Lyapunov-Razumikhin technique; global exponential stability; impulsive control; impulsive high-order Hopfield-type neural network; impulsive stabilization; time-varying delay; Global exponential stability; Lyapunov–Razumikhin technique; Lyapunov-Razumikhin technique; impulsive high-order Hopfield-type neural network (NN); impulsive stabilization; Algorithms; Humans; Models, Neurological; Neural Networks (Computer); Nonlinear Dynamics; Signal Processing, Computer-Assisted;

fLanguage

English

Journal_Title

Neural Networks, IEEE Transactions on

Publisher

ieee

ISSN

1045-9227

Type

jour

DOI

10.1109/TNN.2007.902725

Filename

4359196