Title :
Impulsive Stabilization of High-Order Hopfield-Type Neural Networks With Time-Varying Delays
Author :
Liu, Xinzhi ; Wang, Qing
Author_Institution :
Univ. of Waterloo, Waterloo
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;
Journal_Title :
Neural Networks, IEEE Transactions on
DOI :
10.1109/TNN.2007.902725
