Boundedness and stability for the solutions of impulsive neural networks with time-varying delay

Authors:
Xuyang Lou;Ruliang Wang;Baotong Cui
Affiliations:
College of Communication and Control Engineering, Jiangnan University, Wuxi, China;Department of Information Technology, Guangxi Teachers Education University, Nanning, China;College of Communication and Control Engineering, Jiangnan University, Wuxi, China
Venue:
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Year:
2009

Citing 5
Cited 0

On delayed impulsive Hopfield neural networks

Neural Networks
Impulsive stabilization of functional differential equations by Lyapunov-Razumikhin functions

Nonlinear Analysis: Theory, Methods & Applications
Impulsive Systems and Control: Theory and Applications

Impulsive Systems and Control: Theory and Applications
Globally exponential stability conditions for cellular neural networks with time-varying delays

Applied Mathematics and Computation
Global exponential stability and global convergence in finite time of delayed neural networks with infinite gain

IEEE Transactions on Neural Networks

Quantified Score

Hi-index	0.00

Visualization

Abstract

By employing Lyapunov functions and Razumikhin techniques, we analyze the uniform boundedness and uniform asymptotic stability for a large class of impulsive neural networks with time-varying delay. Some new criteria are obtained to ensure the uniform boundedness and uniform asymptotic stability of the impulsive neural networks. The results remove the usual assumption that the activation functions fj (ċ) are of bounded, monotonous or differential character. Moreover, the time-varying delay function is not required to be differential. Therefore, the results which are easy to check and apply in practice, extend and improve the earlier publications.