Exponential stability of interval neural networks with variable delays

Authors:
Jiye Zhang;Dianbo Ren;Weihua Zhang
Affiliations:
National Traction Power Laboratory, Southwest Jiaotong University, Chengdu, People’s Republic of China;National Traction Power Laboratory, Southwest Jiaotong University, Chengdu, People’s Republic of China;National Traction Power Laboratory, Southwest Jiaotong University, Chengdu, People’s Republic of China
Venue:
ICIC'06 Proceedings of the 2006 international conference on Intelligent Computing - Volume Part I
Year:
2006

Citing 3
Cited 0

Global attractivity in delayed Hopfield neural network models

SIAM Journal on Applied Mathematics
Global stability analysis in delayed Hopfield neural network models

Neural Networks
Global exponential stability of delayed Hopfield neural networks

Neural Networks

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, the conditions ensuring existence, uniqueness, and global exponential stability of the equilibrium point of interval neural networks with variable delays are studied. Applying idea of vector Liapunov function, the sufficient conditions for global exponential stability of interval neural networks are obtained.