Global and robust stability of interval Hopfield neural networks with time-varying delays

Xiaofeng Liao; Jun Wang; Jinde Cao

doi:10.1142/S012906570300142X

Global and robust stability of interval Hopfield neural networks with time-varying delays

Int J Neural Syst. 2003 Jun;13(3):171-82. doi: 10.1142/S012906570300142X.

Authors

Xiaofeng Liao¹, Jun Wang, Jinde Cao

Affiliation

¹ Department of Computer Science and Engineering, Chongqing University, Chongqing 400044, P. R. China. xfliao@cqu.edu.cn

PMID: 12884450
DOI: 10.1142/S012906570300142X

Abstract

In this paper, we investigate the problem of global and robust stability of a class of interval Hopfield neural networks that have time-varying delays. Some criteria for the global and robust stability of such networks are derived, by means of constructing suitable Lyapunov functionals for the networks. As a by-product, for the conventional Hopfield neural networks with time-varying delays, we also obtain some new criteria for their global and asymptotic stability.

Publication types

Comparative Study
Research Support, Non-U.S. Gov't

MeSH terms

Algorithms
Artificial Intelligence
Computer Simulation
Humans
Models, Neurological*
Neural Networks, Computer*
Nonlinear Dynamics
Time Factors