title: Global and robust stability of interval Hopfield neural networks with time-varying delays.
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.
authors.affiliation: Department of Computer Science and Engineering, Chongqing University, Chongqing 400044, P. R. China. xfliao@cqu.edu.cn
authors.forename: Xiaofeng
authors.initials: X
authors.lastname: Liao
authors.forename: Jun
authors.initials: J
authors.lastname: Wang
authors.forename: Jinde
authors.initials: J
authors.lastname: Cao
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D006801:Humans; D008959:Models, Neurological; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics; D013997:Time Factors