title: Robust stability analysis for interval cohen-grossberg neural networks with unknown time-varying delays.
abstract: In this paper, robust stability problems for interval Cohen-Grossberg neural networks with unknown time-varying delays are investigated. Using linear matrix inequality, M -matrix theory, and Halanay inequality techniques, new sufficient conditions independent of time-varying delays are derived to guarantee the uniqueness and the global robust stability of the equilibrium point of interval Cohen-Grossberg neural networks with time-varying delays. All these results have no restriction on the rate of change of the time-varying delays. Compared to some existing results, these new criteria are less conservative and are more convenient to check. Two numerical examples are used to show the effectiveness of the present results.
authors.affiliation: School of Information Science and Engineering, Northeastern University, Shenyang, Liaoning 110004, China. hgzhang@ieee.org
authors.forename: Huaguang
authors.initials: H
authors.lastname: Zhang
authors.forename: Zhanshan
authors.initials: Z
authors.lastname: Wang
authors.forename: Derong
authors.initials: D
authors.lastname: Liu
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D005246:Feedback; D015233:Models, Statistical; D010363:Pattern Recognition, Automated / Q000379:methods*; D013997:Time Factors