title: Stability analysis of neural networks with interval time-varying delays.
abstract: The global exponential stability is investigated for neural networks with interval time-varying delays. Based on the Leibniz-Newton formula and linear matrix inequality technique, delay-dependent stability criteria are proposed to guarantee the exponential stability of neural networks with interval time-varying delays. Some numerical examples and comparisons are provided to show that the proposed results significantly improve the allowable upper and lower bounds of delays over some existing ones in the literature.
authors: Department of Engineering Science, National Cheng Kung University, Tainan 701, Taiwan.
authors: Yi-You
authors: YY
authors: Hou
authors: Teh-Lu
authors: TL
authors: Liao
authors: Chang-Hua
authors: CH
authors: Lien
authors: Jun-Juh
authors: JJ
authors: Yan
mesh_terms: D001683:Biological Clocks / Q000502:physiology*; D003198:Computer Simulation; D005246:Feedback / Q000502:physiology; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics; D009435:Synaptic Transmission / Q000502:physiology*; D013997:Time Factors