Stability analysis of neural networks with interval time-varying delays.
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.
Hou
Yi-You
YY
Department of Engineering Science, National Cheng Kung University, Tainan 701, Taiwan.
Liao
Teh-Lu
TL
Lien
Chang-Hua
CH
Yan
Jun-Juh
JJ
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