Time-delay is frequently encountered in neural networks,and it is often a source of instability and oscillatio...
Xue-Li Wu~(1,2),Zhantong Zhou~1,Wen-Xia Du~(2,3) Yang Li~1 1.Hebei University of Science and Technology,Shijiazhuang,050054 Engineering Technology Research Centre of Hebei Province for Producing Process Automation 2.YanShan University Qinhuangdao 066004 3.Hebei Normal University,Shijiazhuang 050031
A new sufficient conditions for the global exponential stability of the equilibrium point for delayed cellular neural networks (DCNNs) is presented. It is shown that the use of a more general type of Lyapunov–Krasovskii function enables the derivation of new results for an exponential stability of the equilibrium point for DCNNs. The results establish a relation between the delay time and the parameters of the network. The results are also compared with one of the most recent results derived in the literature.
