title: A novel global exponential stability result for discrete-time cellular neural networks with variable delays.
abstract: Global exponential stability is considered for a class of discrete-time cellular neural networks with variable delays. By employing a discrete Halanay inequality, a new result is presented ensuring global exponential stability of the unique equilibrium point of the networks. The result extends and improves the earlier publications due to the fact that it removes some restrictions on the delay. An example is given to illustrate the effectiveness of the global exponential stability condition provided here.
authors.affiliation: Liaoning Key Lab of Intelligent Information Processing, Dalian University, Dalian, 116622, China. zhangq30@yahoo.com
authors.forename: Qiang
authors.initials: Q
authors.lastname: Zhang
authors.forename: Xiaopeng
authors.initials: X
authors.lastname: Wei
authors.forename: Jin
authors.initials: J
authors.lastname: Xu
mesh_terms: D003198:Computer Simulation; D016571:Neural Networks, Computer; D009474:Neurons / Q000502:physiology; D017711:Nonlinear Dynamics; D013997:Time Factors