A new method for complete stability analysis of cellular neural networks with time delay.
This paper presents new complete stability results for delayed cellular neural networks (DCNNs). A novel method is proposed for complete stability analysis of DCNNs. By applying the M-matrix theory and introducing some new estimation techniques on the solutions of DCNNs, a simple and improved complete stability criterion is derived. The new criterion unifies the delay-dependent and delay-independent complete stability conditions for DCNNs. Moreover, the obtained delay-dependent criterion can give a larger upper bound of the time delay than the existing ones such that the complete stability can still be retained. Numerical examples are presented which show that the new complete stability results for DCNNs are compared favorably with the existing results.
Chen
Wu-Hua
WH
School of Computing and Mathematics, University of Western Sydney, Sydney, NSW 1797, Australia. wuhua_chen2002@yahoo.com.cn
Zheng
Wei Xing
WX
D000465:Algorithms; D000818:Animals; D003198:Computer Simulation; D016571:Neural Networks, Computer; D013997:Time Factors