Abstract This paper studies the global exponential stability of competitive neural networks with different time scales and time-varying delays. By using the method of the proper Lyapunov functions and inequality technique, some sufficient conditions are presented for global exponential stability of delay competitive neural networks with different time scales. These conditions obtained have important leading significance in the designs and applications of global exponential stability for competitive neural networks. Finally, an example with its simulation is provided to demonstrate the usefulness of the proposed criteria.
Received: 06 August 2007
Revised: 20 September 2007
Accepted manuscript online:
Fund: Project supported by National
Natural Science Foundation of China (Grant No 60674026), the Jiangsu
Provincial Natural Science Foundation of China (Grant No BK2007016)
and Program for Innovative Research Team of Jiangnan University of
China.
Cite this article:
Cui Bao-Tong(崔宝同), Chen Jun(陈君), and Lou Xu-Yang(楼旭阳) New results on global exponential stability of competitive neural networks with different time scales and time-varying delays 2008 Chin. Phys. B 17 1670
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