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New results on global exponential stability of competitive neural networks with different time scales and time-varying delays 被引量:1

New results on global exponential stability of competitive neural networks with different time scales and time-varying delays
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摘要 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. 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.
出处 《Chinese Physics B》 SCIE EI CAS CSCD 2008年第5期1670-1677,共8页 中国物理B(英文版)
基金 supported by National Natural Science Foundation of China (Grant No 60674026) the Jiangsu Provincial Natural Science Foundation of China (Grant No BK2007016) Program for Innovative Research Team of Jiangnan University of China
关键词 competitive neural network different time scale global exponential stability DELAY competitive neural network, different time scale, global exponential stability, delay
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参考文献23

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