Global exponential stability of mixed discrete and distributively delayed cellular neural network

doi:10.1088/1674-1056/20/1/010701

中国物理B ›› 2011, Vol. 20 ›› Issue (1): 10701-010701.doi: 10.1088/1674-1056/20/1/010701

Global exponential stability of mixed discrete and distributively delayed cellular neural network

姚洪兴, 周佳燕

Nonlinear Scientific Research Center, Jiangsu University, Zhenjiang 212013, China

收稿日期:2010-04-17 修回日期:2010-06-18 出版日期:2011-01-15 发布日期:2011-01-15
基金资助:
Project supported by the National Natural Science Foundations of China (Grant No. 70871056), the Society Science Foundation from Ministry of Education of China (Grant No. 08JA790057) and the Advanced Talents' Foundation and Student's Foundation of Jiangsu University, China (Grant Nos. 07JDG054 and 07A075).

Global exponential stability of mixed discrete and distributively delayed cellular neural network

Yao Hong-Xing(姚洪兴) and Zhou Jia-Yan(周佳燕)^†

Nonlinear Scientific Research Center, Jiangsu University, Zhenjiang 212013, China

Received:2010-04-17 Revised:2010-06-18 Online:2011-01-15 Published:2011-01-15
Supported by:
Project supported by the National Natural Science Foundations of China (Grant No. 70871056), the Society Science Foundation from Ministry of Education of China (Grant No. 08JA790057) and the Advanced Talents' Foundation and Student's Foundation of Jiangsu University, China (Grant Nos. 07JDG054 and 07A075).

摘要/Abstract

摘要： This paper concernes analysis for the global exponential stability of a class of recurrent neural networks with mixed discrete and distributed delays. It first proves the existence and uniqueness of the balance point，then by employing the Lyapunov--Krasovskii functional and Young inequality, it gives the sufficient condition of global exponential stability of cellular neural network with mixed discrete and distributed delays，in addition, the example is provided to illustrate the applicability of the result.

Abstract: This paper concernes analysis for the global exponential stability of a class of recurrent neural networks with mixed discrete and distributed delays. It first proves the existence and uniqueness of the balance point, then by employing the Lyapunov–Krasovskii functional and Young inequality, it gives the sufficient condition of global exponential stability of cellular neural network with mixed discrete and distributed delays, in addition, the example is provided to illustrate the applicability of the result.

Key words: global exponential stability, cellular neural network, mixed discrete and distributed delays, Lyapunov–Krasovskii functional and Young inequality

中图分类号: (Neural networks, fuzzy logic, artificial intelligence)

07.05.Mh

姚洪兴, 周佳燕. Global exponential stability of mixed discrete and distributively delayed cellular neural network[J]. 中国物理B, 2011, 20(1): 10701-010701.

Yao Hong-Xing(姚洪兴) and Zhou Jia-Yan(周佳燕). Global exponential stability of mixed discrete and distributively delayed cellular neural network[J]. Chin. Phys. B, 2011, 20(1): 10701-010701.

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Global exponential stability of mixed discrete and distributively delayed cellular neural network

Global exponential stability of mixed discrete and distributively delayed cellular neural network

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