Exponential stability for cellular neural networks: an LMI approach 被引量：1

Exponential stability for cellular neural networks: an LMI approach

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摘要 A new sufficient conditions for the global exponential stability of the equilibrium point for delayed cellular neural networks （DCNNs） is presented. It is shown that the use of a more general type of Lyapunov-Krasovskii function enables the derivation of new results for an exponential stability of the equilibrium point for DCNNs. The results establish a relation between the delay time and the parameters of the network. The results are also compared with one of the most recent results derived in the literature. A new sufficient conditions for the global exponential stability of the equilibrium point for delayed cellular neural networks （DCNNs） is presented. It is shown that the use of a more general type of Lyapunov-Krasovskii function enables the derivation of new results for an exponential stability of the equilibrium point for DCNNs. The results establish a relation between the delay time and the parameters of the network. The results are also compared with one of the most recent results derived in the literature.

作者 Liu Deyou Zhang Jianhua Guan Xinping

机构地区 Coll. of Science

出处《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2007年第1期68-71,共4页 系统工程与电子技术（英文版）

基金 This project was supported in part by the National Natural Science Foundation of China (60404022, 60604004) the Key Scientific Research project of Education Ministry of China (204014) the National Natural Science Foundation of China for Distinguished Young Scholars (60525303).

关键词 Delayed cellular neural networks LMI Neural networks Exponential stability Delayed cellular neural networks, LMI, Neural networks, Exponential stability

分类号 TP183 [自动化与计算机技术—控制理论与控制工程]

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Journal of Systems Engineering and Electronics

2007年第1期

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