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Generalized LMI-based approach to global asymptotic stability of cellular neural networks with delay 被引量:1

Generalized LMI-based approach to global asymptotic stability of cellular neural networks with delay
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摘要 A global asymptotic stability problem of cellular neural networks with delay is investigated. A new stability condition is presented based on the Lyapunov-Krasovskii method, which is dependent on the amount of delay. A result is given in the form of a linear matrix inequality, and the admitted upper bound of the delay can be easily obtained. The time delay dependent and independent results can be obtained, which include some previously published results. A numerical example is given to show the effectiveness of the main results. A global asymptotic stability problem of cellular neural networks with delay is investigated. A new stability condition is presented based on the Lyapunov-Krasovskii method, which is dependent on the amount of delay. A result is given in the form of a linear matrix inequality, and the admitted upper bound of the delay can be easily obtained. The time delay dependent and independent results can be obtained, which include some previously published results. A numerical example is given to show the effectiveness of the main results.
机构地区 College of Science
出处 《Applied Mathematics and Mechanics(English Edition)》 SCIE EI 2008年第6期811-816,共6页 应用数学和力学(英文版)
基金 Project supported by the National Natural Science Foundation of China (No.60604004) the Natural Science Foundation of Hebei Province of China (No.F2007000637) the National Natural Science Foundation for Distinguished Young Scholars (No.60525303)
关键词 delayed cellular neural networks (DCNNs) linear matrix inequality (LMI) global stability delayed cellular neural networks (DCNNs), linear matrix inequality (LMI),global stability
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